Vector-Based Integration of Local and Long-Range Information in Visual Cortex
Integration of inputs by cortical neurons provides the basis for the complex information processing performed in the cerebral cortex. Here, we propose a new analytic framework for understanding integration within cortical neuronal receptive fields. Based on the synaptic organization of cortex,...
| Main Authors: | , , , |
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| Language: | en_US |
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2004
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| Online Access: | http://hdl.handle.net/1721.1/7190 |
| _version_ | 1811075164137324544 |
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| author | Somers, David C. Todorov, Emanuel V. Siapas, Athanassios G. Sur, Mriganka |
| author_facet | Somers, David C. Todorov, Emanuel V. Siapas, Athanassios G. Sur, Mriganka |
| author_sort | Somers, David C. |
| collection | MIT |
| description | Integration of inputs by cortical neurons provides the basis for the complex information processing performed in the cerebral cortex. Here, we propose a new analytic framework for understanding integration within cortical neuronal receptive fields. Based on the synaptic organization of cortex, we argue that neuronal integration is a systems--level process better studied in terms of local cortical circuitry than at the level of single neurons, and we present a method for constructing self-contained modules which capture (nonlinear) local circuit interactions. In this framework, receptive field elements naturally have dual (rather than the traditional unitary influence since they drive both excitatory and inhibitory cortical neurons. This vector-based analysis, in contrast to scalarsapproaches, greatly simplifies integration by permitting linear summation of inputs from both "classical" and "extraclassical" receptive field regions. We illustrate this by explaining two complex visual cortical phenomena, which are incompatible with scalar notions of neuronal integration. |
| first_indexed | 2024-09-23T10:01:50Z |
| id | mit-1721.1/7190 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T10:01:50Z |
| publishDate | 2004 |
| record_format | dspace |
| spelling | mit-1721.1/71902019-04-12T08:34:03Z Vector-Based Integration of Local and Long-Range Information in Visual Cortex Somers, David C. Todorov, Emanuel V. Siapas, Athanassios G. Sur, Mriganka MIT Receptive Field Cortical Circuits Modules Cortical Inhibition Computational Neuroscience. Integration of inputs by cortical neurons provides the basis for the complex information processing performed in the cerebral cortex. Here, we propose a new analytic framework for understanding integration within cortical neuronal receptive fields. Based on the synaptic organization of cortex, we argue that neuronal integration is a systems--level process better studied in terms of local cortical circuitry than at the level of single neurons, and we present a method for constructing self-contained modules which capture (nonlinear) local circuit interactions. In this framework, receptive field elements naturally have dual (rather than the traditional unitary influence since they drive both excitatory and inhibitory cortical neurons. This vector-based analysis, in contrast to scalarsapproaches, greatly simplifies integration by permitting linear summation of inputs from both "classical" and "extraclassical" receptive field regions. We illustrate this by explaining two complex visual cortical phenomena, which are incompatible with scalar notions of neuronal integration. 2004-10-20T20:49:17Z 2004-10-20T20:49:17Z 1996-01-18 AIM-1556 CBCL-127 http://hdl.handle.net/1721.1/7190 en_US AIM-1556 CBCL-127 11 p. 2170488 bytes 1066936 bytes application/postscript application/pdf application/postscript application/pdf |
| spellingShingle | MIT Receptive Field Cortical Circuits Modules Cortical Inhibition Computational Neuroscience. Somers, David C. Todorov, Emanuel V. Siapas, Athanassios G. Sur, Mriganka Vector-Based Integration of Local and Long-Range Information in Visual Cortex |
| title | Vector-Based Integration of Local and Long-Range Information in Visual Cortex |
| title_full | Vector-Based Integration of Local and Long-Range Information in Visual Cortex |
| title_fullStr | Vector-Based Integration of Local and Long-Range Information in Visual Cortex |
| title_full_unstemmed | Vector-Based Integration of Local and Long-Range Information in Visual Cortex |
| title_short | Vector-Based Integration of Local and Long-Range Information in Visual Cortex |
| title_sort | vector based integration of local and long range information in visual cortex |
| topic | MIT Receptive Field Cortical Circuits Modules Cortical Inhibition Computational Neuroscience. |
| url | http://hdl.handle.net/1721.1/7190 |
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