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The model assumes that higher cortical levels modulate the temporal dynamics of lower levels, correcting their predictions of dynamics using prediction errors. As a result, lower levels form representations that encode sequences at shorter timescales (e.g., a single step) while higher levels form representations that encode sequences at longer timescales (e.g., an entire sequence). We tested this model using a two-level neural network, where the top-down modulation creates low-dimensional combinations of a set of learned temporal dynamics to explain input sequences. When trained on natural videos, the lower-level model neurons developed space-time receptive fields similar to those of simple cells in the primary visual cortex while the higher-level responses spanned longer timescales, mimicking temporal response hierarchies in the cortex. Additionally, the network\u2019s hierarchical sequence representation exhibited both predictive and postdictive effects resembling those observed in visual motion processing in humans (e.g., in the flash-lag illusion). When coupled with an associative memory emulating the role of the hippocampus, the model allowed episodic memories to be stored and retrieved, supporting cue-triggered recall of an input sequence similar to activity recall in the visual cortex. When extended to three hierarchical levels, the model learned progressively more abstract temporal representations along the hierarchy. Taken together, our results suggest that cortical processing and learning of sequences can be interpreted as dynamic predictive coding based on a hierarchical spatiotemporal generative model of the visual world.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1011801","type":"journal-article","created":{"date-parts":[[2024,2,8]],"date-time":"2024-02-08T18:53:07Z","timestamp":1707418387000},"page":"e1011801","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":10,"title":["Dynamic predictive coding: A model of hierarchical sequence learning and prediction in the neocortex"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-7318-8833","authenticated-orcid":true,"given":"Linxing Preston","family":"Jiang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0682-8952","authenticated-orcid":true,"given":"Rajesh P. 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Predictive Coding Theories of Cortical Function. Oxford Research Encyclopedia of Neuroscience. 2022;.","DOI":"10.1093\/acrefore\/9780190264086.013.328"},{"key":"pcbi.1011801.ref015","unstructured":"Ha D, Dai AM, Le QV. HyperNetworks. In: 5th International Conference on Learning Representations (ICLR 2017); 2017."},{"issue":"2","key":"pcbi.1011801.ref016","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1038\/s41583-019-0253-y","article-title":"Mechanisms underlying gain modulation in the cortex","volume":"21","author":"KA Ferguson","year":"2020","journal-title":"Nature Reviews Neuroscience"},{"issue":"6","key":"pcbi.1011801.ref017","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1038\/s41593-021-00824-6","article-title":"Computational models link cellular mechanisms of neuromodulation to large-scale neural dynamics","volume":"24","author":"JM Shine","year":"2021","journal-title":"Nature Neuroscience"},{"key":"pcbi.1011801.ref018","doi-asserted-by":"crossref","first-page":"2315","DOI":"10.1098\/rspb.1998.0577","article-title":"Independent component analysis of natural image sequences yields spatio-temporal filters similar to simple cells in primary visual cortex","volume":"265","author":"JH van Hateren","year":"1998","journal-title":"Proceedings of the Royal Society of London Series B: Biological Sciences"},{"key":"pcbi.1011801.ref019","doi-asserted-by":"crossref","unstructured":"Kayser C, Einh\u00e4user W, D\u00fcmmer O, K\u00f6nig P, K\u00f6rding K. Extracting Slow Subspaces from Natural Videos Leads to Complex Cells. In: International Conference on Artificial Neural Networks. Lecture Notes in Computer Science; 2001. p. 1075\u20131080.","DOI":"10.1007\/3-540-44668-0_149"},{"issue":"7","key":"pcbi.1011801.ref020","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1167\/2.7.130","article-title":"Sparse coding of time-varying natural images","volume":"2","author":"BA Olshausen","year":"2002","journal-title":"Journal of Vision"},{"issue":"4","key":"pcbi.1011801.ref021","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1162\/089976602317318938","article-title":"Slow