Planet Neuroscience

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Mapping Emotions in the Brain: A Bi-Hemispheric Neural Model with Explainable Deep Learning

arXiv:2507.12625v1 Announce Type: new Abstract: Recent advances have shown promise in emotion recognition from electroencephalogram (EEG) signals by employing bi-hemispheric neural architectures that incorporate neuroscientific priors into deep learning models. However, interpretability remains a significant limitation for their application in sensitive fields such as affective computing and cognitive modeling. In this work, we introduce a post-hoc interpretability framework tailored to dual-stream EEG classifiers, extending the Local Interpretable Model-Agnostic Explanations (LIME) approach to accommodate structured, bi-hemispheric inputs. Our method adapts LIME to handle structured two-branch inputs corresponding to left and right-hemisphere EEG channel groups. It decomposes prediction relevance into per-channel contributions across hemispheres and emotional classes. We apply this framework to a previously validated dual-branch recurrent neural network trained on EmoNeuroDB, a dataset of EEG recordings captured during a VR-based emotion elicitation task. The resulting explanations reveal emotion-specific hemispheric activation patterns consistent with known neurophysiological phenomena, such as frontal lateralization in joy and posterior asymmetry in sadness. Furthermore, we aggregate local explanations across samples to derive global channel importance profiles, enabling a neurophysiologically grounded interpretation of the model's decisions. Correlation analysis between symmetric electrodes further highlights the model's emotion-dependent lateralization behavior, supporting the functional asymmetries reported in affective neuroscience.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-18 04:00:00 UTC.

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Emergence of Functionally Differentiated Structures via Mutual Information Optimization in Recurrent Neural Networks

arXiv:2507.12858v1 Announce Type: new Abstract: Functional differentiation in the brain emerges as distinct regions specialize and is key to understanding brain function as a complex system. Previous research has modeled this process using artificial neural networks with specific constraints. Here, we propose a novel approach that induces functional differentiation in recurrent neural networks by minimizing mutual information between neural subgroups via mutual information neural estimation. We apply our method to a 2-bit working memory task and a chaotic signal separation task involving Lorenz and R\"ossler time series. Analysis of network performance, correlation patterns, and weight matrices reveals that mutual information minimization yields high task performance alongside clear functional modularity and moderate structural modularity. Importantly, our results show that functional differentiation, which is measured through correlation structures, emerges earlier than structural modularity defined by synaptic weights. This suggests that functional specialization precedes and probably drives structural reorganization within developing neural networks. Our findings provide new insights into how information-theoretic principles may govern the emergence of specialized functions and modular structures during artificial and biological brain development.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-18 04:00:00 UTC.

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Geometric Hyperscanning of Affect under Active Inference

arXiv:2506.08599v2 Announce Type: replace Abstract: Second-person neuroscience holds social cognition as embodied meaning co-regulation through reciprocal interaction, modeled here as coupled active inference with affect emerging as inference over identity-relevant surprise. Each agent maintains a self-model that tracks violations in its predictive coherence while recursively modeling the other. Valence is computed from self-model prediction error, weighted by self-relevance, and modulated by prior affective states and by what we term temporal aiming, which captures affective appraisal over time. This accommodates shifts in the self-other boundary, allowing affect to emerge at individual and dyadic levels. We propose a novel method termed geometric hyperscanning, based on the Forman-Ricci curvature, to empirically operationalize these processes: it tracks topological reconfigurations in inter-brain networks, with its entro-py serving as a proxy for affective phase transitions such as rupture, co-regulation, and re-attunement.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-18 04:00:00 UTC.

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Leveraging Quantum Superposition to Infer the Dynamic Behavior of a Spatial-Temporal Neural Network Signaling Model

arXiv:2403.18963v4 Announce Type: replace-cross Abstract: The exploration of new problem classes for quantum computation is an active area of research. In this paper, we introduce and solve a novel problem class related to dynamics on large-scale networks relevant to neurobiology and machine learning. Specifically, we ask if a network can sustain inherent dynamic activity beyond some arbitrary observation time or if the activity ceases through quiescence or saturation via an epileptic-like state. We show that this class of problems can be formulated and structured to take advantage of quantum superposition and solved efficiently using a coupled workflow between the Grover and Deutsch-Jozsa quantum algorithms. To do so, we extend their functionality to address the unique requirements of how input (sub)sets into the algorithms must be mathematically structured while simultaneously constructing the inputs so that measurement outputs can be interpreted as meaningful properties of the network dynamics. This, in turn, allows us to answer the question we pose.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-18 04:00:00 UTC.

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The Generalist Brain Module: Module Repetition in Neural Networks in Light of the Minicolumn Hypothesis

arXiv:2507.12473v1 Announce Type: cross Abstract: While modern AI continues to advance, the biological brain remains the pinnacle of neural networks in its robustness, adaptability, and efficiency. This review explores an AI architectural path inspired by the brain's structure, particularly the minicolumn hypothesis, which views the neocortex as a distributed system of repeated modules - a structure we connect to collective intelligence (CI). Despite existing work, there is a lack of comprehensive reviews connecting the cortical column to the architectures of repeated neural modules. This review aims to fill that gap by synthesizing historical, theoretical, and methodological perspectives on neural module repetition. We distinguish between architectural repetition - reusing structure - and parameter-shared module repetition, where the same functional unit is repeated across a network. The latter exhibits key CI properties such as robustness, adaptability, and generalization. Evidence suggests that the repeated module tends to converge toward a generalist module: simple, flexible problem solvers capable of handling many roles in the ensemble. This generalist tendency may offer solutions to longstanding challenges in modern AI: improved energy efficiency during training through simplicity and scalability, and robust embodied control via generalization. While empirical results suggest such systems can generalize to out-of-distribution problems, theoretical results are still lacking. Overall, architectures featuring module repetition remain an emerging and unexplored architectural strategy, with significant untapped potential for both efficiency, robustness, and adaptiveness. We believe that a system that adopts the benefits of CI, while adhering to architectural and functional principles of the minicolumns, could challenge the modern AI problems of scalability, energy consumption, and democratization.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-18 04:00:00 UTC.

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Cognitive Modelling Aspects of Neurodevelopmental Disorders Using Standard and Oscillating Neighbourhood SOM Neural Networks

arXiv:2507.12567v1 Announce Type: cross Abstract: Background/Introduction: In this paper, the neural network class of Self-Organising Maps (SOMs) is investigated in terms of its theoretical and applied validity for cognitive modelling, particularly of neurodevelopmental disorders. Methods: A modified SOM network type, with increased biological plausibility, incorporating a type of cortical columnar oscillation in the form of an oscillating Topological Neighbourhood (TN), is introduced and applied alongside the standard SOM. Aspects of two neurodevelopmental disorders, autism and schizophrenia, are modelled using SOM networks, based on existing neurocomputational theories. Both standard and oscillating-TN SOM training is employed with targeted modifications in the TN width function. Computer simulations are conducted using revised versions of a previously introduced model (IPSOM) based on a new modelling hypothesis. Results/Conclusions: The results demonstrate that there is strong similarity between standard and oscillating-TN SOM modelling in terms of map formation behaviour, output and structure, while the oscillating version offers a more realistic computational analogue of brain function. Neuroscientific and computational arguments are presented to validate the proposed SOM modification within a cognitive modelling framework.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-18 04:00:00 UTC.

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Adversarial attacks to image classification systems using evolutionary algorithms

arXiv:2507.13136v1 Announce Type: new Abstract: Image classification currently faces significant security challenges due to adversarial attacks, which consist of intentional alterations designed to deceive classification models based on artificial intelligence. This article explores an approach to generate adversarial attacks against image classifiers using a combination of evolutionary algorithms and generative adversarial networks. The proposed approach explores the latent space of a generative adversarial network with an evolutionary algorithm to find vectors representing adversarial attacks. The approach was evaluated in two case studies corresponding to the classification of handwritten digits and object images. The results showed success rates of up to 35% for handwritten digits, and up to 75% for object images, improving over other search methods and reported results in related works. The applied method proved to be effective in handling data diversity on the target datasets, even in problem instances that presented additional challenges due to the complexity and richness of information.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-18 04:00:00 UTC.

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Multi-population GAN Training: Analyzing Co-Evolutionary Algorithms

arXiv:2507.13157v1 Announce Type: new Abstract: Generative adversarial networks (GANs) are powerful generative models but remain challenging to train due to pathologies suchas mode collapse and instability. Recent research has explored co-evolutionary approaches, in which populations of generators and discriminators are evolved, as a promising solution. This paper presents an empirical analysis of different coevolutionary GAN training strategies, focusing on the impact of selection and replacement mechanisms. We compare (mu,lambda), (mu+lambda) with elitism, and (mu+lambda) with tournament selection coevolutionary schemes, along with a non-evolutionary population based multi-generator multi-discriminator GAN baseline, across both synthetic low-dimensional datasets (blob and gaussian mixtures) and an image-based benchmark (MNIST). Results show that full generational replacement, i.e., (mu,lambda), consistently outperforms in terms of both sample quality and diversity, particularly when combined with larger offspring sizes. In contrast, elitist approaches tend to converge prematurely and suffer from reduced diversity. These findings highlight the importance of balancing exploration and exploitation dynamics in coevolutionary GAN training and provide guidance for designing more effective population-based generative models.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-18 04:00:00 UTC.

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Topology-Aware Activation Functions in Neural Networks

arXiv:2507.12874v1 Announce Type: cross Abstract: This study explores novel activation functions that enhance the ability of neural networks to manipulate data topology during training. Building on the limitations of traditional activation functions like $\mathrm{ReLU}$, we propose $\mathrm{SmoothSplit}$ and $\mathrm{ParametricSplit}$, which introduce topology "cutting" capabilities. These functions enable networks to transform complex data manifolds effectively, improving performance in scenarios with low-dimensional layers. Through experiments on synthetic and real-world datasets, we demonstrate that $\mathrm{ParametricSplit}$ outperforms traditional activations in low-dimensional settings while maintaining competitive performance in higher-dimensional ones. Our findings highlight the potential of topology-aware activation functions in advancing neural network architectures. The code is available via https://github.com/Snopoff/Topology-Aware-Activations.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-18 04:00:00 UTC.

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The late-stage training dynamics of (stochastic) subgradient descent on homogeneous neural networks

arXiv:2502.05668v3 Announce Type: replace-cross Abstract: We analyze the implicit bias of constant step stochastic subgradient descent (SGD). We consider the setting of binary classification with homogeneous neural networks - a large class of deep neural networks with ReLU-type activation functions such as MLPs and CNNs without biases. We interpret the dynamics of normalized SGD iterates as an Euler-like discretization of a conservative field flow that is naturally associated to the normalized classification margin. Owing to this interpretation, we show that normalized SGD iterates converge to the set of critical points of the normalized margin at late-stage training (i.e., assuming that the data is correctly classified with positive normalized margin). Up to our knowledge, this is the first extension of the analysis of Lyu and Li (2020) on the discrete dynamics of gradient descent to the nonsmooth and stochastic setting. Our main result applies to binary classification with exponential or logistic losses. We additionally discuss extensions to more general settings.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-18 04:00:00 UTC.

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Multiple-Frequencies Population-Based Training

arXiv:2506.03225v2 Announce Type: replace-cross Abstract: Reinforcement Learning's high sensitivity to hyperparameters is a source of instability and inefficiency, creating significant challenges for practitioners. Hyperparameter Optimization (HPO) algorithms have been developed to address this issue, among them Population-Based Training (PBT) stands out for its ability to generate hyperparameters schedules instead of fixed configurations. PBT trains a population of agents, each with its own hyperparameters, frequently ranking them and replacing the worst performers with mutations of the best agents. These intermediate selection steps can cause PBT to focus on short-term improvements, leading it to get stuck in local optima and eventually fall behind vanilla Random Search over longer timescales. This paper studies how this greediness issue is connected to the choice of evolution frequency, the rate at which the selection is done. We propose Multiple-Frequencies Population-Based Training (MF-PBT), a novel HPO algorithm that addresses greediness by employing sub-populations, each evolving at distinct frequencies. MF-PBT introduces a migration process to transfer information between sub-populations, with an asymmetric design to balance short and long-term optimization. Extensive experiments on the Brax suite demonstrate that MF-PBT improves sample efficiency and long-term performance, even without actually tuning hyperparameters.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-18 04:00:00 UTC.

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No apparent state-dependency of equilibrium climate sensitivity between the Pleistocene glacial and interglacial climate states

Nature Communications, Published online: 18 July 2025; doi:10.1038/s41467-025-61941-5

A new paleosol-based CO₂ record from the Chinese Loess Plateau reveals a stepwise decline in glacial CO₂ over the past 2.6 million years and suggests that climate sensitivity remained stable across glacial–interglacial cycles.

in Nature Communications on 2025-07-18 00:00:00 UTC.

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Targeting CD37 promotes macrophage-dependent phagocytosis of multiple cancer cell types and facilitates tumor clearance in mice

Nature Communications, Published online: 18 July 2025; doi:10.1038/s41467-025-61348-2

Cancer cells evade the immune system by disrupting phagocytic clearance. Here, the authors identify CD37 as a potential checkpoint molecule expressed on non-phagocytes and propose that binding to tumor-derived MIF reduces the phagocytic ability via inhibiting the AKT pathway. In preclinical mouse models, anti-CD37-based therapy enhances phagocytosis by macrophages, facilitating tumor clearance.

in Nature Communications on 2025-07-18 00:00:00 UTC.

