Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation
Our brain perceives the world by exploiting multisensory cues to extract information about various aspects of external stimuli. The sensory cues from the same stimulus should be integrated to improve perception, and otherwise segregated to distinguish different stimuli. In reality, however, the brai...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
eLife Sciences Publications Ltd
2019-05-01
|
| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/43753 |
| _version_ | 1811227544281677824 |
|---|---|
| author | Wen-Hao Zhang He Wang Aihua Chen Yong Gu Tai Sing Lee KY Michael Wong Si Wu |
| author_facet | Wen-Hao Zhang He Wang Aihua Chen Yong Gu Tai Sing Lee KY Michael Wong Si Wu |
| author_sort | Wen-Hao Zhang |
| collection | DOAJ |
| description | Our brain perceives the world by exploiting multisensory cues to extract information about various aspects of external stimuli. The sensory cues from the same stimulus should be integrated to improve perception, and otherwise segregated to distinguish different stimuli. In reality, however, the brain faces the challenge of recognizing stimuli without knowing in advance the sources of sensory cues. To address this challenge, we propose that the brain conducts integration and segregation concurrently with complementary neurons. Studying the inference of heading-direction via visual and vestibular cues, we develop a network model with two reciprocally connected modules modeling interacting visual-vestibular areas. In each module, there are two groups of neurons whose tunings under each sensory cue are either congruent or opposite. We show that congruent neurons implement integration, while opposite neurons compute cue disparity information for segregation, and the interplay between two groups of neurons achieves efficient multisensory information processing. |
| first_indexed | 2024-04-12T09:44:23Z |
| format | Article |
| id | doaj.art-68e2d284a49248d18d676d6adbf69d91 |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-12T09:44:23Z |
| publishDate | 2019-05-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-68e2d284a49248d18d676d6adbf69d912022-12-22T03:37:59ZengeLife Sciences Publications LtdeLife2050-084X2019-05-01810.7554/eLife.43753Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregationWen-Hao Zhang0https://orcid.org/0000-0001-7641-5024He Wang1https://orcid.org/0000-0003-2101-8683Aihua Chen2Yong Gu3https://orcid.org/0000-0003-4437-8956Tai Sing Lee4KY Michael Wong5https://orcid.org/0000-0002-3078-4577Si Wu6Department of Physics, Hong Kong University of Science and Technology, Hong Kong; Center of the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United StatesDepartment of Physics, Hong Kong University of Science and Technology, Hong KongKey Laboratory of Brain Functional Genomics, Primate Research Center, East China Normal University, Shanghai, ChinaInstitute of Neuroscience, Chinese Academy of Sciences, Shanghai, ChinaCenter of the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United StatesDepartment of Physics, Hong Kong University of Science and Technology, Hong KongSchool of Electronics Engineering and Computer Science, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, ChinaOur brain perceives the world by exploiting multisensory cues to extract information about various aspects of external stimuli. The sensory cues from the same stimulus should be integrated to improve perception, and otherwise segregated to distinguish different stimuli. In reality, however, the brain faces the challenge of recognizing stimuli without knowing in advance the sources of sensory cues. To address this challenge, we propose that the brain conducts integration and segregation concurrently with complementary neurons. Studying the inference of heading-direction via visual and vestibular cues, we develop a network model with two reciprocally connected modules modeling interacting visual-vestibular areas. In each module, there are two groups of neurons whose tunings under each sensory cue are either congruent or opposite. We show that congruent neurons implement integration, while opposite neurons compute cue disparity information for segregation, and the interplay between two groups of neurons achieves efficient multisensory information processing.https://elifesciences.org/articles/43753opposite neuronmultisensory integrationconcurrent integration and segregationdecentralized architecturecontinuous attractor neural networkBayesian inference |
| spellingShingle | Wen-Hao Zhang He Wang Aihua Chen Yong Gu Tai Sing Lee KY Michael Wong Si Wu Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation eLife opposite neuron multisensory integration concurrent integration and segregation decentralized architecture continuous attractor neural network Bayesian inference |
| title | Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation |
| title_full | Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation |
| title_fullStr | Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation |
| title_full_unstemmed | Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation |
| title_short | Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation |
| title_sort | complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation |
| topic | opposite neuron multisensory integration concurrent integration and segregation decentralized architecture continuous attractor neural network Bayesian inference |
| url | https://elifesciences.org/articles/43753 |
| work_keys_str_mv | AT wenhaozhang complementarycongruentandoppositeneuronsachieveconcurrentmultisensoryintegrationandsegregation AT hewang complementarycongruentandoppositeneuronsachieveconcurrentmultisensoryintegrationandsegregation AT aihuachen complementarycongruentandoppositeneuronsachieveconcurrentmultisensoryintegrationandsegregation AT yonggu complementarycongruentandoppositeneuronsachieveconcurrentmultisensoryintegrationandsegregation AT taisinglee complementarycongruentandoppositeneuronsachieveconcurrentmultisensoryintegrationandsegregation AT kymichaelwong complementarycongruentandoppositeneuronsachieveconcurrentmultisensoryintegrationandsegregation AT siwu complementarycongruentandoppositeneuronsachieveconcurrentmultisensoryintegrationandsegregation |