Nature neuroscience最新文献

{"title":"Functionally distinct GABAergic amacrine cell types regulate spatiotemporal encoding in the mouse retina","authors":"Akihiro Matsumoto, Jacqueline Morris, Loren L. Looger, Keisuke Yonehara","doi":"10.1038/s41593-025-01935-0","DOIUrl":"https://doi.org/10.1038/s41593-025-01935-0","url":null,"abstract":"<p>GABA (γ-aminobutyric acid) is the primary inhibitory neurotransmitter in the mammalian central nervous system. GABAergic neuronal types play important roles in neural processing and the etiology of neurological disorders; however, there is no comprehensive understanding of their functional diversity. Here we perform two-photon imaging of GABA release in the inner plexiform layer of male and female mice retinae (8–16 weeks old) using the GABA sensor iGABASnFR2. By applying varied light stimuli to isolated retinae, we reveal over 40 different GABA-releasing neuron types. Individual types show layer-specific visual encoding within inner plexiform layer sublayers. Synaptic input and output sites are aligned along specific retinal orientations. The combination of cell type-specific spatial structure and unique release kinetics enables inhibitory neurons to sculpt excitatory signals in response to a wide range of behaviorally relevant motion structures. Our findings emphasize the importance of functional diversity and intricate specialization of GABAergic neurons in the central nervous system.</p>","PeriodicalId":19076,"journal":{"name":"Nature neuroscience","volume":"40 1","pages":""},"PeriodicalIF":25.0,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143831701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatially clustered neurons in the bat midbrain encode vocalization categories","authors":"Jennifer Lawlor, Melville J. Wohlgemuth, Cynthia F. Moss, Kishore V. Kuchibhotla","doi":"10.1038/s41593-025-01932-3","DOIUrl":"https://doi.org/10.1038/s41593-025-01932-3","url":null,"abstract":"<p>Rapid categorization of vocalizations enables adaptive behavior across species. While categorical perception is thought to arise in the neocortex, humans and animals could benefit from a functional organization tailored to ethologically relevant sound processing earlier in the auditory pathway. Here we developed two-photon calcium imaging in the awake echolocating bat (<i>Eptesicus fuscus)</i> to study the representation of vocalizations in the inferior colliculus, which is as few as two synapses from the inner ear. Echolocating bats rely on frequency-sweep-based vocalizations for social communication and navigation. Auditory playback experiments demonstrated that individual neurons responded selectively to social or navigation calls, enabling robust population-level decoding across categories. When social calls were morphed into navigation calls in equidistant step-wise increments, individual neurons showed switch-like properties and population-level response patterns sharply transitioned at the category boundary. Strikingly, category-selective neurons formed spatial clusters, independent of tonotopy within the dorsal cortex of the inferior colliculus. These findings support a revised view of categorical processing in which specified channels for ethologically relevant sounds are spatially segregated early in the auditory hierarchy, enabling rapid subcortical organization into categorical primitives.</p>","PeriodicalId":19076,"journal":{"name":"Nature neuroscience","volume":"183 1","pages":""},"PeriodicalIF":25.0,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143827147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hippocampal output suppresses orbitofrontal cortex schema cell formation","authors":"Wenhui Zong, Jingfeng Zhou, Matthew P. H. Gardner, Zhewei Zhang, Kauê Machado Costa, Geoffrey Schoenbaum","doi":"10.1038/s41593-025-01928-z","DOIUrl":"https://doi.org/10.1038/s41593-025-01928-z","url":null,"abstract":"<p>Both the orbitofrontal cortex (OFC) and the hippocampus (HC) are implicated in the formation of cognitive maps and their generalization into schemas. However, how these areas interact in supporting this function remains unclear, with some proposals supporting a serial model in which the OFC draws on task representations created by the HC to extract key behavioral features and others suggesting a parallel model in