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Generating brain-wide connectome using synthetic axonal morphologies

Nature Communications, Published online: 18 July 2025; doi:10.1038/s41467-025-62030-3

In this work, the authors present a method for numerically synthesizing long-range axonal morphologies of the mouse brain, by leveraging recent advances in unsupervised clustering techniques and clustering input axons by their projecting pattern.

in Nature Communications on 2025-07-18 00:00:00 UTC.

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Light-induced CoOX surface reconstruction in hollow heterostructure for durable photocatalytic seawater splitting

Nature Communications, Published online: 18 July 2025; doi:10.1038/s41467-025-62033-0

Photocorrosion caused by unreacted holes limits the performance of photocatalysts for photocatalytic seawater splitting. Here, the authors report that a hollow ZnIn2S4 structure with CoOx and Pt single atoms enables efficient, durable hydrogen production from seawater via dynamic self-reconstruction.

in Nature Communications on 2025-07-18 00:00:00 UTC.

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Silicon nanocolumn-based disposable and flexible ultrasound patches

Nature Communications, Published online: 18 July 2025; doi:10.1038/s41467-025-61903-x

A lead-free, flexible, and disposable ultrasound patch using silicon nanocolumns enables vascular imaging and real-time blood pressure monitoring, offering a low-cost and eco-friendly solution for wearable medical diagnostics.

in Nature Communications on 2025-07-18 00:00:00 UTC.

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Somatostatin-expressing interneurons induce early NO-driven and late specific astrocyte-mediated vasodilation

Nature Communications, Published online: 18 July 2025; doi:10.1038/s41467-025-61771-5

The precise role of somatostatin-expressing interneurons in regulating hemodynamics remains unclear. Here, authors find that the activation of these neurons induces astrocytic calcium signaling, which subsequently drives delayed vasodilation and enhances layer-specific fMRI signals in response to prolonged sensory stimulation.

in Nature Communications on 2025-07-18 00:00:00 UTC.

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Persistent Disruptions in Prefrontal Connectivity Despite Behavioral Rescue by Environmental Enrichment in a Mouse Model of Rett Syndrome

This study reveals that the loss of MeCP2 in Rett syndrome model mice disrupts prefrontal connectivity. Although early environmental enrichment helps mitigate behavioral deficits and restores hippocampal BDNF levels, it fails to reverse the altered prefrontal connectivity or prevent the prefrontal-specific decline in BDNF.

ABSTRACT

Rett syndrome, a neurodevelopmental disorder caused by loss-of-function mutations in the MECP2 gene, is characterized by severe motor, cognitive, and emotional impairments. Some of the deficits may result from changes in cortical connections, especially downstream projections of the prefrontal cortex (PFC), which may also be targets of restoration following rearing conditions such as environmental enrichment that alleviate specific symptoms. Here, using a heterozygous Mecp2^+/− female mouse model closely analogous to human Rett syndrome, we investigated the impact of early environmental enrichment on behavioral deficits and PFC connectivity. Behavioral analyses revealed that enriched housing rescued fine motor deficits and reduced anxiety, with enrichment-housed Mecp2^+/− mice performing comparably to wild-type (WT) controls in rotarod and open field assays. Anatomical mapping of top-down anterior cingulate cortex (ACA) projections demonstrated altered PFC connectivity in Mecp2^+/− mice, with increased axonal density in the somatosensory cortex and decreased density in the motor cortex compared to WT controls. ACA axons revealed shifts in hemispheric distribution, particularly in the medial network regions, with Mecp2^+/− mice exhibiting reduced ipsilateral dominance. These changes were unaffected by enriched housing, suggesting that structural abnormalities in PFC connectivity persist despite behavioral improvements. Enriched housing rescued brain-derived neurotrophic factor (BDNF) levels in the hippocampus but failed to restore BDNF levels in the PFC, consistent with the persistent deficits observed in prefrontal axonal projections. These findings highlight the focal nature of changes induced by reduction of MeCP2 and by exposure to environmental enrichment and suggest that environmental enrichment starting in adolescence can alleviate behavioral deficits in Mecp2^+/− mice without reversing abnormalities in large-scale cortical connectivity.

in Journal of Comparative Neurology on 2025-07-17 14:53:46 UTC.

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Modular, focused data science education improves biomedical learners’ abilities: A study of the Data and Analytics for Research Training (DART) program

by Rose Hartman, K. Joy Payton, Rose Franzen, Meredith Lee, Elizabeth Drellich, Ali Shokoufandeh, Jeffrey Pennington

The increasing availability of big data and adoption of sophisticated computational techniques in biomedical research has exciting implications for our scientific understanding of human health. However, researchers report struggling to find data science education that meets their needs, despite the fact that many training programs and online resources exist. There is a lack of evidence on the strengths and weaknesses of various training options, making selecting an educational path daunting. We created a new data science training program focused on rigorous, reproducible methods for biomedical research, making use of tightly scoped modular content that can be flexibly arranged to provide a curriculum tailored to a researcher’s specific needs and skill level. Moreover, we ran a study testing the program’s effectiveness, providing not only another option for data science training but also a model for collecting and sharing relevant data on data science education programs. We ran two waves of research participants, adjusting our materials in between to improve both the training program and our research design. For both waves, we pre-registered hypotheses that learners’ self-reported data science ability and level of agreement with important tenets of open science would increase over the course of the program. Indeed, learners showed significant improvement in data science ability (Wave 1: t(47) = 10.18, p < .001, Wave 2: t(238) = 17.12, p < .001) and greater agreement with open science values (Wave 1: t(47) = 3.56, p < .001, Wave 2: t(238) = 7.95, p < .001). Follow up analyses underscore the robustness of improvement in data science ability. The improvement in open science values was more moderate and was significant only in some of our pre-registered hypothesis tests, likely due to a ceiling effect as most learners reported high agreement with open science values at pretest.

in PLoS Computational Biology on 2025-07-17 14:00:00 UTC.

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Penguins exploit tidal currents for efficient navigation and opportunistic foraging

by Richard M. Gunner, Flavio Quintana, Mariano H. Tonini, Mark D. Holton, Ken Yoda, Margaret C. Crofoot, Rory P. Wilson

Animals navigating in fluid environments often face forces from wind or water currents that challenge travel efficiency and route accuracy. We investigated how 27 Magellanic penguins (Spheniscus magellanicus) adapt their navigation strategies to return to their colony amid regional tidal ocean currents. Using GPS-enhanced dead-reckoning loggers and high-resolution ocean current data, we reconstructed penguin travel vectors during foraging trips to assess their responses to variable currents during their colony-bound movements. By integrating estimates of energy costs and prey pursuits, we found that birds balanced direct navigation with current-driven drift: in calm currents, they maintained precise line-of-sight headings to their colony. In stronger currents, they aligned their return with lateral flows, which increased travel distance, but at reduced energy costs, and provided them with increased foraging opportunities. Since the lateral tidal currents always reversed direction over the course of return paths, the penguins’ return paths were consistently S-shaped but still resulted in the birds returning efficiently to their colonies. These findings suggest that Magellanic penguins can sense current drift and use it to enhance energy efficiency by maintaining overall directional accuracy while capitalizing on foraging opportunities.

in PLoS Biology on 2025-07-17 14:00:00 UTC.

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Healing regimes for microscopic wounds in the vertex model of cell tissues

Author(s): R. F. Almada, N. A. M. Araújo, and P. Patrício

Wounds in epithelial tissues compromise their vital role in homeostasis. A rapid and efficient wound healing encompasses different mechanisms, which includes the formation of a contractile actin-myosin cable around its edge, known as the purse-string mechanism. We combine mean-field calculations and…

[Phys. Rev. E 112, 014407] Published Thu Jul 17, 2025

in Physical Review E: Biological physics on 2025-07-17 10:00:00 UTC.

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Maximum entropy models for patterns of gene expression

Author(s): Camilla Sarra, Leopoldo Sarra, Luca Di Carlo, Trevor GrandPre, Yaojun Zhang, Curtis G. Callan, Jr., and William Bialek

New experimental methods make it possible to measure the expression levels of many genes, simultaneously, in snapshots from thousands or even millions of individual cells. Current approaches to analyze these experiments involve clustering or low-dimensional projections, and often start with the assu…

[Phys. Rev. E 112, 014408] Published Thu Jul 17, 2025

in Physical Review E: Biological physics on 2025-07-17 10:00:00 UTC.

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Polyglycine-mediated aggregation of FAM98B disrupts tRNA processing in GGC repeat disorders

Science, Volume 389, Issue 6757, July 2025.

in Science on 2025-07-17 07:00:00 UTC.

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Vaccination to mitigate climate-driven disruptions to malaria control in Madagascar

Science, Volume 389, Issue 6757, July 2025.

in Science on 2025-07-17 07:00:00 UTC.

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Autoinhibition imposed by a large conformational switch of INO80 regulates nucleosome positioning

Science, Volume 389, Issue 6757, July 2025.

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Design of intrinsically disordered region binding proteins

Science, Volume 389, Issue 6757, July 2025.

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Redox-regulated Aux/IAA multimerization modulates auxin responses

Science, Volume 389, Issue 6757, July 2025.

in Science on 2025-07-17 07:00:00 UTC.

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Erratum for the Research Article “Sunlight drives the abiotic formation of nitrous oxide in fresh and marine waters” by E. Leon-Palmero et al.

Science, Volume 389, Issue 6757, July 2025.

in Science on 2025-07-17 07:00:00 UTC.

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This is not the time to step back from diversity, equity, and inclusion

Science, Volume 389, Issue 6757, July 2025.

in Science on 2025-07-17 07:00:00 UTC.

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Skeletal editing of pyrrolidines by nitrogen-atom insertion

Science, Volume 389, Issue 6757, Page 275-281, July 2025.

in Science on 2025-07-17 06:00:04 UTC.

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Two-dimensional indium selenide wafers for integrated electronics

Science, Volume 389, Issue 6757, Page 299-302, July 2025.

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Controlled colonization of the human gut with a genetically engineered microbial therapeutic

Science, Volume 389, Issue 6757, Page 303-308, July 2025.

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Dome-celled aerogels with ultrahigh-temperature superelasticity over 2273 K

Science, Volume 389, Issue 6757, Page 290-294, July 2025.

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Bridging the pyridine-pyridazine synthesis gap by skeletal editing

Science, Volume 389, Issue 6757, Page 295-298, July 2025.

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Global earthquake detection and warning using Android phones

Science, Volume 389, Issue 6757, Page 254-259, July 2025.

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Midline assembloids reveal regulators of human axon guidance

Science, Volume 389, Issue 6757, Page 282-289, July 2025.

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Stigma did not kill my dream

Science, Volume 389, Issue 6757, Page 318-318, July 2025.

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In Other Journals

Science, Volume 389, Issue 6757, Page 247-248, July 2025.

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A new age of molecular chirality

Science, Volume 389, Issue 6757, Page 232-233, July 2025.

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Polyglycine proteins leave transfer RNAs unglued

Science, Volume 389, Issue 6757, Page 234-234, July 2025.

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Disorder meets its match

Science, Volume 389, Issue 6757, Page 235-236, July 2025.

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RORing for oral tolerance

Science, Volume 389, Issue 6757, Page 236-237, July 2025.

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US should reject color-blind racial ideology

Science, Volume 389, Issue 6757, Page 242-243, July 2025.

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Combat disinformation about gender research

Science, Volume 389, Issue 6757, Page 243-243, July 2025.

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US disregards scientific consensus on race

Science, Volume 389, Issue 6757, Page 242-242, July 2025.

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Haunted by sharks

Science, Volume 389, Issue 6757, Page 228-231, July 2025.

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Molecular fossils show how life survived Snowball Earth

Science, Volume 389, Issue 6757, Page 220-221, July 2025.

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Astronomers race to study third known interstellar interloper

Science, Volume 389, Issue 6757, Page 222-223, July 2025.

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NIH suspends alleged ‘gain-of-function’ studies

Science, Volume 389, Issue 6757, Page 223-224, July 2025.

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U.S. cancels hunt for signs of cosmic inflation

Science, Volume 389, Issue 6757, Page 225-226, July 2025.

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Fruit fly studies mostly defy concerns about irreproducibility

Science, Volume 389, Issue 6757, Page 226-227, July 2025.

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Science philanthropy faces a new reality

Science, Volume 389, Issue 6757, Page 219-219, July 2025.

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AI to rewire life’s interactome: Structural foundation models help to elucidate and reprogram molecular biology

Science, Volume 389, Issue 6757, Page 244-245, July 2025.

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Unraveling the emergent chorus of the mind: Machine learning reveals how a hidden neural code orchestrates diverse emotion states

Science, Volume 389, Issue 6757, Page 245-245, July 2025.

in Science on 2025-07-17 06:00:04 UTC.

