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Hazy, MD", "links": { "alternate": { "href": "https://www.zotero.org/thazy", "type": "text/html" } } }, "creatorSummary": "Assran et al.", "parsedDate": "2025-06-11", "numChildren": 2 }, "data": { "key": "FUMJ5AUP", "version": 97818, "itemType": "preprint", "title": "V-JEPA 2: Self-supervised video models enable understanding, prediction and planning", "creators": [ { "creatorType": "author", "firstName": "Mido", "lastName": "Assran" }, { "creatorType": "author", "firstName": "Adrien", "lastName": "Bardes" }, { "creatorType": "author", "firstName": "David", "lastName": "Fan" }, { "creatorType": "author", "firstName": "Quentin", "lastName": "Garrido" }, { "creatorType": "author", "firstName": "Russell", "lastName": "Howes" }, { "creatorType": "author", "firstName": "", "lastName": "Mojtaba" }, { "creatorType": "author", "firstName": "", "lastName": "Komeili" }, { "creatorType": "author", "firstName": "Matthew", "lastName": "Muckley" }, { "creatorType": "author", "firstName": "Ammar", "lastName": "Rizvi" }, { "creatorType": "author", "firstName": "Claire", "lastName": "Roberts" }, { "creatorType": "author", "firstName": "Koustuv", "lastName": "Sinha" }, { "creatorType": "author", "firstName": "Artem", "lastName": "Zholus" }, { "creatorType": "author", "firstName": "Sergio", "lastName": "Arnaud" }, { "creatorType": "author", "firstName": "Abha", "lastName": "Gejji" }, { "creatorType": "author", "firstName": "Ada", "lastName": "Martin" }, { "creatorType": "author", "firstName": "Francois Robert", "lastName": "Hogan" }, { "creatorType": "author", "firstName": "Daniel", "lastName": "Dugas" }, { "creatorType": "author", "firstName": "Piotr", "lastName": "Bojanowski" }, { "creatorType": "author", "firstName": "Vasil", "lastName": "Khalidov" }, { "creatorType": "author", "firstName": "Patrick", "lastName": "Labatut" }, { "creatorType": "author", "firstName": "Francisco", "lastName": "Massa" }, { "creatorType": "author", "firstName": "Marc", "lastName": "Szafraniec" }, { "creatorType": "author", "firstName": "Kapil", "lastName": "Krishnakumar" }, { "creatorType": "author", "firstName": "Yong", "lastName": "Li" }, { "creatorType": "author", "firstName": "Xiaodong", "lastName": "Ma" }, { "creatorType": "author", "firstName": "Sarath", "lastName": "Chandar" }, { "creatorType": "author", "firstName": "Franziska", "lastName": "Meier" }, { "creatorType": "author", "firstName": "Yann", "lastName": "LeCun" }, { "creatorType": "author", "firstName": "Michael", "lastName": "Rabbat" }, { "creatorType": "author", "firstName": "Nicolas", "lastName": "Ballas" } ], "abstractNote": "A major challenge for modern AI is to learn to understand the world and learn to act largely by observation. This paper explores a self-supervised approach that combines internet-scale video data with a small amount of interaction data (robot trajectories), to develop models capable of understanding, predicting, and planning in the physical world. We first pre-train an action-free joint-embedding-predictive architecture, V-JEPA 2, on a video and image dataset comprising over 1 million hours of internet video. V-JEPA 2 achieves strong performance on motion understanding (77.3 top-1 accuracy on Something-Something v2) and state-of-the-art performance on human action anticipation (39.7 recall-at-5 on Epic-Kitchens-100) surpassing previous task-specific models. Additionally, after aligning V-JEPA 2 with a large language model, we demonstrate state-of-the-art performance on multiple video question-answering tasks at the 8 billion parameter scale (e.g., 84.0 on PerceptionTest, 76.9 on TempCompass). Finally, we show how self-supervised learning can be applied to robotic planning tasks by post-training a latent action-conditioned world model, V-JEPA 2-AC, using less than 62 hours of unlabeled robot videos from the Droid dataset. We deploy V-JEPA 2-AC zero-shot on Franka arms in two different labs and enable picking and placing of objects using planning with image goals. Notably, this is achieved without collecting any data from the robots in these environments, and without any task-specific