Entorhinal mismatch: A model of self-supervised learning in the hippocampus
Summary: The hippocampal formation displays a wide range of physiological responses to different spatial manipulations of the environment. However, very few attempts have been made to identify core computational principles underlying those hippocampal responses. Here, we capitalize on the observatio...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-04-01
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| Series: | iScience |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004221003321 |
| _version_ | 1818961185062518784 |
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| author | Diogo Santos-Pata Adrián F. Amil Ivan Georgiev Raikov César Rennó-Costa Anna Mura Ivan Soltesz Paul F.M.J. Verschure |
| author_facet | Diogo Santos-Pata Adrián F. Amil Ivan Georgiev Raikov César Rennó-Costa Anna Mura Ivan Soltesz Paul F.M.J. Verschure |
| author_sort | Diogo Santos-Pata |
| collection | DOAJ |
| description | Summary: The hippocampal formation displays a wide range of physiological responses to different spatial manipulations of the environment. However, very few attempts have been made to identify core computational principles underlying those hippocampal responses. Here, we capitalize on the observation that the entorhinal-hippocampal complex (EHC) forms a closed loop and projects inhibitory signals “countercurrent” to the trisynaptic pathway to build a self-supervised model that learns to reconstruct its own inputs by error backpropagation. The EHC is then abstracted as an autoencoder, with the hidden layers acting as an information bottleneck. With the inputs mimicking the firing activity of lateral and medial entorhinal cells, our model is shown to generate place cells and to respond to environmental manipulations as observed in rodent experiments. Altogether, we propose that the hippocampus builds conjunctive compressed representations of the environment by learning to reconstruct its own entorhinal inputs via gradient descent. |
| first_indexed | 2024-12-20T12:09:24Z |
| format | Article |
| id | doaj.art-4f8f6d7d4b9743ec8c645cb69a9b40af |
| institution | Directory Open Access Journal |
| issn | 2589-0042 |
| language | English |
| last_indexed | 2024-12-20T12:09:24Z |
| publishDate | 2021-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj.art-4f8f6d7d4b9743ec8c645cb69a9b40af2022-12-21T19:41:16ZengElsevieriScience2589-00422021-04-01244102364Entorhinal mismatch: A model of self-supervised learning in the hippocampusDiogo Santos-Pata0Adrián F. Amil1Ivan Georgiev Raikov2César Rennó-Costa3Anna Mura4Ivan Soltesz5Paul F.M.J. Verschure6Laboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Institute for Bioengineering of Catalonia (IBEC), Barcelona, SpainLaboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Institute for Bioengineering of Catalonia (IBEC), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, SpainDepartment of Neurosurgery, Stanford University, Stanford, CA, USADigital Metropolis Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, BrazilLaboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Institute for Bioengineering of Catalonia (IBEC), Barcelona, SpainDepartment of Neurosurgery, Stanford University, Stanford, CA, USALaboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Institute for Bioengineering of Catalonia (IBEC), Barcelona, Spain; Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain; Corresponding authorSummary: The hippocampal formation displays a wide range of physiological responses to different spatial manipulations of the environment. However, very few attempts have been made to identify core computational principles underlying those hippocampal responses. Here, we capitalize on the observation that the entorhinal-hippocampal complex (EHC) forms a closed loop and projects inhibitory signals “countercurrent” to the trisynaptic pathway to build a self-supervised model that learns to reconstruct its own inputs by error backpropagation. The EHC is then abstracted as an autoencoder, with the hidden layers acting as an information bottleneck. With the inputs mimicking the firing activity of lateral and medial entorhinal cells, our model is shown to generate place cells and to respond to environmental manipulations as observed in rodent experiments. Altogether, we propose that the hippocampus builds conjunctive compressed representations of the environment by learning to reconstruct its own entorhinal inputs via gradient descent.http://www.sciencedirect.com/science/article/pii/S2589004221003321Cognitive NeuroscienceNeural NetworksSystems Neuroscience |
| spellingShingle | Diogo Santos-Pata Adrián F. Amil Ivan Georgiev Raikov César Rennó-Costa Anna Mura Ivan Soltesz Paul F.M.J. Verschure Entorhinal mismatch: A model of self-supervised learning in the hippocampus iScience Cognitive Neuroscience Neural Networks Systems Neuroscience |
| title | Entorhinal mismatch: A model of self-supervised learning in the hippocampus |
| title_full | Entorhinal mismatch: A model of self-supervised learning in the hippocampus |
| title_fullStr | Entorhinal mismatch: A model of self-supervised learning in the hippocampus |
| title_full_unstemmed | Entorhinal mismatch: A model of self-supervised learning in the hippocampus |
| title_short | Entorhinal mismatch: A model of self-supervised learning in the hippocampus |
| title_sort | entorhinal mismatch a model of self supervised learning in the hippocampus |
| topic | Cognitive Neuroscience Neural Networks Systems Neuroscience |
| url | http://www.sciencedirect.com/science/article/pii/S2589004221003321 |
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