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Mapping the global coastal ocean with AI: Artificial neural networks can help better constrain the global carbon cycle in shallow seas

Science, Volume 389, Issue 6757, Page 245-245, July 2025.

in Science on 2025-07-17 06:00:04 UTC.

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In Science Journals

Science, Volume 389, Issue 6757, Page 246-248, July 2025.

in Science on 2025-07-17 06:00:04 UTC.

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Serotonin Receptors in Areas of the Emotion Regulation Network in Human and Rat Brains—A Comparative Autoradiographic Study

Serotonin receptors in areas of the emotion regulation network in human and rat brains a comparative autoradiographic study. Our systematic comparative analysis revealed significant differences of 5-HT_1A and 5-HT₂ receptor distributions and of their balance within and across components of the human emotion regulation network and homolog areas in rats. The data contribute to validate the rat as an appropriate model in the translational research of human mood disorders and provide reference data for comparisons to disorder related alterations.

ABSTRACT

Serotonergic neurotransmission is crucial for emotion processing and is dysregulated in mood disorders. To analyze the pathophysiology of disease and develop effective pharmacological treatments, the suitability of the rat as a model for translational research must be continuously validated. In vitro receptor autoradiography was used to characterize (dis)similarities of regional and laminar serotonergic 5-HT_1A and 5-HT₂ receptor distributions between components of the human emotion regulation network and homologous rat areas, including areas of the lateral prefrontal, orbitofrontal anterior and midcingulate cortices, hippocampal cornu Ammonis (CA) and dentate gyrus (DG), and the accumbens, central amygdaloid, and mediodorsal thalamic nuclei. In both species, mean 5-HT_1A densities were highest in cingulate area 25/infralimbic cortex and the hippocampus, and lowest in the accumbens. Whereas human CA presented significantly higher 5-HT_1A density than DG, the opposite was found in rats. Across the cortical depth, in humans, layers I–III and V contained the highest and lowest 5-HT_1A densities, respectively. In rats, layers I–II contained the lowest and layers V–VI the highest 5-HT_1A values. Mean 5-HT₂ densities were lower than 5-HT_1A densities in all areas of both species, whereby layers III and VI contained the highest and lowest 5-HT₂ densities, respectively. Rats presented a more widespread range of significant differences concerning the ratio between 5-HT_1A and 5-HT₂ receptors across examined areas than did humans. Concluding, this comparative study reveals species differences in 5-HT_1A and 5-HT₂ receptor densities in components of the emotion regulation network, which should be considered when using the rat as a model in the translational research of mood disorders.

in Journal of Comparative Neurology on 2025-07-17 03:34:27 UTC.

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Task relevance selectively modulates sensorimotor adaptation in the presence of multiple prediction errors

Journal of Neurophysiology, Ahead of Print.

in Journal of Neurophysiology on 2025-07-17 03:09:53 UTC.

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Spinally Projecting Serotonergic Neurons in Motor Network Modulation

Journal of Neurophysiology, Ahead of Print.

in Journal of Neurophysiology on 2025-07-17 03:09:51 UTC.

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Electroencephalogram Signatures of Propanidid-Mediated Sedation and Unconsciousness

Journal of Neurophysiology, Ahead of Print.

in Journal of Neurophysiology on 2025-07-17 03:01:53 UTC.

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Predicted task success and outcome history mediate eye movements toward locations with high informational or motivational value

Journal of Neurophysiology, Ahead of Print.

in Journal of Neurophysiology on 2025-07-17 02:59:57 UTC.

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Partial adaptation to surface movement during hand reaching

Journal of Neurophysiology, Ahead of Print.

in Journal of Neurophysiology on 2025-07-17 02:59:54 UTC.

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Single-nucleus neuronal transcriptional profiling of male C. elegans uncovers regulators of sex-specific and sex-shared behaviors

Morillo et al. generated a single-nucleus RNA sequencing atlas of adult Caenorhabditis elegans male neurons. Compared with hermaphrodite neurons, they identified neuronal markers, sex-biased features, and regulators of male-specific behavior. These data expand the transcriptional landscape of the C. elegans nervous system, providing a foundation for studies on sex differences.

in Cell Reports: Current Issue on 2025-07-17 00:00:00 UTC.

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Divergent sex-specific effects on a ketogenic diet: Male, but not female, mice exhibit oxidative stress and cellular senescence

Wei et al. demonstrate that a ketogenic diet induces oxidative stress and cellular senescence in an estrogen-dependent manner, with effects seen in male, but not female, mice. A similar response was observed with a high-fat diet, suggesting that elevated fatty acid oxidation may contribute to senescence under specific metabolic conditions.

in Cell Reports: Current Issue on 2025-07-17 00:00:00 UTC.

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Epistasis in the receptor-binding domain of contemporary H3N2 viruses that reverted to bind sialylated di-LacNAc repeats

Liang et al. shows how contemporary H3N2 viruses reverted to bind sialylated di-LacNAc at the molecular level. Using complex symmetrical and asymmetric N-glycans, major epistatic interactions were revealed.

in Cell Reports: Current Issue on 2025-07-17 00:00:00 UTC.

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Signaling by intracellular β2-adrenergic receptors regulates AMPA receptor trafficking and synaptic plasticity

Lee et al. show that OCT3 and PMAT transport norepinephrine (NE) into neurons to stimulate β2ARs that are in their interior. The ensuing phosphorylation of GluA1 on S845 by PKA drives AMPARs to the surface and postsynaptic sites during PKA-dependent forms of LTP.

in Cell Reports: Current Issue on 2025-07-17 00:00:00 UTC.

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How the world’s biggest bats got their enormous wingspans

Nature, Published online: 17 July 2025; doi:10.1038/d41586-025-02228-z

Genetic analysis helps to reveal why flying foxes can measure almost 2 metres from wingtip to wingtip.

in Nature on 2025-07-17 00:00:00 UTC.

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How sugar overload in early life affects the brain later

Nature, Published online: 17 July 2025; doi:10.1038/d41586-025-02229-y

A study in mice finds that a high-sucrose diet during youth has long-term implications for learning and brain connectivity.

in Nature on 2025-07-17 00:00:00 UTC.

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How the brain wakes up from sleep — and produces that morning feeling

Nature, Published online: 17 July 2025; doi:10.1038/d41586-025-02225-2

Certain patterns of brain activity during awakening correlate with a lower likelihood of the bleary-eyed state called ‘sleep inertia’.

in Nature on 2025-07-17 00:00:00 UTC.

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How to avoid nuclear war in an era of AI and misinformation

Nature, Published online: 17 July 2025; doi:10.1038/d41586-025-02260-z

Nuclear deterrence is no longer a two-player game, and emerging technologies further threaten the status quo. The result is a risky new nuclear age.

in Nature on 2025-07-17 00:00:00 UTC.

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Google tapped billions of mobile phones to detect quakes worldwide — and send alerts

Nature, Published online: 17 July 2025; doi:10.1038/d41586-025-02278-3

Study reveals how the tech behemoth is using the motions sensors on phones to expand quake warnings to more countries.

in Nature on 2025-07-17 00:00:00 UTC.

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Robots demonstrate principles of collective intelligence

Nature, Published online: 17 July 2025; doi:10.1038/d41586-025-02269-4

Lessons from developmental biology can be used to guide the behaviour of robot swarms.

in Nature on 2025-07-17 00:00:00 UTC.

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Heart from organ donor restarted outside the body — technique offers new source of organs

Nature, Published online: 17 July 2025; doi:10.1038/d41586-025-02243-0

Current procedures for reviving a heart for transplant are ethically fraught or expensive.

in Nature on 2025-07-17 00:00:00 UTC.

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AI and misinformation are supercharging the risk of nuclear war

Nature, Published online: 17 July 2025; doi:10.1038/d41586-025-02271-w

Emerging dangers are reshaping the landscape of nuclear deterrence and increasing the threat of mutual annihilation. Scientists must speak truth to power.

in Nature on 2025-07-17 00:00:00 UTC.

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‘Controlled chaos’: how to create an environment that fosters genius

Nature, Published online: 17 July 2025; doi:10.1038/d41586-025-02264-9

One free-wheeling 1930s cafe nurtured mathematical ideas including the theory of the nuclear bomb. That holds lessons for how to spur creative thought today.

in Nature on 2025-07-17 00:00:00 UTC.

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Reward encoded relative to experience

Nature Reviews Neuroscience, Published online: 17 July 2025; doi:10.1038/s41583-025-00951-0

Population activity of hippocampal place cells in mice flexibly encodes reward-relative representations of experience, which can amplify behaviorally relevant sequences of events in memory.

in Nature Reviews on 2025-07-17 00:00:00 UTC.

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Author Correction: Multifunctional nanoagents for ultrasensitive imaging and photoactive killing of Gram-negative and Gram-positive bacteria

Nature Communications, Published online: 17 July 2025; doi:10.1038/s41467-025-61902-y

Author Correction: Multifunctional nanoagents for ultrasensitive imaging and photoactive killing of Gram-negative and Gram-positive bacteria

in Nature Communications on 2025-07-17 00:00:00 UTC.

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Publisher Correction: Comprehensive evaluation of phosphoproteomic-based kinase activity inference

Nature Communications, Published online: 17 July 2025; doi:10.1038/s41467-025-62094-1

Publisher Correction: Comprehensive evaluation of phosphoproteomic-based kinase activity inference

in Nature Communications on 2025-07-17 00:00:00 UTC.

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Could a new cross-listed method of article publication fuel growth of data from interdisciplinary research

Scientific Data, Published online: 17 July 2025; doi:10.1038/s41597-025-05541-4

Researchers may avoid taking on interdisciplinary projects due to concern that publications outside of their own field would not be rewarded in their home departments. This means that data with an interdisciplinary focus is underprovided. We propose that journal parent publishers facilitate “cross-listed” journal publications where papers can be submitted to and peer-reviewed simultaneously by two journals, in different fields, with joint publication under a single DOI.

in Nature scientific data on 2025-07-17 00:00:00 UTC.

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A high-quality chromosome-scale genome assembly of Xingan mandarin (Citrus reticulata ‘Xingan’), a primitive Mandarin type

Scientific Data, Published online: 17 July 2025; doi:10.1038/s41597-025-05577-6

A high-quality chromosome-scale genome assembly of Xingan mandarin (Citrus reticulata ‘Xingan’), a primitive Mandarin type

in Nature scientific data on 2025-07-17 00:00:00 UTC.

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A chromosomal-level genome assembly of Odontolabis cuvera Hope, 1842 (Coleoptera: Lucanidae)

Scientific Data, Published online: 17 July 2025; doi:10.1038/s41597-025-05613-5

A chromosomal-level genome assembly of Odontolabis cuvera Hope, 1842 (Coleoptera: Lucanidae)

in Nature scientific data on 2025-07-17 00:00:00 UTC.

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A City-scale and Harmonized Dataset for Global Electric Vehicle Charging Demand Analysis

Scientific Data, Published online: 17 July 2025; doi:10.1038/s41597-025-05584-7

A City-scale and Harmonized Dataset for Global Electric Vehicle Charging Demand Analysis

in Nature scientific data on 2025-07-17 00:00:00 UTC.

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A Machine Learning-Reconstructed Dataset of River Discharge, Temperature, and Heat Flux into the Arctic Ocean

Scientific Data, Published online: 17 July 2025; doi:10.1038/s41597-025-05582-9

A Machine Learning-Reconstructed Dataset of River Discharge, Temperature, and Heat Flux into the Arctic Ocean

in Nature scientific data on 2025-07-17 00:00:00 UTC.

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A Global Multi-Sensor Dataset of Surface Water Indices from Landsat-8 and Sentinel-2 Satellite Measurements

Scientific Data, Published online: 17 July 2025; doi:10.1038/s41597-025-05562-z

A Global Multi-Sensor Dataset of Surface Water Indices from Landsat-8 and Sentinel-2 Satellite Measurements

in Nature scientific data on 2025-07-17 00:00:00 UTC.

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How plants pick their friends

A protein called RIN4 has a central role in helping legumes such as soybean and the bacteria rhizobia to develop a mutually beneficial relationship.

in eLife on 2025-07-17 00:00:00 UTC.

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A whole-organism landscape of X-inactivation in humans

As females are mosaic for X-inactivation, direct determination of X-linked allelic expression in bulk tissues is typically unfeasible. Using females that are non-mosaic (completely skewed) for X-inactivation (nmXCI) has proven a powerful and natural genetic system for profiling X-inactivation in humans. By combining allele-resolution data for one previously reported and two newly identified nmXCI females, we directly determined X-inactivation status of 380 X-linked genes across 30 normal tissues, including 198 genes for which XCI status is directly determined for the first time. Our findings represent a substantial advance in our understanding of human X-inactivation and will serve as a reference for dissecting the genetic origin of sex bias in human traits. In addition, our study reveals nmXCI as a common feature of the human female population, with profound consequences for the penetrance and expressivity of X-linked traits in humans.

in eLife on 2025-07-17 00:00:00 UTC.

