Planet Neuroscience

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BOLDSimNet: Examining Brain Network Similarity between Task and Resting-State fMRI

arXiv:2504.01274v1 Announce Type: new Abstract: Traditional causal connectivity methods in task-based and resting-state functional magnetic resonance imaging (fMRI) face challenges in accurately capturing directed information flow due to their sensitivity to noise and inability to model multivariate dependencies. These limitations hinder the effective comparison of brain networks between cognitive states, making it difficult to analyze network reconfiguration during task and resting states. To address these issues, we propose BOLDSimNet, a novel framework utilizing Multivariate Transfer Entropy (MTE) to measure causal connectivity and network similarity across different cognitive states. Our method groups functionally similar regions of interest (ROIs) rather than spatially adjacent nodes, improving accuracy in network alignment. We applied BOLDSimNet to fMRI data from 40 healthy controls and found that children exhibited higher similarity scores between task and resting states compared to adolescents, indicating reduced variability in attention shifts. In contrast, adolescents showed more differences between task and resting states in the Dorsal Attention Network (DAN) and the Default Mode Network (DMN), reflecting enhanced network adaptability. These findings emphasize developmental variations in the reconfiguration of the causal brain network, showcasing BOLDSimNet's ability to quantify network similarity and identify attentional fluctuations between different cognitive states.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-04-03 04:00:00 UTC.

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Emotional Responses to Auditory Hierarchical Structures is Shaped by Bodily Sensations and Listeners' Sensory Traits

arXiv:2504.01287v1 Announce Type: new Abstract: Emotional responses to auditory stimuli are a common part of everyday life. However, for some individuals, these responses can be distressing enough to interfere with daily functioning. Despite their prevalence, the mechanisms underlying auditory-induced emotion remain only partially understood. Prior research has identified contributing factors such as auditory features, listener traits, and bodily sensations. However, most studies have focused on acoustic features, leaving the role of syntactic structure largely unexplored. This study specifically investigates how hierarchical syntactic structures influence emotional experience, in conjunction with listener traits and bodily sensations. An online experiment was conducted with 715 participants, who listened to 26 sound sequences varying systematically in hierarchical syntactic complexity. Sequences were generated by combining three types of local pitch movement with three types of global pitch movement in ascending and descending pitch directions, resulting in nine complexity levels. Participants rated the valence and arousal of each sequence and indicated any bodily sensations on a body map. Measures of sensory processing patterns were also collected. Results showed that emotional valence was associated with the complex interplay of moderate syntactic complexity ("not too simple, not too complex"), sensory sensitivity, and upper torso sensations. These findings expand existing research by identifying syntactic features that shape auditory-induced emotional experience and highlight the link between bodily sensation and emotional response. They also suggest potential applications for incorporating syntactic design into therapeutic approaches to emotion regulation.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-04-03 04:00:00 UTC.

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Tinnitus, lucid dreaming and awakening. An online survey and theoretical implications

arXiv:2504.01453v1 Announce Type: new Abstract: (1) Background: Tinnitus is the perception of phantom sound in the absence of a corresponding external source. Previous studies reported that the presence of tinnitus is notably absent during dreams. This study aimed at replicating previous findings regarding tinnitus-free dreams, while also gaining a deeper understanding of tinnitus manifestations during dreams and after awakening. (2) Methods: For this observational study, 195 tinnitus patients answered an online survey on the mutual-help community Siopi. (3) Results: 160 patients could recall their dreams. Among them, 92.5% state they do not hear their tinnitus while dreaming. The rest (7.5%) report higher tinnitus burden, higher stress and more often exhibit objective tinnitus and/or tinnitus related to peripheral auditory pathology and/or drug intake. 13% of the participants frequently experience lucid dreams. Among them, 36% could perceive their tinnitus during lucid dreams, and this was strongly associated with the concomitant perception of external sounds during lucid dreaming. While the majority of patients report perceiving their tinnitus instantly upon awakening, during nocturnal awakenings, 18% declared they could be awakened by their tinnitus and 9.8% mentioned that their tinnitus can temporarily cease. (4) Conclusions: Our findings confirm the previous findings: tinnitus is rarely perceived during dreams. Remarkably, our study is the first to document the case of tinnitus during lucid dreaming. 64% of these patients gain higher-order consciousness attributes while still experiencing a tinnitus-free state. Our observations suggest that the presence or absence of gating of external auditory information during dreams acts as a tinnitus on-off switch, refining the previously proposed integrative model of auditory phantom perception.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-04-03 04:00:00 UTC.

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Dual mechanism of Anti-Seizure Medications in controlling seizure activity

arXiv:2504.01887v1 Announce Type: new Abstract: Background: Anti-seizure medications (ASMs) can reduce seizure duration, but their precise modes of action are unclear. Specifically, it is unknown whether ASMs shorten seizures by simply compressing existing seizure activity into a shorter time frame or by selectively suppressing certain seizure activity patterns. Methods: We analysed intracranial EEG (iEEG) recordings of 457 seizures from 28 people with epilepsy undergoing ASM tapering. Beyond measuring seizure occurrence and duration, we categorized distinct seizure activity patterns (states) based on spatial and frequency power characteristics and related these to different ASM levels. Results: We found that reducing ASM levels led to increased seizure frequency (r = 0.87, p < 0.001) and longer seizure duration ($\beta$ = -0.033, p < 0.001), consistent with prior research. Further analysis revealed two distinct mechanisms in which seizures became prolonged: Emergence of new seizure patterns - In approx. 40% of patients, ASM tapering unmasked additional seizure activity states, and seizures containing these 'taper-emergent states' were substantially longer (r = 0.49, p < 0.001). Prolongation of existing seizure patterns - Even in seizures without taper-emergent states, lower ASM levels still resulted in approx. 12-224% longer durations depending on the ASM dosage and tapering ($\beta$ = -0.049, p < 0.001). Conclusion: ASMs influence seizures through two mechanisms: they (i) suppress specific seizure activity patterns (states) in an all-or-nothing fashion and (ii) curtail the duration of other seizure patterns. These findings highlight the complex role of ASMs in seizure modulation and could inform personalized dosing strategies for epilepsy management. These findings may also have implications in understanding the effects of ASMs on cognition and mood.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-04-03 04:00:00 UTC.

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SpikeSift: A Computationally Efficient and Drift-Resilient Spike Sorting Algorithm

arXiv:2504.01604v1 Announce Type: cross Abstract: Spike sorting is a fundamental step in analyzing extracellular recordings, enabling the isolation of individual neuronal activity, yet it remains a challenging problem due to overlapping signals and recording instabilities, including electrode drift. While numerous algorithms have been developed to address these challenges, many struggle to balance accuracy and computational efficiency, limiting their applicability to largescale datasets. In response, we introduce SpikeSift, a novel spike sorting algorithm designed to mitigate drift by partitioning recordings into short, relatively stationary segments, with spikes subsequently sorted within each. To preserve neuronal identity across segment boundaries, a computationally efficient alignment process merges clusters without relying on continuous trajectory estimation. In contrast to conventional methods that separate spike detection from clustering, SpikeSift integrates these processes within an iterative detect-andsubtract framework, enhancing clustering accuracy while maintaining computational efficiency. Evaluations on intracellularly validated datasets and biophysically realistic MEArec simulations confirm that SpikeSift maintains high sorting accuracy even in the presence of electrode drift, providing a scalable and computationally efficient solution for large-scale extracellular recordings

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-04-03 04:00:00 UTC.

