An inverse approach for elucidating dendritic function
We outline an inverse approach for investigating dendritic function-structure relationships by optimizing dendritic trees for a-priori chosen computational functions. The inverse approach can be applied in two different ways. First, we can use it as a `hypothesis generator' in which we op...
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2010-09-01
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| Series: | Frontiers in Computational Neuroscience |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fncom.2010.00128/full |
| _version_ | 1819237645400670208 |
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| author | Benjamin Torben-Nielsen Klaus Stiefel |
| author_facet | Benjamin Torben-Nielsen Klaus Stiefel |
| author_sort | Benjamin Torben-Nielsen |
| collection | DOAJ |
| description | We outline an inverse approach for investigating dendritic function-structure relationships by optimizing dendritic trees for a-priori chosen computational functions. The inverse approach can be applied in two different ways. First, we can use it as a `hypothesis generator' in which we optimize dendrites for a function of general interest. The optimization yields an artificial dendrite that is subsequently compared to real neurons. This comparison potentially allows us to propose hypotheses about the function of real neurons. In this way, we investigated dendrites that optimally perform input-order detection. Second, we can use it as a `function confirmation' by optimizing dendrites for functions hypothesized to be performed by classes of neurons. If the optimized, artificial, dendrites resemble the dendrites of real neurons the artificial dendrites corroborate the hypothesized function of the real neuron. Moreover, properties of the artificial dendrites can lead to predictions about yet unmeasured properties. In this way, we investigated wide-field motion integration performed by the VS cells of the fly visual system. In outlining the inverse approach and two applications, we also elaborate on the nature of dendritic function. We furthermore discuss the role of optimality in assigning functions to dendrites and point out interesting future directions. |
| first_indexed | 2024-12-23T13:23:37Z |
| format | Article |
| id | doaj.art-2107bbd700f348d88cf92cb21f350513 |
| institution | Directory Open Access Journal |
| issn | 1662-5188 |
| language | English |
| last_indexed | 2024-12-23T13:23:37Z |
| publishDate | 2010-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computational Neuroscience |
| spelling | doaj.art-2107bbd700f348d88cf92cb21f3505132022-12-21T17:45:22ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882010-09-01410.3389/fncom.2010.001281818An inverse approach for elucidating dendritic functionBenjamin Torben-Nielsen0Klaus Stiefel1Okinawa Institute of Science and TechnologyOkinawa Institute of Science and TechnologyWe outline an inverse approach for investigating dendritic function-structure relationships by optimizing dendritic trees for a-priori chosen computational functions. The inverse approach can be applied in two different ways. First, we can use it as a `hypothesis generator' in which we optimize dendrites for a function of general interest. The optimization yields an artificial dendrite that is subsequently compared to real neurons. This comparison potentially allows us to propose hypotheses about the function of real neurons. In this way, we investigated dendrites that optimally perform input-order detection. Second, we can use it as a `function confirmation' by optimizing dendrites for functions hypothesized to be performed by classes of neurons. If the optimized, artificial, dendrites resemble the dendrites of real neurons the artificial dendrites corroborate the hypothesized function of the real neuron. Moreover, properties of the artificial dendrites can lead to predictions about yet unmeasured properties. In this way, we investigated wide-field motion integration performed by the VS cells of the fly visual system. In outlining the inverse approach and two applications, we also elaborate on the nature of dendritic function. We furthermore discuss the role of optimality in assigning functions to dendrites and point out interesting future directions.http://journal.frontiersin.org/Journal/10.3389/fncom.2010.00128/fullDendritesdendritic functioninverse approachStructure-Function Relationship |
| spellingShingle | Benjamin Torben-Nielsen Klaus Stiefel An inverse approach for elucidating dendritic function Frontiers in Computational Neuroscience Dendrites dendritic function inverse approach Structure-Function Relationship |
| title | An inverse approach for elucidating dendritic function |
| title_full | An inverse approach for elucidating dendritic function |
| title_fullStr | An inverse approach for elucidating dendritic function |
| title_full_unstemmed | An inverse approach for elucidating dendritic function |
| title_short | An inverse approach for elucidating dendritic function |
| title_sort | inverse approach for elucidating dendritic function |
| topic | Dendrites dendritic function inverse approach Structure-Function Relationship |
| url | http://journal.frontiersin.org/Journal/10.3389/fncom.2010.00128/full |
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