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Pu.1/Spi1 dosage controls the turnover and maintenance of microglia in zebrafish and mammals

Microglia are brain-resident macrophages playing pivotal roles in central nervous system (CNS) development and homeostasis. Yet, the cellular and molecular basis governing microglia maintenance remains largely unknown. Here, by utilizing a visible conditional knockout allele of pu.1/spi1b gene (the master regulator for microglia/macrophage lineage development) to generate mosaic microglia populations in adult zebrafish, we show that while pu.1-deficient microglia are immediately viable, they are less competitive, and chronically eliminated through Tp53-mediated cell competition. Interestingly, when conditionally inactivating Pu.1 in adult spi-b (the orthologue of mouse Spi-b) null mutants, microglia are rapidly depleted via apoptosis, suggesting that Pu.1 and Spi-b regulate microglia maintenance in a dosage-dependent manner. The dosage-dependent regulation of microglia maintenance by PU.1/SPI1 is evolutionarily conserved in mice, as shown by conditionally inactivating single and both Spi1 alleles in microglia, respectively. Collectively, our study reveals the conserved cellular and molecular mechanisms controlling microglia turnover and maintenance in teleosts and mammals.

in eLife on 2025-07-17 00:00:00 UTC.

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Decoding protein phosphorylation during oocyte meiotic divisions using phosphoproteomics

Oocyte meiotic divisions represent a critical process in sexual reproduction, as a diploid non-dividing oocyte is transformed into a haploid fertilizable egg, as a prelude for the subsequent embryonic divisions and differentiation. Although cell differentiation and proliferation are governed by transcription, oocyte maturation and early embryonic divisions depend entirely on changes in protein abundance and post-translational modifications. Here, we analyze the abundance and phosphorylation of proteins during Xenopus oocyte meiotic maturation. We reveal significant shifts in protein stability, related to spindle assembly, DNA replication, and RNA-binding. Our analysis pinpoints broad changes in phosphorylation correlating with key cytological meiotic milestones, noteworthy changes in membrane trafficking, nuclear envelope disassembly, and modifications in microtubule dynamics. Additionally, specific phosphorylation events target regulators of protein translation, Cdk1 and the Mos/MAPK pathway, thereby providing insight into the dynamics of Cdk1 activity, as related to the meiotic cell cycle. This study sheds light on the orchestration of protein dynamics and phosphorylation events during oocyte meiotic divisions, providing a rich resource for understanding the molecular pathways orchestrating meiotic progression in the frog, and most likely applicable to other vertebrate species.

in eLife on 2025-07-17 00:00:00 UTC.

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POMC neurons control fertility through differential signaling of MC4R in kisspeptin neurons

Inactivating mutations in the melanocortin 4 receptor (MC4R) gene cause monogenic obesity. Interestingly, female patients also display various degrees of reproductive disorders, in line with the subfertile phenotype of Mc4r KO female mice. However, the cellular mechanisms by which MC4R regulates reproduction are unknown. Kiss1 neurons directly stimulate gonadotropin-releasing hormone (GnRH) release through two distinct populations: the Kiss1^ARH neurons, controlling GnRH pulses, and the sexually dimorphic Kiss1^AVPV/PeN neurons controlling the preovulatory luteinizing hormone (LH) surge. Here, we show that Mc4r expressed in Kiss1 neurons regulates fertility in females. In vivo, deletion of Mc4r from Kiss1 neurons in female mice replicates the reproductive impairments of Mc4r KO mice without inducing obesity. Conversely, re-insertion of Mc4r in Kiss1 neurons of Mc4r null mice restores estrous cyclicity and LH pulsatility without reducing their obese phenotype. In vitro, we dissect the specific action of Mc4r on Kiss1^ARH versus Kiss1^AVPV/PeN neurons and show that Mc4r activation excites Kiss1^ARH neurons through direct synaptic actions. In contrast, Kiss1^AVPV/PeN neurons are normally inhibited by MC4R activation except under elevated estradiol levels, thus facilitating the activation of Kiss1^AVPV/PeN neurons to induce the LH surge driving ovulation in females. Our findings demonstrate that POMC^ARH neurons acting through MC4R directly regulate reproductive function in females by stimulating the ‘pulse generator’ activity of Kiss1^ARH neurons and restricting the activation of Kiss1^AVPV/PeN neurons to the time of the estradiol-dependent LH surge, and thus unveil a novel pathway of the metabolic regulation of fertility by the melanocortin system.

in eLife on 2025-07-17 00:00:00 UTC.

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Interpretable protein-DNA interactions captured by structure-sequence optimization

Sequence-specific DNA recognition underlies essential processes in gene regulation, yet methods for simultaneous predictions of genomic DNA recognition sites and their binding affinity remain lacking. Here, we present the Interpretable protein-DNA Energy Associative (IDEA) model, a residue-level, interpretable biophysical model capable of predicting binding sites and affinities of DNA-binding proteins. By fusing structures and sequences of known protein-DNA complexes into an optimized energy model, IDEA enables direct interpretation of physicochemical interactions among individual amino acids and nucleotides. We demonstrate that this energy model can accurately predict DNA recognition sites and their binding strengths across various protein families. Additionally, the IDEA model is integrated into a coarse-grained simulation framework that quantitatively captures the absolute protein-DNA binding free energies. Overall, IDEA provides an integrated computational platform that alleviates experimental costs and biases in assessing DNA recognition and can be utilized for mechanistic studies of various DNA-recognition processes.

in eLife on 2025-07-17 00:00:00 UTC.

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Integration of parallel pathways for flight control in a hawkmoth reflects prevalence and relevance of natural visual cues

An animal’s behaviour is the result of multiple neural pathways acting in parallel, receiving information across and within sensory modalities at the same time. How these pathways are integrated, particularly when their individual outputs are in conflict, is key to understanding complex natural behaviours. We investigated this question in the visually guided flight of the hummingbird hawkmoth Macroglossum stellatarum. These insects were recently shown to partition their visual field, using ventrolateral optic flow cues to guide their flight like most insects, while the same stimuli in the dorsal visual field evoke a novel directional response. Using behavioural experiments which set the two pathways into conflict, we tested whether and how the ventrolateral and dorsal pathway integrate to guide hawkmoth flight. Combined with environmental imaging, we demonstrate that the partitioning of the visual field followed the prevalence of visual cues in the hawkmoths’ natural habitats, while the integration hierarchy of the two pathways matched the relevance of these cues for the animals’ flight safety, rather than their magnitude in the experimental setup or in natural habitats. These results provide new mechanistic insights into the vision-based flight control of insects and link these to their natural context. We anticipate our findings to be the starting point for comparative investigations into parallel pathways for flight guidance in insects from differently structured natural habitats.

in eLife on 2025-07-17 00:00:00 UTC.

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Duet model of predictive coding unifies diverse neuroscienceexperimental protocols

The brain continuously generates predictions about the external world, allowing us to rapidly detect and prioritize unexpected events, such as a mistuned piano note or an omitted one. Experimental studies have shown that neurons in sensory cortices respond to various types of contextual deviants across different protocols, and sensory response is not reduced to zero when a stimulus is fully expected. To account for diverse forms of observed deviations, here we introduce duet predictive coding, a minimal and biologically plausible framework in which functional subgroups of neurons encode positive and negative prediction errors separately. In contrast to classical predictive coding, which assumes top-down input is purely inhibitory, our theory posits that it is context-dependent rather than absolute. This model reproduces neural responses observed in diverse predictive coding paradigms across visual and auditory cortices. Critically, our framework predicts the existence of neurons tuned to negative prediction errors in the oddball paradigm, a prediction confirmed by our analyses, yet overlooked by classical predictive coding models. Our findings suggest that the brain's deviance detection relies on duet predictive error computation, offering a unifying explanation across seemingly disparate experimental protocols.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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A Novel Approach-Avoidance Task to Study Decision Making Under Outcome Uncertainty

To behave adaptively, people need to integrate information about probabilistic outcomes and balance drives to approach positive outcomes and avoid negative outcomes. However, questions remain about how uncertainty in positive and negative outcomes influence approach-avoid decision-making dynamics. To fill this gap, we developed a novel Probabilistic Approach Avoidance Task (PAAT) and characterized behavior in this task using sequential sampling models. In this task, participants (N=34, 24 females) made a series of choices between pairs of options, each consisting of variable probabilities of reaching a positive outcome (monetary reward) and of reaching a negative outcome (aversive image). Participants tended to choose options that maximized the likelihood of reward and minimized the likelihood of aversive outcomes. Moreover, the weights they placed on each of these differed for choices where these likelihoods were in opposition (i.e., the riskier option was also more rewarding; incongruent trials) relative to when these were aligned (congruent trials). Computational modeling revealed that the relative influence of rewarding and aversive outcomes on choice was captured by differences in the rate of decision-relevant information accumulation. These modeling results were validated with a series of model comparisons and posterior predictive checks, demonstrating that our sequential sampling models reliably captured our behavioral data. Together, these findings improve our understanding of the influence of motivational conflict, outcome type, and levels of uncertainty on approach-avoid decision-making.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Taste dysfunction in Long COVID

Persistent taste dysfunction may occur both as acute and long-term symptoms of SARS-CoV-2 infection (Long COVID), yet the underlying mechanisms are unknown at the histological, cellular, and molecular levels. This study investigates the underlying pathology in 28 non hospitalized subjects who reported persistent taste disturbances for over 12 months after testing positive for SARS-CoV-2. To assess taste function, subjects completed the Waterless Empirical Taste Test (WETT), which quantifies the subject's ability to taste each of the five human taste qualities: sweet, umami, bitter, sour, and salty. Biopsies of fungiform papillae were collected from 20 participants and analyzed histologically for overall taste bud structure and innervation and by quantitative PCR (qPCR) for expression of markers for different taste receptor cells (TRCs). Although all subjects reported subjective taste dysfunction, only five scored below the 20th percentile on overall taste sensitivity. However, 12 subjects exhibited total loss of one or more taste qualities and another 13 subjects tested below the 95% confidence interval for at least one taste modality. Notably, loss of sweet, umami, or bitter tastes - qualities mediated by a PLC{beta}2-transduction cascade - was significantly more common than loss of sour and salty, and this loss correlated with reduced expression of PLC{beta}2 mRNA. Histological analysis revealed generally preserved taste bud structure and innervation in all cases, with occasional disorganization resulting in isolated PLC{beta}2-immunoreactive cells. Our findings suggest long term taste dysfunction after COVID-19 disproportionately impacts PLC{beta}2-dependent taste 38 qualities and is not due to widespread structural damage of the taste periphery.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Spatio-molecular gene expression reflects dorsal anterior cingulate cortex structure and function in the human brain

In the human brain, the dorsal anterior cingulate cortex (dACC) plays key roles in various components of cognitive control, and is particularly relevant for reward processing and conflict monitoring. The dACC regulates expression of fear and pain, and its dysfunction is implicated in a number of neuropsychiatric disorders. Compared to more recently specialized neocortical areas, such as the dorsolateral prefrontal cortex (dlPFC), the dACC is evolutionarily older. The region's agranular structure, and other evolutionary specializations, such as the presence of von Economo neurons (VENs), contribute to its specialized roles in cognitive and emotional processing. Here, we generated paired spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the dACC in ten adult neurotypical donors to define molecular profiles for dACC cell types and spatial domains. Using non-negative matrix factorization (NMF), we integrated these data by identifying gene expression patterns within the snRNA-seq data, which were projected onto the SRT data to infer the spatial localization. Combining these data with publicly available resources, we revealed insights about molecular profiles, spatial topography, enrichment of disease risk, and putative connectivity of spatially-localized dACC cell types, including VENs. Utilizing published dlPFC snRNA-seq and SRT data collected in the same neurotypical brain donors used here, we deployed cross-region comparison analyses between dACC and dlPFC to understand spatio-molecular specializations and laminar organization across human brain evolution. To make this comprehensive molecular resource accessible to the scientific community, we made both raw and processed data freely available, including through interactive web applications.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Variants in glycine decarboxylase activate mechanisms of mitochondrial energy metabolism in the brain.