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Cortical network reconfiguration aligns with shifts of basal ganglia and cerebellar influence

arXiv:2408.07977v2 Announce Type: replace Abstract: Mammalian functional architecture flexibly adapts, transitioning from integration where information is distributed across the cortex, to segregation where information is focal in densely connected communities of brain regions. This flexibility in cortical brain networks is hypothesized to be driven by control signals originating from subcortical pathways, with the basal ganglia shifting the cortex towards integrated processing states and the cerebellum towards segregated states. In a sample of healthy human participants (N=242), we used fMRI to measure temporal variation in global brain networks while participants performed two tasks with similar cognitive demands (Stroop and Multi-Source Inference Task (MSIT)). Using the modularity index, we determined cortical networks shifted from integration (low modularity) at rest to high modularity during easier i.e. congruent (segregation). Increased task difficulty (incongruent) resulted in lower modularity in comparison to the easier counterpart indicating more integration of the cortical network. Influence of basal ganglia and cerebellum was measured using eigenvector centrality. Results correlated with decreases and increases in cortical modularity respectively, with only the basal ganglia influence preceding cortical integration. Our results support the theory the basal ganglia shifts cortical networks to integrated states due to environmental demand. Cerebellar influence correlates with shifts to segregated cortical states, though may not play a causal role.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-04-03 04:00:00 UTC.

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Confidence-weighted integration of human and machine judgments for superior decision-making

arXiv:2408.08083v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have emerged as powerful tools in various domains. Recent studies have shown that LLMs can surpass humans in certain tasks, such as predicting the outcomes of neuroscience studies. What role does this leave for humans in the overall decision process? One possibility is that humans, despite performing worse than LLMs, can still add value when teamed with them. A human and machine team can surpass each individual teammate when team members' confidence is well-calibrated and team members diverge in which tasks they find difficult (i.e., calibration and diversity are needed). We simplified and extended a Bayesian approach to combining judgments using a logistic regression framework that integrates confidence-weighted judgments for any number of team members. Using this straightforward method, we demonstrated in a neuroscience forecasting task that, even when humans were inferior to LLMs, their combination with one or more LLMs consistently improved team performance. Our hope is that this simple and effective strategy for integrating the judgments of humans and machines will lead to productive collaborations.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-04-03 04:00:00 UTC.

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When to Truncate the Archive? On the Effect of the Truncation Frequency in Multi-Objective Optimisation

arXiv:2504.01332v1 Announce Type: new Abstract: Using an archive to store nondominated solutions found during the search of a multi-objective evolutionary algorithm (MOEA) is a useful practice. However, as nondominated solutions of a multi-objective optimisation problem can be enormous or infinitely many, it is desirable to provide the decision-maker with only a small, representative portion of all the nondominated solutions in the archive, thus entailing a truncation operation. Then, an important issue is when to truncate the archive. This can be done once a new solution generated, a batch of new solutions generated, or even using an unbounded archive to keep all nondominated solutions generated and truncate it later. Intuitively, the last approach may lead to a better result since we have all the information in hand before performing the truncation. In this paper, we study this issue and investigate the effect of the timing of truncating the archive. We apply well-established truncation criteria that are commonly used in the population maintenance procedure of MOEAs (e.g., crowding distance, hypervolume indicator, and decomposition). We show that, interestingly, truncating the archive once a new solution generated tends to be the best, whereas considering an unbounded archive is often the worst. We analyse and discuss this phenomenon. Our results highlight the importance of developing effective subset selection techniques (rather than employing the population maintenance methods in MOEAs) when using a large archive.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-04-03 04:00:00 UTC.

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Overcoming Deceptiveness in Fitness Optimization with Unsupervised Quality-Diversity

arXiv:2504.01915v1 Announce Type: new Abstract: Policy optimization seeks the best solution to a control problem according to an objective or fitness function, serving as a fundamental field of engineering and research with applications in robotics. Traditional optimization methods like reinforcement learning and evolutionary algorithms struggle with deceptive fitness landscapes, where following immediate improvements leads to suboptimal solutions. Quality-diversity (QD) algorithms offer a promising approach by maintaining diverse intermediate solutions as stepping stones for escaping local optima. However, QD algorithms require domain expertise to define hand-crafted features, limiting their applicability where characterizing solution diversity remains unclear. In this paper, we show that unsupervised QD algorithms - specifically the AURORA framework, which learns features from sensory data - efficiently solve deceptive optimization problems without domain expertise. By enhancing AURORA with contrastive learning and periodic extinction events, we propose AURORA-XCon, which outperforms all traditional optimization baselines and matches, in some cases even improving by up to 34%, the best QD baseline with domain-specific hand-crafted features. This work establishes a novel application of unsupervised QD algorithms, shifting their focus from discovering novel solutions toward traditional optimization and expanding their potential to domains where defining feature spaces poses challenges.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-04-03 04:00:00 UTC.

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An Explainable Reconfiguration-Based Optimization Algorithm for Industrial and Reliability-Redundancy Allocation Problems

arXiv:2504.01331v1 Announce Type: cross Abstract: Industrial and reliability optimization problems often involve complex constraints and require efficient, interpretable solutions. This paper presents AI-AEFA, an advanced parameter reconfiguration-based metaheuristic algorithm designed to address large-scale industrial and reliability-redundancy allocation problems. AI-AEFA enhances search space exploration and convergence efficiency through a novel log-sigmoid-based parameter adaptation and chaotic mapping mechanism. The algorithm is validated across twenty-eight IEEE CEC 2017 constrained benchmark problems, fifteen large-scale industrial optimization problems, and seven reliability-redundancy allocation problems, consistently outperforming state-of-the-art optimization techniques in terms of feasibility, computational efficiency, and convergence speed. The additional key contribution of this work is the integration of SHAP (Shapley Additive Explanations) to enhance the interpretability of AI-AEFA, providing insights into the impact of key parameters such as Coulomb's constant, charge, acceleration, and electrostatic force. This explainability feature enables a deeper understanding of decision-making within the AI-AEFA framework during the optimization processes. The findings confirm AI-AEFA as a robust, scalable, and interpretable optimization tool with significant real-world applications.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-04-03 04:00:00 UTC.

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Learning Graph Quantized Tokenizers

arXiv:2410.13798v2 Announce Type: replace Abstract: Transformers serve as the backbone architectures of Foundational Models, where domain-specific tokenizers allow them to adapt to various domains. Graph Transformers (GTs) have recently emerged as leading models in geometric deep learning, outperforming Graph Neural Networks (GNNs) in various graph learning tasks. However, the development of tokenizers for graphs has lagged behind other modalities. To address this, we introduce GQT (\textbf{G}raph \textbf{Q}uantized \textbf{T}okenizer), which decouples tokenizer training from Transformer training by leveraging multi-task graph self-supervised learning, yielding robust and generalizable graph tokens. Furthermore, the GQT utilizes Residual Vector Quantization (RVQ) to learn hierarchical discrete tokens, resulting in significantly reduced memory requirements and improved generalization capabilities. By combining the GQT with token modulation, a Transformer encoder achieves state-of-the-art performance on 20 out of 22 benchmarks, including large-scale homophilic and heterophilic datasets.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-04-03 04:00:00 UTC.

