Fast adaptation to rule switching using neuronal surprise.
In humans and animals, surprise is a physiological reaction to an unexpected event, but how surprise can be linked to plausible models of neuronal activity is an open problem. We propose a self-supervised spiking neural network model where a surprise signal is extracted from an increase in neural ac...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2024-02-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1011839&type=printable |
| _version_ | 1797266347946672128 |
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| author | Martin L L R Barry Wulfram Gerstner |
| author_facet | Martin L L R Barry Wulfram Gerstner |
| author_sort | Martin L L R Barry |
| collection | DOAJ |
| description | In humans and animals, surprise is a physiological reaction to an unexpected event, but how surprise can be linked to plausible models of neuronal activity is an open problem. We propose a self-supervised spiking neural network model where a surprise signal is extracted from an increase in neural activity after an imbalance of excitation and inhibition. The surprise signal modulates synaptic plasticity via a three-factor learning rule which increases plasticity at moments of surprise. The surprise signal remains small when transitions between sensory events follow a previously learned rule but increases immediately after rule switching. In a spiking network with several modules, previously learned rules are protected against overwriting, as long as the number of modules is larger than the total number of rules-making a step towards solving the stability-plasticity dilemma in neuroscience. Our model relates the subjective notion of surprise to specific predictions on the circuit level. |
| first_indexed | 2024-04-25T00:59:15Z |
| format | Article |
| id | doaj.art-58a7f6d783004e07bdca3ce11e3faa62 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-04-25T00:59:15Z |
| publishDate | 2024-02-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-58a7f6d783004e07bdca3ce11e3faa622024-03-11T05:31:23ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582024-02-01202e101183910.1371/journal.pcbi.1011839Fast adaptation to rule switching using neuronal surprise.Martin L L R BarryWulfram GerstnerIn humans and animals, surprise is a physiological reaction to an unexpected event, but how surprise can be linked to plausible models of neuronal activity is an open problem. We propose a self-supervised spiking neural network model where a surprise signal is extracted from an increase in neural activity after an imbalance of excitation and inhibition. The surprise signal modulates synaptic plasticity via a three-factor learning rule which increases plasticity at moments of surprise. The surprise signal remains small when transitions between sensory events follow a previously learned rule but increases immediately after rule switching. In a spiking network with several modules, previously learned rules are protected against overwriting, as long as the number of modules is larger than the total number of rules-making a step towards solving the stability-plasticity dilemma in neuroscience. Our model relates the subjective notion of surprise to specific predictions on the circuit level.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1011839&type=printable |
| spellingShingle | Martin L L R Barry Wulfram Gerstner Fast adaptation to rule switching using neuronal surprise. PLoS Computational Biology |
| title | Fast adaptation to rule switching using neuronal surprise. |
| title_full | Fast adaptation to rule switching using neuronal surprise. |
| title_fullStr | Fast adaptation to rule switching using neuronal surprise. |
| title_full_unstemmed | Fast adaptation to rule switching using neuronal surprise. |
| title_short | Fast adaptation to rule switching using neuronal surprise. |
| title_sort | fast adaptation to rule switching using neuronal surprise |
| url | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1011839&type=printable |
| work_keys_str_mv | AT martinllrbarry fastadaptationtoruleswitchingusingneuronalsurprise AT wulframgerstner fastadaptationtoruleswitchingusingneuronalsurprise |