Brain energy metabolism is produced from glucose by mitochondrial oxidative phosphorylation. Variants in the mitochondrial enzyme glycine decarboxylase (GLDC) cause a rare neurological disease, non-ketotic hyperglycinemia (NKH), with expected hallmarks of brain glycine elevation and responsiveness to folate deficiency that are equivalent to the severity of Gldc mutations. We remarkably find that brains of young-attenuated mutant mice with a 1.5-fold increase in glycine are reduced [gt] 5-fold in GLDC, show a decline in both the mitochondrial lipoyl-transfer protein GCSH and lipoylation of the pyruvate dehydrogenase (PDH) complex, as well as concomitant rise in signatures of astrocyte mitochondrial b-oxidation of fatty acids and activation of neuronal PDH. Our findings suggest a novel GLDC mechanism of remodeling mitochondrial energy systems throughout the brain, established early in and sustained throughout post-natal NKH disease.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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A Developmental Atlas of the Drosophila Nerve Cord Uncovers a Global Temporal Code for Neuronal Identity

The assembly of functional neural circuits depends on the generation of diverse neural types with precise molecular identity and connectivity. Unlocking general principles of neuronal specification and wiring across the nervous system requires a systematic and high-resolution characterisation of its diversity, recently enabled by advances in single-cell transcriptomics and connectomics. However, linking the molecular identity of neurons to circuit architecture remains a key challenge. Here, we present a high-resolution developmental transcriptional atlas for the Drosophila melanogaster nerve cord, the central hub for sensory-motor circuits. With an unprecedented 38x coverage, this atlas enabled robust alignment to the adult connectome. We found that birth time sets a discrete versus continuous organisation of neuronal molecular identity, a difference we also identified in the connectome. We discovered a set of 17 transcription factors expressed in a conserved temporal sequence across all lineages, establishing a global temporal code for neuronal identity based on birth order, linking specification to differentiation across the nerve cord. Lastly, by mapping sex-specific transcriptional profiles to the connectome, we uncovered apoptosis and transcriptional divergence as key drivers for sex-specification. By resolving how molecular identity is temporally organized, this atlas opens new avenues to dissect the molecular mechanisms underpinning the development of neural circuits.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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The neural mechanisms supporting the rise and fall of maternal aggression

To protect the helpless young, lactating females dramatically increase aggression towards intruders, known as maternal aggression. However, attack is costly and risky. When pups no longer exist, maternal aggression rapidly declines. Our study reveals the critical role of the pathway from posterior amygdala cells expressing estrogen receptor alpha (PAEsr1) to the ventrolateral part of ventromedial hypothalamus cells expressing neuropeptide Y receptor Y2 (VMHvlNpy2r) in the rise and fall of maternal aggression. Functional manipulations and recordings demonstrate that VMHvl-projecting PAEsr1 (PAEsr1[->]VMHvl) cells are naturally active and required for maternal aggression. During lactation, PA-VMHvlNpy2r connection strengthens, and VMHvlNpy2r excitability increases to facilitate attack. Furthermore, PAEsr1 expresses abundant oxytocin receptors, enabling oxytocin to boost PAEsr1 cell output. After pup separation, the oxytocin level drops, causing decreased maternal aggression, which can be restored by optogenetically increasing the oxytocin level. Thus, diverse forms of plasticity occur at the PAEsr1-VMHvlNpy2r circuit to support need-based maternal aggression.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Sensory neurostimulation promotes stress resilience with frequency-specificity

Chronic stress is a major risk factor for neuropsychiatric disorders, acting via increased neuroinflammation and disrupted synaptic plasticity. While non-invasive visual or audiovisual neurostimulation (AV flicker) at 40Hz has been shown to modulate brain immune signaling and improve cognitive performance in mouse models of Alzheimer's disease, its effects in the context of stress remain unknown. Here we show that AV flicker protects against stress-induced behavioral, microglial, astrocytic, and synaptic changes in a sex- and frequency-specific manner. Male and female mice underwent 28 days of chronic unpredictable stress with concomitant daily AV flicker exposure at 10Hz, 20Hz, or 40Hz. Stress-induced behaviors were most effectively mitigated by 10Hz AV flicker in males and 40Hz AV flicker in females. In the medial prefrontal cortex, AV flicker normalized the balance of mature and immature dendritic spines and counteracted stress-induced molecular changes in neurons, microglia, and astrocytes, including in key neuropsychiatric risk genes. These findings show that frequency optimized AV flicker induces resilience to chronic stress.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Perceived time drives physical fatigue

Recent studies suggested that fundamental physiological processes, such as physical fatigue, rely on the perceived rather than the actual time. However, the neural correlates underlying this effect and its disentanglement from motivational factors (i.e., performance goals) remain unknown. To investigate the time deception effect on fatigue, we developed a novel EEG design in which participants performed 100 isometric contractions at a fixed pace and resistance per session. The actual contraction duration (short or long) and the calibration of the displayed clock (normal or biased to an acceleration or deceleration) were independently manipulated between sessions to examine whether fatigue and its neural correlates evolved based on perceived or actual time. Our results show an accumulation of physical fatigue that follows the perceived time, irrespective of motivational factors. This effect was consistently observed only when the clock was slowed down. This time deception effect was mediated by an oscillatory dynamic that followed perceived time in frontal (theta- and beta-bands) but not motor areas (beta-band). Further analyses highlighted the key role of the frontal oscillatory dynamics in the effectiveness of the time deception effect on physical fatigue.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Neuroligin-3 interaction with CSPG4 regulates normal and malignant glial precursors through PIEZO1

Glioma pathophysiology is robustly regulated by interactions with neurons. Key to these interactions is the role of neuroligin-3 (NLGN3), a synaptic adhesion molecule shed in response to neuronal activity1-5 that functions as a paracrine factor crucial for glioma growth. Here, we elucidate the mechanistic pathway whereby shed NLGN3 interacts with glioma and their normal glial counterpart. NLGN3 interacts with Chondroitin Sulfate Proteoglycan 4 (CSPG4) on both glioma and healthy oligodendrocyte precursor cells (OPCs)6-9, facilitating CSPG4 shedding by ADAM10. NLGN3-CSPG4 interactions and consequent shedding alter membrane tension, thereby activating PIEZO1 mechanosensitive channels and causing membrane depolarization. The NLGN3-CSPG4-PIEZO1 axis maintains OPCs in an undifferentiated, stem-like state and promotes glioma proliferation, underscoring important functional roles for the NLGN3-CSPG4-PIEZO1 axis in both healthy and malignant glial precursors.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Targeting Neuromuscular Junction Regeneration is a Therapeutic Strategy in ALS

Instability and denervation of the neuromuscular junction (NMJ) are early events in Amyotrophic Lateral Sclerosis (ALS), likely reflecting a progressive decline in the regenerative capacity of motor neurons (MNs) and their environment. To investigate this, we evaluated NMJ regeneration throughout disease progression in SOD1G93A mice following reversible axon terminal degeneration induced by -Latrotoxin. In parallel, we monitored the expression of CXCR4, a GPCR upregulated during axonal regeneration, and tested whether its pharmacological activation could mitigate ALS-related functional decline. We found that NMJ regenerative capacity is largely preserved during pre- and early symptomatic stages, and remains active in subsets of NMJs even at later stages. CXCR4 is expressed at axon terminals from early disease stages, declining only at end stage. Its expression is conserved across ALS models, including SOD1G93A pigs, hiPSC-derived MN with ALS mutations, and biopsies from sporadic ALS patients. CXCR4 stimulation improved motor function, NMJ innervation, MN survival, and respiratory performance in ALS mice, and axon outgrowth in iPSC-derived MN. These findings identify the NMJ and CXCR4 as viable therapeutic targets in ALS.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Fast efficient coding and sensory adaptation in gain-adaptive recurrent networks

As the statistics of sensory environments often change, neural sensory systems must adapt to maintain useful representations. Efficient coding prescribes that neuronal tuning curves should be optimized to the prior, but whether they can adapt rapidly is unclear. Empirically, tuning curves after repeated stimulus presentations exhibit "adapter repulsion", whose underlying mechanism remains uncertain, and which contrasts with the "prior attraction" expected under many efficient-coding models. We propose a gain-adaptive, recurrent sensory network model in which gains optimize a novel efficient-coding objective balancing accuracy and spiking cost. From the propagation of modulated gains throughout the network emerge quickly adaptive tuning curves. The model accounts for subtle adapter-repulsion effects under peaked priors and predicts fast prior attraction under broader distributions, for which we provide supporting behavioral evidence. Our framework reconciles seemingly contradictory adaptive phenomena, under a unified theoretical and mechanistic model of efficient coding mediated by gain modulation in recurrent circuits.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Chronic pain is linked to a resting-state neural archetype that optimizes learning from punishments

Chronic pain is a leading cause of disability, yet its underlying susceptibility traits remain unclear. Disorders like chronic pain may stem from extreme neural types, or archetypes, optimized for specific cognitive strategies and reflected in patterns of resting-state networks. Here, we examined a sample from the general population (n = 892) and three clinical samples with subacute back pain (n = 76), chronic back pain (n = 30), and treatment-resistant depression (n = 24). Using the sample from the general population, we found three neural archetypes that prioritize different cognitive strategies. Clinical pain samples, compared to the sample from the general population, mapped close to an archetype optimized for punishment learning (Archetype P). We replicated these results by recomputing the archetypes starting from the clinical pain samples, additionally revealing an association between Archetype P and pain severity. These findings suggest a neural-cognitive trait underlying susceptibility to chronic pain.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Complementary cortical and thalamic contributions to cell-type-specific striatal activity dynamics during movement

Coordinated motor behavior emerges from information flow across brain regions. How long-range inputs drive cell-type-specific activity within motor circuits remains unclear. The dorsolateral striatum (DLS) contains direct- and indirect-pathway medium spiny neurons (dMSNs and iMSNs) with distinct roles in movement control. In mice performing skilled locomotion, we recorded from dMSNs, iMSNs, and their cortical and thalamic inputs identified by monosynaptic rabies tracing. An RNN classifier and clustering analysis revealed functionally heterogeneous subpopulations in each population, with dMSNs preferentially activated at movement onset and offset, and iMSNs during execution. Cortical and thalamic inputs were preferentially activated during onset/offset and execution, respectively, though dMSN- and iMSN-projecting neurons in each region showed similar patterns. Locomotion phase-specific rhythmic activity was found in a subset of thalamic dMSN-projecting neurons and dMSNs. Cortex or thalamus inactivation reduced MSN activity. These findings suggest that corticostriatal and thalamostriatal inputs convey complementary motor signals via shared and cell-type-specific pathways.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Twice as nice: Boosts in adolescent reinforcement learning from Pavlovian bias and age-related prioritization of reward-motivated incidental memory.

Adolescence is a period marked by profound changes in both capacities for learning and the motivational drives that guide behavior. Motivated learning, including the ability to associate cues with actions that lead to positive or negative outcomes, is a fundamental component of adaptive behavior and is essential for survival. Equally important is the encoding of events during learning, which may be influenced by the valence of outcomes. Given the substantial neurocognitive changes in motivated learning and memory that occur from childhood to adulthood, adolescence provides a unique window to investigate mechanisms of these adaptive behaviors. Yet, we know surprisingly little about the development of these behaviors, with sparse extant research fraught with inconsistent findings. In this study, we examined motivated learning and incidental memory using a validated affective learning task in a sample of 174 participants aged 8 to 25 years. The task orthogonalized action and outcome valence and included incidental encoding of trial-unique images presented during feedback, followed by a delayed memory test. We show that adolescents outperform both children and adults in learning by leveraging Pavlovian response biases. In contrast, children exhibit enhanced memory for stimuli associated with positive outcomes compared to adolescents and adults. These findings point to distinct developmental advantages: enhanced learning performance in adolescence and enhanced memory for rewarding events in childhood, each potentially adaptive at their respective developmental stages. Together, these findings suggest opportunities to leverage learning and memory in youth for practical applications, such as education and policy setting.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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One of these things is not like the others: Theta, beta, & ERP dynamics of mismatch detection

Working memory (WM) enables the detection of mistakes by permitting one to notice when sensory input is mismatched to their internal prediction. Prior studies support the role of frontal midline theta activity, with an overlapping N200 event-related potential (ERP), as a mechanism for comparing incoming sensory stimuli to the internal model. Additionally, posterior low-beta activity has been proposed as a mechanism for processing incoming sensory stimuli in WM. However, it is unknown whether frontal midline theta activity and the N200 support mismatch detection, or whether posterior low-beta activity extends from sensory processing to detecting a mismatch between sensory input and the internal model. Here, we reveal that frontal midline theta supports mismatch detection and explains individual WM performance. Unexpectedly, instead of the N200, results show a positive slow wave ERP overlapping with the frontal midline theta mismatch response. Results additionally indicate a late posterior low-beta response persisting from stimulus presentation into the post-stimulus delay. Our findings establish frontal midline theta as a marker of successful mismatch detection, challenge the domain-general role of the N200 in error detection, and support theories linking posterior low-beta to processing incoming sensory stimuli.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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A Complexity-Science Framework for Studying Flow: Using Media to Probe Brain-Phenomenology Dynamics

Consciousness spans a range of phenomenological experiences, from effortless immersion to disengaged monotony, yet how such phenomenology emerges from brain activity is not well understood. Flow, in particular, has drawn attention for its links to performance and wellbeing, but existing neural accounts rely on single-region or small-network analyses that overlook the brain's distributed and dynamic nature. Complexity science offers tools that capture whole-brain dynamics, but this approach has rarely been applied to flow or to its natural comparison states of boredom and frustration. Consequently, it remains unclear whether tools drawn from complexity science can objectively separate phenomenological experiences while also clarifying their neural basis. Here we show that a complexity science approach distinguishes flow from boredom and frustration. We induced each phenomenological experience with a difficulty-titrated video game during functional magnetic resonance imaging and collected concurrent behavioral and self-report data. Whole-brain analyses revealed that flow is marked by lower global entropy, higher dynamical agility, and decreased dynamical complexity, whereas boredom and frustration exhibit different configurations of brain-dynamics metrics. Notably, these findings integrate previously separate prefrontal, network-synchrony, and cerebellar observations within a single dynamical systems framework and identify complexity-based markers that map the neural correlates of media-related benefits.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Cortical neural landscape captures mouse-to-mouse variability in anticipatory vs. inattentive decision making

