Self-organizing path integration using a linked continuous attractor and competitive network: path integration of head direction.
A key issue is how networks in the brain learn to perform path integration, that is update a represented position using a velocity signal. Using head direction cells as an example, we show that a competitive network could self-organize to learn to respond to combinations of head direction and angula...
| Main Authors: | , |
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| Format: | Journal article |
| Language: | English |
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2006
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| _version_ | 1797059890670206976 |
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| author | Stringer, S Rolls, E |
| author_facet | Stringer, S Rolls, E |
| author_sort | Stringer, S |
| collection | OXFORD |
| description | A key issue is how networks in the brain learn to perform path integration, that is update a represented position using a velocity signal. Using head direction cells as an example, we show that a competitive network could self-organize to learn to respond to combinations of head direction and angular head rotation velocity. These combination cells can then be used to drive a continuous attractor network to the next head direction based on the incoming rotation signal. An associative synaptic modification rule with a short term memory trace enables preceding combination cell activity during training to be associated with the next position in the continuous attractor network. The network accounts for the presence of neurons found in the brain that respond to combinations of head direction and angular head rotation velocity. Analogous networks in the hippocampal system could self-organize to perform path integration of place and spatial view representations. |
| first_indexed | 2024-03-06T20:10:28Z |
| format | Journal article |
| id | oxford-uuid:2a618ae8-0eae-471b-9aae-0148e7330922 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T20:10:28Z |
| publishDate | 2006 |
| record_format | dspace |
| spelling | oxford-uuid:2a618ae8-0eae-471b-9aae-0148e73309222022-03-26T12:24:43ZSelf-organizing path integration using a linked continuous attractor and competitive network: path integration of head direction.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:2a618ae8-0eae-471b-9aae-0148e7330922EnglishSymplectic Elements at Oxford2006Stringer, SRolls, EA key issue is how networks in the brain learn to perform path integration, that is update a represented position using a velocity signal. Using head direction cells as an example, we show that a competitive network could self-organize to learn to respond to combinations of head direction and angular head rotation velocity. These combination cells can then be used to drive a continuous attractor network to the next head direction based on the incoming rotation signal. An associative synaptic modification rule with a short term memory trace enables preceding combination cell activity during training to be associated with the next position in the continuous attractor network. The network accounts for the presence of neurons found in the brain that respond to combinations of head direction and angular head rotation velocity. Analogous networks in the hippocampal system could self-organize to perform path integration of place and spatial view representations. |
| spellingShingle | Stringer, S Rolls, E Self-organizing path integration using a linked continuous attractor and competitive network: path integration of head direction. |
| title | Self-organizing path integration using a linked continuous attractor and competitive network: path integration of head direction. |
| title_full | Self-organizing path integration using a linked continuous attractor and competitive network: path integration of head direction. |
| title_fullStr | Self-organizing path integration using a linked continuous attractor and competitive network: path integration of head direction. |
| title_full_unstemmed | Self-organizing path integration using a linked continuous attractor and competitive network: path integration of head direction. |
| title_short | Self-organizing path integration using a linked continuous attractor and competitive network: path integration of head direction. |
| title_sort | self organizing path integration using a linked continuous attractor and competitive network path integration of head direction |
| work_keys_str_mv | AT stringers selforganizingpathintegrationusingalinkedcontinuousattractorandcompetitivenetworkpathintegrationofheaddirection AT rollse selforganizingpathintegrationusingalinkedcontinuousattractorandcompetitivenetworkpathintegrationofheaddirection |