The DOI matches its Crossref record; 222 of the 227 references it cites were found in a registry or an index, and 1 are not checked yet.
Pattern separation, completion, and categorisation in the hippocampus and neocortex
Abstract
The mechanisms for pattern completion and pattern separation are described in the context of a theory of hippocampal function in which the hippocampal CA3 system operates as a single attractor or autoassociation network to enable rapid, one-trial, associations between any spatial location (place in rodents, or spatial view in primates) and an object or reward, and to provide for completion of the whole memory during recall from any part. The factors important in the pattern completion in CA3 and also a large number of independent memories stored in CA3 include: a sparse distributed representation, representations that are independent due to the randomizing effect of the mossy fibres, heterosynaptic long-term depression as well as long-term potentiation in the recurrent collateral synapses, and diluted connectivity to minimize the number of multiple synapses between any pair of CA3 neurons which otherwise distort the basins of attraction. Recall of information from CA3 is implemented by the entorhinal cortex perforant path synapses to CA3 cells, which in acting as a pattern associator allow some pattern generalization. Pattern separation is performed in the dentate granule cells using competitive learning to convert grid-like entorhinal cortex firing to place-like fields, and in the dentate to CA3 connections that have diluted connectivity. Recall to the neocortex is achieved by a reverse hierarchical series of pattern association networks implemented by the hippocampo-cortical backprojections, each one of which performs some pattern generalization, to retrieve a complete pattern of cortical firing in higher-order cortical areas. New results on competitive networks show which factors contribute to their ability to perform pattern separation, pattern clustering, and pattern categorisation, and how these apply in different hippocampal and neocortical systems.
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“This feature seems to depend on a pattern completion mechanism that is able to reinstate complete memories after partial cueing, based on the operation of hippocampal autoassociative neural networks”
From Spatial Cognition in Teleost Fish: Strategies and Mechanisms (2021) · cites this paper as [81]
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Items 201–223 of 223
Daumas, S., Ceccom, J., Halley, H., Francès, B., & Lassalle, J. (2009) · Learning & Memory · doi:10.1101/lm.1418309 · Cited by 50
Spatial view cells in the hippocampus, and their idiothetic update based on place and head direction
Rolls, E. T., & Stringer, S. M. (2005) · Neural Networks · doi:10.1016/j.neunet.2005.08.006 · Cited by 46
Self-citationfMRI of verbal and nonverbal memory processes in healthy and epileptogenic medial temporal lobes
Banks, S. J., Sziklas, V., Sodums, D. J., et al. (2012) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2012.07.003 · Cited by 42
Dilution and sparse coding in threshold-linear nets
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Selective temporal resections and spatial memory impairment: Cue dependent lateralization effects
Barkas, L. J., Henderson, J. L., Hamilton, D. A., Redhead, E. S., & Gray, W. (2010) · Behavioural Brain Research · doi:10.1016/j.bbr.2009.12.035 · Cited by 39
Advantages of dilution in the connectivity of attractor networks in the brain
Rolls, E. T. (2012) · Biologically Inspired Cognitive Architectures · doi:10.1016/j.bica.2012.03.003 · Cited by 37
Self-citationFunctions of the primate hippocampus in spatial processing and memory
Rolls, E. T. (1991) · doi:10.1093/oso/9780198542841.003.0019 · Cited by 34
Self-citationCortical attractor network dynamics with diluted connectivity
Rolls, E. T., & Webb, T. J. (2011) · Brain Research · doi:10.1016/j.brainres.2011.08.002 · Cited by 31
Self-citationRecall of spatial patterns stored in a hippocampal slice by long-term potentiation
Jackson, M. B. (2013) · Journal of Neurophysiology · doi:10.1152/jn.00533.2013 · Cited by 31
The spatial representations acquired in CA3 by self-organizing recurrent connections
Cerasti, E., & Treves, A. (2013) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2013.00112 · Cited by 29
Cortical plasticity LTP and LTD
Fazeli, S., & Collingridge, G. L. (1996) · Medical Entomology and Zoology · Cited by 25
Stringer, S. M., & Rolls, E. T. (2006) · Network Computation in Neural Systems · doi:10.1080/09548980601004032 · Cited by 24
Self-citationPattern retrieval in threshold-linear associative nets
Simmen, M. W., Treves, A., & Rolls, E. T. (1996) · Network Computation in Neural Systems · doi:10.1080/0954898x.1996.11978657 · Cited by 24
Self-citationRolls, E. T. (2015) · Progress in brain research · doi:10.1016/bs.pbr.2015.03.007 · Cited by 21
Self-citationNoise in Attractor Networks in the Brain Produced by Graded Firing Rate Representations
Webb, T. J., Rolls, E. T., Deco, G., & Feng, J. (2011) · PLoS ONE · doi:10.1371/journal.pone.0023630 · Cited by 20
Self-citationNeural dynamics of cross-modal and cross-temporal associations
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Active Spatial Information Processing in the Septo-Hippocampal System
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Self-citationUnveiling the metric structure of internal representations of space
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Kesner, R. P., Morris, A. M., & Weeden, C. S. S. (2012) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780195392661.013.0018 · Cited by 15
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Self-citationThe neuronal representation of information in the human brain
Rolls, E. T. (2015) · Brain · doi:10.1093/brain/awv242 · Cited by 3
Self-citationCortico-hippocampal communication by way of parallel parahippocampal-subicular pathways.