training or reward. This work demonstrates how self-supervised learning from web-scale data and a small amount of robot interaction data can yield a world model capable of planning in the physical world.", "genre": "", "repository": "arXiv", "archiveID": "arXiv:2506.09985", "place": "", "date": "2025-06-11", "series": "", "seriesNumber": "", "DOI": "10.48550/arXiv.2506.09985", "citationKey": "AssranBardesFanEtAl25", "url": "http://arxiv.org/abs/2506.09985", "accessDate": "2026-10-08T20:44:53Z", "archive": "", "archiveLocation": "", "shortTitle": "V-JEPA 2", "language": "", "libraryCatalog": "arXiv.org", "callNumber": "", "rights": "", "extra": "arXiv:2506.09985 [cs.AI]", "tags": [ { "tag": "Computer Science - Artificial Intelligence", "type": 1 }, { "tag": "Computer Science - Computer Vision and Pattern Recognition", "type": 1 }, { "tag": "Computer Science - Machine Learning", "type": 1 }, { "tag": "Computer Science - Robotics", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2026-10-08T20:44:53Z", "dateModified": "2026-10-08T20:45:18Z" } }, { "key": "KA4QYEPQ", "version": 97816, "library": { "type": "group", "id": 340666, "name": "CCNLab", "links": { "alternate": { "href": "https://www.zotero.org/groups/ccnlab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/340666/items/KA4QYEPQ", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/ccnlab/items/KA4QYEPQ", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/340666/items/FUMJ5AUP", "type": "application/json" } }, "meta": { "createdByUser": { "id": 2407002, "username": "thazy", "name": "Thomas E. 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Hazy, MD", "links": { "alternate": { "href": "https://www.zotero.org/thazy", "type": "text/html" } } }, "creatorSummary": "Nam et al.", "parsedDate": "2026-05-28", "numChildren": 2 }, "data": { "key": "8KRVREU8", "version": 97810, "itemType": "preprint", "title": "Causal-JEPA: Learning world models through object-level latent masking", "creators": [ { "creatorType": "author", "firstName": "Heejeong", "lastName": "Nam" }, { "creatorType": "author", "firstName": "Quentin Le", "lastName": "Lidec" }, { "creatorType": "author", "firstName": "Lucas", "lastName": "Maes" }, { "creatorType": "author", "firstName": "Yann", "lastName": "LeCun" }, { "creatorType": "author", "firstName": "Randall", "lastName": "Balestriero" } ], "abstractNote": "World models require robust relational understanding to support prediction, reasoning, and control. While object-centric representations provide a useful abstraction, they are not sufficient to capture interaction-dependent dynamics. We therefore propose C-JEPA, a simple and flexible object-centric world model that extends masked joint embedding prediction from image patches to object-centric representations. By masking object-level latents and requiring each masked object state to be inferred from the surrounding context, C-JEPA imposes structured partial observability during training, creating counterfactual-like prediction queries that discourage shortcut solutions and make interaction-dependent prediction necessary under the learning objective. Empirically, C-JEPA leads to consistent gains in visual question answering, with an absolute improvement of about 20% in counterfactual reasoning over the same architecture without object-level masking. On agent control tasks, C-JEPA enables substantially more efficient planning by using only 1% of the total latent input features required by patch-based world models, while achieving comparable performance. Finally, we provide a formal analysis demonstrating that object-level masking induces useful inductive bias by controlling observability. Our code is available at https://github.com/galilai-group/cjepa.", "genre": "", "repository": "arXiv", "archiveID": "arXiv:2602.11389", "place": "", "date": "2026-05-28", "series": "", "seriesNumber": "", "DOI": "10.48550/arXiv.2602.11389", "citationKey": "NamLidecMaesEtAl26", "url": "http://arxiv.org/abs/2602.11389", "accessDate": "2026-10-08T20:39:29Z", "archive": "", "archiveLocation": "", "shortTitle": "Causal-JEPA", "language": "", "libraryCatalog": "arXiv.org", "callNumber": "", "rights": "", "extra": "arXiv:2602.11389 [cs.AI]", "tags": [ { "tag": "Computer Science - Artificial Intelligence", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2026-10-08T20:39:29Z", "dateModified": "2026-10-08T20:39:55Z" } }, { "key": "NYZKIJ6H", "version": 97806, "library": { "type": "group", "id": 340666, "name": "CCNLab", "links": { "alternate": { "href": "https://www.zotero.org/groups/ccnlab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/340666/items/NYZKIJ6H", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/ccnlab/items/NYZKIJ6H", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/340666/items/8KRVREU8", "type": "application/json" } }, "meta": { "createdByUser": { "id": 2407002, "username": "thazy", "name": "Thomas E. 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We recorded the activity of single neurons in the human medial temporal lobe (MTL) during the formation and retrieval of memories with complex narratives. Here, we show that neurons responded to abstract cognitive boundaries between different episodes. Boundary-induced neural state changes during encoding predicted subsequent recognition accuracy but impaired event order memory, mirroring a fundamental behavioral tradeoff between content and time memory. Furthermore, the neural state following boundaries was reinstated during both successful retrieval and false memories. These findings reveal a neuronal substrate for detecting cognitive boundaries that transform experience into mnemonic episodes and structure mental time travel during retrieval.", "publicationTitle": "Nature Neuroscience", "publisher": "Nature Publishing Group", "place": "", "date": "2022-03", "volume": "25", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "358-368", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Nat Neurosci", "DOI": "10.1038/s41593-022-01020-w", "citationKey": "ZhengSchjetnanYebraEtAl22", "url": "https://www.nature.com/articles/s41593-022-01020-w", "accessDate": "2026-10-08T16:38:42Z", "PMID": "", "PMCID": "", "ISSN": "1546-1726", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "www.nature.com", "callNumber": "", "rights": "2022 The Author(s), under exclusive licence to Springer Nature America, Inc.", "extra": "", "tags": [ { "tag": "Cognitive neuroscience", "type": 1 }, { "tag": "Long-term memory", "type": 1 }, { "tag": "Neurophysiology", "type": 1 } ], "collections": [], "relations": { "owl:sameAs": "http://zotero.org/groups/2525742/items/ARRBDW3B" }, "dateAdded": "2026-10-08T16:39:03Z", "dateModified": "2026-10-08T16:39:03Z" } }, { "key": "9DYJ5ASK", "version": 97798, "library": { "type": "group", "id": 340666, "name": "CCNLab", "links": { "alternate": { "href": "https://www.zotero.org/groups/ccnlab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/340666/items/9DYJ5ASK", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/ccnlab/items/9DYJ5ASK", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/340666/items/25DSGIN3", "type": "application/json" } }, "meta": { "createdByUser": { "id": 2407002, "username": "thazy", "name": "Thomas E. 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Hazy, MD", "links": { "alternate": { "href": "https://www.zotero.org/thazy", "type": "text/html" } } }, "creatorSummary": "Varela et al.", "parsedDate": "2014-05-01", "numChildren": 1 }, "data": { "key": "25DSGIN3", "version": 97796, "itemType": "journalArticle", "title": "Anatomical substrates for direct interactions between hippocampus, medial prefrontal cortex, and the thalamic nucleus reuniens", "creators": [ { "creatorType": "author", "firstName": "C.", "lastName": "Varela" }, { "creatorType": "author", "firstName": "S.", "lastName": "Kumar" }, { "creatorType": "author", "firstName": "J. Y.", "lastName": "Yang" }, { "creatorType": "author", "firstName": "M. A.", "lastName": "Wilson" } ], "abstractNote": "The reuniens nucleus in the midline thalamus projects to the medial prefrontal cortex (mPFC) and the hippocampus, and has been suggested to modulate interactions between these regions, such as spindle–ripple correlations during sleep and theta band coherence during exploratory behavior. Feedback