Understanding individual variability in behavior is crucial for both basic and clinical neuroscience, yet it remains challenging to study in traditional single laboratory experiments with small sample size. Leveraging standardized behavioral and neural datasets from the International Brain Laboratory, comprising approximately 100 mice trained on a visual decision-making task, we investigated the structure and neural correlates of inter-animal behavioral variability. Using reaction time analysis and a deep learning-based embedding of individual animals, we uncovered large but low-dimensional differences in behavioral traits. Some mice consistently exhibited anticipatory responses, marked by fast reaction times, while others showed slower, more disengaged behavior. These behavioral profiles were consistent across sessions, with female mice tending to show more anticipatory behavior than males. We hypothesized that this behavioral spectrum reflects differences in the depth of underlying cortical states, reflected in the temporal dynamics of neural activity. Supporting this idea, we found that the characteristic timescale of population activity, measured during both inter-trial intervals and passive periods, correlated with an animal's anticipatory tendency across cortical areas, especially in medial visual areas. These findings suggest that individual differences in the cortical dynamics may underlie distinct decision-making strategies.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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C-LTMRs Regulate Thermosensation and Gate the Transition from Acute to Chronic Pain

C-low threshold mechanoreceptors (C-LTMRs) are traditionally associated with affective touch, yet emerging evidence suggests broader roles in sensory processing and pain modulation. We developed an intersectional genetic approach to selectively ablate C-LTMRs in adult mice by combining Nav1.8IRES-FLPo and THCreER drivers with a conditional DTR reporter. This approach yields robust, tissue-specific deletion of C-LTMRs without off-target effects in non-sensory tissues. C-LTMR-ablated mice exhibit altered thermotaxis behavior, including a sharpened and spatially restricted preference for warmth, while maintaining largely intact responses to gentle touch. Remarkably, following surgical or chemotherapeutic injury, these mice display and persistent mechanical and cold hypersensitivity, implicating C-LTMRs in the resolution of pain. Transcriptomic profiling of dorsal root ganglia (DRG) and dorsal horn of the spinal cord (DHSC) revealed widespread transcriptional dysregulation in pathways related to extracellular matrix remodeling, vascular function, gliogenesis, and inflammation, in naive mice. In C-LTMR-ablated mice, paclitaxel failed to induce pro-recovery transcriptional programs and instead promoted persistent neuroinflammatory signatures. These findings establish C-LTMRs as key modulators of pain recovery, acting through tissue-specific transcriptional programs that suppress inflammation and support sensory homeostasis.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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The common neural representation in the primary motor area between motor execution and kinesthetic motor imagery

Although motor imagery activates higher-order motor-related areas, the role of the primary motor area (M1) in motor imagery remains unclear. This study aimed to investigate whether motor imagery recruits a neural representation of fingers similar to that of motor execution in the hand M1. Ten healthy right-handed adults executed and kinesthetically imagined tapping using one of four fingers. Using functional magnetic resonance imaging with multi-voxel pattern analysis, we trained the decoder to classify which finger the participants were moving using brain activation during motor execution and tested whether it could predict which finger the participants were imaging to move during motor imagery (cross-classification). We also performed the classification in the reverse direction. The average accuracy of these cross-classifications was significantly higher than chance in the left hemisphere hand M1 (hand-M1). Analysis of the representational geometry showed that the distance of neural representations for the same fingers was statistically shorter than that for different fingers between motor execution and imagery. Furthermore, we conducted a replication study with 14 participants and found results similar to those of the original study. Our results suggest that the neural representation of kinesthetic motor imagery is partially similar to that of motor execution in the contralateral hand M1.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Motor learning drives region-specific transcriptomic remodeling in the motor cortex and dorsal striatum

Motor learning depends on coordinated activity across the motor cortex (M1) and dorsal striatum (dSTR), yet the molecular mechanisms driving learning-related synaptic and circuit remodeling remain unclear. Here, we combine activity-dependent genetic labeling (TRAP) with single-cell RNA sequencing to generate an unbiased, cell type-resolved transcriptional atlas of behaviorally engaged populations during a forelimb reaching task. We identify diverse activated neurons across M1 and dSTR, including a striking enrichment of Htr3a-expressing interneurons (Htr3a INs) in M1 that are selectively recruited during skilled reaching, as confirmed by two-photon calcium imaging. Corticostriatal projection neurons and striatal spiny projection neurons show subtype- and region-specific transcriptional remodeling involving genes linked to synaptic function, translation, and metabolism. Glial cells, including astrocytes, oligodendrocytes, and microglia, exhibit similarly robust, stage- and region-dependent gene regulation. These findings provide a comprehensive molecular framework for motor learning and highlight coordinated, cell type-specific transcriptional programs in neurons and glia that shape the encoding and retrieval of motor memory. Keywords: Motor learning, transcriptomic remodeling, motor cortex, dorsal striatum, Htr3a-expressing interneurons, single-cell RNA sequencing Highlights: -Motor learning activates interneuron cell types in motor cortex and striatum. -Htr3a-expressing interneurons in motor cortex are specifically activated while performing a learned reaching behavior. -Transcriptome remodeling exhibited distinct patterns between motor cortex and striatum. -Glial cells showed stage- and region-specific transcriptomic alteration patterns that align with those in neurons

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Developmental Stage-Dependent Transcriptomic Responses to Neonatal Intraventricular Hemorrhage

Neonatal intraventricular hemorrhage (IVH) is a major complication of preterm birth, yet how developmental stage influences the brains response to injury remains unclear. We performed single-nucleus RNA sequencing on rat brains 24 hours after IVH at postnatal day 2 (PND2) or day 5 (PND5) to define transcriptional responses across cell types. We identified 42 distinct cell populations and found that PND5 brains exhibited a markedly stronger immune and inflammatory response to IVH, with a threefold increase in differentially expressed genes compared to PND2. Microglia were the most perturbed cell type at both stages, showing increased oxidative stress and polarization toward both pro- and anti-inflammatory phenotypes at PND5. Ligand-receptor and regulon analysis revealed a shift from reparative IGF2 and TGF-beta; signaling at PND2 to proinflammatory Wnt signaling and activation of Runx1 and Stat5 at PND5. These findings highlight the importance of developmental timing in shaping the neuroimmune response to IVH and identify potential stage-specific therapeutic targets.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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New Synapse Detection in the Whole-Brain Connectome of Drosophila

The FlyWire Drosophila brain connectome is a graph of roughly 140K neurons and >50 million synaptic connections reconstructed from the FAFB EM dataset4. Challenges in synapse detection were identified for neurons with features such as dark cytosols, axo-axonic synapses, and complex polyadic synapses, due to limitations in ground truth data for these cells and the inherent complexity of these synapse types. To address these issues, we trained new neural networks using iteratively generated ground truth annotations and detected synapses across the entire FAFB dataset, producing what we refer to here as the Princeton synapses. These synapses were evaluated in both control regions, such as subareas of the mushroom body calyx and lateral horn, which were also chosen by Buhmann et al.3 for evaluation, as well as challenging regions, including Johnston Organ neurons (JONs), photoreceptors, and other cell types. The new model shows significant improvements, achieving up to a 0.23 F-score increase in challenging areas, while maintaining performance in control regions. Princeton synapses also show an 8-9% improvement in neuron clustering within cell types and better left/right symmetry scores, especially for photoreceptors. Additionally, neuron type membership can be predicted from connectivity patterns alone with weighted F-scores of 0.93 for Princeton synapses versus 0.91 for Buhmann synapses. The updated Princeton synapses are now accessible via Codex (codex.flywire.ai).

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Bmal1 expression is minimal or absent in human and mouse cerebral microglia

Microglia orchestrate immunological responses in the brain and play an important role in maintaining homeostatic brain functions. Several studies have reported clock gene expression in microglia and the circadian rhythm they drive has been linked to the modulation of immune responses and neuronal functions. In the current study, complementary approaches, including immunofluorescence, multiplexed fluorescence in situ hybridization, and liquid chromatography-mass spectrometry proteomics of isolated CD11b+ microglia, were combined with publicly available transcriptomic and epigenomic datasets to investigate the expression of the core clock gene BMAL1 in human post-mortem cortical and limbic areas as well as mouse brain. The majority of BMAL1-expressing cells were found to be neurons, with microglia representing a negligeable proportion. We also identified significantly lower chromatin accessibility or ''openness'' for BMAL1 gene regulatory regions (such as promoters and enhancers) in microglia compared to neurons. These regulatory regions in microglia were enriched for ETS domain transcription factor (TF) binding sites. Together, this suggests a strong role of chromatin remodeling factors in suppressing BMAL1 gene expression in microglia. Finally, while we observed a very low expression, BMAL1 TF motifs were accessible in open chromatin landscape of microglia, which may lead to downstream gene-regulatory effects upon binding, even if BMAL1 expression is constitutively low. Overall, our results reveal low or absent expression of BMAL1 in microglia and point towards potential epigenetic mechanisms regulating its expression in these cells.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Diet context gates AgRP neuron involvement in Semaglutide-induced weight loss

Semaglutide, a GLP-1R agonist, is widely used for obesity and type 2 diabetes, but its neural mechanisms remain unclear. AgRP neurons regulate energy balance, yet their role in the effects of Semaglutide is unknown. We show that sustained treatment of female mice with Semaglutide leads to activation rather than inhibition of AgRP neurons. Ablation or hypofunction of AgRP neurons through cell-specific knockout of Sirt1 reduces Semaglutide-induced weight loss and impairs its hypoglycemic effects in female mice under Standard Diet. However, acute or chronic exposure to High-Fat Diet makes AgRP neurons dispensable for weight loss, suggesting that neural substrates for the actions of Semaglutide depends on dietary composition. Re-exposure to Standard Diet recovers the necessity for AgRP neurons, underscoring the influence of nutritional status on GLP-1R pathways. Our findings show the necessity for AgRP neurons in sustaining Semaglutide-induced weight loss in female mice on standard diet in vivo.

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Bounds on the computational complexity of neurons due to dendritic morphology

The simple linear threshold units used in many artificial neural networks have a limited computational capacity. Famously, a single unit cannot handle non-linearly separable problems like XOR. In contrast, real neurons exhibit complex morphologies as well as active dendritic integration, suggesting that their computational capacities outperform those of simple linear units. Considering specific families of Boolean functions, we empirically examine the computational limits of single units that incorporate more complex dendritic structures. For random Boolean functions, we show that there is a phase transition in learnability as a function of the input dimension, with most random functions below a certain critical dimension being learnable and those above not. This critical dimension is best predicted by the overall size of the dendritic arbor. This demonstrates that real neurons have a far higher computational complexity than is usually considered in neural models, whether in machine learning or computational neuroscience. Furthermore, using architectures that are, respectively, more 'apical' or 'basal', we show that there are non-trivially disjoint sets of learnable functions by each type of neuron. Importantly, these two types of architectures differ in the robustness and generality of the computations they can perform. The basal-like architecture shows a higher probability of function realization, while the apical-like architecture shows an advantage with fast retraining for different functions. Given the cell-type specificity of morphological characteristics, these results suggest both that different components of the dendritic arbor as well as distinct cell types may have distinct computational roles. Our analysis offers new directions for neuron-level inductive biases in NeuroAI models using scalable models for neuronal cell-type specific computation

in bioRxiv: Neuroscience on 2025-07-17 00:00:00 UTC.

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Exploring Neural Dynamics in the Auditory Telencephalon of Crows Using Functional Ultrasound Imaging

Crows, renowned for advanced cognitive abilities and vocal communication, rely on intricate auditory systems. While the neuroanatomy of corvid auditory pathways is partially explored, the underlying neurophysiological mechanisms are largely unknown. This study used functional ultrasound imaging (fUSi) to investigate sound-induced cerebral blood volume (CBV) changes in the Field L complex of the auditory telencephalon in two female crows. fUSi revealed frequency-specific CBV responses, showing a tonotopic organization within the Field L complex, with low frequencies in the posterior dorsal region and high frequencies in the anterior ventral region. Machine learning analyses showed fUSi signals could be used to classify sound types accurately, in both awake and anesthetized states. Variable CBV responses to longer sound stimuli suggest a delineation of subregions within the Field L complex. Together, these findings highlight the potential of fUSi for providing high-resolution insights into functional systems in corvids, enabling future exploration of experimental task-related cognitive dynamics.

in Journal of Neuroscience on 2025-07-16 16:30:22 UTC.

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This Week in The Journal

in Journal of Neuroscience on 2025-07-16 16:30:22 UTC.

