Planet Neuroscience

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Neuromodulation of the Cingulate Cortex for Pain

The Neuroscientist, Ahead of Print.
The subgenual (sACC) and pregenual (pACC) anterior cingulate and anterior midcingulate (aMCC) cortices are structurally and functionally distinct subregions of the cingulate cortex with critical roles in pain processing. These regions may be promising ...

in The Neuroscientist on 2025-06-27 06:55:10 UTC.

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Predicting Readiness to Engage in Psychotherapy of People with Chronic Pain Based on their Pain-Related Narratives Saar

arXiv:2506.20805v1 Announce Type: new Abstract: Background. Chronic pain afflicts 20 % of the global population. A strictly biomedical mind-set leaves many sufferers chasing somatic cures and has fuelled the opioid crisis. The biopsychosocial model recognises pain subjective, multifactorial nature, yet uptake of psychosocial care remains low. We hypothesised that patients own pain narratives would predict their readiness to engage in psychotherapy. Methods. In a cross-sectional pilot, 24 chronic-pain patients recorded narrated pain stories on Painstory.science. Open questions probed perceived pain source, interference and influencing factors. Narratives were cleaned, embedded with a pretrained large-language model and entered into machine-learning classifiers that output ready/not ready probabilities. Results. The perception-domain model achieved 95.7 % accuracy (specificity = 0.80, sensitivity = 1.00, AUC = 0.90). The factors-influencing-pain model yielded 83.3 % accuracy (specificity = 0.60, sensitivity = 0.90, AUC = 0.75). Sentence count correlated with readiness for perception narratives (r = 0.54, p < .01) and factor narratives (r = 0.24, p < .05). Conclusion. Brief spoken pain narratives carry reliable signals of willingness to start psychosocial treatment. NLP-based screening could help clinicians match chronic-pain patients to appropriate interventions sooner, supporting a patient-centred biopsychosocial pathway.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-06-27 04:00:00 UTC.

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Modulating task outcome value to mitigate real-world procrastination via noninvasive brain stimulation

arXiv:2506.21000v1 Announce Type: new Abstract: Procrastination represents one of the most prevalent behavioral problems affecting individual health and societal productivity. Although it is often conceptualized as a form of self-control failure, its underlying neurocognitive mechanisms are poorly understood. A leading model posits that procrastination arises from imbalanced competing motivations: the avoidance of negative task aversiveness and the pursuit of positive task outcomes, yet this theoretical framework has not fully validated in real-world settings and not applied effectively to guide interventions. Here, we addressed this gap with a preregistered, double-blind, randomized controlled trial. We applied seven sessions of high-definition transcranial direct current stimulation (HD-tDCS) to the left dorsolateral prefrontal cortex (DLPFC), a key region for self-control, in chronic procrastinators. Using the intensive experience sampling method (iESM), we assessed the effect of anodal HD-tDCS on real-world procrastination behavior at offline after-effect (2-day interval) and long-term retention (6-month follow-up). We found that this neuromodulation produced a lasting reduction in real-world procrastination, with effects sustained at a 6-month follow-up. While the intervention both decreased task aversiveness and increased perceived task outcome value, causal mediation analysis revealed a striking mechanism: the increase in task outcome value uniquely and sufficiently mediated the entire behavioral improvement. In conclusion, these findings provide causal evidence that enhancing DLPFC function mitigates procrastination by selectively amplifying the valuation of future rewards, not by simply reducing negative feelings about the task. This establishes a precise, value-driven neurocognitive pathway for self-control and offers a validated, theory-driven strategy for intervention.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-06-27 04:00:00 UTC.

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Amortizing personalization in virtual brain twins

arXiv:2506.21155v1 Announce Type: new Abstract: Virtual brain twins are personalized digital models of individual human subject or patient's brains, allowing for mechanistic interpretation of neuroimaging data features. Training and inference with these models however presents a pair of challenges: large shared infrastructure do not allow for use of personal data and inference in clinical applications should not require significant resources. We introduce "anonymized personalization" to address both by expanding model priors to include personalization which under amortized inference allows training to be performed anonymously, while inference is both personalized and lightweight. We illustrate the basic approach, demonstrate reliability in an example, and discuss the impact on both experimental and computational neuroscience. Code is available at https://github.com/ins-amu/apvbt.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-06-27 04:00:00 UTC.

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Wirelessly transmitted subthalamic nucleus signals predict endogenous pain levels in Parkinson's disease patients

arXiv:2506.21439v1 Announce Type: new Abstract: Parkinson disease (PD) patients experience pain fluctuations that significantly reduce their quality of life. Despite the vast knowledge of the subthalamic nucleus (STN) role in PD, the STN biomarkers for pain fluctuations and the relationship between bilateral subthalamic nucleus (STN) activities and pain occurrence are still less understood. This observational study used data-driven methods by collecting annotated pain followed by a series of corresponding binary pain ratings and wirelessly transmitted STN signals, then leveraging the explainable machine learning algorithm to predict binary pain levels and sort the feature influence. The binary pain levels could be predicted among annotated pain reports corresponding to PD-related pain characteristics. The STN activity from both sides could impact pain prediction, with gamma and beta bands in the contralateral STN and delta and theta bands in the ipsilateral STN showing a prominent role. This study emphasizes the role of bilateral STN biomarkers on endogenous pain fluctuations.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-06-27 04:00:00 UTC.

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The assumptions that restrain us from understanding consciousness

arXiv:2506.21485v1 Announce Type: new Abstract: The science of consciousness has been successful over the last decades. Yet, it seems that some of the key questions remain unanswered. Perhaps, as a science of consciousness, we cannot move forward using the same theoretical commitments that brought us here. It might be necessary to revise some assumptions we have made along the way. In this piece, I offer no answers, but I will question some of these fundamental assumptions. We will try to take a fresh look at the classical question about the neural and explanatory correlates of consciousness. A key assumption is that neural correlates are to be found at the level of spiking responses. However, perhaps we should not simply take it for granted that this assumption holds true. Another common assumption is that we are close to understanding the computations underlying consciousness. I will try to show that computations related to consciousness might be far more complex than our current theories envision. There is little reason to think that consciousness is an abstract computation, as traditionally believed. Furthermore, I will try to demonstrate that consciousness research could benefit from investigating internal changes of consciousness, such as aha-moments. Finally, I will ask which theories the science of consciousness really needs.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-06-27 04:00:00 UTC.

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Inverse Reinforcement Learning via Convex Optimization

arXiv:2501.15957v2 Announce Type: replace-cross Abstract: We consider the inverse reinforcement learning (IRL) problem, where an unknown reward function of some Markov decision process is estimated based on observed expert demonstrations. In most existing approaches, IRL is formulated and solved as a nonconvex optimization problem, posing challenges in scenarios where robustness and reproducibility are critical. We discuss a convex formulation of the IRL problem (CIRL) initially proposed by Ng and Russel, and reformulate the problem such that the domain-specific language CVXPY can be applied directly to specify and solve the convex problem. We also extend the CIRL problem to scenarios where the expert policy is not given analytically but by trajectory as state-action pairs, which can be strongly inconsistent with optimality, by augmenting some of the constraints. Theoretical analysis and practical implementation for hyperparameter auto-selection are introduced. This note helps the users to easily apply CIRL for their problems, without background knowledge on convex optimization.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-06-27 04:00:00 UTC.

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Solving Inverse Problem for Multi-armed Bandits via Convex Optimization

arXiv:2501.18945v3 Announce Type: replace-cross Abstract: We consider the inverse problem of multi-armed bandits (IMAB) that are widely used in neuroscience and psychology research for behavior modelling. We first show that the IMAB problem is not convex in general, but can be relaxed to a convex problem via variable transformation. Based on this result, we propose a two-step sequential heuristic for (approximately) solving the IMAB problem. We discuss a condition where our method provides global solution to the IMAB problem with certificate, as well as approximations to further save computing time. Numerical experiments indicate that our heuristic method is more robust than directly solving the IMAB problem via repeated local optimization, and can achieve the performance of Monte Carlo methods within a significantly decreased running time. We provide the implementation of our method based on CVXPY, which allows straightforward application by users not well versed in convex optimization.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-06-27 04:00:00 UTC.

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Revealing higher-order neural representations of uncertainty with the Noise Estimation through Reinforcement-based Diffusion (NERD) model

arXiv:2503.14333v2 Announce Type: replace-cross Abstract: Studies often aim to reveal ``first-order" representations (FORs), which encode aspects of an observer's environment, such as contents or structure. A less-common target is ``higher-order" representations (HORs), which are ``about" FORs -- e.g., their strength or uncertainty -- and which may contribute to learning. HORs about uncertainty are unlikely to be direct ``read-outs" of FOR characteristics, instead reflecting noisy estimation processes incorporating prior expectations about uncertainty, but how the brain represents such expected uncertainty distributions remains largely unexplored. Here, we study ``noise expectation" HORs using neural data from a task which may require the brain to learn about its own noise: decoded neurofeedback, wherein human subjects learn to volitionally produce target neural patterns. We develop and apply a Noise Estimation through Reinforcement-based Diffusion (NERD) model to characterize how brains may undertake this process, and show that NERD offers high explanatory power for human behavior.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-06-27 04:00:00 UTC.

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Brain2Model Transfer: Training sensory and decision models with human neural activity as a teacher

arXiv:2506.20834v1 Announce Type: new Abstract: Transfer learning enhances the training of novel sensory and decision models by employing rich feature representations from large, pre-trained teacher models. Cognitive neuroscience shows that the human brain creates low-dimensional, abstract representations for efficient sensorimotor coding. Importantly, the brain can learn these representations with significantly fewer data points and less computational power than artificial models require. We introduce Brain2Model Transfer Learning (B2M), a framework where neural activity from human sensory and decision-making tasks acts as the teacher model for training artificial neural networks. We propose two B2M strategies: (1) Brain Contrastive Transfer, which aligns brain activity and network activations through a contrastive objective; and (2) Brain Latent Transfer, which projects latent dynamics from similar cognitive tasks onto student networks via supervised regression of brain-derived features. We validate B2M in memory-based decision-making with a recurrent neural network and scene reconstruction for autonomous driving with a variational autoencoder. The results show that student networks benefiting from brain-based transfer converge faster and achieve higher predictive accuracy than networks trained in isolation. Our findings indicate that the brain's representations are valuable for artificial learners, paving the way for more efficient learning of complex decision-making representations, which would be costly or slow through purely artificial training.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-06-27 04:00:00 UTC.

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Spiking Neural Networks for SAR Interferometric Phase Unwrapping: A Theoretical Framework for Energy-Efficient Processing

arXiv:2506.20782v1 Announce Type: new Abstract: We present the first theoretical framework for applying spiking neural networks (SNNs) to synthetic aperture radar (SAR) interferometric phase unwrapping. Despite extensive research in both domains, our comprehensive literature review confirms that SNNs have never been applied to phase unwrapping, representing a significant gap in current methodologies. As Earth observation data volumes continue to grow exponentially (with missions like NISAR expected to generate 100PB in two years) energy-efficient processing becomes critical for sustainable data center operations. SNNs, with their event-driven computation model, offer potential energy savings of 30-100x compared to conventional approaches while maintaining comparable accuracy. We develop spike encoding schemes specifically designed for wrapped phase data, propose SNN architectures that leverage the spatial propagation nature of phase unwrapping, and provide theoretical analysis of computational complexity and convergence properties. Our framework demonstrates how the temporal dynamics inherent in SNNs can naturally model the spatial continuity constraints fundamental to phase unwrapping. This work opens a new research direction at the intersection of neuromorphic computing and SAR interferometry, offering a complementary approach to existing algorithms that could enable more sustainable large-scale InSAR processing.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-06-27 04:00:00 UTC.

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Stochastic Quantum Spiking Neural Networks with Quantum Memory and Local Learning

arXiv:2506.21324v1 Announce Type: new Abstract: Neuromorphic and quantum computing have recently emerged as promising paradigms for advancing artificial intelligence, each offering complementary strengths. Neuromorphic systems built on spiking neurons excel at processing time-series data efficiently through sparse, event-driven computation, consuming energy only upon input events. Quantum computing, on the other hand, leverages superposition and entanglement to explore feature spaces that are exponentially large in the number of qubits. Hybrid approaches combining these paradigms have begun to show potential, but existing quantum spiking models have important limitations. Notably, prior quantum spiking neuron implementations rely on classical memory mechanisms on single qubits, requiring repeated measurements to estimate firing probabilities, and they use conventional backpropagation on classical simulators for training. Here we propose a stochastic quantum spiking (SQS) neuron model that addresses these challenges. The SQS neuron uses multi-qubit quantum circuits to realize a spiking unit with internal quantum memory, enabling event-driven probabilistic spike generation in a single shot. Furthermore, we outline how networks of SQS neurons -- dubbed SQS neural networks (SQSNNs) -- can be trained via a hardware-friendly local learning rule, eliminating the need for global classical backpropagation. The proposed SQSNN model fuses the time-series efficiency of neuromorphic computing with the exponentially large inner state space of quantum computing, paving the way for quantum spiking neural networks that are modular, scalable, and trainable on quantum hardware.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-06-27 04:00:00 UTC.

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Assessing an evolutionary search engine for small language models, prompts, and evaluation metrics

arXiv:2506.21512v1 Announce Type: new Abstract: The concurrent optimization of language models and instructional prompts presents a significant challenge for deploying efficient and effective AI systems, particularly when balancing performance against computational costs like token usage. This paper introduces and assesses a bi-objective evolutionary search engine designed to navigate this complex space, focusing specifically on Small Language Models (SLMs). We employ the NSGA-II algorithm and prompt grammar to simultaneously optimize for task accuracy and token efficiency across some reasoning tasks. Our results successfully identify diverse, high-performing model-prompt combinations, quantitatively revealing the critical trade-off between the two objectives. This research highlights task-specific affinities between particular SLMs and prompt structures (e.g., instructions, context, chain of thought). The generated practical Pareto fronts offer decision-makers a portfolio of optimized solutions adaptable to their specific constraints. This automated approach moves beyond traditional manual tuning, providing a foundational framework for discovering effective human-AI interaction patterns.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-06-27 04:00:00 UTC.

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Efficient Event-based Delay Learning in Spiking Neural Networks

arXiv:2501.07331v3 Announce Type: replace Abstract: Spiking Neural Networks (SNNs) compute using sparse communication and are attracting increased attention as a more energy-efficient alternative to traditional Artificial Neural Networks~(ANNs). While standard ANNs are stateless, spiking neurons are stateful and hence intrinsically recurrent, making them well-suited for spatio-temporal tasks. However, the duration of this intrinsic memory is limited by synaptic and membrane time constants. Delays are a powerful additional mechanism and, in this paper, we propose a novel event-based training method for SNNs with delays, grounded in the EventProp formalism which enables the calculation of exact gradients with respect to weights and delays. Our method supports multiple spikes per neuron and, to the best of our knowledge, is the first delay learning algorithm to be applied to recurrent SNNs. We evaluate our method on a simple sequence detection task, as well as the Yin-Yang, Spiking Heidelberg Digits, Spiking Speech Commands and Braille letter reading datasets, demonstrating that our algorithm can optimise delays from suboptimal initial conditions and enhance classification accuracy compared to architectures without delays. We also find that recurrent delays are particularly beneficial in small networks. Finally, we show that our approach uses less than half the memory of the current state-of-the-art delay-learning method and is up to 26x faster.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-06-27 04:00:00 UTC.