Feature Analysis: Unsupervised Learning of Invariances","volume":"14","author":"L Wiskott","year":"2002","journal-title":"Neural Computation"},{"issue":"6","key":"pcbi.1011801.ref022","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1167\/5.6.9","article-title":"Slow feature analysis yields a rich repertoire of complex cell properties","volume":"5","author":"P Berkes","year":"2005","journal-title":"Journal of Vision"},{"key":"pcbi.1011801.ref023","doi-asserted-by":"crossref","first-page":"e31557","DOI":"10.7554\/eLife.31557","article-title":"Sensory cortex is optimized for prediction of future input","volume":"7","author":"Y Singer","year":"2018","journal-title":"eLife"},{"journal-title":"Hierarchical temporal prediction captures motion processing from retina to higher visual cortex","year":"2019","author":"Y Singer","key":"pcbi.1011801.ref024"},{"issue":"10","key":"pcbi.1011801.ref025","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1016\/0166-2236(95)94496-R","article-title":"Receptive-field dynamics in the central visual pathways","volume":"18","author":"GC DeAngelis","year":"1995","journal-title":"Trends in Neurosciences"},{"issue":"5460","key":"pcbi.1011801.ref026","doi-asserted-by":"crossref","first-page":"2036","DOI":"10.1126\/science.287.5460.2036","article-title":"Motion Integration and Postdiction in Visual Awareness","volume":"287","author":"DM Eagleman","year":"2000","journal-title":"Science"},{"issue":"7","key":"pcbi.1011801.ref027","doi-asserted-by":"crossref","first-page":"872","DOI":"10.1016\/j.visres.2007.12.019","article-title":"Interpolation and extrapolation on the path of apparent motion","volume":"48","author":"H Hogendoorn","year":"2008","journal-title":"Vision Research"},{"key":"pcbi.1011801.ref028","doi-asserted-by":"crossref","DOI":"10.3389\/fpsyg.2014.00196","article-title":"Postdiction: its implications on visual awareness, hindsight, and sense of agency","volume":"5","author":"S Shimojo","year":"2014","journal-title":"Frontiers in Psychology"},{"issue":"2","key":"pcbi.1011801.ref029","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.tics.2021.11.003","article-title":"Perception in real-time: predicting the present, reconstructing the past","volume":"26","author":"H Hogendoorn","year":"2022","journal-title":"Trends in Cognitive Sciences"},{"issue":"6487","key":"pcbi.1011801.ref030","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1038\/370256b0","article-title":"Motion extrapolation in catching","volume":"370","author":"R Nijhawan","year":"1994","journal-title":"Nature"},{"issue":"2","key":"pcbi.1011801.ref031","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1017\/S0140525X08003804","article-title":"Visual prediction: Psychophysics and neurophysiology of compensation for time delays","volume":"31","author":"R Nijhawan","year":"2008","journal-title":"Behavioral and Brain Sciences"},{"issue":"1","key":"pcbi.1011801.ref032","doi-asserted-by":"crossref","first-page":"15276","DOI":"10.1038\/ncomms15276","article-title":"Time-compressed preplay of anticipated events in human primary visual cortex","volume":"8","author":"M Ekman","year":"2017","journal-title":"Nature Communications"},{"issue":"45","key":"pcbi.1011801.ref033","doi-asserted-by":"crossref","first-page":"9648","DOI":"10.1523\/JNEUROSCI.0884-18.2018","article-title":"Feature-Specific Awake Reactivation in Human V1 after Visual Training","volume":"38","author":"JW Bang","year":"2018","journal-title":"Journal of Neuroscience"},{"issue":"1","key":"pcbi.1011801.ref034","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1007\/s11427-020-1726-5","article-title":"Cue-triggered activity replay in human early visual cortex","volume":"64","author":"J Lu","year":"2021","journal-title":"Science China Life Sciences"},{"issue":"47","key":"pcbi.1011801.ref035","doi-asserted-by":"crossref","first-page":"19450","DOI":"10.1073\/pnas.1212059109","article-title":"Image sequence reactivation in awake V4 networks","volume":"109","author":"SL Eagleman","year":"2012","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"pcbi.1011801.ref036","unstructured":"Jiang LP, Rao RPN. Dynamic Predictive Coding Explains Both Prediction and Postdiction in Visual Motion Perception. Proceedings of the Annual Meeting of the Cognitive Science Society. 2023;45(45)."