Individual brains exhibit striking structural and physiological heterogeneity, yet neural circuits can generate remarkably consistent functional properties across individuals, an apparent paradox in neuroscience. While recent studies have observed preserved neural representations in motor cortex through manual alignment across subjects, the zero-shot validation of such preservation and its generalization to more cortices remain unexplored. Here we present PNBA (Probabilistic Neural-Behavioral Representation Alignment), a new framework that leverages probabilistic modeling to address hierarchical variability across trials, sessions, and subjects, with generative constraints preventing representation degeneration. By establishing reliable cross-modal representational alignment, PNBA reveals robust preserved neural representations in monkey primary motor cortex (M1) and dorsal premotor cortex (PMd) through zero-shot validation. We further establish similar representational preservation in mouse primary visual cortex (V1), reflecting a general neural basis. These findings resolve the paradox of neural heterogeneity by establishing zero-shot preserved neural representations across cortices and species, enriching neural coding insights and enabling zero-shot behavior decoding.
Distinguishing representational geometries with controversial stimuli: Bayesian experimental design and its application to face dissimilarity judgments
Zuckerman Mind Brain Behavior Institute（祖克曼心智脑行为研究所）；Columbia University（哥伦比亚大学）
Similarity-based representation factorization for revealing interpretable dimensions in representational data
Max Planck Institute for Human Cognitive and Brain Sciences（人类认知与脑科学最大平面研究所）；National Institute of Mental Health（心理健康国家研究所）；Justus Liebig University Giessen（吉森约斯特-利普大学）；Center for Mind, Brain and Behavior（心智、脑与行为中心）
Representational drift changes the encoding of fast and slow-varying natural scene features differently
SUNY Stony Brook University（纽约州立大学石溪分校）；National Institute for Theory and Mathematics in Biology, Northwestern University and The University of Chicago（西北大学和芝加哥大学生物理论与数学国家研究所）；University of Chicago（芝加哥大学）
Same Compression Principle, Different Geometry: Rate-Distortion Signatures Dissociate Biological and Artificial Visual Systems
Windreich Department of AI；Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA；Department of Computing, Imperial College London, London, UK；Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA；Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA；Berkman Klein Center for Internet \& Society, Harvard University, Cambridge, MA, USA
Large language models reorganize representational geometry during in-context learning
School of Psychological and Brain Sciences, Georgia Tech（佐治亚理工学院心理与脑科学学院）；Department of Psychology, New York University（纽约大学心理学系）；Center of Excellence for Computational Cognition, Georgia Tech（佐治亚理工学院计算认知卓越中心）；Honda Research Institute（本田研究院）；Departments of Neuroscience and Psychology, The University of Texas at Austin（德克萨斯大学奥斯汀分校神经科学与心理学系）
Shared representations in brains and models reveal a two-route cortical organization during scene perception
Department of Cognition, Development and Education Psychology, Faculty of Psychology, University of Barcelona（认知、发展与教育心理学系，心理学学院，巴塞罗那大学）；Institute of Neurosciences, University of Barcelona（神经科学研究所，巴塞罗那大学）；Bellvitge Institute for Biomedical Research（Bellvitge生物医学研究 institute）
Recurrence is required to capture the representational dynamics of the human visual system
MRC Cognition and Brain Sciences Unit, University of Cambridge（英国医学研究委员会认知与脑科学单元，剑桥大学）；Radboud University（拉德堡德大学）；Donders Institute for Brain, Cognition and Behaviour（邓德斯脑、认知与行为研究所）；University of Amsterdam（阿姆斯特丹大学）；Freie Universität Berlin（柏林自由大学）；Columbia University（哥伦比亚大学）
Convergent Representations of Linguistic Constructions in Human and Artificial Neural Systems
Department of English and American Studies, University Erlangen-Nuremberg（英语与美国研究系，埃尔朗根-纽伦堡大学）；Pattern Recognition Lab, University Erlangen-Nuremberg（模式识别实验室，埃尔朗根-纽伦堡大学）；Neuromodulation and Neuroprosthetics, University Hospital Mannheim, University Heidelberg（神经调控与神经假体，曼海姆大学医院，海德堡大学）；BGU Ludwigshafen, Germany（吕贝克大学吕贝克分校，德国）；Neuroscience Lab, University Hospital Erlangen（神经科学实验室，埃尔朗根大学医院）