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Resolving the Exploration-Exploitation Dilemma in Evolutionary Algorithms: A Novel Human-Centered Framework

arXiv:2501.02153v2 Announce Type: replace Abstract: Evolutionary Algorithms (EAs) are widely employed tools for complex search and optimization tasks; however, the absence of an overarching operational framework that permits a systematic regulation of the exploration-exploitation tradeoff--critical for efficient convergence--restricts the full actualization of their potential, leading to the so-called exploration-exploitation dilemma in algorithm design. A systematic resolution to this dilemma requires: (1) an independent yet coordinated control over exploration and exploitation, and (2) an explicit, computationally feasible, adaptive regulation mechanism. The current, almost decentralized, traditional parameter tuning-centeric approach--lacks the foundation to satisfy these requirements under encoding-imposed structural constraints. We propose a Human-Centered Two-Phase Search (HCTPS) framework, in which the actualization of (1) and (2) is enabled through an external configuration variable--the Search Space Control Parameter (SSCP). As the sole control knob of HCTPS, the SSCP centralizes exploration adjustments, sparing users from micromanaging traditional parameters with unintelligible interdependencies. To this construct, the human user serves as a meta-parameter, adaptively steering the regulatory process via SSCP adjustments. We prove that the HCTPS strictly surpasses the current approach in terms of search space coverage without disrupting the EAs' inherent convergence mechanisms, demonstrate a concrete instantiation of it--using the Genetic Algorithm as the underlying heuristic on a suite of global benchmark unconstrained optimization problems, provide a through assessment of the proposed framework, and envision future research directions. Any search algorithm prone to this dilemma can be applied in light of the proposed framework, being algorithm-agnostic by design.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-04-03 04:00:00 UTC.

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Stochastic Reservoir Computers

arXiv:2405.12382v2 Announce Type: replace-cross Abstract: Reservoir computing is a form of machine learning that utilizes nonlinear dynamical systems to perform complex tasks in a cost-effective manner when compared to typical neural networks. Many recent advancements in reservoir computing, in particular quantum reservoir computing, make use of reservoirs that are inherently stochastic. However, the theoretical justification for using these systems has not yet been well established. In this paper, we investigate the universality of stochastic reservoir computers, in which we use a stochastic system for reservoir computing using the probabilities of each reservoir state as the readout instead of the states themselves. In stochastic reservoir computing, the number of distinct states of the entire reservoir computer can potentially scale exponentially with the size of the reservoir hardware, offering the advantage of compact device size. We prove that classes of stochastic echo state networks, and therefore the class of all stochastic reservoir computers, are universal approximating classes. We also investigate the performance of two practical examples of stochastic reservoir computers in classification and chaotic time series prediction. While shot noise is a limiting factor in the performance of stochastic reservoir computing, we show significantly improved performance compared to a deterministic reservoir computer with similar hardware in cases where the effects of noise are small.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-04-03 04:00:00 UTC.

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EVOS: Efficient Implicit Neural Training via EVOlutionary Selector

arXiv:2412.10153v2 Announce Type: replace-cross Abstract: We propose EVOlutionary Selector (EVOS), an efficient training paradigm for accelerating Implicit Neural Representation (INR). Unlike conventional INR training that feeds all samples through the neural network in each iteration, our approach restricts training to strategically selected points, reducing computational overhead by eliminating redundant forward passes. Specifically, we treat each sample as an individual in an evolutionary process, where only those fittest ones survive and merit inclusion in training, adaptively evolving with the neural network dynamics. While this is conceptually similar to Evolutionary Algorithms, their distinct objectives (selection for acceleration vs. iterative solution optimization) require a fundamental redefinition of evolutionary mechanisms for our context. In response, we design sparse fitness evaluation, frequency-guided crossover, and augmented unbiased mutation to comprise EVOS. These components respectively guide sample selection with reduced computational cost, enhance performance through frequency-domain balance, and mitigate selection bias from cached evaluation. Extensive experiments demonstrate that our method achieves approximately 48%-66% reduction in training time while ensuring superior convergence without additional cost, establishing state-of-the-art acceleration among recent sampling-based strategies.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-04-03 04:00:00 UTC.

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Enantio-, atrop-, and diastereoselective macrolactonization to access type III cyclophanes

Nature Communications, Published online: 03 April 2025; doi:10.1038/s41467-025-58241-3

Here, the authors describe an N-heterocyclic carbene and chiral phosphoric acid dual-catalytic process for the desymmetrization of 1,3-diols, to achieve macrocyclization and stereoselective control over two chiral elements.

in Nature Communications on 2025-04-03 00:00:00 UTC.

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Stereoselective synthesis of tetra- and tri-substituted alkenyl nitriles via aminative ring-opening of cyclopropenes with iron-aminyl radical

Nature Communications, Published online: 03 April 2025; doi:10.1038/s41467-025-58555-2

The ring opening of cyclopropenes provides a compelling platform for the rapid synthesis of various polysubstituted acyclic alkenes, but radical-mediated reactions of this type remain underexplored. Here, the authors report an aminative ring-opening of cyclopropenes with iron-aminyl radical to afford tetrasubstituted alkenyl nitriles.

in Nature Communications on 2025-04-03 00:00:00 UTC.

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Comparative single-nucleus RNA-seq analysis revealed localized and cell type-specific pathways governing root-microbiome interactions

Nature Communications, Published online: 03 April 2025; doi:10.1038/s41467-025-58395-0

Plant roots are exposed to a diverse range of soil-dwelling microbial “friends” and “foes.” Here, via single-nucleus RNA-seq, the authors reveal cell type-specific responses to beneficial and pathogenic microbes in roots and identify regulators of root-microbiome interactions.

in Nature Communications on 2025-04-03 00:00:00 UTC.

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Aging reduces excitatory bandwidth, alters spectral tuning curve diversity, and reduces sideband inhibition in L2/3 of primary auditory cortex

Presbycusis, or age-related hearing loss, is caused by changes in both the peripheral and the central auditory system. Many of the peripheral structures that degrade with age have been identified and characterized, but there is still a dearth of information pertaining to what changes occur in the aging central auditory pathway that are independent of peripheral degradation. The primary auditory cortex (A1) of aging mice shows reduced suppressive responses and reduced diversity of temporal responses suggesting alteration of inhibitory processing. To gain a better understanding of how tuning features of the auditory cortex change with age, we performed in vivo 2-photon Ca2+ imaging on L2/3 of the auditory cortex of both adult (n=14, 11-24 weeks old) and aging (n=12, 12-17 months old) mice that retain peripheral hearing in old age. To reveal inhibitory inputs to L2/3 neurons we characterized spectral receptive fields with pure tones and two tone complexes. We find that in contrast to adult mice, L2/3 excitatory neurons from aging mice showed fewer distinct categories of spectral receptive fields, though in a subset of FRA types, we found increased diversity. We also noted a decrease in excitatory bandwidth with age among broadly tuned neurons, but that sideband inhibition became weaker across all FRA types due to a reduced amplitude in inhibitory responses. These results suggest that aging causes changes in circuit organization leading to more homogenous spectrotemporal receptive fields and that the lack of response diversity contributes to a decreased encoding capacity observed in aging A1.

in bioRxiv: Neuroscience on 2025-04-03 00:00:00 UTC.