},{"issue":"10","key":"pcbi.1011801.ref037","doi-asserted-by":"crossref","first-page":"e1000532","DOI":"10.1371\/journal.pcbi.1000532","article-title":"Towards a Mathematical Theory of Cortical Micro-circuits","volume":"5","author":"D George","year":"2009","journal-title":"PLOS Computational Biology"},{"issue":"6583","key":"pcbi.1011801.ref038","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1038\/381607a0","article-title":"Emergence of simple-cell receptive field properties by learning a sparse code for natural images","volume":"381","author":"BA Olshausen","year":"1996","journal-title":"Nature"},{"issue":"10","key":"pcbi.1011801.ref039","doi-asserted-by":"crossref","first-page":"1059","DOI":"10.1093\/cercor\/bhh065","article-title":"Top-down Dendritic Input Increases the Gain of Layer 5 Pyramidal Neurons","volume":"14","author":"ME Larkum","year":"2004","journal-title":"Cerebral Cortex"},{"issue":"11","key":"pcbi.1011801.ref040","doi-asserted-by":"crossref","first-page":"1963","DOI":"10.1016\/S0042-6989(98)00279-X","article-title":"An optimal estimation approach to visual perception and learning","volume":"39","author":"RPN Rao","year":"1999","journal-title":"Vision Research"},{"issue":"3","key":"pcbi.1011801.ref041","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1088\/0954-898X_6_3_003","article-title":"Statistics of natural time-varying images","volume":"6","author":"DW Dong","year":"1995","journal-title":"Network: Computation in Neural Systems"},{"issue":"3","key":"pcbi.1011801.ref042","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1113\/jphysiol.1959.sp006308","article-title":"Receptive fields of single neurones in the cat\u2019s striate cortex","volume":"148","author":"DH Hubel","year":"1959","journal-title":"The Journal of Physiology"},{"issue":"2","key":"pcbi.1011801.ref043","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1207\/s15516709cog2802_2","article-title":"Reverse correlation in neurophysiology","volume":"28","author":"D Ringach","year":"2004","journal-title":"Cognitive Science"},{"issue":"5","key":"pcbi.1011801.ref044","doi-asserted-by":"crossref","first-page":"1560","DOI":"10.1523\/JNEUROSCI.4661-12.2012","article-title":"Natural versus Synthetic Stimuli for Estimating Receptive Field Models: A Comparison of Predictive Robustness","volume":"32","author":"V Talebi","year":"2012","journal-title":"Journal of Neuroscience"},{"key":"pcbi.1011801.ref045","unstructured":"Srivastava N, Mansimov E, Salakhudinov R. Unsupervised Learning of Video Representations using LSTMs. In: Proceedings of the 32nd International Conference on Machine Learning; 2015. p. 843\u2013852. Available from: https:\/\/proceedings.mlr.press\/v37\/srivastava15.html."},{"volume-title":"Machine learning: a probabilistic perspective","year":"2013","author":"KP Murphy","key":"pcbi.1011801.ref046"},{"issue":"6","key":"pcbi.1011801.ref047","doi-asserted-by":"crossref","first-page":"1194","DOI":"10.1016\/j.neuron.2020.09.024","article-title":"Opposing Influence of Top-down and Bottom-up Input on Excitatory Layer 2\/3 Neurons in Mouse Primary Visual Cortex","volume":"108","author":"R Jordan","year":"2020","journal-title":"Neuron"},{"journal-title":"Probabilistic forward replay of anticipated stimulus sequences in human primary visual cortex and hippocampus","year":"2022","author":"M Ekman","key":"pcbi.1011801.ref048"},{"key":"pcbi.1011801.ref049","unstructured":"Rao RPN. Correlates of Attention in a Model of Dynamic Visual Recognition. In: Advances in Neural Information Processing Systems; 1998.Available from: http:\/\/papers.nips.cc\/paper\/1416-correlates-of-attention-in-a-model-of-dynamic-visual-recognition.pdf."},{"issue":"9","key":"pcbi.1011801.ref050","doi-asserted-by":"crossref","first-page":"795","DOI":"10.1002\/hipo.20205","article-title":"Evolution of declarative memory","volume":"16","author":"JR Manns","year":"2006","journal-title":"Hippocampus"},{"issue":"4","key":"pcbi.1011801.ref051","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1016\/S0896-6273(02)00830-9","article-title":"The Human Hippocampus and Spatial and Episodic Memory","volume":"35","author":"N Burgess","year":"2002","journal-title":"Neuron"},{"issue":"1","key":"pcbi.1011801.ref052","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1146\/annurev.psych.53.100901.135114","article-title":"Episodic memory: From mind to brain","volume":"53","author":"E Tulving","year":"2002","journal-title":"Annual Review of