which both regions construct representations that highlight different types of information. In the present study, we tested between these two models by asking how schema correlates in rat OFC would be affected by inactivating the output of the HC, after learning and during transfer across problems. We found that the prevalence and content of schema correlates were unaffected by inactivating one major HC output area, the ventral subiculum, after learning, whereas inactivation during transfer accelerated their formation. These results favor the proposal that the OFC and HC operate in parallel to extract different features defining cognitive maps and schemas.</p>","PeriodicalId":19076,"journal":{"name":"Nature neuroscience","volume":"112 1","pages":""},"PeriodicalIF":25.0,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143827148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-cell genomics of the mouse olfactory cortex reveals contrasts with neocortex and ancestral signatures of cell type evolution","authors":"Sara Zeppilli, Alonso O. Gurrola, Pinar Demetci, David H. Brann, Tuan M. Pham, Robin Attey, Noga Zilkha, Tali Kimchi, Sandeep R. Datta, Ritambhara Singh, Maria A. Tosches, Anton Crombach, Alexander Fleischmann","doi":"10.1038/s41593-025-01924-3","DOIUrl":"https://doi.org/10.1038/s41593-025-01924-3","url":null,"abstract":"<p>Understanding the molecular logic of cortical cell-type diversity can illuminate cortical circuit function and evolution. Here, we performed single-nucleus transcriptome and chromatin accessibility analyses to compare neurons across three- to six-layered cortical areas of adult mice and across tetrapod species. We found that, in contrast to the six-layered neocortex, glutamatergic neurons of the three-layered mouse olfactory (piriform) cortex displayed continuous rather than discrete variation in transcriptomic profiles. Subsets of piriform and neocortical glutamatergic cells with conserved transcriptomic profiles were distinguished by distinct, area-specific epigenetic states. Furthermore, we identified a prominent population of immature neurons in piriform cortex and observed that, in contrast to the neocortex, piriform cortex exhibited divergence between glutamatergic cells in laboratory versus wild-derived mice. Finally, we showed that piriform neurons displayed greater transcriptomic similarity to cortical neurons of turtles, lizards and salamanders than to those of the neocortex. In summary, despite over 200 million years of coevolution alongside the neocortex, olfactory cortex neurons retain molecular signatures of ancestral cortical identity.</p>","PeriodicalId":19076,"journal":{"name":"Nature neuroscience","volume":"74 1","pages":""},"PeriodicalIF":25.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143797824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microglia heterogeneity, modeling and cell-state annotation in development and neurodegeneration","authors":"Laura Fumagalli, Alma Nazlie Mohebiany, Jessie Premereur, Paula Polanco Miquel, Baukje Bijnens, Pieter Van de Walle, Nicola Fattorelli, Renzo Mancuso","doi":"10.1038/s41593-025-01931-4","DOIUrl":"https://doi.org/10.1038/s41593-025-01931-4","url":null,"abstract":"<p>Within the CNS, microglia execute various functions associated with brain development, maintenance of homeostasis and elimination of pathogens and protein aggregates. This wide range of activities is closely associated with a plethora of cellular states, which may reciprocally influence or be influenced by their functional dynamics. Advancements in single-cell RNA sequencing have enabled a nuanced exploration of the intricate diversity of microglia, both in health and disease. Here, we review our current understanding of microglial transcriptional heterogeneity. We provide an overview of mouse and human microglial diversity encompassing aspects of development, neurodegeneration, sex and CNS regions. We offer an insight into state-of-the-art technologies and model systems that are poised to improve our understanding of microglial cell states and functions. We also provide suggestions and a tool to annotate microglial cell states on the basis of gene expression.</p>","PeriodicalId":19076,"journal":{"name":"Nature neuroscience","volume":"87 1","pages":""},"PeriodicalIF":25.