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Positron Emission Tomography (PET) Neuroimaging of the Pink1-/- Rat Parkinson Disease Model with the Norepinephrine Transporter (NET) Ligand [18F]NS12137

Evidence suggests that the neurotransmitter norepinephrine may play an important role in Parkinson disease (PD). The norepinephrine transporter (NET) regulates noradrenergic signaling and can serve as an index of noradrenergic innervation in neuroimaging studies. The Pink1-/- rat model, which exhibits many signs similar to PD, notably in the nonmotor domain, exhibits abnormal noradrenergic markers. Here, we sought to (1) implement reference region pharmacokinetic modeling of positron emission tomography (PET) imaging with the novel NET ligand [¹⁸F]NS12137, (2) validate the resulting indices of NET concentration, and (3) characterize NET in the Pink1-/- model. Long–Evans Pink1-/- male rats were imaged by PET with [¹⁸F]NS12137 at 9 and 11 months and compared with wild-type (WT) controls. An additional group of WT rats of both sexes were imaged with [¹⁸F]NS12137 PET after pretreatment with the specific and selective NET ligand nisoxetine. Binding in locus coeruleus (LC), thalamus (Thal), and prelimbic area (PrL), regions rich in NET, was analyzed by a two-tissue compartment reversible binding model using a cerebellar reference region. [¹⁸F]NS12137 binding exhibited moderate test–retest reproducibility in LC, Thal, and PrL. Nisoxetine blockade yielded substantial reductions of [¹⁸F]NS12137 binding in LC. Compared with WT controls, Pink1-/- rats exhibited reduced binding in Thal and PrL. Pharmacokinetic analysis of [¹⁸F]NS12137 PET provides a reproducible and specific measure of NET binding and indicates reduced NET in PD-related brain regions in Pink1-/- rats. Noninvasive in vivo [¹⁸F]NS12137 PET imaging is therefore a promising method for the study of potential therapies in the Pink1-/- rat.

in Journal of Neuroscience on 2025-07-16 16:30:22 UTC.

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A Normative Account of 3D Motion Perception from Natural Scenes

in Journal of Neuroscience on 2025-07-16 16:30:22 UTC.

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Erratum: Ostroff et al., "Combined Active Humoral and Cellular Immunization Approaches for the Treatment of Synucleinopathies"

in Journal of Neuroscience on 2025-07-16 16:30:22 UTC.

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Neuropathic Pain-Like Responses in a Chronic CNS Injury Model Are Mediated by Corticospinal-Targeted Spinal Interneurons

Chronic neuropathic pain is a persistent and debilitating outcome of traumatic central nervous system injury, affecting up to 80% of individuals. Postinjury pain is refractory to treatments due to the limited understanding of the brain–spinal cord circuits that underlie pain signal processing. The corticospinal tract (CST) plays critical roles in sensory modulation during skilled movements and tactile sensation; however, a direct role for the CST in injury-associated neuropathic pain is unclear. Here we show that complete, selective CST transection at the medullary pyramids leads to hyperexcitability within lumbar deep dorsal horn and hindlimb allodynia-like behavior in chronically injured adult male and female mice. Chemogenetic regulation of CST-targeted lumbar spinal interneurons demonstrates that dysregulation of activity in this circuit underlies the development of tactile allodynia in chronic injury. Our findings shed light on an unrecognized circuit mechanism implicated in CNS injury-induced neuropathic pain and provide a novel target for therapeutic intervention.

in Journal of Neuroscience on 2025-07-16 16:30:22 UTC.

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V2b Neurons Act via Multiple Targets to Produce in Phase Inhibition during Locomotion

Spinal interneurons shape motor neuron activity. Gata3⁺ V2b neurons are a major inhibitory spinal population. These neurons are present at multiple spinal levels in mice, suggesting an important function in motor control. In zebrafish, our previous work showed that V2b neurons are evenly distributed along the spinal cord, where they act to slow down locomotion. However, the timing of V2b activity during locomotion, their postsynaptic targets other than motor neurons, and their recruitment across different behaviors remain unknown. In this study, we address these questions using larval zebrafish. First, via optogenetic mapping of output in the rostrocaudal axis, we demonstrate that V2b neurons robustly inhibit motor neurons and other major spinal populations, including V2a, V1, commissural neurons, and other V2b neurons. V2b inhibition is patterned along the rostrocaudal axis, providing long-range inhibition to motor and V2a neurons but more localized inhibition of V1 neurons. Next, by recording V2b activity during different visually and electrically evoked movements, we show that V2b neurons are specifically recruited for forward swims and turns, but not for fast escape movements. Furthermore, a subset of V2b neurons also exhibited short-latency sensory-evoked activity preceding motor initiation. Finally, we show that V2b inhibition occurs in phase with the leading edge of the motor burst, in contrast to V1 inhibition which occurs in phase with the falling edge of the motor burst. Taken together, these data show that in axial motor networks, V2b neurons act via multiple targets to produce in phase, leading inhibition during locomotion.

in Journal of Neuroscience on 2025-07-16 16:30:22 UTC.

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HDAC3 Serine 424 Phospho-mimic and Phospho-null Mutants Bidirectionally Modulate Long-Term Memory Formation and Synaptic Plasticity in the Adult and Aging Mouse Brain

Long-term memory (LTM) formation is negatively regulated by histone deacetylase 3 (HDAC3), a transcriptional repressor. Emerging evidence suggests that posttranslational phosphorylation of HDAC3 at its serine 424 (S424) residue is critical for its deacetylase activity in transcription. However, it remains unknown if HDAC3 S424 phosphorylation regulates the ability of HDAC3 to modulate LTM formation. To examine the functionality of S424, we expressed an HDAC3-S424D phospho-mimic mutant (constitutively active form) or an HDAC3-S424A phospho-null mutant (phospho-dead form) in the dorsal hippocampus of mice. We assessed the functional consequence of these mutants on LTM formation and long-term potentiation (LTP) in young adult male mice. We also assessed whether the HDAC3-S424A mutant could ameliorate age-related deficits in LTM and LTP in aging male and female mice. Results demonstrate that young adult male mice expressing the HDAC3-S424D phospho-mimic mutant in the dorsal hippocampus exhibit significantly impaired LTM and LTP. In contrast, the HDAC3-S424A phospho-null mutant expressed in the hippocampus of young adult male mice enabled the transformation of subthreshold learning into robust LTM and enhanced LTP. Similarly, expression of the HDAC3-S424A mutant enabled LTM formation and enhanced LTP in aging male and aging female mice. Overall, these findings demonstrate that HDAC3 S424 is a pivotal residue that has the ability to bidirectionally regulate synaptic plasticity and LTM formation in the adult and aging brain.

in Journal of Neuroscience on 2025-07-16 16:30:22 UTC.

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Oddball Evoked Deviant Responses Reflect Complex Context-Dependent Expectations in Mouse V1

Evoked responses in the mouse primary visual cortex can be modulated by the temporal context in which visual inputs are presented. Oddball stimuli embedded in a sequence of regularly repeated visual elements have been shown to drive relatively large deviant responses, a finding that is generally consistent with the theory that cortical circuits implement a form of predictive coding. These results can be confounded by short-term adaptation effects, however, that make interpretation difficult. Here we use various forms of the oddball paradigm to disentangle temporal and ordinal components of the deviant response, showing that it is a complex phenomenon affected by temporal structure, ordinal expectation, and event frequency. Specifically, we use visually evoked potentials to show that deviant responses occur over a large range of time in male and female mice, cannot be explained by a simple adaptation model, scale with predictability, and are modulated by violations of both first- and second-order sequential expectations. We also show that visual sequences can lead to long-term plasticity in some circumstances.

in Journal of Neuroscience on 2025-07-16 16:30:22 UTC.

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Phospho-CREB Regulation on NMDA Glutamate Receptor 2B and Mitochondrial Calcium Uniporter in the Ventrolateral Periaqueductal Gray Controls Chronic Morphine Withdrawal in Male Rats

Opioid use disorder (OUD) is a chronic disease of the brain, and it currently continues at crisis proportions in the United States. Opioid physical withdrawal is a major driver of compulsive drug-taking behavior, triggering short-term relapse of opioid addiction. Early pharmacological evidence shows that midbrain periaqueductal gray (PAG) plays an important role in morphine withdrawal (MW). However, we still know few details about the underlying molecular mechanisms. Improving our understanding of such mechanisms will enable increasingly safe and effective treatments for patients with OUD. Here, MW was induced by the naloxone precipitation after chronic intraperitoneal administration of morphine for a period of 5 d in Sprague Dawley male rats. MW increased phosphorylation of cAMP response element binding protein (pCREB, a primary marker of CREB functional activation), NMDA glutamate receptor 2B subunit (NR2B), and mitochondrial calcium uniporter (MCU) within the ventrolateral PAG (vlPAG). Inhibition of pCREB, NR2B, or MCU within this brain region reduced the severity of MW. Chromatin immunoprecipitation (ChIP) assay and luciferase report assay demonstrated that pCREB mediated the transcription of the Grin2b (glutamate ionotropic receptor NMDA type subunit 2B, encoding NR2B) and Ccdc109a (encoding MCU) genes. These findings describe the role of pCREB in Grin2b and Ccdc109a gene transcription levels in the vlPAG during MW. The study may provide a novel therapeutic approach for OUD.

in Journal of Neuroscience on 2025-07-16 16:30:22 UTC.

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Change of Spiny Neuron Structure in the Basal Ganglia Song Circuit and Its Regulation by miR-9 during Song Development

Juvenile zebra finches learn to sing by imitating conspecific songs of adults during a sensitive period early in life. Area X is a basal ganglia nucleus of the song control circuit specialized for song-related sensory–motor learning during song development. The structural plasticity and the molecular mechanisms regulating neuronal structure in Area X during song development and maturation are unclear. In this study, we examined the structure of spiny neurons, the main neuron type in Area X, at key stages of song development in male zebra finches. We report that dendritic arbor of spiny neurons expands during the sensitive period for song learning, and this initial growth is followed by pruning of dendrites and spines accompanied by changes in spine morphology as the song circuit matures. Previously, we showed that overexpression of miR-9 in Area X impairs song learning and performance and alters the expression of many genes that have important roles in neuronal structure and function (Shi et al., 2018). As an extension of that study, we report here that overexpression of miR-9 in spiny neurons in juvenile zebra finches reduces dendritic arbor complexity and spine density in a developmental stage-specific manner. We also show that miR-9 regulates the structural maintenance of spiny neurons in adulthood. Together, these findings reveal dynamic microstructural changes in the song circuit during the sensitive period of song development and provide evidence that miR-9 regulates neuronal structure during song development and maintenance.

in Journal of Neuroscience on 2025-07-16 16:30:22 UTC.

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Is It Me or the Train Moving? Humans Resolve Sensory Conflicts with a Nonlinear Feedback Mechanism in Balance Control

Humans use multiple sensory systems to estimate body orientation in space. Sensory contributions change depending on context. A predominant concept for the underlying multisensory integration (MSI) is the linear summation of weighted inputs from individual sensory systems. Changes of sensory contributions are typically attributed to some mechanism explicitly adjusting weighting factors. We provide evidence for a conceptually different mechanism that performs a multisensory correction if the reference of a sensory input moves in space without the need to explicitly change sensory weights. The correction is based on a reconstruction of the sensory reference frame motion (RFM) and automatically corrects erroneous inputs, e.g., when looking at a moving train. The proposed RFM estimator contains a nonlinear dead zone that blocks corrections at slow velocities. We first demonstrate that this mechanism accounts for the apparent changes in sensory contributions. Second, using a balance control model, we show predictions of specific distortions in body sway responses to perturbations caused by this nonlinearity. Experiments measuring sway responses of 24 subjects (13 female, 11 male) to visual scene movements confirmed these predictions. The findings indicate that the central nervous system resolves sensory conflicts by an internal reconstruction of the cause of the conflict. Thus, the mechanism links the concept of causal inference to shifts in sensory contributions, providing a cohesive picture of the MSI for the estimation of body orientation in space.

in Journal of Neuroscience on 2025-07-16 16:30:22 UTC.

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Increased Neuronal Expression of the Early Endosomal Adaptor APPL1 Replicates Alzheimers Disease-Related Endosomal and Synaptic Dysfunction with Cholinergic Neurodegeneration

Endosomal system dysfunction within neurons is a prominent early feature of Alzheimer's disease (AD) pathology. Multiple AD risk factors are regulators of endocytosis and known to cause hyperactivity of the early endosome small GTPase rab5, resulting in neuronal endosomal pathway disruption and cholinergic neurodegeneration. Adaptor protein containing Pleckstrin homology domain, Phosphotyrosine binding domain, Leucine zipper motif (APPL1), an important rab5 effector protein and signaling molecule has been shown in vitro to interface between endosomal and neuronal dysfunction through a rab5-activating interaction with the BACE1-generated C-terminal fragment of amyloid precursor protein (APP-βCTF), a pathogenic APP fragment generated within endosomal compartments. To understand the contribution of APPL1 to AD-related endosomal dysfunction in vivo, we generated a transgenic mouse model overexpressing human APPL1 within neurons (Thy1-APPL1). Strongly supporting the important endosomal regulatory roles of APPL1 and their relevance to AD etiology, Thy1-APPL1 mice (both sexes) develop enlarged neuronal early endosomes and increased synaptic endocytosis due to increased rab5 activation. We demonstrated pathophysiological consequences of APPL1 overexpression, including functional changes in hippocampal long-term potentiation (LTP) and long-term depression (LTD), degeneration of large projection cholinergic neurons of the basal forebrain, and impaired hippocampal-dependent memory. Our evidence shows that neuronal APPL1 elevation modeling its functional increase in the AD brain induces a cascade of AD-related pathological effects within neurons, including early endosome anomalies, synaptic dysfunction, and selective neurodegeneration. Our in vivo model highlights the contributions of APPL1 to the pathobiology and neuronal consequences of early endosomal pathway disruption and its potential value as a therapeutic target.

in Journal of Neuroscience on 2025-07-16 16:30:22 UTC.