from the hippocampus to the nucleus reuniens has received less attention but has the potential to influence thalamocortical networks as a function of hippocampal activation. We used the retrograde tracer cholera toxin B conjugated to two fluorophores to study thalamic projections to the dorsal and ventral hippocampus and to the prelimbic and infralimbic subregions of mPFC. We also examined the feedback connections from the hippocampus to reuniens. The goal was to evaluate the anatomical basis for direct coordination between reuniens, mPFC, and hippocampus by looking for double-labeled cells in reuniens and hippocampus. In confirmation of previous reports, the nucleus reuniens was the origin of most thalamic afferents to the dorsal hippocampus, whereas both reuniens and the lateral dorsal nucleus projected to ventral hippocampus. Feedback from hippocampus to reuniens originated primarily in the dorsal and ventral subiculum. Thalamic cells with collaterals to mPFC and hippocampus were found in reuniens, across its anteroposterior axis, and represented, on average, about 8 % of the labeled cells in reuniens. Hippocampal cells with collaterals to mPFC and reuniens were less common (~1 % of the labeled subicular cells), and located in the molecular layer of the subiculum. The results indicate that a subset of reuniens cells can directly coordinate activity in mPFC and hippocampus. Cells with collaterals in the hippocampus–reuniens–mPFC network may be important for the systems consolidation of memory traces and for theta synchronization during exploratory behavior.", "publicationTitle": "Brain Structure and Function", "publisher": "", "place": "", "date": "2014-05-01", "volume": "219", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "911-929", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Brain Struct Funct", "DOI": "10.1007/s00429-013-0543-5", "citationKey": "VarelaKumarYangEtAl14", "url": "https://doi.org/10.1007/s00429-013-0543-5", "accessDate": "2026-10-07T19:14:38Z", "PMID": "", "PMCID": "", "ISSN": "1863-2661", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "Springer Link", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Hippocampus", "type": 1 }, { "tag": "Memory consolidation", "type": 1 }, { "tag": "Prefrontal cortex", "type": 1 }, { "tag": "Reuniens", "type": 1 }, { "tag": "Thalamus", "type": 1 }, { "tag": "Theta", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2026-10-07T19:14:38Z", "dateModified": "2026-10-07T19:14:38Z" } }, { "key": "UPU3W7AE", "version": 97794, "library": { "type": "group", "id": 340666, "name": "CCNLab", "links": { "alternate": { "href": "https://www.zotero.org/groups/ccnlab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/340666/items/UPU3W7AE", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/ccnlab/items/UPU3W7AE", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/340666/items/J5ICXMJA", "type": "application/json" } }, "meta": { "createdByUser": { "id": 2407002, "username": "thazy", "name": "Thomas E. Hazy, MD", "links": { "alternate": { "href": "https://www.zotero.org/thazy", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "UPU3W7AE", "version": 97794, "parentItem": "J5ICXMJA", "itemType": "attachment", "linkMode": "imported_url", "title": "Full Text PDF", "accessDate": "2026-10-07T19:07:07Z", "url": "https://www.nature.com/articles/s41593-025-01883-9.pdf", "note": "", "contentType": "application/pdf", "charset": "", "filename": "ButolaHernandez-FraustoBlankvoortEtAl25.pdf", "md5": "a5aa965a53a8e28abd3727884984409b", "mtime": 1791400027302, "tags": [], "relations": {}, "dateAdded": "2026-10-07T19:07:07Z", "dateModified": "2026-10-07T19:07:07Z" } }, { "key": "J5ICXMJA", "version": 97793, "library": { "type": "group", "id": 340666, "name": "CCNLab", "links": { "alternate": { "href": "https://www.zotero.org/groups/ccnlab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/340666/items/J5ICXMJA", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/ccnlab/items/J5ICXMJA", "type": "text/html" } }, "meta": { "createdByUser": { "id": 2407002, "username": "thazy", "name": "Thomas