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Bridging the Gap Between Approximation and Learning via Optimal Approximation by ReLU MLPs of Maximal Regularity

arXiv:2409.12335v4 Announce Type: replace-cross Abstract: The foundations of deep learning are supported by the seemingly opposing perspectives of approximation or learning theory. The former advocates for large/expressive models that need not generalize, while the latter considers classes that generalize but may be too small/constrained to be universal approximators. Motivated by real-world deep learning implementations that are both expressive and statistically reliable, we ask: "Is there a class of neural networks that is both large enough to be universal but structured enough to generalize?" This paper constructively provides a positive answer to this question by identifying a highly structured class of ReLU multilayer perceptions (MLPs), which are optimal function approximators and are statistically well-behaved. We show that any $(L,\alpha)$-H\"{o}lder function from $[0,1]^d$ to $[-n,n]$ can be approximated to a uniform $\mathcal{O}(1/n)$ error on $[0,1]^d$ with a sparsely connected ReLU MLP with the same H\"{o}lder exponent $\alpha$ and coefficient $L$, of width $\mathcal{O}(dn^{d/\alpha})$, depth $\mathcal{O}(\log(d))$, with $\mathcal{O}(dn^{d/\alpha})$ nonzero parameters, and whose weights and biases take values in $\{0,\pm 1/2\}$ except in the first and last layers which instead have magnitude at-most $n$. Further, our class of MLPs achieves a near-optimal sample complexity of $\mathcal{O}(\log(N)/\sqrt{N})$ when given $N$ i.i.d. normalized sub-Gaussian training samples. We achieve this through a new construction that perfectly fits together linear pieces using Kuhn triangulations, along with a new proof technique which shows that our construction preserves the regularity of not only the H\"{o}lder functions, but also any uniformly continuous function. Our results imply that neural networks can solve the McShane extension problem on suitable finite sets.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-06-27 04:00:00 UTC.

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Genetic Algorithm with Innovative Chromosome Patterns in the Breeding Process

arXiv:2501.18184v3 Announce Type: replace-cross Abstract: This paper proposes Genetic Algorithm with Border Trades (GAB), a novel modification of the standard genetic algorithm that enhances exploration by incorporating new chromosome patterns in the breeding process. This approach significantly mitigates premature convergence and improves search diversity. Empirically, GAB achieves up to 8x higher fitness and 10x faster convergence on complex job scheduling problems compared to standard Genetic Algorithms, reaching average fitness scores of 888 versus 106 in under 20 seconds. On the classic Flip-Flop problem, GAB consistently finds optimal or near-optimal solutions in fewer generations, even as input sizes scale to thousands of bits. These results highlight GAB as a highly effective and computationally efficient alternative for solving large-scale combinatorial optimization problems.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-06-27 04:00:00 UTC.

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Interference Underlies Attenuation upon Relearning in Sensorimotor Adaptation

Savings refers to the gain in performance upon relearning. In sensorimotor adaptation, savings is tested by having participants adapt to perturbed feedback and, following a washout block during which the system resets to baseline, presenting the same perturbation again. While savings has been observed with these tasks, we have shown that the contribution from implicit adaptation, a process that uses errors to recalibrate the sensorimotor map, is attenuated upon relearning ( Avraham et al., 2021). Here, we test the hypothesis that this attenuation is due to interference arising from the different relationship between the movement and the feedback during washout. Removing the perturbation at the start of the washout block typically results in a salient error signal in the opposite direction to that observed during learning. We first replicated the finding that implicit adaptation is attenuated following a washout period that introduces salient opposite errors. When we eliminated feedback during washout, relearning was no longer attenuated, consistent with the interference hypothesis. Next, we created a scenario in which the perceived errors during washout were not salient, falling within the range of motor noise. Nonetheless, attenuation was still prominent. Inspired by this observation, we tested participants with an extended initial experience with veridical feedback and found that this was sufficient to attenuate adaptation during the first learning block. This effect was context specific and did not generalize to other movements. Taken together, the implicit sensorimotor adaptation system is highly sensitive to memory interference from a recent experience with a discrepant action-outcome contingency.

in eNeuro on 2025-06-26 16:30:28 UTC.

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Release of Extracellular Matrix Components after Human Traumatic Brain Injury

Animal studies and human tissue experiments have demonstrated that traumatic brain injury (TBI) causes damage to the extracellular matrix (ECM). To test the hypothesis that TBI causes disruption of sulfated glycosaminoglycan (sGAG) in the ECM, we measured levels of sGAG in the cerebrospinal fluid (CSF), blood, and urine, in patients with severe TBI in the acute postinjury period. Samples of CSF, blood, and urine were obtained within 72 h of injury in patients who received external ventricular drains as part of their treatment of severe TBI. Levels of chondroitin and heparan sGAGs were measured, along with their disaccharide constituents. Demographic information, presence of polytrauma, brain injury load, and distance of radiologically visible parenchymal injury from the ventricle were analyzed for correlation with total subtype sGAG levels. Levels were measured in 14 patients ranging in age from 17 to 90 years. CSF sGAG levels were variable among patients, with higher sGAG levels in plasma compared with CSF. Patients with polytrauma had nonsignificantly higher blood sGAG compared with patients with isolated head injury. Subcategories of CSF sGAG levels correlated with distance from the ventricle of parenchymal injury but not with brain injury load. This study is the first to measure sGAG levels in ventricular CSF and the first to analyze levels in TBI. These data demonstrate the elevation locally of intracranial sGAGs after severe TBI and suggest rapid local metabolism of these breakdown products. The consequences of ECM breakdown may provide unique therapeutic and preventive avenues to mitigate postinjury sequelae.

in eNeuro on 2025-06-26 16:30:28 UTC.

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Allosteric modulation of proton binding confers Cl- activation and glutamate selectivity to vesicular glutamate transporters

by Bart Borghans, Daniel Kortzak, Piersilvio Longo, Bettina Kolen, Jan-Philipp Machtens, Christoph Fahlke

Vesicular glutamate transporters (VGLUTs) fill synaptic vesicles with glutamate and remove luminal Cl^- via an additional anion channel mode. Both of these transport functions are stimulated by luminal acidification, luminal-positive membrane potential, and luminal Cl^-. We studied VGLUT1 transporter/channel activation using a combination of heterologous expression, cellular electrophysiology, fast solution exchange, and mathematical modeling. Cl^- channel gating can be described with a kinetic scheme that includes two protonation sites and distinct opening, closing, and Cl^--binding rates for each protonation state. Cl^- binding promotes channel opening by modifying the pK_a values of the protonation sites and rates of pore opening and closure. VGLUT1 transports glutamate and aspartate at distinct stoichiometries: H⁺-glutamate exchange at 1:1 stoichiometry and aspartate uniport. Neurotransmitter transport with variable stoichiometry can be described with an alternating access model that assumes that transporters without substrate translocate in the doubly protonated state to the inward-facing conformation and return with the bound amino acid substrate as either singly or doubly protonated. Glutamate, but not aspartate, promotes the release of one proton from inward-facing VGLUT1, resulting in preferential H⁺-coupled glutamate exchange. Cl^- stimulates glutamate transport by making the glutamate-binding site accessible to cytoplasmic glutamate and by facilitating transitions to the inward-facing conformation after outward substrate release. We conclude that allosteric modification of transporter protonation by Cl^- is crucial for both VGLUT1 transport functions.

in PLoS Computational Biology on 2025-06-26 14:00:00 UTC.

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Robust pleiotropy-decomposed polygenic scores identify distinct contributions to elevated coronary artery disease polygenic risk

by Jiaqi Hu, Yixuan Ye, Chi Zhang, Yunfeng Ruan, Pradeep Natarajan, Hongyu Zhao

Background

Polygenic risk score (PRS) have proved to offer robust risk prediction for coronary artery disease (CAD). However, the global CAD PRS summarizes the joint effects of all the markers in the genome, masking potential genetic heterogeneity that may be important for disease interpretation and targeted interventions.

Methods

Using summary-level data, we identified 43 significant CAD-related traits based on genetic correlations, and further classified them into eight pleiotropy clusters based on their biological functions. We then partitioned the genome into 2,353 near-independent regions. Variants in each region were assigned to the trait most genetically similar to CAD, and then were labeled with the corresponding pleiotropy cluster. We grouped variants without labels into a ninth, non-specific cluster. The Pleiotropy Decomposed (PD) PRSs for each of the nine clusters were calculated using variants assigned to each cluster for 407,903 samples of European ancestry from the UK Biobank (UKBB).

Results

We decomposed the CAD PRS into nine PD-PRSs and further stratified individuals with high CAD-PRS into nine subgroups. Each PD-PRS accounted for a higher proportion of the global CAD-PRS within its corresponding subgroup than in the remaining subjects with high CAD-PRS (e.g., 25.2% (0.07) vs. 10.06% (0.07) for lipids-PD-PRS). Additionally, these subgroups showed distinct clinical features. For example, in the lipids-related subgroup, lipoprotein(a) and LDL-cholesterol levels were 67.5% and 18.3% higher, respectively, compared to the remaining high-risk individuals. Furthermore, significant interactions were observed between blood pressure and BP PD-PRS, and between current smoking and respiratory system PD-PRS.

Conclusion

Our findings suggest that PD-PRSs may reveal substantial genetic and phenotypic heterogeneity among individuals with high CAD-PRS. The unique PD-PRS compositions of each individual can highlight the relative importance of different pleiotropic regions.

in PLoS Computational Biology on 2025-06-26 14:00:00 UTC.

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AI-first structural identification of pathogenic protein target interfaces

by Mihkel Saluri, Michael Landreh, Patrick Bryant

The risk of pandemics is increasing as global population growth and interconnectedness accelerate. Understanding the structural basis of protein-protein interactions between pathogens and hosts is critical for elucidating pathogenic mechanisms and guiding treatment or vaccine development. Despite 21,064 experimentally supported human-pathogen interactions in the HPIDB, only 52 have resolved structures in the PDB, representing just 0.2%. Advances in protein complex structure prediction, such as AlphaFold, now enable highly accurate modelling of heterodimeric complexes, though their application to host-pathogen interactions, which have distinct evolutionary dynamics, remains underexplored. Here, we investigate the structural protein-protein interaction network between humans and ten pathogens, predicting structures for 9,452 interactions, only 10 of which have known structures. We identify 30 interactions with an expected TM-score ≥0.9, tripling the structural coverage in these networks. A detailed analysis of the Francisella tularensis dihydroprolyl dehydrogenase (IPD) complex with human immunoglobulin kappa constant (IGKC) using homology modelling and native mass spectrometry confirms a predicted 1:2:1 heterotetramer, suggesting potential roles in immune evasion. These findings highlight the transformative potential of structure prediction for rapidly advancing vaccine and drug development against novel pathogenic targets.

in PLoS Computational Biology on 2025-06-26 14:00:00 UTC.

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On the usage of artificial intelligence in leprosy care: A systematic literature review

by Hilson Gomes Vilar de Andrade, Elisson da Silva Rocha, Kayo H. de Carvalho Monteiro, Cleber Matos de Morais, Danielle Christine Moura dos Santos, Dimas Cassimiro Nascimento, Raphael A. Dourado, Theo Lynn, Patricia Takako Endo

Leprosy, or Hansen’s disease, is a Neglected Tropical Disease (NTD) caused by Mycobacterium leprae that mainly affects the skin and peripheral nerves, causing neuropathy to varying degrees. It can result in physical disabilities and functional loss and is particularly prevalent amongst the most vulnerable populations in tropical and subtropical regions worldwide. The persistent stigma and social exclusion associated with leprosy complicate eradication efforts exacerbate the wider challenges faced by NTDs in sourcing the necessary resources and attention for control and elimination. The introduction of Multidrug Therapy (MDT) significantly lowers the global disease burden. Despite this breakthrough in the treatment of leprosy, over 200,000 new leprosy cases are reported annually across more than 120 countries, emphasizing the need for ongoing detection and management efforts. Artificial Intelligence (AI) has the potential to transform leprosy care by accelerating early detection, improving accurate diagnosis, and enabling predictive modeling to improve the quality for those affected. The potential of AI to provide information to assist healthcare professionals in interventions that reduce the risk of disability, and consequently stigma, particularly in endemic regions, presents a promising path to reducing the incidence of leprosy and improving integration social status of patients. This systematic literature review (SLR) examines the state of the art in research on the use of AI for leprosy care. From an initial 657 works from six scientific databases (ACM Digital Library, IEEE Xplore, PubMed, Scopus, Science Direct and Springer), only 30 relevant works were identified, after analysis of three independent reviewers. We have excluded works due duplication, couldn’t be retrieved and quality assessment. Results show that current research is focused primarily on the identification of symptoms using image based classification using three main techniques, neural networks, convolutional neural networks, and support vector machines; a small number of studies focus on other thematic areas of leprosy care. A comprehensive systematic approach to research on the application of AI to leprosy care can make a meaningful contribution to a leprosy-free world and help deliver on the promise of the Sustainable Development Goals (SDG).

in PLoS Computational Biology on 2025-06-26 14:00:00 UTC.

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N2 sleep promotes the occurrence of ‘aha’ moments in a perceptual insight task

by Anika T. Löwe, Marit Petzka, Maria M. Tzegka, Nicolas W. Schuck

Humans sometimes have an insight that leads to a sudden and drastic performance improvement on the task they are working on. The precise origins of such insights are unknown. Some evidence has shown that sleep facilitates insights, while other work has not found such a relationship. One recent suggestion that could explain this mixed evidence is that different sleep stages have differential effects on insight. In addition, computational work has suggested that neural variability and regularisation play a role in increasing the likelihood of insight. To investigate the link between insight and different sleep stages as well as regularisation, we conducted a preregistered study in which N=90 participants performed a perceptual insight task before and after a 20 minute daytime nap. Sleep EEG data showed that N2 sleep, but not N1 sleep, increases the likelihood of insight after a nap, suggesting a specific role of deeper sleep. Exploratory analyses of EEG power spectra showed that spectral slopes could predict insight beyond sleep stages, which is broadly in line with theoretical suggestions of a link between insight and regularisation. In combination, our findings point towards a role of N2 sleep and aperiodic, but not oscillatory, neural activity for insight.

in PLoS Biology on 2025-06-26 14:00:00 UTC.

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Reply to “Enhancing the Evaluation of IVT in DOAC‐Treated Stroke Patients: Addressing Methodological Considerations for Future Research”

in Annals of Neurology on 2025-06-26 12:04:23 UTC.

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Enhancing the Evaluation of IVT in DOAC‐Treated Stroke Patients: Addressing Methodological Considerations for Future Research

in Annals of Neurology on 2025-06-26 12:00:03 UTC.

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μ‐Opioid Receptor Dynamics in the Parameningeal Tissue During Migraine Attacks

Objective

The possible impact of meningeal μ-opioid receptor (μOR) binding in migraine remains unknown. This study investigated μOR availability in the cranial parameninges involved in migraine initiation via nociceptor activation.

Methods

We used positron emission tomography with [¹¹C] carfentanil, and measured μOR availability in meninges and adjacent skull bone (parameningeal tissue [PMT]) under resting and sustained thermal pain threshold stress challenge conditions. μOR availability was compared between individuals with migraine in interictal and ictal phases and healthy controls. Furthermore, we examined the relationship between μOR availability and headache intensity, as well as the potential influence of sex on this measure.