Psychology"},{"issue":"12","key":"pcbi.1011801.ref053","doi-asserted-by":"crossref","first-page":"1190","DOI":"10.1002\/hipo.23132","article-title":"Episodic memory: Neuronal codes for what, where, and when","volume":"29","author":"J Sugar","year":"2019","journal-title":"Hippocampus"},{"issue":"5898","key":"pcbi.1011801.ref054","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1126\/science.1164685","article-title":"Internally Generated Reactivation of Single Neurons in Human Hippocampus During Free Recall","volume":"322","author":"H Gelbard-Sagiv","year":"2008","journal-title":"Science"},{"issue":"22","key":"pcbi.1011801.ref055","doi-asserted-by":"crossref","first-page":"7493","DOI":"10.1523\/JNEUROSCI.0805-14.2014","article-title":"Reinstatement of Associative Memories in Early Visual Cortex Is Signaled by the Hippocampus","volume":"34","author":"SE Bosch","year":"2014","journal-title":"Journal of Neuroscience"},{"issue":"5","key":"pcbi.1011801.ref056","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1038\/nn.4284","article-title":"Linking pattern completion in the hippocampus to predictive coding in visual cortex","volume":"19","author":"NC Hindy","year":"2016","journal-title":"Nature Neuroscience"},{"key":"pcbi.1011801.ref057","doi-asserted-by":"crossref","first-page":"101821","DOI":"10.1016\/j.pneurobio.2020.101821","article-title":"Prediction and memory: A predictive coding account","volume":"192","author":"HC Barron","year":"2020","journal-title":"Progress in Neurobiology"},{"key":"pcbi.1011801.ref058","unstructured":"Salvatori T, Song Y, Hong Y, Sha L, Frieder S, Xu Z, et al. Associative Memories via Predictive Coding. In: Advances in Neural Information Processing Systems. vol. 34; 2021. p. 3874\u20133886."},{"issue":"1","key":"pcbi.1011801.ref059","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1023\/A:1007469218079","article-title":"The Hierarchical Hidden Markov Model: Analysis and Applications","volume":"32","author":"S Fine","year":"1998","journal-title":"Machine Learning"},{"issue":"30","key":"pcbi.1011801.ref060","doi-asserted-by":"crossref","first-page":"5698","DOI":"10.1523\/JNEUROSCI.0275-20.2020","article-title":"Motion Extrapolation in Visual Processing: Lessons from 25 Years of Flash-Lag Debate","volume":"40","author":"H Hogendoorn","year":"2020","journal-title":"Journal of Neuroscience"},{"key":"pcbi.1011801.ref061","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1016\/0166-2236(83)90190-X","article-title":"Object vision and spatial vision: two cortical pathways","volume":"6","author":"M Mishkin","year":"1983","journal-title":"Trends in Neurosciences"},{"issue":"7474","key":"pcbi.1011801.ref062","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1038\/nature12742","article-title":"Context-dependent computation by recurrent dynamics in prefrontal cortex","volume":"503","author":"V Mante","year":"2013","journal-title":"Nature"},{"issue":"12","key":"pcbi.1011801.ref063","doi-asserted-by":"crossref","first-page":"1774","DOI":"10.1038\/s41593-018-0276-0","article-title":"Motor primitives in space and time via targeted gain modulation in cortical networks","volume":"21","author":"JP Stroud","year":"2018","journal-title":"Nature Neuroscience"},{"issue":"44","key":"pcbi.1011801.ref064","doi-asserted-by":"crossref","first-page":"E10467","DOI":"10.1073\/pnas.1803839115","article-title":"Alleviating catastrophic forgetting using context-dependent gating and synaptic stabilization","volume":"115","author":"NY Masse","year":"2018","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"3","key":"pcbi.1011801.ref065","doi-asserted-by":"crossref","first-page":"e1004090","DOI":"10.1371\/journal.pcbi.1004090","article-title":"Physiology of Layer 5 Pyramidal Neurons in Mouse Primary Visual Cortex: Coincidence Detection through Bursting","volume":"11","author":"AS Shai","year":"2015","journal-title":"PLOS Computational Biology"},{"issue":"6319","key":"pcbi.1011801.ref066","doi-asserted-by":"crossref","first-page":"1587","DOI":"10.1126\/science.aah6066","article-title":"Active cortical dendrites modulate perception","volume":"354","author":"N Takahashi","year":"2016","journal-title":"Science"},{"key":"pcbi.1011801.ref067","unstructured":"Galanti T, Wolf L. On the Modularity of Hypernetworks. In: Advances in Neural Information Processing Systems. vol. 33. Curran Associates, Inc.; 2020. p. 10409\u201310419."