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The extended language network: Language selective brain areas whose contributions to language remain to be discovered

Although language neuroscience has largely focused on core left frontal and temporal brain areas and their right-hemisphere homotopes, numerous other areas - cortical, subcortical, and cerebellar - have been implicated in linguistic processing. However, these areas' contributions to language remain unclear given that the evidence for their recruitment comes from diverse paradigms, many of which conflate language processing with perceptual, motor, or task-related cognitive processes. Using fMRI data from 772 participants performing an extensively-validated language localizer paradigm that isolates language processing from other processes, we a) delineate a comprehensive set of areas that respond reliably to language across written and auditory modalities, and b) evaluate these areas' selectivity for language relative to a demanding non-linguistic task. In line with prior claims, many areas outside the core fronto-temporal network respond during language processing, and most of them show selectivity for language relative to general task demands. These language-selective areas of the extended language network include areas around the temporal poles, in the medial frontal cortex, in the hippocampus, and in the cerebellum, among others. Although distributed across many parts of the brain, the extended language-selective network still only comprises ~1.2% of the brain's volume and is about the size of a strawberry, challenging the view that language processing is broadly distributed across the cortical surface. These newly identified language-selective areas can now be systematically characterized to decipher their contributions to language processing, including testing whether these contributions differ from those of the core language areas.

in bioRxiv: Neuroscience on 2025-04-03 00:00:00 UTC.

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Neural Tracking of the Maternal Voice in the Infant Brain

Infants preferentially process familiar social signals, but the neural mechanisms underlying continuous processing of maternal speech remain unclear. Using EEG-based neural encoding models based on temporal response functions, we investigated how 7-month-old infants track maternal vs. unfamiliar speech and whether this affects simultaneous face processing. Infants showed stronger neural tracking of their mother's voice, independent of acoustic properties, suggesting an early neural signature of voice familiarity. Face tracking responses differed depending on the voice infants heard. When listening to a stranger's voice, face-tracking accuracy at central electrodes increased with occipital face tracking, suggesting heightened attentional engagement. However, we found no evidence for differential processing of happy vs. fearful faces, contrasting previous findings on early emotion discrimination. Our results reveal interactive effects of voice familiarity on multimodal processing in infancy: while maternal speech enhances neural tracking, it may also alter how other social cues, such as faces, are processed. The findings suggest that early auditory experiences shape how infants allocate cognitive resources to social stimuli, emphasizing the need to consider cross-modal influences in early development.

in bioRxiv: Neuroscience on 2025-04-03 00:00:00 UTC.

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Mapping the coupling between tract reachability and cortical geometry of the human brain

The study of cortical geometry and connectivity is prevalent in research on the human brain. However, these two aspects of brain structure are usually examined separately, leaving the essential connections between the brain's folding patterns and white matter connectivity unexplored. In this study, we aimed to elucidate fundamental links between cortical geometry and white matter tract connectivity. We developed the concept of tract-geometry coupling (TGC) by optimizing the alignment between tract connectivity to the cortex and multiscale cortical geometry. Specifically, spectral analyses of the cortical surface yielded a set of geometrical eigenmodes, which were then used to explain the locations on the cortical surface reached by specific white matter tracts, referred to as tract reachability. In two independent datasets, we confirmed that tract reachability was well characterized by cortical geometry. We further observed that TGC had high test-retest ability and was specific to each individual. Interestingly, low-frequency TGC was found to be heritable and more informative than the high-frequency components in behavior prediction. Finally, we found that TGC could reproduce task-evoked cortical activation patterns. Collectively, our study provides a new approach to mapping coupling between cortical geometry and connectivity, highlighting how these two aspects jointly shape the connected brain.

in bioRxiv: Neuroscience on 2025-04-03 00:00:00 UTC.

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Common and distinct neural mechanisms of aversive and appetitive pain-related learning

Appetitive and aversive conditioning are both fundamental to adaptive behaviour, yet there remains limited understanding of how they differ on the behavioural and neural level. We investigated the two processes during acquisition and extinction using functional magnetic resonance imaging and behavioural measures. In a within-subject differential conditioning paradigm (preregistration DRKS00027448), aversive learning was induced by pairing visual cues with a temperature increase (pain rise), while appetitive learning involved a temperature decrease (pain reduction). Valence and contingency ratings confirmed successful learning for both types of learning, though only the appetitive condition showed a return to baseline ratings during extinction, suggesting incomplete extinction in the aversive condition. On the neural level, both engaged the visual cortex during acquisition (with increased functional connectivity with the right frontal operculum) and the ventromedial prefrontal cortex (vmPFC) during extinction. However, aversive learning showed a stronger activation increase in the mediodorsal thalamus with heightened connectivity with the locus coeruleus during acquisition, as well as sustained parahippocampal activity during extinction. Moreover, incomplete extinction in the aversive condition (as indicated by contingency ratings) was associated with sustained activity in the visual cortex during pain anticipation. These results suggest that while appetitive and aversive learning share activation in regions involved in sensory processing (occipital lobe) and learning (vmPFC), aversive learning uniquely engages areas promoting rapid acquisition (mediodorsal thalamus and locus coeruleus) and cautious unlearning, in line with the notion of a "better-safe-than-sorry" strategy.

in bioRxiv: Neuroscience on 2025-04-03 00:00:00 UTC.

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This Week in The Journal

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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A New Molecular Mechanism for the Late-Onset Alzheimer's Disease Risk Gene CD2AP

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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Long-Term Excessive Alcohol Consumption Enhances Myelination in the Mouse Nucleus Accumbens

Chronic excessive alcohol (ethanol) consumption induces neuroadaptations in the brain's reward system, including biochemical and structural abnormalities in white matter that are implicated in addiction phenotypes. Here, we demonstrate that long-term (12 week) voluntary ethanol consumption enhances myelination in the nucleus accumbens (NAc) of female and male adult mice, as evidenced by molecular, ultrastructural, and cellular alterations. Specifically, transmission electron microscopy analysis showed increased myelin thickness in the NAc following long-term ethanol consumption, while axon diameter remained unaffected. These changes were paralleled by increased mRNA transcript levels of key transcription factors essential for oligodendrocyte (OL) differentiation, along with elevated expression of critical myelination-related genes. In addition, diffusion tensor imaging revealed increased connectivity between the NAc and the prefrontal cortex, reflected by a higher number of tracts connecting these regions. We also observed ethanol-induced effects on OL lineage cells, with a reduction in the number of mature OLs after 3 weeks of ethanol consumption, followed by an increase after 6 weeks. These findings suggest that ethanol alters OL development prior to increasing myelination in the NAc. Finally, chronic administration of the promyelination drug clemastine to mice with a history of heavy ethanol consumption further elevated ethanol intake and preference, suggesting that increased myelination may contribute to escalated drinking behavior. Together, these findings suggest that heavy ethanol consumption disrupts OL development, induces enhanced myelination in the NAc, and may drive further ethanol intake, reinforcing addictive behaviors.

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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Neurophysiology of Perceptual Decision-Making and Its Alterations in Attention-Deficit Hyperactivity Disorder

Despite the prevalence of attention-deficit hyperactivity disorder (ADHD), efforts to develop a detailed understanding of the neuropsychology of this neurodevelopmental condition are complicated by the diversity of interindividual presentations and the inability of current clinical tests to distinguish between its sensory, attentional, arousal, or motoric contributions. Identifying objective methods that can explain the diverse performance profiles across individuals diagnosed with ADHD has been a long-held goal. Achieving this could significantly advance our understanding of etiological processes and potentially inform the development of personalized treatment approaches. Here, we examine key neuropsychological components of ADHD within an electrophysiological (EEG) perceptual decision-making paradigm that is capable of isolating distinct neural signals of several key information processing stages necessary for sensory-guided actions from attentional selection to motor responses. Using a perceptual decision-making task (random dot motion), we evaluated the performance of 79 children (aged 8–17 years) and found slower and less accurate responses, along with a reduced rate of evidence accumulation (drift rate parameter of drift diffusion model), in children with ADHD (n = 37; 13 female) compared with typically developing peers (n = 42; 18 female). This was driven by the atypical dynamics of discrete electrophysiological signatures of attentional selection, the accumulation of sensory evidence, and strategic adjustments reflecting urgency of response. These findings offer an integrated account of decision-making in ADHD and establish discrete neural signals that might be used to understand the wide range of neuropsychological performance variations in individuals with ADHD.

