Frontiers in Systems Neuroscience最新文献

{"title":"Convergence-divergence circuits for multimodal integration of innate and learned opponent valences.","authors":"Wenjing Wang, Yaokai Yang, Qiong Liu, Yunming Gao, Qiantao Lv, Kaiqi Zhang, Jing Ning, Yi Sun","doi":"10.3389/fnsys.2026.1822122","DOIUrl":"10.3389/fnsys.2026.1822122","url":null,"abstract":"<p><p>Valence detection in complex environment is critical for natural behaviors like foraging. Previous studies have explored valence processing in brain regions like lateral horn (LH) and mushroom body (MB) using simple synthetic stimuli in <i>Drosophila</i>. However, the neural basis for valence detection of natural objects in complex contexts remains unclear. Here, by brain-wide connectome analysis, we identified the evolutionarily conserved superior protocerebrum (SP) that integrates brain-wide multimodal inputs mainly via LH and MB, and sends widespread outputs particularly to the central complex (CX). This forms a convergence-divergence circuit resembling an autoencoder architecture, with SP as the bottleneck integrating multimodal information into low-dimensional valence signals. Specifically, SP input LH neurons integrate ethologically related innate valences for robust valence detection in natural environments, and the integration can be unimodal, such as that of diverse odors signaling food, or multimodal, such as that of wind and temperature signaling lousy weather. Opponent valences of attraction and aversion are further integrated into SP for complex valence detection. MB learned valences are also integrated into SP to update LH innate valences with recent experience for flexible valence detection. Attractive and aversive valences, either innate or learned, are integrated via excitatory and inhibitory synapses, respectively to form complex valence signals in a single SP neuron. Organized synaptic compartments support dendritic computation, with SP neurons exhibiting opposite synaptic organizations for opponent valences, indicating dendritic integration for complex valence detection. Our study highlights the importance of SP in multimodal opponent valence integration and suggests generalizable network and dendritic structures for complex valence processing.</p>","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"20 ","pages":"1822122"},"PeriodicalIF":3.6,"publicationDate":"2026-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13190573/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148014820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The body does not keep the score: trauma, predictive coding, and the restoration of metastability.","authors":"Steven Kotler, Michael Mannino, Glenn Fox, Karl Friston","doi":"10.3389/fnsys.2026.1812957","DOIUrl":"10.3389/fnsys.2026.1812957","url":null,"abstract":"","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"20 ","pages":"1812957"},"PeriodicalIF":3.6,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13171788/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147963375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative investigation on working memory patterns through EEG based on visual attention task for children with learning disability.","authors":"S Vidhusha, S Karthika, N Sahana, A Sabari Srinivas, Shitharth Selvarajan, Nithya Rekha Sivakumar, Sumendra Yogarayan","doi":"10.3389/fnsys.2025.1687354","DOIUrl":"10.3389/fnsys.2025.1687354","url":null,"abstract":"<p><p>Learning disabilities in children are exhibited through difficulties in reading and writing due to lack of cognitive skills. It is generally diagnosed by analyzing the behavior and processing capacity of children by understanding their academic candidature. This can also be evidenced by capturing and analyzing their working memory patterns in the brain that show the effectiveness of therapeutic interventions in children with learning disabilities. This research works with the electroencephalography (EEG) signal data from the IEEE dataport consisting of 121 participants in total, of which 61 are ADHD and 60 are normal children aged 7-12 years. The usage of these data has influenced ground truth research by providing reliable data and mitigating the challenge with real-time availability of EEG data. This manuscript focuses on classifying the dataset into categories of children, viz normal and attention deficit hyperactivity disorder (ADHD), using brain connectivity parameters and validation through machine learning (ML) algorithms. Children with learning disabilities undergo therapeutic interventions to manage their disability. Generally, the progress of their intellectual capability can be assessed through visual cues and the responses that the children exhibit. Rather, their differences in brain cognition need to be analyzed to realize the outcomes of therapeutical effect. In this research, the brain connectivity parameters such as power spectral density (PSD), granger causality (GC), phase slope index (PSI), partial directed coherence (PDC), and directed transmission function (DTF) are estimated, quantified, and analyzed. Further, using the measures of brain connectivity parameters, certain ML algorithms-such as the logistic regression (LR), support vector machine (SVM), decision tree (DT), the k-nearest neighbor (KNN), and random forest (RF)-along with a deep learning model, viz. deep belief networks (DBN) have been employed for validating this study. Among these models, DBN offered a model accuracy of 89.7%. Hence, this concept emphasizes the validation and effectiveness of therapeutic interventions that can support clinical evaluations in children with learning disability.