},{"issue":"1205","key":"pcbi.1011801.ref068","first-page":"427","article-title":"Predictive coding: a fresh view of inhibition in the retina","volume":"216","author":"MV Srinivasan","year":"1982","journal-title":"Proceedings of the Royal Society of London Series B Biological Sciences"},{"issue":"1","key":"pcbi.1011801.ref069","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1038\/s42256-021-00430-y","article-title":"Neurons learn by predicting future activity","volume":"4","author":"A Luczak","year":"2022","journal-title":"Nature Machine Intelligence"},{"issue":"7553","key":"pcbi.1011801.ref070","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"Y LeCun","year":"2015","journal-title":"Nature"},{"key":"pcbi.1011801.ref071","unstructured":"Lotter W, Kreiman G, Cox DD. Deep predictive coding networks for video prediction and unsupervised learning. In: International Conference on Learning Representations; 2017. Available from: https:\/\/openreview.net\/forum?id=B1ewdt9xe."},{"issue":"4","key":"pcbi.1011801.ref072","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1038\/s42256-020-0170-9","article-title":"A neural network trained for prediction mimics diverse features of biological neurons and perception","volume":"2","author":"W Lotter","year":"2020","journal-title":"Nature Machine Intelligence"},{"issue":"1","key":"pcbi.1011801.ref073","doi-asserted-by":"crossref","first-page":"4448","DOI":"10.1038\/s41467-021-24456-3","article-title":"Temporal stability of stimulus representation increases along rodent visual cortical hierarchies","volume":"12","author":"E Piasini","year":"2021","journal-title":"Nature Communications"},{"key":"pcbi.1011801.ref074","doi-asserted-by":"crossref","DOI":"10.1126\/sciadv.abc4530","article-title":"Learning hierarchical sequence representations across human cortex and hippocampus","volume":"7","author":"S Henin","year":"2021","journal-title":"Science Advances"},{"issue":"2","key":"pcbi.1011801.ref075","doi-asserted-by":"crossref","first-page":"419","DOI":"10.1016\/j.neuron.2015.09.008","article-title":"A Large-Scale Circuit Mechanism for Hierarchical Dynamical Processing in the Primate Cortex","volume":"88","author":"R Chaudhuri","year":"2015","journal-title":"Neuron"},{"issue":"1","key":"pcbi.1011801.ref076","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1016\/j.neuron.2018.02.031","article-title":"Inter-areal Balanced Amplification Enhances Signal Propagation in a Large-Scale Circuit Model of the Primate Cortex","volume":"98","author":"MR Joglekar","year":"2018","journal-title":"Neuron"},{"issue":"4","key":"pcbi.1011801.ref077","doi-asserted-by":"crossref","first-page":"043077","DOI":"10.1103\/PhysRevResearch.3.043077","article-title":"Microscopic theory of intrinsic timescales in spiking neural networks","volume":"3","author":"A van Meegen","year":"2021","journal-title":"Physical Review Research"},{"issue":"11","key":"pcbi.1011801.ref078","doi-asserted-by":"crossref","first-page":"e1000209","DOI":"10.1371\/journal.pcbi.1000209","article-title":"A Hierarchy of Time-Scales and the Brain","volume":"4","author":"SJ Kiebel","year":"2008","journal-title":"PLOS Computational Biology"},{"key":"pcbi.1011801.ref079","doi-asserted-by":"crossref","first-page":"e61277","DOI":"10.7554\/eLife.61277","article-title":"Neuronal timescales are functionally dynamic and shaped by cortical microarchitecture","volume":"9","author":"R Gao","year":"2020","journal-title":"eLife"},{"issue":"6","key":"pcbi.1011801.ref080","doi-asserted-by":"crossref","first-page":"1243","DOI":"10.1162\/08997660152002843","article-title":"Optimal Smoothing in Visual Motion Perception","volume":"13","author":"RPN Rao","year":"2001","journal-title":"Neural Computation"},{"issue":"1","key":"pcbi.1011801.ref081","doi-asserted-by":"crossref","first-page":"e1005068","DOI":"10.1371\/journal.pcbi.1005068","article-title":"The Flash-Lag Effect as a Motion-Based Predictive Shift","volume":"13","author":"MA Khoei","year":"2017","journal-title":"PLOS Computational Biology"},{"issue":"18","key":"pcbi.1011801.ref082","doi-asserted-by":"crossref","first-page":"3996","DOI":"10.1016\/j.cub.2021.06.079","article-title":"The spatiotemporal organization of experience dictates hippocampal involvement in primary visual cortical plasticity","volume":"31","author":"PSB Finnie","year":"2021","journal-title":"Current Biology"},{"issue":"1","key":"pcbi.1011801.ref083","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1146\/annurev-neuro-072116-031538","article-title":"Replay