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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Multiple Distinct Timescales of Rapid Sensory Adaption in the Thalamocortical Circuit

Numerous studies have shown that neuronal representations in sensory pathways are far from static but are instead strongly shaped by the complex properties of the sensory inputs they receive. Adaptation dynamically shapes the neural signaling that underlies our perception of the world yet remains poorly understood. We investigated rapid adaptation across timescales from hundreds of milliseconds to seconds through simultaneous multielectrode recordings from the ventro-posteromedial nucleus of the thalamus (VPm) and layer 4 of the primary somatosensory cortex (S1) in male and female anesthetized mice in response to controlled, persistent whisker stimulation. Observations in VPm and S1 reveal a degree of adaptation that progresses through the pathway. Under these experimental conditions, signatures of two distinct timescales of rapid adaptation in the firing rates of both thalamic and cortical neuronal populations were revealed, also reflected in the synchrony of the thalamic population and in the thalamocortical synaptic efficacy that was measured in putatively monosynaptically connected thalamocortical pairs. Controlled optogenetic activation of VPm further demonstrated that the longer timescale adaptation observed in S1 is likely inherited from slow decreases in thalamic firing rate and synchrony. Despite the degraded sensory responses, adaptation induced by the controlled repetitive stimulation presented here resulted in a shift in coding strategy that favors theoretical discrimination over detection across the observed timescales of adaptation. Overall, although multiple mechanisms contribute to rapid adaptation at distinct timescales, they support a unifying framework on the role of adaptation in sensory processing.

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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Detection of Individual Differences Encoded in Sequential Variations of Elements in Zebra Finch Songs

Zebra finches sing individually unique songs and recognize conspecific songs and individual identities in songs. Their songs comprise several syllables/elements that share acoustic features within the species, with unique sequential arrangements. However, the neuronal mechanisms underlying the detection of individual differences and species specificity have yet to be elucidated. Herein, we examined the neuronal auditory responsiveness of neurons in the higher auditory area, the caudal nidopallium (NCM), to songs and their elements in male zebra finches to understand the mechanism for detecting species and individual identities in zebra finch songs. We found that various adult male zebra finch songs share acoustically similar song elements but differ in their sequential arrangement between individuals. The broader spiking (BS) neurons in the NCM detected only a small subset of zebra finch songs, whereas NCM BS neurons, as a neuronal ensemble, responded to all zebra finch songs. Notably, distinct combinations of BS neurons responded to each of the 18 presented songs in one bird. Subsets of NCM BS neurons were sensitive to sequential arrangements of species-specific elements, which dramatically increasing the capacity for song variation with a limited number of species-specific elements. The naive Bayes decoder analysis further showed that the response of sequence-sensitive BS neurons increased the accuracy of song stimulus predictions based on the response strength of neuronal ensembles. Our results suggest the neuronal mechanisms that NCM neurons as an ensemble decode the individual identities of songs, while each neuron detects a small subset of song elements and their sequential arrangement.

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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VTA {micro}-Opioidergic Neurons Facilitate Low Sociability in Protracted Opioid Abstinence

Opioids initiate dynamic maladaptation in brain reward and affect circuits that occur throughout chronic exposure and withdrawal that persist beyond cessation. Protracted abstinence is characterized by negative affective behaviors such as heightened anxiety, irritability, dysphoria, and anhedonia, which pose a significant risk factor for relapse. While the ventral tegmental area (VTA) and μ-opioid receptors (MORs) are critical for opioid reinforcement, the specific contributions of VTA^MOR neurons in mediating protracted abstinence-induced negative affect is not fully understood. In our study, we elucidate the role of VTA^MOR neurons in mediating negative affect and altered brain-wide neuronal activities following forced opioid exposure and abstinence in male and female mice. Utilizing a chronic oral morphine administration model, we observe increased social deficit, anxiety-related, and despair-like behaviors during protracted forced abstinence. VTA^MOR neurons show heightened neuronal FOS activation at the onset of withdrawal and connect to an array of brain regions that mediate reward and affective processes. Viral re-expression of MORs selectively within the VTA of MOR knock-out mice demonstrates that the disrupted social interaction observed during protracted abstinence is facilitated by this neural population, without affecting other protracted abstinence behaviors. Lastly, VTA^MORs contribute to heightened neuronal FOS activation in the anterior cingulate cortex (ACC) in response to an acute morphine challenge, suggesting their unique role in modulating ACC-specific neuronal activity. These findings identify VTA^MOR neurons as critical modulators of low sociability during protracted abstinence and highlight their potential as a mechanistic target to alleviate negative affective behaviors associated with opioid abstinence.

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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Smell the Label: Odors Influence Label Perception and Their Neural Processing

Providing nutrition or health labels on product packaging can be an effective strategy to promote a conscious and healthier diet. However, such labels also have the potential to be counterproductive by creating obstructive expectations about the flavor of the food and influencing odor perception. Conversely, olfaction could significantly influence label perception, whereby negative expectations could be mitigated by pleasant odors. This study explored the neural processing of the interplay between odors and nutrition labels using fMRI in 63 participants of either sex, to whom we presented beverage labels with different nutrition-related statements either with or without a congruent odor. On a behavioral level, the products for which the label was presented together with the odor were in general perceived as more positive than the same labels without an odor. Neuroimaging results revealed that added odors significantly altered activity in brain regions associated with flavor and label processing as well as decision-making, with higher activations in the right amygdala/piriform cortex (Amy/pirC) and orbitofrontal cortex. The presentation of odors induced pattern-based encoding in the right dorsolateral prefrontal cortex, the left ventral striatum/nucleus accumbens, and the right Amy/pirC when accounting for behavioral differences. This suggests that odors influence the effects of labels both on a neural and behavioral level and may offer the possibility of compensating for obstructive associations. The detailed mechanisms of odor and statement interactions within the relevant brain areas should be further investigated, especially for labels that evoke negative expectations.

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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Increased Modulation of Low-Frequency Cardiac Rhythms on Resting-State Left Insula Alpha Oscillations in Major Depressive Disorder: Evidence from a Magnetoencephalography Study

A growing body of evidence suggests that the link between the cardiac autonomic nervous system (ANS) and the central nervous system (CNS) is crucial to the onset and development of major depressive disorder (MDD), affecting perception, cognition, and emotional processing. The bottom-up heart–brain communication pathway plays a significant role in this process. Previous studies have shown that slow-frequency oscillations of peripheral signals (e.g., respiration, stomach) can influence faster neural activities in the CNS via phase–amplitude coupling (PAC). However, the understanding of heart–brain coupling remains limited. Additionally, while MDD patients exhibit altered brain activity patterns, little is known about how heart rate variability (HRV) affects brain oscillations. Therefore, we used PAC to investigate heart–brain coupling and its association with depression. We recorded MEG and ECG data from 55 MDD patients (35 females) and 52 healthy subjects (28 females) at rest and evaluated heart–brain PAC at a broadband level. The results showed that the low-frequency component of HRV (HRV-LF) significantly modulated MEG alpha power (10 Hz) in humans. Compared with the healthy group, the MDD group exhibited more extensive heart–brain coupling cortical networks, including the pars triangularis. LF-alpha coupling was observed in the bilateral insula in both groups. Notably, results revealed a significantly increased sympathetic-dominated HRV-LF modulation effect on left insula alpha oscillations, along with increased depressive severity. These findings suggest that MDD patients may attempt to regulate their internal state through enhanced heart–brain modulation, striving to restore normal physiological and psychological balance.

