Bistable perception modeled as competing stochastic integrations at two levels.
We propose a novel explanation for bistable perception, namely, the collective dynamics of multiple neural populations that are individually meta-stable. Distributed representations of sensory input and of perceptual state build gradually through noise-driven transitions in these populations, until...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2009-07-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/19593372/pdf/?tool=EBI |
| _version_ | 1818742401276051456 |
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| author | Guido Gigante Maurizio Mattia Jochen Braun Paolo Del Giudice |
| author_facet | Guido Gigante Maurizio Mattia Jochen Braun Paolo Del Giudice |
| author_sort | Guido Gigante |
| collection | DOAJ |
| description | We propose a novel explanation for bistable perception, namely, the collective dynamics of multiple neural populations that are individually meta-stable. Distributed representations of sensory input and of perceptual state build gradually through noise-driven transitions in these populations, until the competition between alternative representations is resolved by a threshold mechanism. The perpetual repetition of this collective race to threshold renders perception bistable. This collective dynamics - which is largely uncoupled from the time-scales that govern individual populations or neurons - explains many hitherto puzzling observations about bistable perception: the wide range of mean alternation rates exhibited by bistable phenomena, the consistent variability of successive dominance periods, and the stabilizing effect of past perceptual states. It also predicts a number of previously unsuspected relationships between observable quantities characterizing bistable perception. We conclude that bistable perception reflects the collective nature of neural decision making rather than properties of individual populations or neurons. |
| first_indexed | 2024-12-18T02:11:56Z |
| format | Article |
| id | doaj.art-494855c47d8448ec90ff5a9c5d1e8100 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-18T02:11:56Z |
| publishDate | 2009-07-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-494855c47d8448ec90ff5a9c5d1e81002022-12-21T21:24:28ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582009-07-0157e100043010.1371/journal.pcbi.1000430Bistable perception modeled as competing stochastic integrations at two levels.Guido GiganteMaurizio MattiaJochen BraunPaolo Del GiudiceWe propose a novel explanation for bistable perception, namely, the collective dynamics of multiple neural populations that are individually meta-stable. Distributed representations of sensory input and of perceptual state build gradually through noise-driven transitions in these populations, until the competition between alternative representations is resolved by a threshold mechanism. The perpetual repetition of this collective race to threshold renders perception bistable. This collective dynamics - which is largely uncoupled from the time-scales that govern individual populations or neurons - explains many hitherto puzzling observations about bistable perception: the wide range of mean alternation rates exhibited by bistable phenomena, the consistent variability of successive dominance periods, and the stabilizing effect of past perceptual states. It also predicts a number of previously unsuspected relationships between observable quantities characterizing bistable perception. We conclude that bistable perception reflects the collective nature of neural decision making rather than properties of individual populations or neurons.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/19593372/pdf/?tool=EBI |
| spellingShingle | Guido Gigante Maurizio Mattia Jochen Braun Paolo Del Giudice Bistable perception modeled as competing stochastic integrations at two levels. PLoS Computational Biology |
| title | Bistable perception modeled as competing stochastic integrations at two levels. |
| title_full | Bistable perception modeled as competing stochastic integrations at two levels. |
| title_fullStr | Bistable perception modeled as competing stochastic integrations at two levels. |
| title_full_unstemmed | Bistable perception modeled as competing stochastic integrations at two levels. |
| title_short | Bistable perception modeled as competing stochastic integrations at two levels. |
| title_sort | bistable perception modeled as competing stochastic integrations at two levels |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/19593372/pdf/?tool=EBI |
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