Results

A total of 36 patients with interictal episodic migraine (8 also assessed ictally), 7 patients with ictal chronic migraine, and 22 healthy controls were included in the analysis. Both the episodic migraine and chronic migraine groups showed lower μOR availability in the parietal PMT than healthy controls during the ictal resting phase. No significant differences were observed during the interictal phase. Exploratory analyses on the effects of sex indicated that both healthy women and migraine patients of both sexes showed lower μOR availability in the frontal PMT compared with healthy men in the ictal sustained thermal pain threshold stress condition. Furthermore, the interictal μOR availability in the frontal PMT was negatively associated with headache intensity in the preceding month.

Interpretation

The observed variability in PMT μOR availability across the different cortical regions and migraine episodes, along with its association with pain intensity, underscores the critical role of extracerebral mechanisms in migraine pathophysiology. ANN NEUROL 2025

in Annals of Neurology on 2025-06-26 10:28:15 UTC.

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The Role of Electroencephalography in Predicting Post‐Stroke Seizures and an Updated Prognostic Model (SeLECT‐EEG)

Objective

Seizures negatively impact stroke outcomes, highlighting the need for reliable predictors of post-stroke epilepsy. Although acute symptomatic seizures are a known risk factor, most stroke survivors who develop epilepsy do not experience them. Early electroencephalography (EEG) findings may enhance risk prediction, particularly in patients without acute symptomatic seizures, aiding in patient management and counseling.

Methods

We conducted a multicenter cohort study using data from 1,105 stroke survivors (mean age 71 years, 54% male) with neuroimaging-confirmed ischemic stroke who underwent EEG within 7 days post-stroke. Electrographic biomarkers, including epileptiform activity and regional slowing, were analyzed for their association with post-stroke epilepsy using Cox proportional hazards regression and Fine–Gray subdistribution hazard models, adjusted for differences in EEG timing and patient characteristics.

Results

Post-stroke epilepsy developed in 119 patients (11%), whereas 233 (21%) had acute symptomatic seizures. The 5-year epilepsy risk was 42% (95% confidence interval [CI]: 30–49%) in patients with epileptiform activity versus 13% (95% CI: 9–16%) in those without. Regional slowing doubled the 5-year epilepsy risk (23%, 95% CI: 17–30% vs 11%, 95% CI: 7–16%). Epileptiform activity (subdistribution hazard ratio: 2.3, 95% CI: 1.5–3.4, p < 0.001) and regional slowing (subdistribution hazard ratio: 1.7, 95% CI: 1.1–2.7, p = 0.02) were independently associated with post-stroke epilepsy. A novel prognostic model, SeLECT-EEG (concordance statistic: 0.75, 95% CI: 0.71–0.80), outperformed the previous standard (SeLECT_2.0; 0.71, 95% CI: 0.65–0.76, p < 0.001).

Interpretation

Electrographic biomarkers improve post-stroke epilepsy prediction beyond clinical risk factors. The SeLECT-EEG model enhances early risk stratification, particularly in patients without acute symptomatic seizures, informing management strategies and patient counseling. ANN NEUROL 2025

in Annals of Neurology on 2025-06-26 10:24:08 UTC.

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Dynamic landscapes and statistical limits on growth during cell fate specification

Author(s): Gautam Reddy

Motivated by developmental processes in biology, this study extends a classical optimal transport framework to processes that include growth. One key result presented here is the derivation of an analog of the Benamou-Brenier theorem, which identifies the conditions under which the transport map is described by stochastic dynamics on a potential landscape. The author exploits a mathematical connection between stochastic control theory, optimal transport and nonequilibrium thermodynamics. The framework can be used to find a potential landscape that describes the map from any (non-degenerate) initial distribution over cell states (of arbitrary dimensionality) to any target distribution in a finite time.

[Phys. Rev. E 111, 064418] Published Thu Jun 26, 2025

in Physical Review E: Biological physics on 2025-06-26 10:00:00 UTC.

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Enhancing global clinical trial transparency for better health outcomes for all  [version 1; peer review: awaiting peer review]

Background In 2022, WHO’s World Health Assembly adopted resolution WHA75.8, emphasizing the critical role of clinical trials in generating high-quality evidence and promoting equitable access to health interventions globally. In response, rapid landscape reviews were conducted to assess global clinical trial regulations, capacities, and funding distribution. Methods The analysis synthesized regulatory frameworks from 94 countries, institutional capacity data from the WHO International Clinical Trial Registry Platform (ICTRP), and funding data from World RePORT for trials registered between 2018-2022. Gaps in data availability and quality were assessed. Results Most countries reference international ethical guidelines, with universal requirements for ethics approval and informed consent. However, only 66% mandate public trial registration, and 40% require results reporting, with stark disparities between high- and low-income countries. High-income countries host over half of global trials; low-income countries contribute less than 1% despite high disease burden. Clinical trials sponsored by non-commercial entities are particularly scarce in low- and middle-income countries. Funding remains concentrated in the Americas and European regions, primarily driven by major funders such as the National Institutes of Health in the United States of America and European Commission. Significant data accessibility challenges persist due to incomplete registry records, inconsistent standards, lack of harmonized identifiers, and limited bulk data access. Recommendations Urgent actions include reinforcing international standards for trial registries, harmonizing data fields, improving registry interoperability, leveraging unique identifiers, enhancing multilingual accessibility, auditing data quality, pooling analytical resources, promoting open data policies, and investing in registry infrastructure and trained personnel. Conclusion Addressing data gaps and inequities in clinical trial ecosystems requires concerted action by global stakeholders. Improved data transparency and interoperability are essential to guide equitable research investments, foster coordination, and strengthen clinical trial capacity worldwide.

in F1000Research on 2025-06-26 08:55:00 UTC.

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Contribution of glutamatergic projections to neurons in the nonhuman primate substantia nigra pars reticulata for reactive inhibition

Proceedings of the National Academy of Sciences, Volume 122, Issue 26, July 2025.
SignificanceUnderstanding how the basal ganglia facilitate desired actions while suppressing unwanted ones is fundamental to neuroscience. This study shows that neurons in the primate substantia nigra pars reticulata (SNr) bidirectionally modulate ...

in PNAS on 2025-06-26 07:00:00 UTC.

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Synergistic deficits in parvalbumin interneurons and dopamine signaling drive ACC dysfunction in chronic pain

Proceedings of the National Academy of Sciences, Volume 122, Issue 26, July 2025.
SignificanceChronic pain is a major global health issue with few effective long-term treatments. While abnormal signaling in the anterior cingulate cortex (ACC) is known to drive chronic pain, the underlying mechanisms remain unclear. We identify a loss ...

in PNAS on 2025-06-26 07:00:00 UTC.

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Reactivation of mammalian regeneration by turning on an evolutionarily disabled genetic switch

Science, Volume 388, Issue 6754, June 2025.

in Science on 2025-06-26 07:00:00 UTC.

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Event structure sculpts neural population dynamics in the lateral entorhinal cortex

Science, Volume 388, Issue 6754, June 2025.

in Science on 2025-06-26 07:00:00 UTC.

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Out-of-Anatolia: Cultural and genetic interactions during the Neolithic expansion in the Aegean

Science, Volume 388, Issue 6754, June 2025.

in Science on 2025-06-26 07:00:00 UTC.

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Structural basis of BAX pore formation

Science, Volume 388, Issue 6754, June 2025.

in Science on 2025-06-26 07:00:00 UTC.

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Female lineages and changing kinship patterns in Neolithic Çatalhöyük

Science, Volume 388, Issue 6754, June 2025.

in Science on 2025-06-26 07:00:00 UTC.

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Cascading land surface hazards as a nexus in the Earth system

Science, Volume 388, Issue 6754, June 2025.

in Science on 2025-06-26 07:00:00 UTC.

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Let there be light: From passive agricultural sensing to active intervention

Science, Volume 388, Issue 6754, June 2025.

in Science on 2025-06-26 07:00:00 UTC.

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Facing life’s wild unknowns

Science, Volume 388, Issue 6754, Page 1379-1379, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Producing hunger

Science, Volume 388, Issue 6754, Page 1378-1378, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Death Glitch

Science, Volume 388, Issue 6754, Page 1379-1379, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Gradient refractive indices enable squid structural color and inspire multispectral materials

Science, Volume 388, Issue 6754, Page 1389-1395, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Rapid polygenic adaptation in a wild population of ash trees under a novel fungal epidemic

Science, Volume 388, Issue 6754, Page 1422-1425, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Evidence for Hadean mafic intrusions in the Nuvvuagittuq Greenstone Belt, Canada

Science, Volume 388, Issue 6754, Page 1431-1435, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Migrating shallow slow slip on the Nankai Trough megathrust captured by borehole observatories

Science, Volume 388, Issue 6754, Page 1396-1400, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Origin and radiation of squids revealed by digital fossil-mining

Science, Volume 388, Issue 6754, Page 1406-1409, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Interplate slip before, during, and after the 2024 Mw 7 Hyuga-nada earthquake, southwest Japan

Science, Volume 388, Issue 6754, Page 1401-1405, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Spontaneous formation of urea from carbon dioxide and ammonia in aqueous droplets

Science, Volume 388, Issue 6754, Page 1426-1430, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Accelerated discovery of stable, extra-large-pore nano zeolites with micro-electron diffraction

Science, Volume 388, Issue 6754, Page 1417-1421, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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The power of reinvention

Science, Volume 388, Issue 6754, Page 1442-1442, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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In Other Journals

Science, Volume 388, Issue 6754, Page 1382-1383, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Where slow and large earthquakes meet

Science, Volume 388, Issue 6754, Page 1369-1370, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Now you see me, now you don’t

Science, Volume 388, Issue 6754, Page 1368-1369, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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A caged drug enables precision delivery

Science, Volume 388, Issue 6754, Page 1371-1372, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Genomic insights into social life in Neolithic Anatolia

Science, Volume 388, Issue 6754, Page 1372-1373, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Japan wires up offshore trenches to warn of ruptures

Science, Volume 388, Issue 6754, Page 1354-1355, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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National Academies adopts new business model amid financial storm

Science, Volume 388, Issue 6754, Page 1356-1357, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Tumors may get energy boost from nerve cells’ mitochondria

Science, Volume 388, Issue 6754, Page 1357-1358, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Order to restore NIH grants heartens scientists

Science, Volume 388, Issue 6754, Page 1359-1360, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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U.S. researchers speak up in local newspapers

Science, Volume 388, Issue 6754, Page 1360-1361, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Without a lifeline

Science, Volume 388, Issue 6754, Page 1362-1367, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Ten times faster is not 10 times better

Science, Volume 388, Issue 6754, Page 1353-1353, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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In Science Journals

Science, Volume 388, Issue 6754, Page 1381-1383, June 2025.

in Science on 2025-06-26 06:00:26 UTC.

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Evolution of SARS-CoV-2 T cell responses as a function of multiple COVID-19 boosters

da Silva Antunes et al. examine SARS-CoV-2-specific immunity across 3 years of repeated vaccinations. While antibodies increase with each booster, T cells responses plateau early and remain stable without signs of exhaustion or functional impairment. Asymptomatic infections promote Th17-like and regulatory CD4+ T cell expansion, suggesting balanced immunity.

in Cell Reports: Current Issue on 2025-06-26 00:00:00 UTC.

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Gut microbiota dysbiosis induced by brain tumors modulates the efficacy of immunotherapy

Brain tumors alter gut microbiota composition, influencing immune responses. Kim et al. show that tryptophan supplementation restores microbiota balance, particularly increasing Duncaniella dubosii, which replicates the beneficial effects of tryptophan on T cell responses and immunotherapy efficacy.

in Cell Reports: In press on 2025-06-26 00:00:00 UTC.

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Addendum: Unravelling cysteine-deficiency-associated rapid weight loss

Nature, Published online: 26 June 2025; doi:10.1038/s41586-025-09282-7

Addendum: Unravelling cysteine-deficiency-associated rapid weight loss

in Nature on 2025-06-26 00:00:00 UTC.

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Everyday painkiller made from plastic — by E. coli

Nature, Published online: 26 June 2025; doi:10.1038/d41586-025-01986-0

Study highlights potential for sustainable synthesis of paracetamol.

in Nature on 2025-06-26 00:00:00 UTC.

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Killer whales exfoliate each other with home-made scrubbers

Nature, Published online: 26 June 2025; doi:10.1038/d41586-025-01993-1

Kelp ‘loofahs’ might be first example of toolmaking by marine mammals.

in Nature on 2025-06-26 00:00:00 UTC.

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Are these the world’s oldest rocks? Fresh data confirm contested claim

Nature, Published online: 26 June 2025; doi:10.1038/d41586-025-02010-1

Scientists debate age of ancient Canadian crust as Inuit leaders work to preserve the location.

in Nature on 2025-06-26 00:00:00 UTC.

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NIH-funded science must now be free to read instantly: what you should know

Nature, Published online: 26 June 2025; doi:10.1038/d41586-025-01938-8

US biomedical agency’s public-access policy kicks in on 1 July. Nature talks to specialists about how to comply.

in Nature on 2025-06-26 00:00:00 UTC.

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‘I didn’t know someone could pursue astronomy as a career’

Nature, Published online: 26 June 2025; doi:10.1038/d41586-025-01816-3

Astronomer Willice Obonyo describes how scholarship programmes seeded a fresh crop of radioastronomers in Africa.

in Nature on 2025-06-26 00:00:00 UTC.

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RFK Jr’s vaccine advisers vote down flu-shot ingredient — but back some jabs

Nature, Published online: 26 June 2025; doi:10.1038/d41586-025-02000-3

Thimerosal is found in only a small fraction of US vaccine doses but has long been viewed with suspicion by the anti-vaccination community.

in Nature on 2025-06-26 00:00:00 UTC.

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Harvard vs Trump: what this epic battle means for science

Nature, Published online: 26 June 2025; doi:10.1038/d41586-025-02017-8

Research across science and medicine will probably shrink at one of the world’s most elite universities amid a new political reality.

in Nature on 2025-06-26 00:00:00 UTC.

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A new myeloid cell migration route

Nature Reviews Neuroscience, Published online: 26 June 2025; doi:10.1038/s41583-025-00944-z

In a mouse model of multiple sclerosis, trafficking into the brain parenchyma of the peripheral myeloid cells that are involved in the symptomaptology is shown to occur predominantly via the velum interpositum, a leptomeningeal tract that runs underneath the hippocampal formation.

in Nature Reviews on 2025-06-26 00:00:00 UTC.

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A reality check

Nature Reviews Neuroscience, Published online: 26 June 2025; doi:10.1038/s41583-025-00942-1

This study reveals a mechanism through which the brain can determine whether perceptual signals reflect external reality or arise from imagination.

in Nature Reviews on 2025-06-26 00:00:00 UTC.

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Single-shot spatiotemporal vector field measurements of petawatt laser pulses

Nature Photonics, Published online: 26 June 2025; doi:10.1038/s41566-025-01698-x

A single-shot full-vector-field measurement technique for intense, ultrashort laser pulses is studied, demonstrating the approach on systems ranging from high-repetition-rate oscillators to petawatt-class lasers.

in Nature Photomics on 2025-06-26 00:00:00 UTC.

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Plasmonic biosensor enabled by resonant quantum tunnelling

Nature Photonics, Published online: 26 June 2025; doi:10.1038/s41566-025-01708-y

Exploiting resonant quantum electron tunnelling empowered by an optically resonant, doubly periodic plasmonic nanowire metasurface, a biosensor with no external light source is demonstrated, boosting the integrability of the biosensor.

in Nature Photomics on 2025-06-26 00:00:00 UTC.