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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A Distinct Down-to-Up Transition Assembly in the Retrosplenial Cortex during Slow-Wave Sleep

Understanding the intricate mechanisms underlying slow-wave sleep (SWS) is crucial for deciphering the brain's role in memory consolidation and cognitive functions. It is well established that cortical delta oscillations (0.5–4 Hz) coordinate communications among cortical, hippocampal, and thalamic regions during SWS. These delta oscillations feature periods of Up and Down states, with the latter previously thought to represent complete cortical silence; however, new evidence suggests that Down states serve important functions for information exchange during memory consolidation. The retrosplenial cortex (RSC) is pivotal for memory consolidation due to its extensive connectivity with memory-associated regions, although it remains unclear how RSC neurons engage in delta-associated consolidation processes. Here, we employed multichannel in vivo electrophysiology to study RSC neuronal activity in ad libitum behaving male mice during natural SWS. We discovered a discrete assembly of putative excitatory RSC neurons (~20%) that initiated firing at SWS Down states and reached maximal firing at the Down-to-Up transitions. Therefore, we termed these RSC neurons the Down-to-Up transition assembly (DUA) and the remaining RSC excitatory neurons as non-DUA. Compared with non-DUA, DUA neurons appear to exhibit higher firing rates and larger cell body size and lack monosynaptic connectivity with nearby RSC neurons. Furthermore, optogenetics combined with electrophysiology revealed differential innervation of RSC excitatory neurons by memory-associated inputs. Collectively, these findings provide insight into the distinct activity patterns of RSC neuronal subpopulations during sleep and their potential role in memory processes.

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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The Effect of Microsaccades in the Primary Visual Cortex: Increased Synchronization in the Fovea during a Two-Phase Response Modulation

Our eyes are never still. Even when we attempt to fixate, the visual gaze is never motionless, as we continuously perform miniature oculomotor movements termed as fixational eye movements. The fastest eye movements during the fixation epochs are termed microsaccades (MSs) that are leading to continual motion of the visual input, affecting mainly neurons in the fovea. Yet our vision appears to be stable. To explain this gap, previous studies suggested the existence of an extraretinal input (ERI) into the visual cortex that can account for the motion and produce visual stability. Here, we investigated the existence of an ERI to V1 fovea in macaque monkeys (male) while they performed spontaneous MSs, during fixation. We used voltage-sensitive dye imaging (VSDI) to measure and characterize at high spatiotemporal resolution the influence of MSs on neural population activity, in the foveal region of the primary visual cortex (V1). Microsaccades, performed over a blank screen, induced a two-phase response modulation: an early suppression followed by an enhancement. A correlation analysis revealed a widespread foveal increase in neural synchronization, peaking around ~100 ms after MS onset. Next, we investigated the MS effects in the presence of a small visual stimulus and found that this modulation was different from the blank condition yet both modulations coexisted in the fovea. Finally, the VSD response to an external motion of the fixation point could not explain the MS modulation. These results support an ERI that may be involved in visual stabilization already at the level of V1.

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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Rab27b Promotes Lysosomal Function and Alpha-Synuclein Clearance in Neurons

Alpha-synuclein (αsyn) is the key pathogenic protein implicated in synucleinopathies including Parkinson's disease (PD) and dementia with Lewy bodies (DLB). In these diseases, αsyn is thought to spread between cells where it accumulates and induces pathology; however, mechanisms that drive its propagation or aggregation are poorly understood. We have previously reported that the small GTPase Rab27b is elevated in human PD and DLB and that it can mediate the autophagic clearance and toxicity of αsyn in a paracrine αsyn cell culture model. Here, we expanded our previous work and characterized the role of Rab27b in neuronal lysosomal processing and αsyn clearance. We found that Rab27b KD in this αsyn-inducible neuronal model resulted in lysosomal dysfunction and increased αsyn levels in lysosomes. Similar lysosomal proteolytic defects and enzymatic dysfunction were observed in both primary neuronal cultures and brain lysates from male and female Rab27b knock-out (KO) mice. αSyn aggregation was exacerbated in Rab27b KO neurons upon treatment with αsyn preformed fibrils. We found no changes in lysosomal counts or lysosomal pH in either model, but we did identify changes in acidic vesicle trafficking and in lysosomal enzyme maturation and localization, which may drive lysosomal dysfunction and promote αsyn aggregation. Rab27b OE enhanced lysosomal activity and reduced insoluble αsyn accumulation. Finally we found elevated Rab27b levels in human postmortem incidental Lewy body disease subjects relative to healthy controls. These data suggest the role of Rab27b in neuronal lysosomal activity and identify it as a potential therapeutic target in synucleinopathies.

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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Serotonergic Input into the Cerebellar Cortex Modulates Anxiety-Like Behavior

Because of the important roles of both serotonin (5-HT) and the cerebellum in regulating anxiety, we asked whether 5-HT signaling within the cerebellum is involved in anxiety behavior. Physiological 5-HT levels were measured in vivo by expressing a fluorescent sensor for 5-HT in lobule VII of the cerebellum, while using fiber photometry to measure sensor fluorescence during anxiety behavior on the elevated zero maze. Serotonin increased in lobule VII when male mice were less anxious and decreased when mice were more anxious. To establish a causal role for this serotonergic input in anxiety behavior, we photostimulated or photoinhibited serotonergic terminals in lobule VII while mice were in an elevated zero maze. Photostimulating these terminals reduced anxiety behavior in mice, while photoinhibiting them enhanced anxiety behavior. Our findings add to evidence that cerebellar lobule VII is a topographical locus for anxiety behavior and establish that 5-HT input into this lobule is necessary and sufficient to bidirectionally influence anxiety behavior. These results represent progress toward understanding how the cerebellum regulates anxiety behavior and provide new evidence for a functional connection between the cerebellum and the serotonin system within the anxiety circuit.

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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Superior Colliculus Controls the Activity of the Substantia Nigra Pars Compacta and Ventral Tegmental Area in an Asymmetrical Manner

Dopaminergic (DA) neurons of the substantia nigra pars compacta (SNc) and ventral tegmental area (VTA) play a crucial role in controlling animals’ orienting and approach behaviors toward relevant environmental stimuli. The ventral midbrain receives sensory input from the superior colliculus (SC), a tectal region that processes information from contralateral receptive fields of various modalities. Given the significant influence of dopamine release imbalance in the left and right striatum on animals’ movement direction, our study aimed to investigate the lateralization of the connection between the lateral SC and the midbrain DA system in male rats. We explored the circuit's anatomy using transsynaptic viral tract-tracing and its physiology using in vivo single-unit and ex vivo multi-electrode array recordings of SNc and VTA neuronal activity combined with optogenetic stimulation of either the ipsilateral or contralateral SC or its terminals. During the experiments, DA neurons were identified optogenetically (in vivo recordings) or pharmacologically (ex vivo recordings). Anatomical findings revealed a bilateral innervation pattern of the lateral SC to the ventral midbrain, with a significantly stronger ipsilateral connection, particularly evident in the SNc, involving both DA and non-DA neurons. This anatomical asymmetry was also expressed during in vivo and ex vivo recordings, which showed a predominance of ipsilateral connections, especially within the SNc. Ex vivo recordings also confirmed that this lateralized pathway is direct. The described features of the SC->VTA/SNc neuronal circuit, particularly its anatomical and physiological asymmetry, suggest its involvement in orienting and approach behaviors guided by the direction of incoming sensory stimuli.

