LOW-DIMENSIONAL STRUCTURES: SPARSE CODING FOR NEURONAL ACTIVITY
Neuronal ensemble activity codes working memory. In this work, we developed a neuronal ensemble sparse coding method, which can effectively reduce the dimension of the neuronal activity and express neural coding. Multichannel spike trains were recorded in rat prefrontal cortex during a work memory t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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World Scientific Publishing
2013-01-01
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| Series: | Journal of Innovative Optical Health Sciences |
| Subjects: | |
| Online Access: | http://www.worldscientific.com/doi/pdf/10.1142/S1793545813500028 |
| _version_ | 1819056652750422016 |
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| author | YUNHUA XU WENWEN BAI XIN TIAN |
| author_facet | YUNHUA XU WENWEN BAI XIN TIAN |
| author_sort | YUNHUA XU |
| collection | DOAJ |
| description | Neuronal ensemble activity codes working memory. In this work, we developed a neuronal ensemble sparse coding method, which can effectively reduce the dimension of the neuronal activity and express neural coding. Multichannel spike trains were recorded in rat prefrontal cortex during a work memory task in Y-maze. As discrete signals, spikes were transferred into continuous signals by estimating entropy. Then the normalized continuous signals were decomposed via non-negative sparse method. The non-negative components were extracted to reconstruct a low-dimensional ensemble, while none of the feature components were missed. The results showed that, for well-trained rats, neuronal ensemble activities in the prefrontal cortex changed dynamically during the working memory task. And the neuronal ensemble is more explicit via using non-negative sparse coding. Our results indicate that the neuronal ensemble sparse coding method can effectively reduce the dimension of neuronal activity and it is a useful tool to express neural coding. |
| first_indexed | 2024-12-21T13:26:49Z |
| format | Article |
| id | doaj.art-678fdfbd3119423eb1c079594fda6e24 |
| institution | Directory Open Access Journal |
| issn | 1793-5458 1793-7205 |
| language | English |
| last_indexed | 2024-12-21T13:26:49Z |
| publishDate | 2013-01-01 |
| publisher | World Scientific Publishing |
| record_format | Article |
| series | Journal of Innovative Optical Health Sciences |
| spelling | doaj.art-678fdfbd3119423eb1c079594fda6e242022-12-21T19:02:26ZengWorld Scientific PublishingJournal of Innovative Optical Health Sciences1793-54581793-72052013-01-01611350002-11350002-910.1142/S179354581350002810.1142/S1793545813500028LOW-DIMENSIONAL STRUCTURES: SPARSE CODING FOR NEURONAL ACTIVITYYUNHUA XU0WENWEN BAI1XIN TIAN2School of Biomedical Engineering, Tianjin Medical University, Tianjin 300070, P. R. ChinaSchool of Biomedical Engineering, Tianjin Medical University, Tianjin 300070, P. R. ChinaSchool of Biomedical Engineering, Tianjin Medical University, Tianjin 300070, P. R. ChinaNeuronal ensemble activity codes working memory. In this work, we developed a neuronal ensemble sparse coding method, which can effectively reduce the dimension of the neuronal activity and express neural coding. Multichannel spike trains were recorded in rat prefrontal cortex during a work memory task in Y-maze. As discrete signals, spikes were transferred into continuous signals by estimating entropy. Then the normalized continuous signals were decomposed via non-negative sparse method. The non-negative components were extracted to reconstruct a low-dimensional ensemble, while none of the feature components were missed. The results showed that, for well-trained rats, neuronal ensemble activities in the prefrontal cortex changed dynamically during the working memory task. And the neuronal ensemble is more explicit via using non-negative sparse coding. Our results indicate that the neuronal ensemble sparse coding method can effectively reduce the dimension of neuronal activity and it is a useful tool to express neural coding.http://www.worldscientific.com/doi/pdf/10.1142/S1793545813500028Low-dimensional structuressparse codingneuronal ensemble activityworking memoryrat |
| spellingShingle | YUNHUA XU WENWEN BAI XIN TIAN LOW-DIMENSIONAL STRUCTURES: SPARSE CODING FOR NEURONAL ACTIVITY Journal of Innovative Optical Health Sciences Low-dimensional structures sparse coding neuronal ensemble activity working memory rat |
| title | LOW-DIMENSIONAL STRUCTURES: SPARSE CODING FOR NEURONAL ACTIVITY |
| title_full | LOW-DIMENSIONAL STRUCTURES: SPARSE CODING FOR NEURONAL ACTIVITY |
| title_fullStr | LOW-DIMENSIONAL STRUCTURES: SPARSE CODING FOR NEURONAL ACTIVITY |
| title_full_unstemmed | LOW-DIMENSIONAL STRUCTURES: SPARSE CODING FOR NEURONAL ACTIVITY |
| title_short | LOW-DIMENSIONAL STRUCTURES: SPARSE CODING FOR NEURONAL ACTIVITY |
| title_sort | low dimensional structures sparse coding for neuronal activity |
| topic | Low-dimensional structures sparse coding neuronal ensemble activity working memory rat |
| url | http://www.worldscientific.com/doi/pdf/10.1142/S1793545813500028 |
| work_keys_str_mv | AT yunhuaxu lowdimensionalstructuressparsecodingforneuronalactivity AT wenwenbai lowdimensionalstructuressparsecodingforneuronalactivity AT xintian lowdimensionalstructuressparsecodingforneuronalactivity |