</p>","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"19 ","pages":"1687354"},"PeriodicalIF":3.6,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13169502/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147941219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Information-theoretic and physical constraints on advanced neural signal decoding.","authors":"Enzhuo Zhang, Syed Ishtiaque Ahmed","doi":"10.3389/fnsys.2026.1786729","DOIUrl":"10.3389/fnsys.2026.1786729","url":null,"abstract":"<p><p>Recent interdisciplinary research has raised interest in whether non-classical physical principles may impose fundamental constraints on how neural information can be observed, extracted, or decoded. While conventional neuroscience models neural signaling primarily through classical electrochemical processes, a growing body of theoretical literature has speculated that quantum-mechanical concepts-such as coherence, entanglement, or quantum-inspired information processing-may offer alternative perspectives on the limits of neural observability. This article provides a critical and integrative review of theoretical proposals situated at the intersection of neuroscience, quantum biology, and information theory, without assuming the physical realizability of quantum information processing in biological neural systems. We examine conceptual motivations, key physical constraints (including decoherence, thermal noise, and system complexity), and unresolved theoretical challenges that arise when extending classical neural decoding frameworks toward non-classical regimes. Rather than proposing an experimentally validated mechanism for brain decoding, this work focuses on identifying conceptual boundaries, potential misinterpretations, and open questions that must be addressed before non-classical approaches to neural signal decoding can be meaningfully evaluated. Ethical considerations, methodological limitations, and future research directions are discussed to clarify the conditions under which such speculative frameworks may contribute to neuroscience, while avoiding overextension beyond current empirical evidence.</p>","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"20 ","pages":"1786729"},"PeriodicalIF":3.6,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13162149/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147928502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deciphering the regulatory mechanism of neural behavioral decisions through biogenic amine-mediated modulation of neural circuits in <i>Caenorhabditis elegans</i>.","authors":"Hui Liu, Yunlong Shen, Dejian Peng","doi":"10.3389/fnsys.2026.1727180","DOIUrl":"10.3389/fnsys.2026.1727180","url":null,"abstract":"<p><p>Brain function is not simply the sum of individual neuronal activities, but rather emerges from functional neural circuits comprising thousands to millions of neurons with specific topological structures and dynamic properties. Investigating the functions and information-processing architectures of these neural circuits is essential for understanding how the brain performs \"computation\" and \"operation.\" Biological neural regulatory networks are captivating due to their extensive utilization of diverse signaling molecules for interneuronal communication. Neurotransmitters, receptors, and neurons together compose neuroregulatory circuits, which act as fundamental functional units in the network for generating behavioral instructions. However, the discovery and decipherment of neural circuits remain challenging, due to the necessity of comprehending the functions of signaling molecules and neuronal cells, as well as their regulatory mechanisms. In this review, we focus on four biogenic amines signals, including dopamine, serotonin, octopamine and tyramine, and discuss their regulatory roles with their receptors in <i>Caenorhabditis elegans</i> neural circuits. In particular, we summarize the functional roles of the biogenic amine neurons and their complex interaction mechanisms in neural circuits. We also provide perspectives on the fine-scale neural connectivity, which will bridge microscopic neuronal activity with macroscopic cognitive behaviors, offering a theoretical framework for further elucidating the neural mechanisms underlying brain adaptation, learning, and memory.</p>","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"20 ","pages":"1727180"},"PeriodicalIF":3.6,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13128624/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147814079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying emotion-dependent brain-eye interactions during audiovisual emotional stimulation.","authors":"Feryal A Alskafi, Ahsan H Khandoker, Faezeh Marzbanrad, Herbert F Jelinek","doi":"10.3389/fnsys.2026.1744042","DOIUrl":"10.3389/fnsys.2026.1744042","url":null,"abstract":"<p><strong>Purpose: </strong>Electrooculography (EOG) provides a noninvasive measure of eye movements linked to affective processing, yet it is mainly used for artifact correction of electroencephalography (EEG) signals rather than analyzed as a physiological signal in its own right. EEG-EOG coupling has therefore not been well-established. This study aimed to determine whether emotion-specific changes in arousal and valence are reflected in directional and frequency-specific interactions between EEG rhythms and EOG signals.