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Cardiogenic and chronobiological mechanisms in seizure-induced sinus arrhythmias

by Pan Li, Sangbo Lee, Kwang-Yeon Choi, Jonathan E. Rubin, Jae Kyoung Kim

Seizure-induced cardiac arrhythmias, such as ictal (during seizure) or postictal (post-seizure) sinus arrhythmias, are potential triggers for sudden unexpected death in epilepsy. Traditionally, these arrhythmias have been attributed to changes in autonomic balance during ictal or postictal phases, as per the neurogenic mechanism. However, it remains unclear if these arrhythmias may involve intrinsic cardiogenic mechanisms. Furthermore, while circadian and sleep-wake patterns influence both neurogenic and cardiogenic mechanisms, a direct mechanistic link to seizure-induced arrhythmias remains to be established. In this study, we utilized a mathematical model of mouse sinoatrial nodal cell pacemaking and an autonomic clamping protocol, to dissect neurocardiogenic mechanisms in seizure-induced sinus arrhythmias and to test the hypothesis that circadian and sleep-wake rhythms directly modulate cellular susceptibility to these arrhythmias. Our simulations revealed that, in the context of altered autonomic levels associated with seizure progression, diverse seizure-induced sinoatrial nodal cell firing patterns during ictal or postictal phases can be triggered directly by intrinsic cardiac dynamics, without the need for dynamical changes in within-phase autonomic activities. This finding highlights the distinct roles of neurogenic and cardiogenic mechanisms in shaping sinoatrial nodal cell firing patterns, challenging the predominance of the neurogenic mechanism. This neurocardiogenic framework also successfully captures distinct circadian and vigilance state patterns of seizure-induced arrhythmias. Specifically, while daytime sleep predisposed sinoatrial nodal cells to postictal sinus arrhythmias, nighttime wakefulness promoted ictal sinus arrhythmias. However, these circadian patterns can be disrupted when sleep-wake cycles are decoupled from circadian rhythms, supporting the hypothesis that sleep-wake patterns can directly be a key determinant of seizure-induced sinus arrhythmias. Our findings may potentially facilitate the development of novel therapeutic strategies for managing the risk of sudden unexpected death in epilepsy.

in PLoS Computational Biology on 2025-07-16 14:00:00 UTC.

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EUP: Enhanced cross-species prediction of ubiquitination sites via a conditional variational autoencoder network based on ESM2

by Junhao Liu, Zeyu Luo, Rui Wang, Xin Li, Yawen Sun, Zongqing Chen, Yu-Juan Zhang

Ubiquitination is critical in biomedical research. Predicting ubiquitination sites based on deep learning model have advanced the study of ubiquitination. However, traditional supervised model limits in the scenarios where labels are scarcity across species. To address this issue, we introduce EUP, an online webserver for ubiquitination prediction and model interpretation for multi-species. EUP is constructed by extracting lysine site-dependent features from pretrained language model ESM2. Then, utilizing conditional variational inference to reduce the ESM2 features to a lower-dimensional latent representation. By constructing downstream models built on this latent feature representation, EUP exhibited superior performance in predicting ubiquitination sites across species, while maintaining low inference latency. Furthermore, key features for predicting ubiquitination sites were identified across animals, plants, and microbes. The identification of shared key features that capture evolutionarily conserved traits enhances the interpretability of the EUP model for ubiquitination prediction. EUP is free and available at (https://eup.aibtit.com/).

in PLoS Computational Biology on 2025-07-16 14:00:00 UTC.

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Impact of ligand binding on VEGFR1, VEGFR2, and NRP1 localization in human endothelial cells

by Sarvenaz Sarabipour, Karina Kinghorn, Kaitlyn M. Quigley, Anita Kovacs-Kasa, Brian H. Annex, Victoria L. Bautch, Feilim Mac Gabhann

The vascular endothelial growth factor receptors (VEGFRs) bind to cognate ligands to facilitate signaling pathways critical for angiogenesis, the growth of new capillaries from existing vasculature. Intracellular trafficking regulates the availability of receptors on the cell surface to bind ligands, which regulate activation, and the movement of activated receptors between the surface and intracellular pools, where they can initiate different signaling pathways. Using experimental data and computational modeling, we recently demonstrated and quantified the differential trafficking of three VEGF receptors, VEGFR1, VEGFR2, and coreceptor Neuropilin-1 (NRP1). Here, we expand that approach to quantify how the binding of different VEGF ligands alters the trafficking of these VEGF receptors and demonstrate the consequences of receptor localization and ligand binding on the localization and dynamics of signal initiation complexes. We include simulations of four different splice isoforms of VEGF-A and PLGF, each of which binds to different combinations of the VEGF receptors, and we use new experimental data for two of these ligands to parameterize and validate our model. We show that VEGFR2 trafficking is altered in response to ligand binding, but that trafficking of VEGFR1 is not; we also show that the altered trafficking can be explained by a single mechanistic process, increased internalization of the VEGFR2 receptor when bound to ligand; other processes are unaffected. We further show that even though the canonical view of receptor tyrosine kinases is of activation on the cell surface, most of the ligand-receptor complexes for both VEGFR1 and VEGFR2 are intracellular. We also explore the competition between the receptors for ligand binding, the so-called ‘decoy effect’, and show that while in vitro on the cell surface minimal such effect would be observed, inside the cell the effect can be substantial and may influence signaling. We term this location dependence the ‘reservoir effect’ as the size of the local ligand reservoir (large outside the cell, small inside the cell) plays an integral role in the receptor-receptor competition. These results expand our understanding of receptor-ligand trafficking dynamics and are critical for the design of therapeutic agents to regulate ligand availability to VEGFR1 and hence VEGF receptor signaling in angiogenesis.

in PLoS Computational Biology on 2025-07-16 14:00:00 UTC.

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Multi-scale computational modeling towards efficacy in radiopharmaceutical therapies while minimizing side effects: Modeling of amino acid infusion

by Aryan Golzaryan, Mohammad Souri, Farshad M. Kashkooli, Arman Rahmim, M. Soltani

Amino acid infusion (AAI) is a technique used in radiopharmaceutical therapy (RPT) to reduce toxicity in kidney and increase clearance rate of radiopharmaceuticals from body. In this study our aim is to evaluate its effect in personalized RPT considering kidney and salivary glands as dose limiting organs using a multiscale modeling framework. We developed a Physiologically-Based Pharmacokinetic (PBPK) model consisting of 19 compartments, personalized it for four prostate cancer patients using data derived from gamma camera imaging. This model was used to investigate the influence of AAI on the absorbed dose to tumors and organs at risk. We then computed the maximum safe injected activity based on the PBPK model. To address the effects of interstitial fluid pressure (IFP) and tumor heterogeneity, we coupled the PBPK model with convection-diffusion-reaction (CDR) equations. To compare the effectiveness of our modeling approaches, we calculated absorbed doses to the tumors with and without AAI, using both the standalone PBPK model and the coupled PBPK-CDR model. Our findings revealed a relative error (RE) of 9.6% ± 2.2% (mean ± SD) in total tumor absorbed dose calculation between PBPK and CDR equations, attributable to the consideration of IFP. Moreover, AAI proved beneficial for RPT when the kidney was designated as the organ-at-risk. It enabled an increase in radiopharmaceutical injection from 12.3 ± 6.32 MBq (mean ± SD) to 15.45 ± 6.95 MBq (RE: 28.5% ± 15.7%), resulting in a corresponding increase in tumor absorbed dose from 67.8 ± 47.45 Gy to 72.43 ± 51.03 Gy (RE: 8.6% ± 5.4%), while maintaining critical kidney absorbed dose limits. However, this was not observed when the salivary gland was considered the dose-limiting organ. Although, AAI allowed for increased therapeutic injection ranging from 4.22 ± 2.23 MBq to 5.25 ± 3.14 MBq (RE: 19.2% ± 9.9%), it results in a minimal increase in tumor absorbed dose of 0.22 ± 0.04 (RE: 1.4% ± 1.3%). Statistical analysis using the Wilcoxon Signed-Rank Test revealed significant effects of AAI on administered activity and tumor absorbed dose (p-value = 0.007 < 0.05). Finally, a local sensitivity analysis was performed on selected radiation and tumor transportation parameters individually to evaluate their impact on the tumor absorbed dose. In conclusion, selection of organ-at-risk in personalized RPT is critical, as it determines the injected activity amount and the efficacy of delivery-enhancing techniques.

in PLoS Computational Biology on 2025-07-16 14:00:00 UTC.

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Influenza A virus induces PI4P production at the endoplasmic reticulum in an ATG16L1-dependent manner to promote the egress of viral ribonucleoproteins

by Carla Alemany, Juliane Da Graça, Quentin Giai Gianetto, Maud Dupont, Sylvain Paisant, Thibaut Douché, Catherine Isel, Cédric Delevoye, Lydia Danglot, Mariette Matondo, Etienne Morel, Jean-Baptiste Brault, Nadia Naffakh

The genomic RNAs of influenza A viruses (IAVs) are replicated in the nucleus of infected cells in the form of viral ribonucleoproteins (vRNPs) before being exported to the cytoplasm. The small GTPase RAB11A is involved in the transport of vRNPs to the sites of viral assembly at the plasma membrane, but the molecular mechanisms involved remain largely unknown. Here we show that IAV infection remodels the architecture of the endoplasmic reticulum (ER) sheets, where vRNPs tend to accumulate in the absence of RAB11A. To decipher the interplay between RAB11A, vRNPs, and the ER, we investigated viral-induced perturbations of RAB11A proximity interactome. To this end, we generated cells stably expressing a TurboID-RAB11A fusion protein and performed biotin-based proximity labeling upon viral infection. We found that cellular regulators of phophatidylinositol-4-phosphate (PI4P) homeostasis, including the autophagic and stress response protein ATG16L1, are significantly enriched at the vicinity of RAB11A in infected cells. Infection induces an increase in cellular PI4P levels in an ATG16L1-dependent manner, while ATG16L1 relocalizes to ER membranes upon infection. Depletion of ATG16L1 decreases the co-distribution of vRNPs with PI4P punctae on ER membranes, and reduces the accumulation of vRNPs at the plasma membrane as well as the production of IAV infectious particles. Our data extend to IAVs the notion that viruses can modulate the metabolism and localization of phosphoinositides to control host membrane dynamics and point to the ER as an essential platform for vRNP transport. They provide evidence for a pivotal role of ATG16L1 in regulating the identity of endomembranes and coordinating RAB11A and PI4P-enriched membranes to ensure delivery of vRNPs to the plasma membrane.

in PLoS Biology on 2025-07-16 14:00:00 UTC.

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Forthcoming Articles

The Neuroscientist, Volume 31, Issue 4, Page 332-332, August 2025.

in The Neuroscientist on 2025-07-16 12:01:42 UTC.

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mRNA in axonal terminals: a role in memory

The Neuroscientist, Volume 31, Issue 4, Page 333-333, August 2025.

in The Neuroscientist on 2025-07-16 12:01:42 UTC.

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Neurite density in autism: new lessons from MRI

The Neuroscientist, Volume 31, Issue 4, Page 333-334, August 2025.

in The Neuroscientist on 2025-07-16 12:01:42 UTC.

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Mapping emotional responses across the brain

The Neuroscientist, Volume 31, Issue 4, Page 335-335, August 2025.

in The Neuroscientist on 2025-07-16 12:01:42 UTC.

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Sternocleidomastoid Muscle Overactivity: A Potentially Critical Contributor to Postural Abnormalities in Parkinson's Disease

Objective

Overactivity of muscles is thought to be involved in postural abnormalities (PA) in Parkinson's disease (PD). Here, we investigated the relationship between muscle activity and postural parameters to explore the peripheral mechanisms of PA.

Methods

A total of 90 PD patients and 19 healthy controls were enrolled. Posture features (F1–F8) and the index for PA were collected. Surface electromyography was acquired from cervical and thoracolumbar muscles during lying, sitting, standing, and walking, respectively. Follow-up was completed for a subset of PD patients.

Results

Root mean square (RMS) amplitudes of the sternocleidomastoid muscle (SCM) and external oblique muscle, were higher in PD patients with PA (PD_PA) than PD patients without PA (PD_NPA) and healthy controls during lying and standing. Extensor activity in PD_PA patients increased only in the antigravity position compared with PD_NPA patients. Spearman's correlation showed that RMS amplitude of SCM in the lying position was associated with index for PA and forward flexion angles including F3–F8, whereas RMS amplitude of the external oblique muscle in the lying position was correlated with F5 alone. Longitudinal analysis showed that changes in F3, F4, and index for PA were significantly correlated with changes in RMS amplitude of the SCM in the lying position. Additionally, PD_NPA patients with SCM overactivity had a significantly higher risk of progressing to PA than those with normal SCM activity.

Interpretation

The SCM and external oblique muscle are involved in forward trunk flexion in PD patients, while extensors may play a compensatory role. SCM may be the key muscle in PA for PD patients, participating in the pathogenesis of PA. ANN NEUROL 2025

in Annals of Neurology on 2025-07-16 11:28:22 UTC.

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