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143789742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sugar-coating the BBB","authors":"Shari Wiseman","doi":"10.1038/s41593-025-01939-w","DOIUrl":"10.1038/s41593-025-01939-w","url":null,"abstract":"","PeriodicalId":19076,"journal":{"name":"Nature neuroscience","volume":"28 4","pages":"709-709"},"PeriodicalIF":21.2,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143782484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opening the deep learning box","authors":"Luis A. Mejia","doi":"10.1038/s41593-025-01938-x","DOIUrl":"10.1038/s41593-025-01938-x","url":null,"abstract":"","PeriodicalId":19076,"journal":{"name":"Nature neuroscience","volume":"28 4","pages":"709-709"},"PeriodicalIF":21.2,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143782482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI predicts risk of mental health disorders","authors":"Laura Zelenka","doi":"10.1038/s41593-025-01940-3","DOIUrl":"10.1038/s41593-025-01940-3","url":null,"abstract":"","PeriodicalId":19076,"journal":{"name":"Nature neuroscience","volume":"28 4","pages":"709-709"},"PeriodicalIF":21.2,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143782483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human lifespan changes in the brain’s functional connectome","authors":"Lianglong Sun,&nbsp;Tengda Zhao,&nbsp;Xinyuan Liang,&nbsp;Mingrui Xia,&nbsp;Qiongling Li,&nbsp;Xuhong Liao,&nbsp;Gaolang Gong,&nbsp;Qian Wang,&nbsp;Chenxuan Pang,&nbsp;Qian Yu,&nbsp;Yanchao Bi,&nbsp;Pindong Chen,&nbsp;Rui Chen,&nbsp;Yuan Chen,&nbsp;Taolin Chen,&nbsp;Jingliang Cheng,&nbsp;Yuqi Cheng,&nbsp;Zaixu Cui,&nbsp;Zhengjia Dai,&nbsp;Yao Deng,&nbsp;Yuyin Ding,&nbsp;Qi Dong,&nbsp;Dingna Duan,&nbsp;Jia-Hong Gao,&nbsp;Qiyong Gong,&nbsp;Ying Han,&nbsp;Zaizhu Han,&nbsp;Chu-Chung Huang,&nbsp;Ruiwang Huang,&nbsp;Ran Huo,&nbsp;Lingjiang Li,&nbsp;Ching-Po Lin,&nbsp;Qixiang Lin,&nbsp;Bangshan Liu,&nbsp;Chao Liu,&nbsp;Ningyu Liu,&nbsp;Ying Liu,&nbsp;Yong Liu,&nbsp;Jing Lu,&nbsp;Leilei Ma,&nbsp;Weiwei Men,&nbsp;Shaozheng Qin,&nbsp;Jiang Qiu,&nbsp;Shijun Qiu,&nbsp;Tianmei Si,&nbsp;Shuping Tan,&nbsp;Yanqing Tang,&nbsp;Sha Tao,&nbsp;Dawei Wang,&nbsp;Fei Wang,&nbsp;Jiali Wang,&nbsp;Pan Wang,&nbsp;Xiaoqin Wang,&nbsp;Yanpei Wang,&nbsp;Dongtao Wei,&nbsp;Yankun Wu,&nbsp;Peng Xie,&nbsp;Xiufeng Xu,&nbsp;Yuehua Xu,&nbsp;Zhilei Xu,&nbsp;Liyuan Yang,&nbsp;Huishu Yuan,&nbsp;Zilong Zeng,&nbsp;Haibo Zhang,&nbsp;Xi Zhang,&nbsp;Gai Zhao,&nbsp;Yanting Zheng,&nbsp;Suyu Zhong,&nbsp;Alzheimer’s Disease Neuroimaging Initiative,&nbsp;DIDA-MDD Working Group,&nbsp;MCADI,&nbsp;Yong He","doi":"10.1038/s41593-025-01907-4","DOIUrl":"10.1038/s41593-025-01907-4","url":null,"abstract":"Functional connectivity of the human brain changes through life. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals at 32 weeks of postmenstrual age to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a spatiotemporal cortical axis, transitioning from primary sensorimotor regions to higher-order association regions. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging and neuropsychiatric disorders. Sun et al. report human lifespan changes in the brain’s functional connectome in 33,250 individuals, which highlights critical growth milestones and distinct maturation patterns and offers a normative reference for development, aging and diseases.","PeriodicalId":19076,"journal":{"name":"Nature neuroscience","volume":"28 4","pages":"891-901"},"PeriodicalIF":21.2,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143766546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Author Correction: An activity-regulated transcriptional program directly drives synaptogenesis","authors":"Callista Yee, Yutong Xiao, Hongwen Chen, Anay R. Reddy, Bing Xu, Taylor N. Medwig-Kinney, Wan Zhang, Alan P. Boyle, Wendy A. Herbst, Yang Kevin Xiang, David Q. Matus, Kang Shen","doi":"10.1038/s41593-025-01950-1","DOIUrl":"https://doi.org/10.1038/s41593-025-01950-1","url":null,"abstract":"<p>Correction to: <i>Nature Neuroscience</i> https://doi.org/10.1038/s41593-024-01728-x, published online 5 August 2024.</p>","PeriodicalId":19076,"journal":{"name":"Nature neuroscience","volume":"38 1","pages":""},"PeriodicalIF":25.0,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143758694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}