E. Hazy, MD", "links": { "alternate": { "href": "https://www.zotero.org/thazy", "type": "text/html" } } }, "creatorSummary": "Butola et al.", "parsedDate": "2025-04", "numChildren": 1 }, "data": { "key": "J5ICXMJA", "version": 97793, "itemType": "journalArticle", "title": "Hippocampus shapes entorhinal cortical output through a direct feedback circuit", "creators": [ { "creatorType": "author", "firstName": "Tanvi", "lastName": "Butola" }, { "creatorType": "author", "firstName": "Melissa", "lastName": "Hernández-Frausto" }, { "creatorType": "author", "firstName": "Stefan", "lastName": "Blankvoort" }, { "creatorType": "author", "firstName": "Marcus Sandbukt", "lastName": "Flatset" }, { "creatorType": "author", "firstName": "Lulu", "lastName": "Peng" }, { "creatorType": "author", "firstName": "Ariel", "lastName": "Hairston" }, { "creatorType": "author", "firstName": "Cara Deanna", "lastName": "Johnson" }, { "creatorType": "author", "firstName": "Margot", "lastName": "Elmaleh" }, { "creatorType": "author", "firstName": "Amanda", "lastName": "Amilcar" }, { "creatorType": "author", "firstName": "Fabliha", "lastName": "Hussain" }, { "creatorType": "author", "firstName": "Claudia", "lastName": "Clopath" }, { "creatorType": "author", "firstName": "Clifford", "lastName": "Kentros" }, { "creatorType": "author", "firstName": "Jayeeta", "lastName": "Basu" } ], "abstractNote": "Our brains integrate sensory, cognitive and internal state information with memories to extract behavioral relevance. Cortico–hippocampal interactions likely mediate this interplay, but underlying circuit mechanisms remain elusive. Unlike the entorhinal cortex-to-hippocampus pathway, we know little about the organization and function of the hippocampus-to-cortex feedback circuit. Here we report in mice, two functionally distinct parallel hippocampus-to-entorhinal cortex feedback pathways: the canonical disynaptic route via layer 5 and a novel monosynaptic input to layer 2/3. Circuit mapping reveals that hippocampal input predominantly drives excitation in layer 5 but feed-forward inhibition in layer 2/3. Upon repetitive pairing with cortical layer 1 inputs, hippocampal inputs undergo homosynaptic potentiation in layer 5, but induce heterosynaptic plasticity and spike output in layer 2/3. Behaviorally, hippocampal inputs to layer 5 and layer 2/3 support object memory encoding versus recall, respectively. Two-photon imaging during navigation reveals hippocampal suppression reduces spatially tuned cortical axonal activity. We present a model, where hippocampal feedback could iteratively shape ongoing cortical processing.", "publicationTitle": "Nature Neuroscience", "publisher": "Nature Publishing Group", "place": "", "date": "2025-04", "volume": "28", "issue": "4", "section": "", "partNumber": "", "partTitle": "", "pages": "811-822", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Nat Neurosci", "DOI": "10.1038/s41593-025-01883-9", "citationKey": "ButolaHernandez-FraustoBlankvoortEtAl25", "url": "https://www.nature.com/articles/s41593-025-01883-9", "accessDate": "2026-10-07T19:07:01Z", "PMID": "", "PMCID": "", "ISSN": "1546-1726", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "www.nature.com", "callNumber": "", "rights": "2025 The Author(s), under exclusive licence to Springer Nature America, Inc.", "extra": "", "tags": [ { "tag": "Hippocampus", "type": 1 }, { "tag": "Inhibition–excitation balance", "type": 1 }, { "tag": "Long-term potentiation", "type": 1 }, { "tag": "Neural circuits", "type": 1 }, { "tag": "Sensory processing", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2026-10-07T19:07:01Z", "dateModified": "2026-10-07T19:07:01Z" } }, { "key": "RMP2IFAD", "version": 97789, "library": { "type": "group", "id": 340666, "name": "CCNLab", "links": { "alternate": { "href": "https://www.zotero.org/groups/ccnlab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/340666/items/RMP2IFAD", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/ccnlab/items/RMP2IFAD", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/340666/items/HWREAK28", "type": "application/json" } }, "meta": { "createdByUser": { "id": 2407002, "username": "thazy", "name": "Thomas