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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Salience-Dependent Disruption of Sustained Auditory Attention Can Be Inferred from Evoked Pupil Responses and Neural Tracking of Task-Irrelevant Sounds

Stimulus-driven attention allows us to react to relevant stimuli (and imminent danger!) outside our current focus of attention. But irrelevant stimuli can also disrupt attention, for example, during listening to speech. The degree to which sound captures attention is called salience, which can be estimated by existing, behaviorally validated, computational models (Huang and Elhilali, 2017). Here we examined whether neurophysiological responses to task-irrelevant sounds indicate the degree of distraction during a sustained-listening task and how much this depends on individual hearing thresholds. Forty-seven Danish-speaking adults (28/19 female/male; mean age, 60.1; SD, 15.9 years) with heterogenous hearing thresholds (PTA; mean, 25.5; SD, 18.0 db HL) listened to continuous speech while 1-s-long, task-irrelevant natural sounds (distractors) of varying computed salience were presented at unpredictable times and locations. Eye tracking and electroencephalography were used to estimate pupil response and neural tracking, respectively. The task-irrelevant sounds evoked a consistent pupil response (PR), distractor-tracking (DT), and a drop of target-tracking (TT), and statistical modeling of these three measures within subjects showed that all three are enhanced for sounds with higher computed salience. Participants with larger PR showed a stronger drop in target tracking (TT) and performed worse in target speech comprehension. We conclude that distraction can be inferred from neurophysiological responses to task-irrelevant stimuli. These results are a first step toward neurophysiological assessment of attention dynamics during continuous listening, with potential applications in hearing care diagnostics.

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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Adaptation with Naturalistic Textures in Macaque V1 and V2

Adaptation affects neuronal responsivity and selectivity throughout the visual hierarchy. However, because most prior studies have tailored stimuli to a single brain area of interest, we have a poor understanding of how exposure to a particular image alters responsivity and tuning at different stages of visual processing. Here we assess how adaptation with naturalistic textures alters neuronal responsivity and selectivity in primary visual cortex (V1) and area V2 of macaque monkeys. Neurons in both areas respond to textures, but V2 neurons are sensitive to higher-order image statistics which do not strongly modulate V1 responsivity. We tested the specificity of adaptation in each area with textures and spectrally matched "noise" stimuli. Adaptation reduced responsivity in both V1 and V2, but only in V2 was the reduction dependent on the presence of higher-order texture statistics. Despite this specificity, the texture information provided by single neurons and populations was reduced after adaptation, in both V1 and V2. Our results suggest that adaptation effects for a given feature are induced at the stage of processing that tuning for that feature first arises and that stimulus-specific adaptation effects need not result in improved sensory encoding.

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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Memory Boost for Recurring Emotional Events Is Driven by Initial Amygdala Response Promoting Stable Neocortical Patterns across Repetitions

Emotionally arousing events are typically vividly remembered, which is generally adaptive but may contribute to mental disorders such as post-traumatic stress disorder. Previous research on emotional memory focused primarily on events that were experienced only once, leaving the memory mechanisms underlying repeatedly encountered emotional events largely unexplored. Here, we aimed to elucidate the brain mechanisms associated with memory for recurring emotional events. Specifically, we sought to determine whether the memory enhancement for recurring emotional events is linked to more variable neural representations, as predicted by the encoding-variability hypothesis, or to more stable representations across repetitions, as suggested by a memory reinstatement account. To investigate this, we repeatedly presented healthy men and women with images of emotionally negative or neutral scenes during three consecutive runs in an MRI scanner. Subsequent free recall was, as expected, enhanced for emotional compared with neutral images. Neural data showed that this emotional enhancement of memory was linked to (1) activation of the amygdala and anterior hippocampus during the initial encounter of the emotional event and (2) increased neural pattern similarity in frontoparietal cortices across event repetitions. Most importantly, a multilevel-moderated mediation analysis revealed that the impact of neocortical pattern stability across repetitions on emotional memory enhancement was moderated by amygdala activity during the initial exposure to the emotional event. Together, our findings show that the amygdala response during the initial encounter of an emotional event boosts subsequent remembering through a more precise reinstatement of the event representation during subsequent encounters of the same event.

in Journal of Neuroscience on 2025-04-02 16:30:29 UTC.

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Integrated water quality assessment and health risk analysis of heavy metal and microbial contamination in the Ichu River, Peru [version 1; peer review: awaiting peer review]

Background The Ichu River serves as the primary water source for urban and agricultural use and industrial operations, but anthropogenic pollution has a serious negative impact on its water quality. Methods The investigation measured water quality and health-related risks by analyzing physicochemical parameters, heavy metals, and microbial pollutants at eight sampling points, site 1 (S1) through (S8). Results The research data showed that water quality worsened progressively from upstream to downstream locations such as turbidity, TDS, conductivity, and BOD levels increased. Oil pollution and oxygen depletion arose from a reduction in dissolved oxygen from 6.3 to 4.5 mg/L at the different sampling sites (S1 to S8). Heavy metals (As, Pb, Cd, and Cr) in the samples exceeded the standards established by the World Health Organization (WHO) established standards because of mining and industrial wastewater and local wastewater discharge. The presence of excessive Escherichia coli (E. coli) and total coliforms in microbial tests proved that the water was severely contaminated by fecal matter. Principal Component Analysis showed that heavy metals exist with microbial pollution and organic load as the main sources of water quality decline, and pollution indicators were found to establish powerful relationships with depleted oxygen levels. Conclusion The severe contamination risks found in this study justify immediate pollution control measures, wastewater treatment enforcement, and sustainable watershed management practices. Urgent action is necessary because vital parameters surpass the standards set by the WHO and (United States Environmental Protection Agency (USEPA) to avoid enduring environmental damage and health problems. This research demonstrates the value of continuing water quality assessments while enforcing policies and raising public awareness to improve the water quality of the Ichu River.

in F1000Research on 2025-04-02 15:54:30 UTC.

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Case Report: A new modification of Loma Linda pouch technique [version 1; peer review: awaiting peer review]

Dental implants provide a reliable treatment option for completely or partially edentulous patients. In case of a membrane perforation, the gap can be closed using a piece of resorbable collagen membrane or by suturing the Schneiderian membrane using a resorbable suture. The present study shows a new development in this technique, which involves modifying the design of the absorbable membrane and using bins to fix the membrane. This study concluded that the novel design of the collagen membrane and its fixation with the bins led to greater stability of the bone graft and led to subsequent bone gain that enables dental implantation. Still, this technique requires a histological study to determine the nature of the bone formed.

in F1000Research on 2025-04-02 15:44:51 UTC.