Comes of Age","volume":"40","author":"DJ Foster","year":"2017","journal-title":"Annual Review of Neuroscience"},{"issue":"1456","key":"pcbi.1011801.ref084","doi-asserted-by":"crossref","first-page":"815","DOI":"10.1098\/rstb.2005.1622","article-title":"A theory of cortical responses","volume":"360","author":"K Friston","year":"2005","journal-title":"Philosophical Transactions of the Royal Society B: Biological Sciences"},{"key":"pcbi.1011801.ref085","unstructured":"Linderman S, Johnson M, Miller A, Adams R, Blei D, Paninski L. Bayesian Learning and Inference in Recurrent Switching Linear Dynamical Systems. In: Proceedings of the 20th International Conference on Artificial Intelligence and Statistics. PMLR; 2017. p. 914\u2013922. Available from: https:\/\/proceedings.mlr.press\/v54\/linderman17a.html."},{"issue":"1","key":"pcbi.1011801.ref086","first-page":"1","article-title":"Active Predictive Coding: A Unifying Neural Model for Active Perception, Compositional Learning, and Hierarchical Planning","volume":"36","author":"RPN Rao","year":"2024","journal-title":"Neural Computation"},{"issue":"4","key":"pcbi.1011801.ref087","doi-asserted-by":"crossref","first-page":"766","DOI":"10.1016\/j.neuron.2016.09.057","article-title":"Mismatch Receptive Fields in Mouse Visual Cortex","volume":"92","author":"P Zmarz","year":"2016","journal-title":"Neuron"},{"key":"pcbi.1011801.ref088","unstructured":"Attias H. Planning by Probabilistic Inference. In: International Workshop on Artificial Intelligence and Statistics; 2003. p. 9\u201316. Available from: http:\/\/proceedings.mlr.press\/r4\/attias03a.html."},{"key":"pcbi.1011801.ref089","unstructured":"Verma D, Rao RP. Goal-Based Imitation as Probabilistic Inference over Graphical Models. Advances in Neural Information Processing Systems. 2005;18."},{"key":"pcbi.1011801.ref090","doi-asserted-by":"crossref","unstructured":"Verma D, Rao RPN. Planning and Acting in Uncertain Environments using Probabilistic Inference. In: 2006 IEEE\/RSJ International Conference on Intelligent Robots and Systems; 2006. p. 2382\u20132387.","DOI":"10.1109\/IROS.2006.281675"},{"issue":"10","key":"pcbi.1011801.ref091","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1016\/j.tics.2012.08.006","article-title":"Planning as inference","volume":"16","author":"M Botvinick","year":"2012","journal-title":"Trends in Cognitive Sciences"},{"key":"pcbi.1011801.ref092","unstructured":"Levine S. Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review. arXiv:180500909 [cs, stat]. 2018;."},{"key":"pcbi.1011801.ref093","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.cobeha.2020.02.017","article-title":"Learning Structures: Predictive Representations, Replay, and Generalization","volume":"32","author":"I Momennejad","year":"2020","journal-title":"Current Opinion in Behavioral Sciences"},{"issue":"11","key":"pcbi.1011801.ref094","doi-asserted-by":"crossref","first-page":"1643","DOI":"10.1038\/nn.4650","article-title":"The hippocampus as a predictive map","volume":"20","author":"KL Stachenfeld","year":"2017","journal-title":"Nature Neuroscience"},{"issue":"2","key":"pcbi.1011801.ref095","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1088\/0954-898X_6_2_003","article-title":"Temporal decorrelation: a theory of lagged and nonlagged responses in the lateral geniculate nucleus","volume":"6","author":"DW Dong","year":"1995","journal-title":"Network: Computation in neural systems"}],"updated-by":[{"updated":{"date-parts":[[2024,2,21]],"date-time":"2024-02-21T00:00:00Z","timestamp":1708473600000},"DOI":"10.1371\/journal.pcbi.1011801","type":"new_version","source":"publisher","label":"New version"}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1011801","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,21]],"date-time":"2024-02-21T18:36:48Z","timestamp":1708540608000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1011801"}},"subtitle":[],"editor":[{"given":"Jonathan","family":"Rubin","sequence":"first","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2024,2,8]]},"references-count":95,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2024,2,8]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1011801","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2022.06.23.497415","asserted-by":"object"}]},"ISSN":["1553-7358"],"issn-type":[{"type":"electronic","value":"1553-7358"}],"subject":[],"published":{"date-parts":[[2024,2,8]]}}}