E. Hazy, MD", "links": { "alternate": { "href": "https://www.zotero.org/thazy", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "RMP2IFAD", "version": 97789, "parentItem": "HWREAK28", "itemType": "attachment", "linkMode": "imported_url", "title": "Full Text PDF", "accessDate": "2026-10-07T00:16:30Z", "url": "https://www.nature.com/articles/s41467-017-01912-7.pdf", "note": "", "contentType": "application/pdf", "charset": "", "filename": "ChangBaoTsao17.pdf", "md5": "8662ce721dec01e90273e4f868333d3d", "mtime": 1791332190822, "tags": [], "relations": {}, "dateAdded": "2026-10-07T00:16:30Z", "dateModified": "2026-10-07T00:16:30Z" } }, { "key": "HWREAK28", "version": 97787, "library": { "type": "group", "id": 340666, "name": "CCNLab", "links": { "alternate": { "href": "https://www.zotero.org/groups/ccnlab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/340666/items/HWREAK28", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/ccnlab/items/HWREAK28", "type": "text/html" } }, "meta": { "createdByUser": { "id": 2407002, "username": "thazy", "name": "Thomas E. Hazy, MD", "links": { "alternate": { "href": "https://www.zotero.org/thazy", "type": "text/html" } } }, "creatorSummary": "Chang et al.", "parsedDate": "2017-12-12", "numChildren": 1 }, "data": { "key": "HWREAK28", "version": 97787, "itemType": "journalArticle", "title": "The representation of colored objects in macaque color patches", "creators": [ { "creatorType": "author", "firstName": "Le", "lastName": "Chang" }, { "creatorType": "author", "firstName": "Pinglei", "lastName": "Bao" }, { "creatorType": "author", "firstName": "Doris Y.", "lastName": "Tsao" } ], "abstractNote": "An important question about color vision is how does the brain represent the color of an object? The recent discovery of “color patches” in macaque inferotemporal (IT) cortex, the part of the brain responsible for object recognition, makes this problem experimentally tractable. Here we recorded neurons in three color patches, middle color patch CLC (central lateral color patch), and two anterior color patches ALC (anterior lateral color patch) and AMC (anterior medial color patch), while presenting images of objects systematically varied in hue. We found that all three patches contain high concentrations of hue-selective cells, and that the three patches use distinct computational strategies to represent colored objects: while all three patches multiplex hue and shape information, shape-invariant hue information is much stronger in anterior color patches ALC/AMC than CLC. Furthermore, hue and object shape specifically for primate faces/bodies are over-represented in AMC, but not in the other two patches.", "publicationTitle": "Nature Communications", "publisher": "Nature Publishing Group", "place": "", "date": "2017-12-12", "volume": "8", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "2064", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Nat Commun", "DOI": "10.1038/s41467-017-01912-7", "citationKey": "ChangBaoTsao17", "url": "https://www.nature.com/articles/s41467-017-01912-7", "accessDate": "2026-10-07T00:16:27Z", "PMID": "", "PMCID": "", "ISSN": "2041-1723", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "www.nature.com", "callNumber": "", "rights": "2017 The Author(s)", "extra": "", "tags": [ { "tag": "Colour vision", "type": 1 }, { "tag": "Sensory processing", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2026-10-07T00:16:27Z", "dateModified": "2026-10-07T00:16:27Z" } }, { "key": "IS568R9P", "version": 97785, "library": { "type": "group", "id": 340666, "name": "CCNLab", "links": { "alternate": { "href": "https://www.zotero.org/groups/ccnlab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/340666/items/IS568R9P", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/ccnlab/items/IS568R9P", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/340666/items/2FPWKGNQ", "type": "application/json" } }, "meta": { "createdByUser": { "id": 2407002, "username": "thazy", "name": "Thomas E. Hazy, MD", "links": { "alternate": { "href": "https://www.zotero.org/thazy", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "IS568R9P", "version": 