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GW: ultra-fast chromosome-scale visualization of genomics data

Nature Methods, Published online: 26 June 2025; doi:10.1038/s41592-025-02749-5

GW: ultra-fast chromosome-scale visualization of genomics data

in Nature Methods on 2025-06-26 00:00:00 UTC.

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CryoDRGN-AI: neural ab initio reconstruction of challenging cryo-EM and cryo-ET datasets

Nature Methods, Published online: 26 June 2025; doi:10.1038/s41592-025-02720-4

CryoDRGN-AI is a deep learning system for ab initio reconstruction of dynamic biomolecular complexes from cryo-electron microscopy and cryo-electron tomography imaging datasets.

in Nature Methods on 2025-06-26 00:00:00 UTC.

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Author Correction: Mitochondrion-specific dendritic lipopeptide liposomes for targeted sub-cellular delivery

Nature Communications, Published online: 26 June 2025; doi:10.1038/s41467-025-61381-1

Author Correction: Mitochondrion-specific dendritic lipopeptide liposomes for targeted sub-cellular delivery

in Nature Communications on 2025-06-26 00:00:00 UTC.

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Author Correction: Modular RNA motifs for orthogonal phase separated compartments

Nature Communications, Published online: 26 June 2025; doi:10.1038/s41467-025-61207-0

Author Correction: Modular RNA motifs for orthogonal phase separated compartments

in Nature Communications on 2025-06-26 00:00:00 UTC.

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Author Correction: Reconstruction of human dispersal during Aurignacian on pan-European scale

Nature Communications, Published online: 26 June 2025; doi:10.1038/s41467-025-61311-1

Author Correction: Reconstruction of human dispersal during Aurignacian on pan-European scale

in Nature Communications on 2025-06-26 00:00:00 UTC.

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Author Correction: Support-free iridium hydroxide for high-efficiency proton-exchange membrane water electrolysis

Nature Communications, Published online: 26 June 2025; doi:10.1038/s41467-025-61210-5

Author Correction: Support-free iridium hydroxide for high-efficiency proton-exchange membrane water electrolysis

in Nature Communications on 2025-06-26 00:00:00 UTC.

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Doublet decoding of tRNASer3 demonstrates plasticity of ribosomal decoding center

Nature Communications, Published online: 26 June 2025; doi:10.1038/s41467-025-61016-5

The ribosomal decoding center monitors accurate translation of 3-base mRNA codons. Here, the authors use cryo-EM to show how one of the monitoring bases of the ribosome enables a frameshift-inducing tRNA to instead read a 2-base codon.

in Nature Communications on 2025-06-26 00:00:00 UTC.

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Uncovering minimal pathways in melanoma initiation

Nature Communications, Published online: 26 June 2025; doi:10.1038/s41467-025-60742-0

Identifying the sequence of molecular events that leads to melanoma remains challenging. Here, the authors analyse the early stages of melanoma development in mouse models of minimal genetic induction, identifying melanoma emergence with little evidence of consistent DNA mutation or common copy number variation.

in Nature Communications on 2025-06-26 00:00:00 UTC.

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Daily electric field treatment improves functional outcomes after thoracic contusion spinal cord injury in rats

Nature Communications, Published online: 26 June 2025; doi:10.1038/s41467-025-60332-0

Spinal cord injury leads to lasting motor and sensory loss, with limited treatment options. Here, the authors show that subdural electric field stimulation delivered across the injury via an ultra-thin implant improves functional recovery in rats.

in Nature Communications on 2025-06-26 00:00:00 UTC.

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Integrin beta 1 facilitates non-enveloped hepatitis E virus cell entry through the recycling endosome

Nature Communications, Published online: 26 June 2025; doi:10.1038/s41467-025-61071-y

Hepatitis E virus exists in two forms in patients: naked and quasi-enveloped. Using a new imaging method, the authors found that these forms enter cells through different pathways, directed by interaction of the capsid protein with integrin beta 1.

in Nature Communications on 2025-06-26 00:00:00 UTC.

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Membraneless protocell confined by a heat flow

Nature Physics, Published online: 26 June 2025; doi:10.1038/s41567-025-02935-4

It is unclear how cell compartmentalization emerged in prebiotic conditions. Now it is shown that a temperature gradient in a confined space can bring the core components of a cell together.

in Nature Physics on 2025-06-26 00:00:00 UTC.

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Observation of the transverse Thomson effect

Nature Physics, Published online: 26 June 2025; doi:10.1038/s41567-025-02936-3

When a charge current, a temperature gradient and a magnetic field are applied orthogonally to each other, a conductor is expected to heat or cool. This so-called transverse Thomson effect has now been observed for a bismuth–antimony alloy.

in Nature Physics on 2025-06-26 00:00:00 UTC.

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Tunable interplay between light and heavy electrons in twisted trilayer graphene

Nature Physics, Published online: 26 June 2025; doi:10.1038/s41567-025-02956-z

Graphene multilayers can host heavy electrons in flat bands alongside light electrons in Dirac cones. Local probes now reveal that a finite Dirac electron population persists at the Fermi level while correlated states form in the flat bands.

in Nature Physics on 2025-06-26 00:00:00 UTC.

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Correction: Snow depth measurements from Arctic tundra and boreal forest collected during NASA SnowEx Alaska campaign

Scientific Data, Published online: 26 June 2025; doi:10.1038/s41597-025-05430-w

Correction: Snow depth measurements from Arctic tundra and boreal forest collected during NASA SnowEx Alaska campaign

in Nature scientific data on 2025-06-26 00:00:00 UTC.

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Gamma Knife stereotactic radiotherapy combined with tislelizumab as later-line therapy in pMMR/MSS/MSI-L metastatic colorectal cancer: a phase II trial analysis

-/-

in eLife on 2025-06-26 00:00:00 UTC.

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Focal adhesion-derived liquid-liquid phase separations regulate mRNA translation

Liquid-liquid phase separation (LLPS) has emerged as a major organizing principle in cells. Recent work showed that multiple components of integrin-mediated focal adhesions, including p130Cas can form LLPS, which govern adhesion dynamics and related cell behaviors. In this study, we found that the focal adhesion protein p130Cas drives the formation of structures with the characteristics of LLPS that bud from focal adhesions into the cytoplasm. Condensing concentrated cytoplasm around p130Cas-coated beads allowed their isolation, which were enriched in a subset of focal adhesion proteins, mRNAs, and RNA binding proteins, including those implicated in inhibiting mRNA translation. Plating cells on very high concentrations of fibronectin to induce large focal adhesions inhibited message translation which required p130Cas and correlated with droplet formation. Photo-induction of p130Cas condensates using the Cry2 system also reduced translation. These results identify a novel regulatory mechanism in which high adhesion limits message translation via induction of p130Cas-dependent cytoplasmic LLPS. This mechanism may contribute to the quiescent state of very strongly adhesive myofibroblasts and senescent cells.

in eLife on 2025-06-26 00:00:00 UTC.

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Untargeted Plasma Metabolomics in Canine Cognitive Dysfunction: The Naturally Occurring Alzheimer's Disease Analog in Dogs

Introduction: Canine Cognitive Dysfunction (CCD) is an increasingly prevalent naturally occurring neurodegenerative condition in senescent dogs that share neuropathological and clinical features with human Alzheimers disease (AD). Metabolic profiling allows for identification of new candidates for AD biomarkers, diagnostics, and therapeutics. Despite its translational potential, plasma metabolomic profiling of dogs with CDD has not been previously characterized. Methods: This case control study analyzed plasma samples from ten client owned geriatric dogs, including five with severe CCD and five age matched, clinically healthy controls. Untargeted plasma metabolomics was performed using ultra-performance liquid chromatography mass spectrometry (UPLC-MS). Multivariate and univariate statistical analyses identified significant metabolic differences between the groups. Metabolites were considered significant based on a variable importance in projection (VIP) score > 1.5, fold change (FC) > 2.0, and adjusted p-value < 0.05. Results: Fifteen metabolites across seven chemical classes were significantly altered in CCD dogs compared to controls, including glycerophospholipids, steroid derivatives, indoles, and mitochondrial-related compounds. Notably, elevated lysophosphatidic acid (LPA 20:2/0:0) and reduced ubiquinone-2 levels suggest dysregulation in neuroinflammatory and oxidative stress pathways. Cholesterol exhibited the highest FC and VIP scores, further reinforcing its role in AD pathogenesis. Hierarchical clustering and pathway enrichment analyses supported distinct metabolic signatures in CCD that mirror those observed in human AD. Discussion: This is the first untargeted plasma metabolomic profiling of dogs with CCD, revealing systemic metabolic disturbances that align with AD pathophysiology. Data was collected from senescent community-dwelling companion dogs, which enhances the studys ecological and translational relevance. It supports the utility of CCD as an AD model and highlight candidate plasma biomarkers that warrant further investigation. Future longitudinal studies integrating metabolomics with neuroimaging, histopathology, and behavioral assessments are required to validate these findings and contribute to AD biomarker discovery and therapeutic development

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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CATERPillar: A Flexible Framework for Generating White Matter Numerical Substrates with incorporated Glial Cells

Monte Carlo diffusion simulations in numerical substrates are valuable for exploring the sensitivity and specificity of the diffusion MRI (dMRI) signal to realistic cell microstructure features. A crucial component of such simulations is the use of numerical phantoms that accurately represent the target tissue, which is in this case, cerebral white matter (WM). This study introduces CATERPillar (Computational Axonal Threading Engine for Realistic Proliferation), a novel method that simulates the mechanic of axonal growth using overlapping spheres as elementary units. CATERPillar facilitates parallel axon development while preventing collisions, offering user control over key structural parameters such as cellular density, tortuosity, beading and myelination. Its uniqueness lies in its ability to generate not only realistic axonal structures but also realistic glial cells, enhancing the biological fidelity of simulations. We showed that our grown substrates feature distributions of key morphological parameters that agree with those from histological studies. The structural realism of the astrocytic components was quantitatively validated using Sholl analysis. Furthermore, the time-dependent diffusion in the extra- and intra-axonal compartments accurately reflected expected characteristics of short-range disorder, as predicted by theoretical models. CATERPillar is open source and can be used to (a) develop new acquisition schemes that sensitise the MRI signal to unique tissue microstructure features, (b) test the accuracy of a broad range of analytical models, and (c) build a set of substrates to train machine learning models on.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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Similar States, Different Paths: Neurodynamics of diverse meditation techniques

Meditation encompasses diverse practices that train attention inward, in contrast to externally oriented task states. However, the neurodynamic features distinguishing meditative states from non-meditative states across traditions remain unclear. We analyzed high-density EEG data (N=170; 121 advanced meditators, 49 controls) across four traditions: Vipassana, Brahma Kumaris Raja Yoga, Heartfulness, and Isha Yoga. EEG features spanned oscillatory, aperiodic, nonlinear, and timescale components. Using random forest classifiers, we distinguished meditative from non-meditative states with robust classification performance (91%). Nonlinear features contributed the most, suggesting a core neurodynamic profile. Classification performance was higher in advanced meditators (92%) than in controls (85%), with distinct feature importance: nonlinear and aperiodic features dominated in meditators, and oscillatory and timescale features in controls. Each tradition showed distinct neurodynamic profiles, indicating technique-specific constellations. Our findings revealed shared yet distinct neurodynamic signatures across meditation techniques, suggesting that multiple neurodynamic pathways lead to meditative states.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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Shallow Recurrent Decoders for Neural and Behavioral Dynamics

Machine learning algorithms are affording new opportunities for building bio-inspired and data-driven models characterizing neural activity. Critical to understanding decision making and behavior is quantifying the relationship between the activity of neuronal population codes and individual neurons. We leverage a SHallow REcurrent Decoding (SHRED) architecture for mapping the dynamics of population codes to individual neurons and other proxy measures of neural activity and behavior. SHRED is a robust and flexible sensing strategy which allows for decoding the diversity of neural measurements with only a few sensor measurements. Thus estimates of whole brain activity, behavior and individual neurons can be constructed with only a few neural time-series recordings. This opens up the potential for using non-invasive, or minimally invasive, measurements for estimating difficult to achieve , or invasive, large scale brain and neural recordings. SHRED is constructed from a temporal sequence model, which encodes the temporal dynamics of limited sensor data in multiple scenarios, and a shallow decoder, which reconstructs the corresponding high-dimensional neuronal and/or behavioral states. We demonstrate the capabilities of the method on a number of model organisms including emph{C.~elegans}, mouse, zebrafish, and human biolocomotion.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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In vivo palpation of anisotropic human brain tissue using MRI

The mechanical stiffness of brain parenchyma varies across physiological states and pathophysiological conditions, such as during normal and abnormal development, in degenerative diseases and disorders, like Alzheimers disease and traumatic brain injury (TBI), neuronal activation, and sleep via the glymphatic brain waste clearance mechanism. Despite its biological and clinical importance, relatively few techniques exist to measure and map mechanical properties of brain tissue non-invasively and in vivo. MR elastography (MRE) is an established method that has been widely used to estimate tissue stiffness in the liver by applying mechanical waves using an external tamper and measuring their resulting deformations. However, applying MRE in the brain is more challenging due to the skull and cerebrospinal fluid (CSF), which impede mechanical wave propagation, and tissue mechanical anisotropy, which requires a 4th-order tensor description. In this study, we propose using the intrinsic deformation of brain tissue caused by periodic cardiac pulsation to measure the 4th-order stiffness tensor throughout the brain while simultaneously estimating the 2nd-order diffusion tensor in each voxel throughout the cardiac cycle, which we use as a priori information in the reconstruction of the stiffness tensor. While the DTI-derived mean diffusivity (MD) appears uniform throughout brain parenchyma, stiffness maps obtained at about 1 Hz (i.e., at the fundamental cardiac frequency) show contrast within gray matter, and within white matter pathways such as along the corpus callosum, internal capsule, corona radiata, etc. Generally, stiffness differences at internal tissue boundaries are expected to lead to local stress concentration, which may predispose tissues to damage in TBI. Therefore, our novel tamperless MRE method has the potential to not only identify such interfaces, but assess changes in tissue stiffness there that might occur following injury.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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Early transcriptional signatures of MeCP2 positive and negative cells in Rett syndrome

Rett syndrome (RTT) is an X-linked neurological disorder caused by MECP2 mutations. Like other X-linked disorders, RTT patients have sex-specific differences in clinical presentation due to distinct cellular environments, where females have ~50% of cells expressing either a mutant or wild-type copy of MECP2 (mosaic) and males have 100% of cells expressing a mutant MECP2 (non-mosaic). Typical RTT females have a short window of normal early development until ~6-18 months, followed by regression and progressive decline, whereas neonatal encephalopathy is more likely in RTT males. How these sex-specific differences in cellular context contribute molecularly to RTT pathogenesis, particularly in the presymptomatic stages of RTT females, remains poorly understood. Here, we profiled the hippocampal transcriptomes of female (Mecp2+/-) and male (Mecp2-/y) RTT mice at early timepoints using both bulk and single-nucleus RNA-seq, including sorted MeCP2 positive (MeCP2+) and MeCP2 negative (MeCP2-) neurons in female mice. We identified a core disease signature consisting of 12 genes consistently dysregulated only in MeCP2- cells across RTT models. Moreover, we uncovered non-cell-autonomous effects exclusively in female MeCP2+ excitatory neurons, but not inhibitory neurons, suggesting excitatory circuits are more vulnerable early in the mosaic RTT environment. The single-nuclei data also revealed that a previously underappreciated MeCP2- interneuron subtype had the most transcriptional dysregulation in both male and female RTT hippocampi. Together, these data highlight the different effects of MeCP2 loss on excitatory and inhibitory circuits between the mosaic and non-mosaic environment that appear early in RTT pathogenesis.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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Asymmetric increase in episodic and procedural memory interference in older adults