</p><p><strong>Methods: </strong>The DEAP dataset with 32 participants, where each viewed 40 1-min music videos and rated their arousal/valence, was used (1,280 samples). EEG from eight electrodes was filtered into theta, alpha, beta, and gamma frequency bands, while horizontal and vertical EOG were also preprocessed. EOG complexity was assessed using sample, fuzzy, and permutation entropy. EEG-EOG coupling was assessed with the controlled time delay stability (CTDS) framework, which evaluates stability of partial cross-correlation delays.</p><p><strong>Results: </strong>Entropy analysis showed emotion-related differences in horizontal and vertical EOG complexity (<i>p</i> < 0.005). EEG-EOG coupling varied with emotion, with the strongest effects at sensorimotor and frontal sites, primarily within the gamma band. Directional EOG-to-EEG coupling predominating at frontal, sensorimotor, and occipital sites. Differences were most pronounced when arousal and valence varied independently or in opposite directions, with fewer effects during parallel shifts.</p><p><strong>Conclusion: </strong>Emotional states are mirrored by frequency- and channel-specific shifts in EEG-EOG interactions, a core component of the affective behavioral network. These results clarify the directional dynamics linking eye movement and cortical activity, revealing a structured, context-sensitive neural architecture for affective processing.</p>","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"20 ","pages":"1744042"},"PeriodicalIF":3.6,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13124692/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147814056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"dCA1 cells encode and update contextual place preference.","authors":"Kwon Choi, Ignitius Ezekiel Lim, Ajn Vats, Sonni Marie Tarver, Tashonda Benoit Vaughn, Olalekan Michael Ogundele","doi":"10.3389/fnsys.2026.1702298","DOIUrl":"10.3389/fnsys.2026.1702298","url":null,"abstract":"<p><p>Pyramidal cells in the dorsal hippocampus (dCA1) are excitatory neurons modulated by environmental cues. While a population of dCA1 cells encodes spatial location, other groups are activated by reward probability and encounters. <i>Since \"rewards\" are predicted at \"locations,\" we sought to determine how spatiotemporal coding patterns in the dCA1 resolve contextual preference and subsequent change in preference that is driven by reward encounters.</i> Specifically, we examined these encoding patterns in biased place-preference tasks for simple reward acquisition and for complex discrimination of reward magnitudes. Initial behavioral tests for mice without neural implants revealed a higher sensitivity to discriminating between <i>two locations</i> associated with reward magnitude, in comparison to reward detection. Analysis of dCA1 single-unit spatiotemporal activity during pre-conditioning revealed that these cells exhibited peak firing as they approached the less preferred context. Therefore, when the contextual preference is biased toward a reward or a higher-magnitude reward, a change in dCA1 firing rate around context entry events reflects the updated spatial preference. Interestingly, the context of lower preference with no associated reward or a lower-value reward elicits a stronger firing response than the alternative contexts with higher reward values. Together, we conclude that the spatiotemporal firing patterns of dCA1 single units and the threshold of peak FR change encode contextual preference. Ultimately, the spatiotemporal pattern is updated (remapped) when there is a change in the contextual preference driven by reward contingencies.</p>","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"20 ","pages":"1702298"},"PeriodicalIF":3.6,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13102668/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147769518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quadrupedal training approaches in post-stroke rehabilitation: a scoping review of evidence, mechanisms, and clinical applications.","authors":"Jan A Kuipers, Frederick R Carrick, Monèm Jemni","doi":"10.3389/fnsys.2026.1773330","DOIUrl":"10.3389/fnsys.2026.1773330","url":null,"abstract":"<p><strong>Background: </strong>Persistent impairments in trunk control, balance, and mobility are frequently observed after stroke, even after standard task-specific rehabilitation. Quadrupedal-derived training (QT)-which involves four-point support, dynamic contralateral tasks, transitional kneeling, and crawling-has attracted clinical interest because it may activate bilateral and spinal sensorimotor networks. Nonetheless, the evidence supporting QT has not been thoroughly systematically mapped. Objective: To synthesize the extent, characteristics, mechanisms, and clinical applications of quadrupedal-derived training in adult post-stroke rehabilitation.</p><p><strong>Methods: </strong>A scoping review was conducted in accordance with the JBI Manual for Evidence Synthesis and the PRISMA-ScR guidelines. It involved searching five databases and additional sources from 2010 to 2025 to find studies on QT in stroke populations, along with mechanistic and translational evidence. The outcomes were pre-mapped to the International Classification of Functioning (ICF) domains. Data on intervention types, total dosage, supervision, progression criteria, safety, and feasibility were gathered. Stakeholder input from stroke survivors, clinicians, and researchers helped shape implementation considerations.