97785, "parentItem": "2FPWKGNQ", "itemType": "attachment", "linkMode": "imported_url", "title": "Full Text PDF", "accessDate": "2026-10-06T20:57:38Z", "url": "https://www.nature.com/articles/s41583-024-00893-z.pdf", "note": "", "contentType": "application/pdf", "charset": "", "filename": "BeinNiv25.pdf", "md5": "7d389e45f8451e27c505d9f10604c0e8", "mtime": 1791320258671, "tags": [], "relations": {}, "dateAdded": "2026-10-06T20:57:38Z", "dateModified": "2026-10-06T20:57:38Z" } }, { "key": "2FPWKGNQ", "version": 97783, "library": { "type": "group", "id": 340666, "name": "CCNLab", "links": { "alternate": { "href": "https://www.zotero.org/groups/ccnlab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/340666/items/2FPWKGNQ", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/ccnlab/items/2FPWKGNQ", "type": "text/html" } }, "meta": { "createdByUser": { "id": 2407002, "username": "thazy", "name": "Thomas E. Hazy, MD", "links": { "alternate": { "href": "https://www.zotero.org/thazy", "type": "text/html" } } }, "creatorSummary": "Bein and Niv", "parsedDate": "2025-03", "numChildren": 1 }, "data": { "key": "2FPWKGNQ", "version": 97783, "itemType": "journalArticle", "title": "Schemas, reinforcement learning and the medial prefrontal cortex", "creators": [ { "creatorType": "author", "firstName": "Oded", "lastName": "Bein" }, { "creatorType": "author", "firstName": "Yael", "lastName": "Niv" } ], "abstractNote": "Schemas are rich and complex knowledge structures about the typical unfolding of events in a context; for example, a schema of a dinner at a restaurant. In this Perspective, we suggest that reinforcement learning (RL), a computational theory of learning the structure of the world and relevant goal-oriented behaviour, underlies schema learning. We synthesize literature about schemas and RL to offer that three RL principles might govern the learning of schemas: learning via prediction errors, constructing hierarchical knowledge using hierarchical RL, and dimensionality reduction through learning a simplified and abstract representation of the world. We then suggest that the orbitomedial prefrontal cortex is involved in both schemas and RL due to its involvement in dimensionality reduction and in guiding memory reactivation through interactions with posterior brain regions. Last, we hypothesize that the amount of dimensionality reduction might underlie gradients of involvement along the ventral–dorsal and posterior–anterior axes of the orbitomedial prefrontal cortex. More specific and detailed representations might engage the ventral and posterior parts, whereas abstraction might shift representations towards the dorsal and anterior parts of the medial prefrontal cortex.", "publicationTitle": "Nature Reviews Neuroscience", "publisher": "Nature Publishing Group", "place": "", "date": "2025-03", "volume": "26", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "141-157", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Nat. Rev. Neurosci.", "DOI": "10.1038/s41583-024-00893-z", "citationKey": "BeinNiv25", "url": "https://www.nature.com/articles/s41583-024-00893-z", "accessDate": "2026-10-06T20:57:34Z", "PMID": "", "PMCID": "", "ISSN": "1471-0048", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "www.nature.com", "callNumber": "", "rights": "2025 Springer Nature Limited", "extra": "", "tags": [ { "tag": "Cognitive neuroscience", "type": 1 }, { "tag": "Human behaviour", "type": 1 }, { "tag": "Learning algorithms", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2026-10-06T20:57:34Z", "dateModified": "2026-10-06T20:57:34Z" } }, { "key": "M2AGLPGS", "version": 97781, "library": { "type": "group", "id": 340666, "name": "CCNLab", "links": { "alternate": { "href": "https://www.zotero.org/groups/ccnlab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/340666/items/M2AGLPGS", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/ccnlab/items/M2AGLPGS", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/340666/items/6M7ZYGRT", "type": "application/json" } }, "meta": { "createdByUser": { "id": 2406800, "username": "rcoreilly", "name": "Randall C. 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