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Experiences of women living with HIV who underwent long loop excision of the transformation zone (LLETZ) in selected hospitals of Vhembe district, Limpopo province, South Africa [version 1; peer review: awaiting peer review]

Background Cervical cancer poses a significant health threat, especially for women living with HIV, who are at increased risk of developing premalignant cervical lesions. Large Loop Excision of the Transformation Zone (LLETZ) is a standard treatment for cervical intraepithelial neoplasia (CIN) to prevent progression to malignancy. This study explores the experiences of HIV-positive women who underwent LLETZ in Vhembe District, South Africa, where access to such specialized treatments remains limited. Methods Using a qualitative, phenomenological approach, this study engaged seven HIV-positive women who underwent LLETZ, capturing their lived experiences through in-depth, unstructured interviews. Thematic analysis identified key themes and subthemes to elucidate their psychological, physical, and social encounters related to the procedure. Results Analysis revealed eight central themes: psychological and physical experiences, psychosocial and financial support, misconceptions, education, recommendations, and time-related factors. Participants reported anxiety, fear, and initial stress about the procedure, coupled with resilience and acceptance over time. Physical effects such as pain and bleeding were common, though recovery experiences varied. Social support from family and community played a critical role in coping, while financial constraints impacted access to and continuity of care. Misunderstandings about the LLETZ procedure underscored the need for enhanced patient education. Participants emphasized timely screening and support systems to improve treatment outcomes and reduce psychological distress. Conclusions The study highlights the multifaceted impact of LLETZ on HIV-positive women, including the psychological and financial burdens and the importance of clear communication and patient education. Improved support structures, timely result communication, and access to follow-up care are essential to enhance patient outcomes. Recommendations advocate for health system improvements, partner involvement, and proactive counselling to address the specific needs of HIV-positive women undergoing cervical cancer prevention treatments.

in F1000Research on 2025-04-02 15:41:49 UTC.

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Host centric drug repurposing for viral diseases

by Suzana de Siqueira Santos, Haixuan Yang, Aldo Galeano, Alberto Paccanaro

Computational approaches for drug repurposing for viral diseases have mainly focused on a small number of antivirals that directly target pathogens (virus centric therapies). In this work, we combine ideas from collaborative filtering and network medicine for making predictions on a much larger set of drugs that could be repurposed for host centric therapies, that are aimed at interfering with host cell factors required by a pathogen. Our idea is to create matrices quantifying the perturbation that drugs and viruses induce on human protein interaction networks. Then, we decompose these matrices to learn embeddings of drugs, viruses, and proteins in a low dimensional space. Predictions of host-centric antivirals are obtained by taking the dot product between the corresponding drug and virus representations. Our approach is general and can be applied systematically to any compound with known targets and any virus whose host proteins are known. We show that our predictions have high accuracy and that the embeddings contain meaningful biological information that may provide insights into the underlying biology of viral infections. Our approach can integrate different types of information, does not rely on known drug-virus associations and can be applied to new viral diseases and drugs.

in PLoS Computational Biology on 2025-04-02 14:00:00 UTC.

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Ploidy plasticity drives fungal resistance to azoles used in agriculture and clinics

by Kaustuv Sanyal, Aswathy Narayanan

The rapid growth in antimicrobial resistance is of great medical concern. A new study in PLOS Biology unveils the link between ploidy plasticity and the emergence of antifungal resistance in Candida tropicalis. The rapid growth in antimicrobial resistance is of great medical concern. This Primer highlights a new study in PLOS Biology that unveils the link between ploidy plasticity and the emergence of antifungal resistance in Candida tropicalis.

in PLoS Biology on 2025-04-02 14:00:00 UTC.

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A single enzyme becomes a Swiss Army knife

by Andreas Sichert

An alga that abandoned photosynthesis? This Primer explores a PLOS Biology study showing that a single horizontal gene transfer event allowed the diatom Nitzschia sing1 to evolve a complete enzymatic machinery to break down alginate from brown algae, unlocking a new ecological niche.

in PLoS Biology on 2025-04-02 14:00:00 UTC.

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Autophagy-related protein Atg11 is essential for microtubule-mediated chromosome segregation

by Md. Hashim Reza, Rashi Aggarwal, Jigyasa Verma, Nitesh Kumar Podh, Ratul Chowdhury, Gunjan Mehta, Ravi Manjithaya, Kaustuv Sanyal

Emerging studies hint at the roles of autophagy-related proteins in various cellular processes. To understand if autophagy-related proteins influence genome stability, we sought to examine a cohort of 35 autophagy mutants in Saccharomyces cerevisiae. We observe cells lacking Atg11 show poor mitotic stability of minichromosomes. Single-molecule tracking assays and live cell microscopy reveal that Atg11 molecules dynamically localize to the spindle pole bodies (SPBs) in a microtubule (MT)-dependent manner. Loss of Atg11 leads to a delayed cell cycle progression. Such cells accumulate at metaphase at an elevated temperature that is relieved when the spindle assembly checkpoint (SAC) is inactivated. Indeed, atg11∆ cells have stabilized securin levels, that prevent anaphase onset. Ipl1-mediated activation of SAC also confirms that atg11∆ mutants are defective in chromosome biorientation. Atg11 functions in the Kar9-dependent spindle positioning pathway. Stabilized Clb4 levels in atg11∆ cells suggest that Atg11 maintains Kar9 asymmetry by facilitating proper dynamic instability of astral microtubules (aMTs). Loss of Spc72 asymmetry contributes to non-random SPB inheritance in atg11∆ cells. Overall, this study uncovers an essential non-canonical role of Atg11 in the MT-mediated process of chromosome segregation.

in PLoS Biology on 2025-04-02 14:00:00 UTC.

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Social knowledge about others is anchored to self-knowledge in the hippocampal formation

by Marta Rodríguez Aramendía, Mariachiara Esposito, Raphael Kaplan

Mounting evidence suggests the human hippocampal formation (HF) maps how different people’s attributes relate to each other. Yet, it’s unclear if hippocampal map-like knowledge representations of other people are shaped by self-knowledge. Here, we test if a prominent heuristic involving an implicit reliance on self-knowledge when rating others, egocentric anchoring-and-adjustment, is present in the HF when relational information about different social entities is retrieved. Participants first provided likelihood ratings of partaking in everyday activities for themselves, fictitious individuals, and familiar social groups. During a neuroimaging task that doesn’t require using self-knowledge, participants then learned a stranger’s preference for an activity relative to one of the fictitious individuals and inferred how the stranger’s preference related to the groups’ preferences. Isolating the neural representation of egocentric anchoring when retrieving relational social knowledge, the HF and dorsomedial prefrontal cortex (dmPFC) represented group entities’ preferences relative to the self. Furthermore, the HF selectively represented group identity over other learned entities, confirming the HF was primarily engaged by social comparisons in the more ample map-like reference frame. Taken together, these results imply that self-knowledge implicitly influences how the HF learns about others.

in PLoS Biology on 2025-04-02 14:00:00 UTC.

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Hyperbolic embedding of brain networks detects regions disrupted by neurodegeneration in Alzheimer's disease

Author(s): Alice Longhena, Martin Guillemaud, Fabrizio De Vico Fallani, Raffaella Migliaccio, and Mario Chavez

Alzheimer’s disease disrupts the brain’s connectivity structure, through processes such as progressive neuronal loss and brain atrophy. In this study, the authors propose a method based on a hyperbolic representation of brain networks to characterize brain regions with connectivity anomalies. They show that the method successfully identifies regions affected by neurodegeneration, opening the door to use it as a biomarker for disease progression.

#BiophysicsSpotlight #Interdisciplinary

[Phys. Rev. E 111, 044402] Published Wed Apr 02, 2025

in Physical Review E: Biological physics on 2025-04-02 10:00:00 UTC.

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microRNA-218-5p coordinates scaling of excitatory and inhibitory synapses during homeostatic synaptic plasticity

Proceedings of the National Academy of Sciences, Volume 122, Issue 14, April 2025.
SignificanceHomeostatic synaptic plasticity mechanisms evolved to keep neuronal firing rates within a physiological range in response to alterations in neural network activity. Similar mechanisms take place during slow wave sleep, a non-rapid-eye-movement ...

in PNAS on 2025-04-02 07:00:00 UTC.

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