In younger adults, newly formed procedural memories are weakened by the subsequent formation of episodic memories (E[->]P interference) and vice versa (P[->]E interference; "cross-memory interference"). Older adults experience significant decline in episodic memory but maintain relatively intact procedural memory. This asymmetric decline in memory may also cause an asymmetric change in cross-memory interference compared to younger adults. For example, older adults may experience a significant increase in one type of cross-memory interference while leaving the other unchanged. Additionally, decline in episodic memory may cause E[->]P interference to either increase or decrease depending on how the episodic and procedural memory systems interact. However, no study to our knowledge has compared cross-memory interference between younger and older adults. We investigated cross-memory interference in younger and older adults by measuring E[->]P (Exp. 1) and P[->]E (Exp. 2) interference in 40 younger (18-40 years old) and 40 older ([≥] 55 years old) adults. Compared to younger adults, the results show that older adults experience significantly stronger E[->]P interference while P[->]E interference was statistically indistinguishable between groups. These results confirm that older adults experience an asymmetric increase in cross-memory interference and suggest that the increase in E[->]P interference is related to the asymmetric decline in episodic memory relative to procedural memory.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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Comparative Systematic Analysis of Gray Matter BiophysicalModels on a Public Dataset

Biophysical models of diffusion tailored to characterize gray matter (GM) microstructure are gaining traction in the neuroimaging community. NEXI, SMEX, SANDI, and SANDIX represent recent efforts to incorporate different microstructural features,such as soma contributions and inter-compartment exchange, into the diffusion MRI (dMRI) signal. In this work, we present a comparative evaluation of these four gray matter models on a single, publicly available in vivo human dataset, the Connectome Diffusion Microstructure Dataset (CDMD), acquired with two diffusion times. Using the open-source Gray Matter Swiss Knife toolbox, we estimate cortical microstructure metrics in 26 healthy subjects and evaluate goodness of fit, anatomical patterns and consistency with previous studies. CDMD data yielded GM parameter estimates consistent with values reported in previous studies. This retrospective cross-model analysis establishes the feasibility of estimating exchange models from only two diffusion times and highlights trade-offs in biological specificity, model complexity, and fitting robustness, critical considerations when choosing a model for future clinical and research applications

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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Scanning for Representation: A Scoping Review of Racial and Ethnic Diversity in MRI Studies of the Maternal Brain

A growing number of magnetic resonance imaging (MRI) studies are examining brain changes across pregnancy and early motherhood, gaining fundamental insight into the neural adaptations of motherhood, with critical clinical and policy implications for supporting mother, child, and family unit. As the field takes off, now is the time to take stock of the current literature and neuroscience practices, to ensure that the field is based on studies that are robust, representative, and transparent. Here, we conducted a scoping review to understand the racial and ethnic diversity of participants reported in MRI studies of the maternal brain, guided by the Joanna Briggs Institute methodology. Our findings highlight three key issues in the 185 identified studies of the maternal brain using MRI: (1) the widespread underreporting of participant racial and ethnic data, with only 38.38% of studies reporting race and/or ethnicity demographics; (2) the overrepresentation of white participants, with 46.83% of the samples that report race and/or ethnicity identifying as white/Caucasian; and (3) the disproportionate geographical locations of studies, with 68.65% of studies from North America or Europe and Central Asia. These findings raise concerns about the generalizability of existing research beyond WEIRD (western, educated, industrialized, rich and democratic) populations, and underscore the urgent need for concerted structural change in neuroscience research practices. While identifying a lack of diversity is only the first step, this scoping review serves as a call to action for greater representation in future research, for our own research group as well as others.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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Neuromechanical Simulation with NEURON and MuJoCo

In computational neuroscience, simulation platforms generally do not have adequate tools to model the brain, body and environment simultaneously. We demonstrate a method for simulating neuromechanical models using a novel combination of widely used software platforms: NEURON and MuJoCo. Different neural models are used to control a realistic musculoskeletal model in both open-loop and closed-loop configurations. Three models are presented: (1) an open-loop model using simple spiking neurons from the NEURON model library; (2) an open-loop model using realistic, spiking motoneurons; and (3) a closed-loop central pattern generator with feedback from the physics engine.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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Mapping the projectional architecture of the mouse midbrain dopaminergic system using cell type-specific barcoding

Brain-wide neural circuits are formed by the diverse axonal branching patterns of many individual neurons. Here we introduce POINTseq (projections of interest by sequencing), a high-throughput and user-friendly barcoded connectomics method that uses cell type specific barcoding and sequencing to rapidly map single-cell projections of a cell type of interest for thousands of neurons per animal. POINTseq leverages pseudotyping of Sindbis virus and a specific alphavirus-cellular receptor pair to make Sindbis infections cell type specific. It thus integrates MAPseq-style high-throughput barcoded projection mapping with the established viral-genetic neural circuit analysis toolbox. We validated POINTseq by mapping genetically and projection-defined cell populations in the mouse motor cortex. We then applied POINTseq to midbrain dopaminergic neurons and reconstructed the brain-wide single-cell projections of 3,813 dopaminergic neurons in ventral tegmental area (VTA) and substantia nigra pars compacta (SNc). We define over 30 connectomic cell types, vastly exceeding the known diversity of dopaminergic cell types, and identify stereotyped projection motifs that may mediate parallel dopamine signaling. This data constitutes the anatomical substrate on which the diverse functions of dopamine in the brain are built.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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Learning, sleep replay and consolidation of contextual fear memories: A neural network model

Contextual fear conditioning is an experimental framework widely used to investigate how aversive experiences affect the valence an animal associates with an environment. While the initial formation of associative context-fear memories is well studied -- dependent on plasticity in hippocampus and amygdala -- the neural mechanisms underlying their subsequent consolidation remain less understood. Recent evidence suggests that the recall of contextual fear memories shifts from hippocampal-amygdalar to amygdalo-cortical networks as they age. This transition is thought to rely on sleep. In particular, neural replay during hippocampal sharp-wave ripple events seems crucial, though open questions regarding the involved neural interactions remain. Here, we propose a biologically informed neural network model of context-fear learning. It expands the scope of previous models through the addition of a sleep phase. Hippocampal representations of context, formed during wakefulness, are replayed in conjunction with cortical and amygdalar activity patterns to establish long-term encodings of learned fear associations. Additionally, valence-coding synapses within the amygdala undergo overnight adjustments consistent with the synaptic homeostasis hypothesis of sleep. The model reproduces experimentally observed phenomena, including context-dependent fear renewal and time-dependent increases in fear generalisation. Few neural network models have addressed fear memory consolidation and to our knowledge, ours is the first to incorporate a neural mechanism enabling it. Our framework yields testable predictions about how disruptions in synaptic homeostasis may lead to pathological fear sensitization and generalisation, thus potentially bridging computational models of fear learning and mechanisms underlying anxiety symptoms in disorders such as PTSD.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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Dynamic feedforward and feedback influences on left ventral occipitotemporal cortex: evidence from word and pseudoword reading

Left ventral occipitotemporal cortex (vOT) is crucial in reading, yet its functional role remains debated. Competing theories paint it as either a prelexical feedforward hub or a bidirectional interface between sensory and higher-order linguistic systems. To address the debate, we investigated the temporal and spectral dynamics of information flow involving left vOT during visual word and pseudoword reading using magnetoencephalography (MEG). The pseudowords varied in the degree to which they orthographically resembled real words. By combining two directed connectivity metrics, i.e., phase slope index (PSI) and Granger causality (GC), we converged on a hybrid model of left vOT function that reconciles the competing perspectives. Feedforward connectivity from low-level visual areas to vOT emerged at around 100 ms post stimulus similarly across all conditions, spanning a wide frequency range. Subsequently, feedforward orthographic information flowed from left vOT to higher-order areas, especially left superior temporal cortex (ST), at the low gamma band. This flow strength was modulated by word-likeness, being stronger for real words and word-like pseudowords than complete pseudowords. Conversely, feedback flow from left ST to vOT was observed in the low beta band for pseudowords, and occurred later for word-like than complete pseudowords. This indicates that greater processing demands modulate the direction of information flow, necessitating top-down linguistic constraints to facilitate reading. Our findings clarify the functional role of left vOT and explain when and why its connectivity may show as feedforward or bidirectional depending on time and task.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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NERVE GROWTH FACTOR IS SUFFICIENT TO CAUSE MULTIPLE OSTEOARTHRITIS-RELEVANT PATHOLOGICAL FEATURES IN NAIVE MURINE KNEE JOINTS

BACKGROUND: Nerve growth factor (NGF), a key mediator of pain and inflammation, is increased in joints with osteoarthritis (OA). Neutralizing NGF with monoclonal antibodies has shown analgesic effects in painful knee OA, but clinical development was stopped due to side effects in the joints. Knowledge about the biological effects of long-term exposure of joint tissues to NGF is limited. Therefore, we aimed to explore the effects of repeated intra-articular (IA) injections of NGF into the knee joints of healthy mice on pain and sensitization, as well as joint innervation and structure. METHODS: We conducted five experiments in male C57BL/6 mice. In Experiment 1, NGF (50ng or 500ng) or vehicle was injected IA into the knee of naive wildtype (WT) mice, twice a week for 4 weeks. We assessed knee swelling, knee hyperalgesia and histopathology. In Experiment 2, mice were injected with 500ng NGF or vehicle, twice a week for 4 weeks and microCT of the knee was performed. In Experiment 3, NaV1.8-tdTomato reporter mice were injected with 500ng NGF or vehicle, twice a week for 4 weeks, and joint innervation was assessed. In Experiment 4, WT mice received 500ng NGF or vehicle twice a week for 4 weeks and were used for single cell RNA sequencing (scRNAseq) of the synovium. In Experiment 5, L3-L5 DRGs of mice that received 3 IA injections of 500ng NGF or vehicle twice a week were used for bulk RNA sequencing. RESULTS: Repeated bi-weekly IA injections of NGF caused knee hyperalgesia in naive mice. NGF caused dose-dependent knee swelling, synovial pathology, increased bone mineral density and trabecular bone thickness in the medial subchondral bone, growth of pre-osteophytes in the medial compartment, but no cartilage degeneration. NGF injection caused sprouting of NaV1.8+ neurons in the medial but not the lateral synovium. ScRNAseq of the synovium revealed upregulated genes related to neuronal sprouting, synovial fibrosis and ossification, confirming histopathological findings. Bulk RNA seq of DRG showed upregulated pathways related to axonal growth. CONCLUSIONS: In healthy mouse knees, NGF induced mechanical sensitization, synovitis, neoinnervation in the medial synovium, subchondral bone changes and pre-osteophyte growth in the medial compartment, thus capturing many pathological changes observed in OA, except cartilage damage.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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Neural correlates of evidence accumulation in social-affective decision-making under perceptual ambiguity

Evidence accumulation models have been successfully applied to decision-making in sensory and cognitive domains; however, it remains unclear how this process is regulated when perceptual ambiguity arises from social-affective content. Here, we integrate computational modeling with multimodal neuroscience to characterize how perceptual ambiguity in emotion judgment shapes decision dynamics. Participants viewed perceptually ambiguous stimuli, morphed images of two categories, such as happy and fearful facial expression, and made binary categorization decisions. Using drift diffusion modeling (DDM), we first demonstrate that drift rate, a key index of evidence accumulation, decreases as perceptual ambiguity increases. Scalp electroencephalography (EEG) data reveal that the magnitude of the late positive potential (LPP) tracks the speed of evidence accumulation in both emotional and non-emotional stimulus categories, but only when the ambiguous dimension is relevant to the categorization decision. Similar to LPP magnitude, single unit recordings from the dorsomedial prefrontal cortex (dmPFC) and amygdala show that neuronal firing rates in the two regions also encode drift rate. Moreover, fMRI-based functional connectivity reveals that the strength of connectivity between the amygdala and dmPFC correlates with individual differences in drift rate. To establish the causal role of the dmPFC, we applied anodal transcranial direct current stimulation (tDCS) targeting the dmPFC in patients with schizophrenia and found that stimulation enhanced evidence accumulation speed in emotion categorization under perceptual ambiguity. These findings identify a distributed corticolimbic circuit that dynamically modulates evidence accumulation during social-affective decision-making under perceptual ambiguity. Our results bridge social-affective and perceptual neuroscience, offering a translational framework for understanding emotion recognition and decision-making impairments.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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Anterior cingulate folding pattern is altered in autism spectrum disorder

Neuroimaging research has identified focal differences in the cerebral cortex of individuals with autism spectrum disorder (ASD), particularly in the cortical folds (sulci) within higher-level association cortices. The present study investigated the sulcal patterning and morphology of the anterior cingulate cortex (ACC) in individuals with ASD compared to neurotypical (NT) individuals for the first time. We used neuroimaging data from 50 NT and 50 ASD participants. All participants were under 20 years old and male. The two groups were age-matched. Using established criteria and cortical reconstructions generated from each participant's T1-weighted magnetic resonance imaging scans with FreeSurfer, we identified the defining sulcal feature of ACC, the variably present paracingulate sulcus (PCGS): its presence in the left and right hemispheres, and asymmetry in PCGS presence between hemispheres. Finally, multiple quantitative morphological features (length, depth, and cortical thickness mean and standard deviation) were extracted from the PCGS using FreeSurfer tools. Analyses revealed that NT participants were more likely to have asymmetrical PCGS patterns than ASD participants (controlling for age and scanner site). However, none of the quantitative morphological features differed between groups. These findings suggest the presence of a variation in the prenatal neurodevelopment of ACC in young males with ASD; however, further research is necessary to uncover the role of this observed difference in the pathogenesis of ASD. The present study also adds to the growing literature implicating variations in PCGS patterning as a trait marker across multiple disorders.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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Gamma - Theta - Spike Coupling Coordinates Sequential Memory in Human MTL

It has been suggested that hierarchical synchronization of theta and gamma oscillations coordinates neural activity during sequence memory. Yet, the role of gamma oscillations and their interaction with theta and single - unit activity (SUA) has not been directly examined in humans. We analysed simultaneous micro wire recordings of SUA (N = 1417 units) and local field potentials (N = 917 channels) from the medial temporal lobe (MTL) of epilepsy patients performing a visual multi-item sequence memory task. During encoding, both spiking activity and gamma power contained item - specific information and were temporally coupled. During memory maintenance, stimulus-specific gamma and spiking were structured in brief burst periods during which both signals were tightly synchronized and preferentially aligned to similar theta phases predictive of sequential stimulus position. These findings demonstrate that theta - gamma - spike interactions support a phase - based multiplexed code for sequential memories in the human MTL.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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Misinterpreting electrophysiology in human cognitiveneuroscience

An axiomatic view in contemporary neuroscience is that EEG components such as eventrelated brain potentials (ERPs) and oscillations are directly interpretable as manifestations of biological processes that support sensory, motor, and cognitive constructs of interest. This premise justifies and propels research programs in laboratories worldwide, but with a substantial social and economic cost, warranted by the potential for basic-science discovery and the resulting bench-to-bedside transfer for health and disease. But a different premise would be more fruitful. This article proposes that EEG components in psychophysiological experiments relate to cognition indirectly through their more direct relationship with oculomotor action. The common experimental design that includes a baseline ocular fixation period preceding stimulus presentation provides an excellent template with which to develop the present proposal. Electrophysiological and eye-tracking evidence (3 published and 3 new data sets: 6 experiments, Ntotal = 204, in the context of face and affective picture viewing, reading, listening, rest, and microsleep) demonstrates how and why common conclusions, and reliance on them in clinical practice/treatment efficacy and drug development studies, are at best premature. Results indicate that the oculomotor system plays a mediating role between such EEG phenomena and cognition. Present evidence supports a complementary view of how EEG can shape the development of a broader thought horizon in psychophysiological theory and practice.

in bioRxiv: Neuroscience on 2025-06-26 00:00:00 UTC.

