Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity
Neurons in the hippocampus and adjacent brain areas show a large diversity in their tuning to location and head direction, and the underlying circuit mechanisms are not yet resolved. In particular, it is unclear why certain cell types are selective to one spatial variable, but invariant to another....
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2018-02-01
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| Series: | eLife |
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| Online Access: | https://elifesciences.org/articles/34560 |
| _version_ | 1811180357102338048 |
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| author | Simon Nikolaus Weber Henning Sprekeler |
| author_facet | Simon Nikolaus Weber Henning Sprekeler |
| author_sort | Simon Nikolaus Weber |
| collection | DOAJ |
| description | Neurons in the hippocampus and adjacent brain areas show a large diversity in their tuning to location and head direction, and the underlying circuit mechanisms are not yet resolved. In particular, it is unclear why certain cell types are selective to one spatial variable, but invariant to another. For example, place cells are typically invariant to head direction. We propose that all observed spatial tuning patterns – in both their selectivity and their invariance – arise from the same mechanism: Excitatory and inhibitory synaptic plasticity driven by the spatial tuning statistics of synaptic inputs. Using simulations and a mathematical analysis, we show that combined excitatory and inhibitory plasticity can lead to localized, grid-like or invariant activity. Combinations of different input statistics along different spatial dimensions reproduce all major spatial tuning patterns observed in rodents. Our proposed model is robust to changes in parameters, develops patterns on behavioral timescales and makes distinctive experimental predictions. |
| first_indexed | 2024-04-11T09:01:57Z |
| format | Article |
| id | doaj.art-8c20d06812534880993576cdd0ae4d69 |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-11T09:01:57Z |
| publishDate | 2018-02-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-8c20d06812534880993576cdd0ae4d692022-12-22T04:32:45ZengeLife Sciences Publications LtdeLife2050-084X2018-02-01710.7554/eLife.34560Learning place cells, grid cells and invariances with excitatory and inhibitory plasticitySimon Nikolaus Weber0https://orcid.org/0000-0002-1169-9879Henning Sprekeler1https://orcid.org/0000-0003-0690-3553Modelling of Cognitive Processes, Institute of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, GermanyModelling of Cognitive Processes, Institute of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, GermanyNeurons in the hippocampus and adjacent brain areas show a large diversity in their tuning to location and head direction, and the underlying circuit mechanisms are not yet resolved. In particular, it is unclear why certain cell types are selective to one spatial variable, but invariant to another. For example, place cells are typically invariant to head direction. We propose that all observed spatial tuning patterns – in both their selectivity and their invariance – arise from the same mechanism: Excitatory and inhibitory synaptic plasticity driven by the spatial tuning statistics of synaptic inputs. Using simulations and a mathematical analysis, we show that combined excitatory and inhibitory plasticity can lead to localized, grid-like or invariant activity. Combinations of different input statistics along different spatial dimensions reproduce all major spatial tuning patterns observed in rodents. Our proposed model is robust to changes in parameters, develops patterns on behavioral timescales and makes distinctive experimental predictions.https://elifesciences.org/articles/34560synaptic plasticityinhibitiongrid cellsplace cellshippocampal formationcomputational neuroscience |
| spellingShingle | Simon Nikolaus Weber Henning Sprekeler Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity eLife synaptic plasticity inhibition grid cells place cells hippocampal formation computational neuroscience |
| title | Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity |
| title_full | Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity |
| title_fullStr | Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity |
| title_full_unstemmed | Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity |
| title_short | Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity |
| title_sort | learning place cells grid cells and invariances with excitatory and inhibitory plasticity |
| topic | synaptic plasticity inhibition grid cells place cells hippocampal formation computational neuroscience |
| url | https://elifesciences.org/articles/34560 |
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