Lavenex (2000) · Pure Amsterdam UMC · doi:10.1002/1098-1063(2000)10:4 · Cited by 1
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4 of the 227 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
- McNaughton, 1991, Associative pattern completion in hippocampal circuits: New evidence and new questions, Brain Research Reviews, 16, 193
- Rolls, 1995, A model of the operation of the hippocampus and entorhinal cortex in memory, International Journal of Neural Systems, 6, 51
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Sorted by citations
Roddy, D. W., Farrell, C., Doolin, K., Roman, E., Tozzi, L., Frodl, T., O’Keane, V., & O’Hanlon, E. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.08.021 · Cited by 287
The enigmatic mossy cell of the dentate gyrus
Scharfman, H. E. (2016) · Nature reviews. Neuroscience · doi:10.1038/nrn.2016.87 · Cited by 281
Re-evaluating Circuit Mechanisms Underlying Pattern Separation
Cayco-Gajic, N. A., & Silver, R. A. (2019) · Neuron · doi:10.1016/j.neuron.2019.01.044 · Cited by 234
“As the first stage in this pathway, the dentate gyrus is thought to separate entorhinal input patterns prior to memory storage in the hippocampus (Marr, 1971; McNaughton and Morris, 1987; Yassa and Stark, 2011; Schmidt et al., 2012; Knierim and Neunuebel, 2016; Rolls, 2016).”
Cerebral cortex : principles of operation
Rolls, E. T. (2016) · doi:10.82444/warw.33712699 · Cited by 187
Self-citationThe storage and recall of memories in the hippocampo-cortical system
Rolls, E. T. (2017) · Cell and Tissue Research · doi:10.1007/s00441-017-2744-3 · Cited by 195
“For recall, the hippocampal output can be thought of as a pointer to neocortical neurons via which memories can be called by using the backprojection pathways (Kesner and Rolls 2015; Rolls 2016a).”
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Metadata
- Authors
- Rolls, E. T.
- Affiliations
- University of Warwick (GB)
- Corresponding author
- Rolls, Edmund T.
- ORCID
- Rolls, Edmund T.
- Venue
- Neurobiology of Learning and Memory
- Publisher
- Elsevier BV
- Published
- 2016-03
- Volume
- 129
- Pages
- 4-28
- ISSN
- 1074-7427 (ISSN-L)
- OpenAlex
- W889908523
- Semantic Scholar
- dee8fed2414a8b21d9bf5724732f82ca2356190b
- Cited by
- 234
- References
- 227
- Citations by year
- 2026: 28 · 2025: 25 · 2024: 29 · 2023: 24 · 2022: 19 · 2021: 29 · 2020: 18 · 2019: 21 · 2018: 17 · 2017: 15 · 2016: 9
- FWCI
- 8.22
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neurobiology of Learning and Memory (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Medical Research Council
- Human Frontier Science Program
- EEC BRAIN
- MRC Oxford Interdisciplinary Research Centre in Cognitive Neuroscience
- Oxford McDonnell-Pew Centre in Cognitive Neuroscience
- Oxford Centre for Computational Neuroscience
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- pattern separation, pattern completion, hippocampus, CA3, dentate gyrus, neocortex, attractor networks, sparse distributed representations, mossy fibers, long-term potentiation, perforant path, entorhinal cortex, place cells, grid cells, competitive learning, pattern generalization, memory retrieval
- MeSH terms
- Animals, Association Learning, Humans, Models, Neurological, Neural Pathways, Neurons, Mental Recall, Synapses, Neocortex, Pattern Recognition, Physiological, CA3 Region, Hippocampal
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