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Automatic OptoDrive for Extracellular Recordings and Optogenetic Stimulation in Freely Moving Mice

Extracellular recordings in freely moving mice, especially those with movable electrodes (microdrives), are crucial for understanding brain function. However, existing microdrives are often heavy, expensive, fragile, and unsuited for long-term studies with multichannel recordings. The OptoDrive is a new, lightweight (3.2 g), low-cost system for chronic neural recordings and optogenetic manipulation in mice. It features a detachable, 16-channel tungsten-wire electrode assembly with a 3 mm stroke (15 μm step displacement) and an integrated optical fiber. This system enables repeated implantation and explantation without surgery, requiring only gas anesthesia. The OptoDrive has demonstrated stable recordings from the lateral hypothalamus of freely behaving mice for nearly 1 month and successful optogenetic silencing of neuronal activity. In conclusion, OptoDrive offers a cost-effective, compact solution for long-term electrophysiology and optogenetics in freely moving mice.

in eNeuro on 2025-06-25 16:30:30 UTC.

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Accurate Tracking of Locomotory Kinematics in Mice Moving Freely in Three-Dimensional Environments

Marker-based motion capture (MBMC) is a powerful tool for precise, high-speed, three-dimensional tracking of animal movements, enabling detailed study of behaviors ranging from subtle limb trajectories to broad spatial exploration. Despite its proven utility in larger animals, MBMC has remained underutilized in mice due to the difficulty of robust marker attachment during unrestricted behavior. In response to this challenge, markerless tracking methods, facilitated by machine learning, have become the standard in small animal studies due to their simpler experimental setup. However, trajectories obtained with markerless approaches at best approximate ground-truth kinematics, with accuracy strongly dependent on video resolution, training dataset quality, and computational resources for data processing. Here, we overcome the primary limitation of MBMC in mice by implanting minimally invasive markers that remain securely attached over weeks of recordings. This technique produces high-resolution, artifact-free trajectories, eliminating the need for extensive post-processing. We demonstrate the advantages of MBMC by resolving subtle drug-induced kinematic changes that become apparent only within specific behavioral contexts, necessitating precise three-dimensional tracking beyond simple flat-surface locomotion. Furthermore, MBMC uniquely captures the detailed spatiotemporal dynamics of harmaline-induced tremors, revealing previously inaccessible correlations between body parts and thus significantly improving the translational value of preclinical tremor models. While markerless tracking remains optimal for many behavioral neuroscience studies in which general posture estimation suffices, MBMC removes barriers to investigations demanding greater precision, reliability, and low-noise trajectories. This capability significantly broadens the scope for inquiry into the neuroscience of movement and related fields.

in eNeuro on 2025-06-25 16:30:30 UTC.

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This Week in The Journal

in Journal of Neuroscience on 2025-06-25 16:30:27 UTC.

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Modulation of Dopamine Neurons Alters Behavior and Event Encoding in the Nucleus Accumbens during Pavlovian Conditioning

When a cue is located away from its associated reward, some animals will learn to approach the site of reward (goal-tracking behavior) while others will approach the cue (sign-tracking behavior). The acquisition of sign tracking, but not goal tracking, is dependent on dopamine in the nucleus accumbens (NAc), and we have previously demonstrated that reward-evoked activity in the NAc core may reflect different patterns of dopamine release in sign tracker versus goal tracker individuals. However, a causal relationship among dopamine release, NAc activity, and sign tracking has not been established. Using male and female TH::Cre rats, we expressed inhibitory or excitatory opsins in dopamine neurons of the ventral tegmental area (VTA) and examined the impact of optical manipulation of dopamine neurons on behavior and concurrent NAc neuronal activity. We found that inhibition of VTA dopamine neurons at the time of reward suppressed the acquisition of sign-tracking, but not goal-tracking, behavior. On the other hand, stimulation of dopamine neurons did not alter the acquisition of sign tracking; however, cessation of stimulation impeded further acquisition of sign tracking. Finally, both inhibition and stimulation of VTA dopamine neurons rapidly modulated activity in a subset of NAc neurons and led to changes in cue- and reward-related activity across sessions. Overall, these findings support the ideas that sign tracking and goal tracking are the products of two different learning processes—one dopamine-dependent and one not—and that the impact of VTA dopamine on sign tracking may be mediated by activity in the NAc core.

in Journal of Neuroscience on 2025-06-25 16:30:27 UTC.

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{micro}-Opioid Receptor Control of Glutamate/GABA Coreleasing SUM and VTA Projections to the Dentate Gyrus

in Journal of Neuroscience on 2025-06-25 16:30:27 UTC.

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Distinct Regulation of Early Trafficking of the NMDA Receptors by the Ligand-Binding Domains of the GluN1 and GluN2A Subunits

N-Methyl-d-aspartate receptors (NMDARs) play a crucial role in excitatory neurotransmission, with numerous pathogenic variants identified in the GluN subunits, including their ligand-binding domains (LBDs). The prevailing hypothesis postulates that the endoplasmic reticulum (ER) quality control machinery verifies the agonist occupancy of NMDARs, but this was tested in a limited number of studies. Using microscopy and electrophysiology in the human embryonic kidney 293 (HEK293) cells, we found that surface expression of GluN1/GluN2A receptors containing a set of alanine substitutions within the LBDs correlated with the measured EC₅₀ values for glycine (GluN1 subunit mutations) while not correlating with the measured EC₅₀ values for l-glutamate (GluN2A subunit mutations). The mutant cycle of GluN1-S688 residue, including the pathogenic GluN1-S688Y and GluN1-S688P variants, showed a correlation between relative surface expression of the GluN1/GluN2A receptors and the measured EC₅₀ values for glycine, as well as with the calculated G_binding values for glycine obtained from molecular dynamics simulations. In contrast, the mutant cycle of GluN2A-S511 residue did not show any correlation between the relative surface expression of the GluN1/GluN2A receptors and the measured EC₅₀ values for l-glutamate or calculated G_binding values for l-glutamate. Coexpression of both mutated GluN1 and GluN2A subunits led to additive or synergistic alterations in the surface number of GluN1/GluN2A receptors. The synchronized ER release by ARIAD technology confirmed the altered early trafficking of GluN1/GluN2A receptors containing the mutated LBDs. The microscopical analysis from embryonal rat hippocampal neurons (both sexes) corroborated our conclusions from the HEK293 cells.

in Journal of Neuroscience on 2025-06-25 16:30:27 UTC.

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Anchoring Functional Connectivity to Individual Sulcal Morphology Yields Insights in a Pediatric Study of Reasoning

A salient neuroanatomical feature of the human brain is its pronounced cortical folding, and there is mounting evidence that sulcal morphology is relevant to functional brain architecture and cognition. However, the relationships between sulcal anatomy, brain activity, and behavior are still poorly understood. We previously found that the depth of three small, shallow sulci in the lateral prefrontal cortex (LPFC) was linked to reasoning performance during development (Voorhies et al., 2021). These findings beg the question: What is the linking mechanism between sulcal morphology and cognition? Here, we investigated functional connectivity among sulci in LPFC and the lateral parietal cortex in participants drawn from the same sample as our previous study. We leveraged manual parcellations (21 sulci/hemisphere, 1,806 total) and functional magnetic resonance imaging data from a reasoning task from 43 participants aged 7–18 years (20 females). We conducted clustering and classification analyses of individual-level functional connectivity among sulci. Broadly, we found that (1) connectivity patterns of individual sulci could be differentiated and more accurately than cortical patches equated for size and shape; (2) sulcal connectivity did not consistently correspond with that of probabilistic labels or large-scale networks; (3) sulci clustered based on connectivity patterns, not dictated by spatial proximity; and (4) across individuals, greater depth was associated with higher network centrality for several sulci under investigation. These results illustrate how sulcal morphology can be functionally relevant and provide proof of concept that using sulci to define an individual coordinate space for functional connectomes is a promising future direction.

in Journal of Neuroscience on 2025-06-25 16:30:27 UTC.

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Erratum: Bellocchio et al., "Sustained Gq-Protein Signaling Disrupts Striatal Circuits via JNK"

in Journal of Neuroscience on 2025-06-25 16:30:27 UTC.

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Sustained Hippocampal Theta Oscillations Reflect Experience-Dependent Learning in Backward Temporal Order Memory Retrieval

Navigating within our neighborhood or learning a set of concepts requires remembering the relationship between individual items that are presented sequentially. Theta activity in the mammalian hippocampus is related to the encoding and recall of relational structures. However, how theta oscillations are involved in retrieving temporal order information in opposing directionality (forward vs backward) has not been characterized. Here, using intracranial recordings from 10 human epileptic patients of both genders with hippocampal electrodes, we tested the patients with a temporal order memory task in which they learned the spatial relationship among individual items arranged along a circular track and were tested on both forward-cued and backward-cued retrieval conditions. We found that sustained high-power oscillatory events in the hippocampal theta (2–8 Hz) band, as quantified by P_episode rate, were higher for the backward conditions during the later stage but not in the earlier stage. The theta P_episode rate results are consistent with the behavioral memory performance and the theta phase to gamma power cross-frequency coupling. Control analyses on change in theta or gamma power and their peak frequencies, aperiodic activity, hemispheric differences, and P_episode duration confirm that elevated theta rhythmic activity carry specific physiological information with respect to experience-dependent (episodic) learning. In contrast, we observed a stronger effect of forward than backward retrieval for the low gamma (30–70 Hz) P_episode rate irrespective of stages. Our results revealed how theta oscillations are specifically implicated in the learning process for efficient retrieval of temporal order memories under opposing directionality.

in Journal of Neuroscience on 2025-06-25 16:30:27 UTC.

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Abrupt and Gradual Changes in Neuronal Processing upon Falling Asleep and Awakening

The neural processes that change when falling asleep are only partially understood. At the cortical level, features of both spontaneous neural activity and sensory responses change between wakefulness and sleep. For example, in the early auditory cortex, sleep increases the occurrence of postonset silent (OFF) periods and elevates population synchrony. However, it remains unknown whether such changes occur abruptly or gradually around sleep onset and awakening. Here, we recorded spontaneous and sound-evoked neuronal spiking activity in the early auditory cortex along with polysomnography during thousands of episodes when male rats fell asleep or woke up. We found that when falling asleep, stimulus-induced neuronal silent periods (OFF periods), characteristic of nonrapid eye movement sleep, increased within a few seconds around sleep onset. In contrast, a gradual increase in neuronal population synchrony built up over tens of seconds until reaching maximal levels. EEG auditory-evoked potentials likely representing stimulus-triggered "K-complexes" changed along with postonset neuronal firing, whereas ongoing EEG slow-wave activity was associated with neuronal population synchrony. Similar effects, but with opposite direction, were observed around awakenings. The results highlight late stimulus-induced neuronal silence as a key feature changing abruptly around transitions between vigilance states, likely reflecting neuronal bistability and manifesting also in EEG-evoked potentials. More generally, these findings emphasize the added value of going beyond monitoring ongoing activity and perturbing the nervous system to reveal its state—an insight that could also help guide the development of more sensitive noninvasive monitors of falling asleep in humans.

in Journal of Neuroscience on 2025-06-25 16:30:27 UTC.

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Microglia Support Both the Singular Form of LTP Expressed by the Lateral Perforant Path and Episodic Memory

We report here that microglia exert a surprisingly discrete but functionally critical influence on synaptic plasticity in the mouse hippocampus. Treatment of adult male mice with colony-stimulating factor 1 receptor antagonist PLX5622 (PLX), with resultant depletion of forebrain microglia, did not disturb basal synaptic transmission at four synaptic connections in the hippocampus. Long-term potentiation (LTP) was also intact for three of these sites, but the singular, endocannabinoid-dependent form of LTP expressed by lateral perforant path (LPP) input to the dentate gyrus (DG) was severely impaired. The LPP–LTP defect occurred in conjunction with a pronounced increase in DG (but not neocortical) levels of 2-arachidonoylglycerol (2-AG), the retrograde (spine-to-terminal) endocannabinoid messenger that initiates LPP–LTP. Despite this, concentrations of the 2-AG synthetic enzyme diacylglycerol lipase were not affected by PLX treatment. Synaptic levels of the cannabinoid type 1 receptor, which mediates 2-AG effects on LPP–LTP, were similarly unaffected. Prior work has implicated the LPP in episodic memory. We determined that the LPP–LTP impairment in PLX-treated mice was accompanied by a failure to acquire the three basic elements of an episode: the identities, locations, and presentation order for a collection of olfactory cues. Treatment with JZL184, which inhibits the 2-AG degradative enzyme monoglyceride lipase, restored both LPP–LTP and episodic "What" encoding in PLX-treated mice. We conclude that microglia selectively regulate endocannabinoid transmission at the LPP->DG synapse and thereby potently influence synaptic plasticity at the initial stage of a corticohippocampal circuit that is critical for episodic memory.

in Journal of Neuroscience on 2025-06-25 16:30:27 UTC.

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Phonological Representations of Auditory and Visual Speech in the Occipito-temporal Cortex and Beyond

Speech is a multisensory signal that can be extracted from the voice and the lips. Previous studies suggested that occipital and temporal regions encode both auditory and visual speech features but their location and nature remain unclear. We characterized brain activity using fMRI (13 males and 11 females) to functionally and individually define bilateral fusiform face areas (FFA), the left word-selective ventral occipito-temporal cortex (word-VOTC), an audiovisual speech region in the left superior temporal sulcus (lSTS); and control regions in bilateral scene-selective parahippocampal place areas (PPA). In these regions, we performed multivariate pattern classification of corresponding phonemes (speech sounds) and visemes (lip movements). We observed that the word-VOTC and lSTS represent phonological information from both vision and sounds. The multisensory nature of phonological representations appeared selective to the word-VOTC, as we found viseme but not phoneme representation in adjacent FFA, while PPA did not encode phonology in any modality. Interestingly, cross-modal decoding revealed aligned phonological representations across the senses in lSTS, but not in word-VOTC. A whole-brain cross-modal searchlight analysis additionally revealed aligned audiovisual phonological representations in bilateral pSTS and left somato-motor cortex overlapping with oro-facial articulators. Altogether, our results demonstrate that auditory and visual phonology are represented in the word-VOTC, extending its functional coding beyond orthography. The geometries of auditory and visual representations do not align in the word-VOTC as they do in the STS and left somato-motor cortex, suggesting distinct representations across a distributed multisensory phonological network.

in Journal of Neuroscience on 2025-06-25 16:30:27 UTC.