</p><p><strong>Results: </strong>Eighteen studies met the inclusion criteria, including five randomized controlled trials and one case study involving stroke populations, as well as mechanistic and translational research. QT consistently improved trunk control and balance, with effects on functional mobility and certain gait parameters varying depending on the variant and dose. Kneeling-based QT showed greater balance benefits than treadmill-based training in subacute inpatient settings, while static and dynamic four-point variants were mainly used with chronic outpatient groups. No serious adverse events occurred, and adherence was high where recorded. Mechanistic evidence indicates a pathway connecting quadrupedal loading to activation of spinal and interlimb networks, bilateral proximal muscles, and functional improvements.</p><p><strong>Conclusion: </strong>Quadrupedal-based training is a biologically plausible, resource-efficient, and clinically practical method for improving trunk and balance issues after a stroke. More well-designed studies that include standardized progression, dose-response evaluations, and neurophysiological biomarkers are needed.</p>","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"20 ","pages":"1773330"},"PeriodicalIF":3.6,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13099906/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147769585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Grand challenges for systems neuroscience: perspectives and opportunities.","authors":"Wen-Jun Gao","doi":"10.3389/fnsys.2026.1818506","DOIUrl":"10.3389/fnsys.2026.1818506","url":null,"abstract":"<p><p>Systems neuroscience seeks to uncover how diverse neuronal populations and distributed neural types, circuits, and regions in the brain give rise to perception, learning, emotion, cognition, and behavior, and how dysfunction at any of these levels contributes to neurological and psychiatric disorders. The field has rapidly expanded from single-cell studies to large-scale, multimodal interrogation and manipulation of brain-wide activity, creating unprecedented opportunities alongside major conceptual and technical challenges. Systems neuroscience is at a pivotal moment, with advances in basic, translational, and clinical research converging to deepen understanding of how neural activity generates mental life.</p>","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"20 ","pages":"1818506"},"PeriodicalIF":3.6,"publicationDate":"2026-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13096744/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147769555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EEG biomarkers of the sense of embodiment: methodological gaps and evidence-based recommendations from a systematic review.","authors":"Daniela Esteves, Athanasios Vourvopoulos","doi":"10.3389/fnsys.2026.1756407","DOIUrl":"10.3389/fnsys.2026.1756407","url":null,"abstract":"<p><strong>Introduction: </strong>The sense of embodiment (SoE), describing the experience of owning, controlling, and being located within a body, underpins virtual reality (VR) interaction, brain-computer interfaces (BCIs), and multisensory body-illusion research. Although SoE is typically assessed through subjective questionnaires, their variability and limited validity have motivated the search for objective neural markers. Electroencephalography (EEG) has become the most widely used technique given its portability and high temporal resolution; however, the existence of a consistent EEG correlate of embodiment remains unclear.</p><p><strong>Methods: </strong>This systematic review summarizes 35 EEG studies (2010-June 2025) identified through structured database searches, examining SoE across immersive and non-immersive VR, augmented reality, and non-VR paradigms. We analyze EEG features including spectral power, event-related desynchronization/synchronization (ERD/ERS), connectivity, and temporal dynamics, and examine methodological variability in illusion induction and SoE assessment.</p><p><strong>Results: </strong>Across studies, the reduction of the alpha-band over central-parietal regions emerges as the most recurrent correlate of embodiment. Beta-band decreases and gamma-band increases appear in several studies but lack consistent replication, while findings in Delta and Theta bands remain sparse and contradictory. Considerable heterogeneity is found in VR paradigms, EEG setups, preprocessing, and psychometric tools, contributing to inconsistent results and limiting cross-study comparability.</p><p><strong>Discussion: </strong>Critically, no EEG feature demonstrates sufficient reproducibility to qualify as a universal biomarker of SoE, and no standardized protocol for EEG-based embodiment assessment currently exists. Overall, this review highlights both the promise and current limitations of EEG-based approaches to measuring embodiment. We conclude by identifying methodological gaps and outlining recommendations to support the development of reliable EEG markers for future applications in VR rehabilitation, MI-BCIs, cognitive neuroscience, and clinical interventions.</p>","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":"20 ","pages":"1756407"},"PeriodicalIF":3.6,"publicationDate":"2026-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13047143/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147622745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}