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Nonlinear Dendritic Integration Supports Up-Down States in Single Neurons

Changes in the activity profile of cortical neurons are due to effects at the scale of local and long-range networks. Accordingly, abrupt transitions in the state of cortical neurons—a phenomenon known as Up–Down states (UDS)—have been attributed to variation in the activity of afferent neurons. However, cellular physiology and morphology may also play a role in causing UDS. This study examines the impact of dendritic nonlinearities, particularly those mediated by voltage-dependent NMDA receptors, on the response of cortical neurons to balanced excitatory/inhibitory synaptic inputs. Using a neuron model with two segregated dendritic compartments, we compared cells with and without dendritic nonlinearities. NMDA receptors boosted somatic firing in the balanced condition and increased the correlation between membrane potentials across the compartments of the neuron model. Dendritic nonlinearities elicited strong bimodality in the distribution of the somatic potential when the cell was driven with cortical-like input. Moreover, dendritic nonlinearities could detect small input fluctuations and lead to UDS whose statistics and dynamics closely resemble electrophysiological data. UDS also occurred in recurrent networks with oscillatory firing activity, as in anaesthetized animal models, when dendritic NMDA receptors were partially disabled. These findings suggest that there is a dissociation between cellular and network-level features that could both contribute to the emergence of UDS. Our study highlights the complex interplay between dendritic integration and activity-driven dynamics in the origin of cortical bistability.

in Journal of Neuroscience on 2025-06-25 16:30:27 UTC.

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The Epigenetic Reader PHF23 Is Required for Embryonic Neurogenesis

Epigenetic mechanisms are crucial in the tightly regulated process of neurogenesis from radial glial cells (RGCs) to intermediate progenitor cells (IPCs) to neurons during embryonic brain development. Plant homeodomain (PHD) finger proteins as important epigenetic readers are implicated in development and diseases, yet their roles in embryonic neurogenesis remain largely unexplored. In this study, we found different PHD finger proteins are differentially expressed along the neurogenesis trajectory. Among them, we investigated the function of PHF23 using mouse models, which is highly expressed in RGCs and IPCs, but not in neurons. Our findings demonstrate that PHF23 is essential for proper neurogenesis, and Phf23 knock-out (Phf23-KO) results in cortical developmental defects due to differentiation blockade of RGCs. Mechanistically, PHF23 bind with HDAC2, inhibiting its deacetylation activity on the active histone mark H3K27ac, thereby promoting the expression of neuronal differentiation pathway genes such as Tcf4 and Eya1. Overexpression of Tcf4 rescues the differentiation defects of Phf23-KO NSCs. These results establish PHF23 as a pivotal regulator of neurogenesis, indicating cell type-specific functions of PHD finger proteins.

in Journal of Neuroscience on 2025-06-25 16:30:27 UTC.

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Inhibition of Rho-Associated Kinases ROCK1 and ROCK2 as a Therapeutic Strategy to Reactivate the Repressed FXN Gene in Friedreich Ataxia

Friedreich ataxia (FA) is an autosomal recessive disease characterized by progressive damage to the nervous system and severe cardiac abnormalities. The disease is caused by a GAA•TTC triplet repeat expansion in the first intron of the FXN gene, resulting in epigenetic repression of FXN transcription and reduction in FXN (frataxin) protein which results in mitochondrial dysfunction. Factors and pathways that promote FXN repression represent potential therapeutic targets whose inhibition would restore FXN transcription and frataxin protein levels. Here, we performed a candidate-based RNAi screen to identify kinases, a highly druggable class of proteins, that when knocked down upregulate FXN expression. Using this approach, we identified Rho kinase ROCK1 as a critical factor required for FXN repression. ShRNA-mediated knockdown of ROCK1, or the related kinase ROCK2, increases FXN mRNA and frataxin protein levels in FA patient-derived induced pluripotent stem cells (iPSCs) and differentiated neurons and cardiomyocytes to levels observed in normal cells. We demonstrate that small molecule ROCK inhibitors, including the FDA-approved drug belumosudil and fasudil, reactivate FXN expression in cultured FA iPSCs, neurons, cardiomyocytes, and FA patient primary fibroblasts and ameliorate the characteristic mitochondrial defects in these cell types. Remarkably, treatment of transgenic FA mice of both sexes with belumosudil or fasudil upregulates FXN expression, ameliorates the mitochondrial defects in the brain and heart tissues, and improves motor coordination and muscle strength. Collectively, our study identifies ROCK kinases as critical repressors of FXN expression and provides preclinical evidence that FDA-approved ROCK inhibitors may be repurposed for treatment of FA.

in Journal of Neuroscience on 2025-06-25 16:30:27 UTC.

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Task-Switch Related Reductions in Neural Distinctiveness in Children and Adults: Commonalities and Differences

Goal-directed behavior requires the ability to flexibly switch between task sets with changing environmental demands. Switching between tasks generally comes at the cost of slower and less accurate responses. Compared with adults, children often show greater switch costs, presumably reflecting the protracted development of the ability to flexibly update task-set representations. To test whether the distinctiveness of neural task-set representations is more strongly affected by a task switch in children compared with adults, we examined multivoxel patterns of fMRI activation in 88 children (8–11 years, 49 girls, 39 boys) and 52 adults (20–30 years, 27 women, 25 men) during a task-switching paradigm. Using multivariate pattern analysis (MVPA), we investigated whether task-set representations were less distinct on switch than on repeat trials across frontoparietal, cingulo-opercular, and temporo-occipital regions. Children and adults showed lower accuracy and longer response times on switch than on repeat trials. Switch costs were similar across groups. Decoding accuracy was lower on switch than repeat trials, suggesting that switching reduces the distinctiveness of task-set representations. Reliable age differences in switch-related reductions of decoding accuracy were absent. More nuanced analyses using probability measures indicated that the distinctiveness of task sets was more affected by switch demand in children than in adults in a subset of frontal, cingulate, and temporal regions. These results point to a remarkable degree of maturity of neural representations of task-relevant information in late childhood along with more subtle region-specific age differences in the effects of task switching on rule representation.

in Journal of Neuroscience on 2025-06-25 16:30:27 UTC.

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Until the dawn: everyday experiences of people living with COVID-19 during the pandemic in Thailand [version 5; peer review: 1 approved, 1 not approved]

Background This study explores the lived experiences of individuals recovering from COVID-19, aiming to deepen understanding and inform supportive measures in future health crises. Methods Fifteen participants were recruited using purposive and snowball sampling. Data were collected through semi-structured interviews and non-aggregated behavioral observations. Interpretative Phenomenological Analysis (IPA) guided the analytic process, allowing for in-depth exploration of participants’ meaning-making. Reporting adhered to the COREQ qualitative research guidelines. Results Five superordinate themes emerged: stress, economic and social disruption, social stigma, social support, and the reappraisal of adversity (“finding meaning in misfortune”). Participants’ narratives revealed complex adaptive processes shaped by both contextual hardships and relational resources. Conclusion These findings highlight the need for multidisciplinary care approaches that attend to psychosocial and economic dimensions of illness. Results may inform policies on post-COVID-19 recovery, including supportive training for health and community workers, and the development of integrated response frameworks for future public health emergencies.

in F1000Research on 2025-06-25 15:40:43 UTC.

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Improving rigor and reproducibility in chromatin immunoprecipitation assay data analysis workflows with Rocketchip [version 1; peer review: awaiting peer review]

Background As genome sequencing technologies advance, the growing accumulation of sequencing data in public databases highlights the need for more robust and adaptable analysis workflows for chromatin immunoprecipitation assays. These workflows must promote reproducibility and replicability of results while effectively leveraging publicly available data to enhance biological insights. Methods Here, we present Rocketchip, a Python-based command-line tool that integrates existing software through Snakemake, enabling efficient, automated, and reproducible analysis of both newly generated chromatin immunoprecipitation data, including chromatin immunoprecipitation followed by sequencing (ChIP-seq), cleavage under targets and release using nuclease (CUT&RUN), and cleavage under targets and tagmentation (CUT&Tag) as well as existing datasets. Results Rocketchip can analyze chromatin immunoprecipitation data using any available software combination for any reference genome. It enhances the utilization of existing datasets, promotes replicability in analyses, and serves as a platform for benchmarking algorithms. Conclusions By facilitating the reanalysis of existing data and allowing for flexible analysis of newly generated data, Rocketchip allows researchers to identify and apply the most accurate and efficient analytical approaches to their data.

in F1000Research on 2025-06-25 15:37:22 UTC.

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Proposed Solar-Powered Motion Sensor for Farm Monitoring and Surveillance: A Solar-Powered Assisted Process [version 1; peer review: awaiting peer review]

Background The farming industry faces continuous threats from pest control and farm security issues because rodents cause significant damage to crops and disrupt farm operations. Traditional pest control methods require continuous human interaction which proves both resource-intensive and inefficient. Modern agricultural practices benefit from sustainable solutions through the combination of renewable energy with smart technologies. Method The research presents an innovative solar-powered motion-sensor system that utilizes OpenCV-based image analysis to detect and classify rodent intruders on farmland autonomously. The system depends on solar panels for energy autonomy while employing computer vision to monitor threats in real time and classify them. Results The system demonstrates its ability to detect and prevent rodent intruders according to initial testing results. The OpenCV system uses motion sensor signals to analyze movement patterns before distinguishing rodents from other detected objects. The solar-powered system operates continuously which decreases human intervention needs and enhances farm surveillance capabilities. The model demonstrates its capability to defend crops from rodent damage and enhance farm resistance against land degradation threats. Conclusion The proposed system demonstrates progress in uniting renewable energy systems with smart surveillance technologies to mitigate agricultural risks. The current system encounters problems with detecting wild animals beyond rodents as well as tracking rodent activity beneath ground level. Future developments could include improved pest capture systems alongside enhanced surveillance features for detecting both unauthorized human intruders and large animals. The research shows that solar power systems need to be connected with automated monitoring technology to create sustainable agricultural operations that are efficient and resilient.

in F1000Research on 2025-06-25 15:31:49 UTC.

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Comparing Competitive and Recreational Table Tennis Training: Impacts on Quality of life in Older Adults - A Randomized Controlled Trial [version 2; peer review: 1 approved, 1 approved with reservations]

Background Owing to its combination of speed, tactics, and accuracy, table tennis is becoming a sport exercise that is suitable for older adults. Casual play is fun and relaxing, and more serious table tennis might further develop skills through focused practice. Methods A randomized controlled trial (RCT) aimed to determine how the practice of competition compared to leisure playing affects the Quality of life (QoL) of people aged 40-70. Selecting subjects at random, one group of subjects undertook a structured competitive regimen, whereas the other group was given time to play recreationally without any structured competition. QoL was measured before and after the intervention using the WHOQOL-BREF, which measures physical, psychological, social, and environmental domains. Data were analyzed using paired and independent t-test. Results The group that received structured competition reported a marked improvement in their QoL indicators, especially in physical health (p < 0.001), psychological health (p < 0.001), and social relationships (p = 0.001), when compared to the control group, which showed few improvements. No significant differences were observed in the environmental domains in either group. Conclusions Regular competitive table tennis practice improves physical condition, emotions, and social relationships, which leads to a higher QoL in older adults. Thus, these results emphasize the utility of competitive sports in the maintenance of active and healthy aging. Registration Thai Clinical Trial Registry (TCTR) ID TCTR20250105001, registered on December 28, 2024

in F1000Research on 2025-06-25 15:25:15 UTC.

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Digital Technologies in a Post-Pandemic Southeast Asia: Measures for Enhancing Regional Approaches [version 1; peer review: awaiting peer review]

The Association of Southeast Asian Nations (ASEAN) has taken some measures to advance collective action to accelerate telehealth in the region. Still, it has encountered the problem of digital readiness and digital health preparedness disparities within the region. To maintain the consolidation of digital health utilization among ASEAN member states, this article offers policy recommendations that help to address the diverse approaches taken and compensate for the capacity diversities among the members. Drawing on insights from published official policies, government health ministry websites of Southeast Asian nations, and ASEAN’s digital health policies, the article first reviews the diversities of digital technologies in a post-pandemic Southeast Asia and then assess measures to enhance regional approaches. Several recommendations are presented: First, ASEAN can standardize regional frameworks on telehealth through the sharing of digital health transformation blueprints and the utilization of ASEAN and ASEAN Plus forums to bridge different understandings and advance the region’s digital health initiatives. Second, ASEAN facilitates investments through a telehealth sandbox and fosters collaborations among different stakeholders. Although the recommendations are consistent with the ‘ASEAN Way,’ concerns over different commitments and expectations, risks of privacy infringements, and misuse of technology in the authoritarian states of the region will be lingering concerns to Southeast Asia’s telehealth landscape.

in F1000Research on 2025-06-25 15:24:02 UTC.

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Therapeutic Use of Cannabis: Perceptions of Youth and Adults in Trujillo, Peru  [version 1; peer review: awaiting peer review]

Background In Peru, the legalization of Cannabis was given in 2017 and approved in 2019; however, there are discrepancies in the knowledge of the therapeutic use of this plant, causing rejection in its application as an alternative medicine. Methods The research was of a basic type with a quantitative approach and a non-experimental design, with a cross-sectional and descriptive scope. Non-probabilistic sampling was used and a total of 324 people (18 – 60 years old) were estimated as the sample. The instrument used was a virtual questionnaire consisting of closed questions with a KR-20 value of 0.825. Finally, the data were treated with descriptive statistics and frequency and percentage tables were used. Results Participants have a positive perception of the benefits of medical cannabis, although their knowledge of its therapeutic application and dosage is limited. The need for its use to be restricted to prescriptions by specialized physicians and backed by scientific evidence is highlighted. Despite having superficial information on applications in chronic diseases and cancer, there is a moderate acceptance of its regular use under medical supervision. Conclusion The population of Trujillo lacks knowledge about the medical benefits and applications of cannabis highlighting the need for educational campaigns. Although regulation is supported, concerns about safety and abuse remain. More studies should be conducted to obtain more accurate data.

in F1000Research on 2025-06-25 15:22:50 UTC.

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Leveraging Synthetic Data to Validate a Benchmark Study for Differential Abundance Tests for 16S Microbiome Sequencing Data  [version 1; peer review: awaiting peer review]

Background Synthetic data’s utility in benchmark studies depends on its ability to closely mimic real-world conditions and reproduce results from experimental data. Building on Nearing et al.‘s study (1), which assessed 14 differential abundance tests using 38 experimental 16S rRNA datasets in a case-control design, we generated synthetic datasets to verify these findings. We rigorously assessed the similarity between synthetic and experimental data and validated the conclusions on the performance of these tests drawn by Nearing et al. (1). This study adheres to the study protocol: Computational Study Protocol: Leveraging Synthetic Data to Validate a Benchmark Study for Differential Abundance Tests for 16S Microbiome Sequencing Data (2). Methods We replicated Nearing et al.’s (1) methodology, incorporating simulated data using two distinct tools (metaSPARSim (3) and sparseDOSSA2 (4)), mirroring the 38 experimental datasets. Equivalence tests were conducted on a set of 30 data characteristics (DC) comparing synthetic and experimental data, complemented by principal component analysis for overall similarity assessment. The 14 differential abundance tests were applied to synthetic datasets, evaluating the consistency of significant feature identification and the proportion of significant features per tool. Correlation analysis, multiple regression and decision trees were used to explore how differences between synthetic and experimental DCs may affect the results. Conclusions Adhering to a formal study protocol in computational benchmarking studies is crucial for ensuring transparency and minimizing bias, though it comes with challenges, including significant effort required for planning, execution, and documentation. In this study, metaSPARSim (3) and sparseDOSSA2 (4) successfully generated synthetic data mirroring the experimental templates, validating trends in differential abundance tests. Of 27 hypotheses tested, 6 were fully validated, with similar trends for 37%. While hypothesis testing remains challenging, especially when translating qualitative observations from text into testable hypotheses, synthetic data for validation and benchmarking shows great promise for future research.

in F1000Research on 2025-06-25 15:18:04 UTC.

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Functional Outcomes of Displaced Midshaft Clavicular Fractures Treated with Precontoured Locked Plates: A Prospective Study [version 2; peer review: 1 approved with reservations]

Abstract Background This study assessed the functional outcomes and complications of open reduction and internal fixation (ORIF) using pre-contoured superior clavicle locking plates for displaced midshaft clavicular fractures. Methods In a prospective two-center study at Al-Thawra Modern General Hospital and Kuwait University Hospital, Sana’a, Yemen, from January 2018 to September 2024, 65 patients (≥18 years) with closed, displaced midshaft clavicular fractures (displacement >2 cm, shortening >2 cm, comminution, or skin tenting) underwent ORIF. Functional outcomes were evaluated six months postoperatively using the University of California, Los Angeles (UCLA) shoulder rating score. Data were analyzed using SPSS version 26. Results The mean patient age was 32.09 years (83.1% male, n=54). Road traffic accidents were the primary mechanism of injury (66.2%, n=43). At 6 months, the mean UCLA score was 32.46 ± 2.54, with 98.5% (n=64) achieving good or excellent outcomes (UCLA score ≥27) and 1.5% (n=1) fair/poor. Complications included hardware irritation (1.5%, n=1), hardware failure (3.1%, n=2), and superficial infections (1.5%, n=1). All patients (100%) reported satisfaction with their outcomes. The UCLA scores varied significantly according to injury mechanism, side, and age, with older patients showing lower scores. Conclusion ORIF with pre-contoured locked plates yielded promising functional outcomes, high patient satisfaction, and low complication rates. However, the observational design, lack of a control group, and 6-month follow-up limit broader conclusions. Larger controlled studies are needed to validate these findings and guide the optimal management of displaced midshaft clavicular fractures.

in F1000Research on 2025-06-25 15:16:29 UTC.

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-The Prevalence and Parental Awareness, Perception, and Attitudes towards Eye Diseases in Children Under 18 years old, in Saudi Arabia [version 1; peer review: awaiting peer review]

Background Identifying and treating visual impairment in young children is crucial because it has a lasting impact on adults. Estimates put the number of children with vision impairment in the world at 19 million, compared to the estimated 1.4 million who are blind. To battle children’s vision issues, studies on children’s eye disorders have highlighted the significance of raising awareness among parents and educators. So, according to various authors, the awareness, perception, and attitudes of parents towards children’s eye diseases in Saudi Arabia need more research. Aims To determines the prevalence of children’s eye diseases among children aged under 18 years old, in Saudi Arabia, as well as assess the awareness, perception, and attitudes of parents towards children’s eye diseases in Saudi Arabia. Methods A cross-sectional web survey with a sample (n = 1276) of parents of children in Saudi Arabia was carried out from November 2023 to August 2024. Results This study highlights significant gaps in parental awareness of Childhood Eye Diseases (CED), with 46.5% of parents demonstrating intermediate awareness and 29.4% exhibiting poor awareness. Refractive errors were the most commonly reported eye issue, affecting 44.23% of children, while congenital glaucoma and cataracts were less common. Factors positively correlating with higher awareness included marital status, gender, age (30-50 years), education level (bachelor’s degree), and employment status. Notably, more than half of the children had never undergone an eye exam. Conclusion This study highlights significant gaps in parental awareness of CED, with 46.5% of parents demonstrating intermediate awareness and 29.4% showing poor awareness. Factors such as marital status, gender, age (30-50 years), education level (bachelor’s degree), and employment status positively correlate with higher awareness. These findings underscore the need for targeted educational interventions to improve knowledge and encourage proactive eye health care among parents.

in F1000Research on 2025-06-25 15:10:25 UTC.

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Community perspectives on drug promotion on social media during the COVID-19 pandemic in KwaZulu-Natal, South Africa [version 2; peer review: 2 approved with reservations]

Background During the COVID-19 pandemic, social media and web-based platforms were widely used to promote medicinal substances. To assess community perspectives on drug promotions on social media, we conducted qualitative research using three workshops. The workshops aimed to highlight the public understanding of drug advertising focusing on community perceptions of social media drug promotions, their risks and benefits. Discussions were conducted on the importance of adhering to national drug regulation policies and the World Health Organisation ethical criteria for promotion, advertisement, and publicity of medicines. Methods Participants for the workshops were purposively sampled from local community youth groups and healthcare facilities. Two workshops included ten young adults aged 18-35, while the third workshop involved three healthcare professionals and one traditional healer. Results The study participants’ highlighted the value of honesty and trust in the drug promotions. Gaps in the ethical conduct of advertising were observed and concerns were raised about the reliability of social media information and the omission of valuable details on the drug advertisements. Conclusion Individuals have a right to informed choices that ensure their health safety. This study has highlighted the need for transparency and accountability in pharmaceutical and complementary medicine marketing on social media. Collaboration is needed between regulatory bodies, pharmaceutical companies, healthcare providers and community members, to make sure that drug advertising upholds ethical standards and public health.

in F1000Research on 2025-06-25 15:08:38 UTC.

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Optimal sampling frequency and site selection for wastewater and environmental surveillance of infectious pathogens: A value of information assessment

by Isabella Impalli, Erik Bergland, Chadi M. Saad-Roy, Bryan T. Grenfell, Simon A. Levin, D. G. Joakim Larsson, Ramanan Laxminarayan

Wastewater and environmental surveillance (WES) is a promising method of detecting infectious diseases in human and animal populations and offers significant advantages over traditional surveillance methods in the early detection of outbreaks. However, WES involves financial and human resources, and public policy decisions must determine whether the benefits of WES outweigh the costs, particularly in low-resource areas. The selection of surveillance sites, sampling frequency, and test sensitivity and specificity are crucial determinants of WES effectiveness and cost-efficiency. We created an analytical model and numerical simulations of disease arrival, spread, and WES strategies to determine the optimal sampling frequency for two interacting patches, each represented by a different sampling site. We show that it is optimal to test in one patch more frequently than it is to test in both patches less frequently if the patches are sufficiently interactive, surveillance is of sufficient sensitivity and specificity, and setup costs are substantial. In our value of information (VOI) assessment, the net value of surveillance information for both patches is non-monotonic with respect to the degree of patch interaction. Increased mixing between the patches allows for quicker surveillance detection but is worse for overall infection burden. Overall, optimizing the value of surveillance information for all patches being surveilled requires coordination and deliberate selection of surveillance sites and sampling frequencies. This paper provides a VOI assessment of WES to determine the optimal number of sites and sampling frequency at a high level of abstraction, leaving opportunity to adapt the model to specific pathogens and populations as needed. Our findings can inform the cost-efficient implementation of WES for infectious diseases, particularly in resource-constrained settings.

in PLoS Computational Biology on 2025-06-25 14:00:00 UTC.

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The roles of feedback loops in the Caenorhabditis elegans rhythmic forward locomotion

by Peng Zhao, Boyang Wang, Yi Rong, Ye Yuan, Jian Liu, Hong Huo, Zhuyong Liu, Zhaoyu Li, Tao Fang

Rhythmic behaviors are essential in biological systems, particularly in animal locomotion. The central pattern generator and sensory feedback loop mechanism have been instrumental in explaining many rhythmic locomotion patterns, however, it is insufficient to account for the tunability and robustness of frequency and amplitude in certain oscillatory movements. This suggests the involvement of additional, less understood circuit mechanisms. This study employs calcium imaging and neuromechanical modelling to investigate the circuit mechanism responsible for sinusoidal forward locomotion in Caenorhabditis elegans. We demonstrate that the feedback loop circuit, consisting of motoneurons and muscles, could govern the generation of oscillations and regulate rhythmic forward movement. This circuit is composed of both negative and positive feedback loops, which together regulate the turnability and robustness of oscillations. The oscillatory behavior of C. elegans typically involves a rhythmic alternation of dorsoventral muscles. Our neuromechanical model of the functional oscillatory unit reveals that asymmetric inputs from interneurons to motoneurons, and asymmetric connections from motoneurons to muscles, are essential for this switching mechanism. Our findings suggest that, besides the established roles of existed oscillator mechanisms, circuits formed by both negative and positive feedback loops contribute to the generation and robust modulation of rhythmic behaviors.

in PLoS Computational Biology on 2025-06-25 14:00:00 UTC.

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Studying gastrulation by invagination: The bending of a cell sheet by mechanical cell properties using 3D deformable cell based simulations

by Roland M. Dries, Kim Y. Renders, Jaap A. Kaandorp

Studying the bending of a cell sheet in vivo, like invagination in embryos, can be complex due to a multitude of cellular processes and properties that interact with each other. Computer simulations can help to unravel this process. 2D computer simulations, however, lack the ability to take into account the effect three-dimensional properties, like endodermal plate shape and cell number, have on the shape of an embryo. Therefore, we developed a 3D cell-based model, that is able to simulate cells as separate deformable entities with a conserved cell volume. A blastula is formed by adhering the cells together as a sphere. The simulation results showed that changing individual mechanical properties, like cell stiffness, cell-cell adhesion, and the apical constriction factor, had a direct effect on the cell’s behavior and future shape. These properties influenced the ability of a cell sheet to bend and eventually change the global shape of the embryo. The observed shape transitions the endodermal region goes through during the inward bending of the cell sheet in the simulation, can give an insight into the mechanisms involved, and timing of events in biological model organisms. Changing geometrical properties (endodermal plate shape, endodermal cell number and the start position of constriction), which is not possible in 2D models, showed that the inwards bending is more dependent on the number of cells involved than on the shape of the endodermal region, and thus that the invagination process is very robust to irregularities. When qualitatively comparing our simulation results to biological data from literature, we saw that our simulations did not exactly reproduce the shapes observed in nature. This might indicate that additional mechanisms are playing a role during invagination.

in PLoS Computational Biology on 2025-06-25 14:00:00 UTC.

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Ancestral [Fe-S] biogenesis system SMS has a unique mechanism of cluster assembly and sulfur utilization

by Macha Dussouchaud, Markel Martinez-Carranza, Pierre-Simon Garcia, Martin Clémancey, Geneviève Blondin, Jean Michel Betton, Ahmed Haouz, Simonetta Gribaldo, Sandrine Ollagnier de Choudens, Ludovic Sauguet, Ariel Mechaly, Frédéric Barras

[Fe-S] clusters are ancient and ubiquitous protein co-factors, which contributed to the emergence of life in an anoxic planet. We have recently identified two minimal [Fe-S] biogenesis systems, MIS and SMS, inferred to be ancestral systems dating back to the Last Universal Common Ancestor and which gave rise to the well-studied modern Iron-Sulfur Cluster (ISC), Nitrogen Fixation (NIF), and Sulfur Mobilization (SUF) machineries. The present study focuses on the ancestor SMS from the hyperthermophilic archaeon Methanocaldococcus jannaschii. Biochemical and structural studies showed that SMS is made of a SmsC₂B₂ heterotetratmer wherein the SmsC subunit hosts both ATP and [Fe-S] cluster binding sites. Binding of ATP and assembly of [Fe-S] were found to be mutually exclusive allowing for a regulatory coupling between binding of both substrates. Mutagenesis and in vitro transfer experiments revealed the key role of SmsC-contained Cys residues in cluster assembly. Strikingly, the SMS system rescued a non-viable Escherichia coli strain lacking endogenous ISC and SUF systems grown under anoxic conditions, in the presence of Na₂S, indicating that sulfide is a source of sulfur for SMS. In addition, we predict that most archaea SmsC proteins hold a similar C-terminal [Fe-S] cluster assembly site. Taking into account those unique structural and functional features, we propose a mechanistic model describing how SmsC₂B₂ assembles and distributes [4Fe-4S] clusters. Altogether this study established SMS as a new bona fide [Fe-S] biogenesis system that operated in anaerobic prokaryotes prior to evolve to SUF after the Great Oxydation Event.

in PLoS Biology on 2025-06-25 14:00:00 UTC.

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Chronic inflammatory pain and chronic THC vapor inhalation alter midbrain neuronal activity

Journal of Neurophysiology, Volume 134, Issue 1, Page 80-93, July 2025.

in Journal of Neurophysiology on 2025-06-25 12:09:00 UTC.

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Simulations reveal that beta burst detection may inappropriately characterize the beta band

Journal of Neurophysiology, Volume 134, Issue 1, Page 10-19, July 2025.

in Journal of Neurophysiology on 2025-06-25 12:08:59 UTC.

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Cortical Excitability as a Prognostic and Phenotypic Stratification Biomarker in Amyotrophic Lateral Sclerosis

Objective

Despite its clinical heterogeneity, amyotrophic lateral sclerosis is unified by early and prominent alterations in cortical excitability, increasingly recognized as contributors to disease progression. This study assessed whether the ratio between motor evoked potential (MEP) amplitude, reflecting upper motor neuron integrity, and compound muscle action potential (CMAP) amplitude, indexing lower motor neuron function, could provide an accessible marker of corticospinal excitability to stratify patients by phenotype, stage, and survival.

Methods

In this multicenter retrospective study, 743 amyotrophic lateral sclerosis patients from 16 tertiary centers in Italy were analyzed. The MEP:CMAP ratio, recorded from upper limb muscles, was categorized as hyperexcitable, normal, or hypoexcitable. Phenotypes included progressive muscular atrophy (or lower motor neuron), flail arm/leg, classic, bulbar, patient with predominant upper motor neuron signs (or pyramidal), and primary lateral sclerosis. Disease stage was assessed using King's staging. Survival was analyzed using Kaplan–Meier curves and Cox regression models.

Results

The MEP:CMAP ratio differed significantly across phenotypes (p < 0.0001), with hyperexcitability predominating in lower motor neuron, flail, classic, and bulbar forms, and hypoexcitability in pyramidal and primary lateral sclerosis. Hypoexcitability increased in advanced King's stages (p < 0.0001). Hyperexcitable patients had shorter survival (p = 0.004), including when tested within 1 year of onset (p = 0.006). Cox regression identified the MEP:CMAP ratio as an independent survival predictor (HR 1.84, 95% CI 1.12–3.03, p = 0.016).

Interpretation

This real-world study supports the clinical value of the MEP:CMAP ratio as a scalable biomarker of cortical excitability in amyotrophic lateral sclerosis, with prognostic relevance across phenotypes and disease stages. ANN NEUROL 2025

in Annals of Neurology on 2025-06-25 11:48:34 UTC.

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Sensory population activity reveals downstream confidence computations in the primate visual system

Proceedings of the National Academy of Sciences, Volume 122, Issue 26, July 2025.
SignificanceIt has long been known that our sense of confidence is indicative of the quality of our decisions and actions. For example, when we feel more confident in a perceptual decision, that decision is more likely to be correct. Yet, the neural ...

in PNAS on 2025-06-25 07:00:00 UTC.

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