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  Receptive Fields without Spike-Triggering

Macke, J., Zeck, G., & Bethge, M. (2008). Receptive Fields without Spike-Triggering. In C., Platt, D., Koller, Y., Singer, & S., Roweis (Eds.), Advances in Neural Information Processing Systems 20: 21st Annual Conference on Neural Information Processing Systems 2007 (pp. 969-976). Red Hook, NY, USA: Curran.

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アイテムのパーマリンク: https://hdl.handle.net/11858/00-001M-0000-0013-C753-F 版のパーマリンク: https://hdl.handle.net/21.11116/0000-0003-38A8-1
資料種別: 会議論文

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 作成者:
Macke, JH1, 2, 3, 著者           
Zeck, G, 著者           
Bethge, M1, 2, 3, 著者           
所属:
1Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              
2Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
3Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 要旨: Stimulus selectivity of sensory neurons is often characterized by estimating their receptive field properties such as orientation selectivity. Receptive fields are usually derived from the mean (or covariance) of the spike-triggered stimulus ensemble. This approach treats each spike as an independent message but does not take into account that information might be conveyed through patterns of neural activity that are distributed across space or time. Can we find a concise description for the processing of a whole population of neurons analogous to the receptive field for single neurons? Here, we present a generalization of the linear receptive field which is not bound to be triggered on individual spikes but can be meaningfully
linked to distributed response patterns. More precisely, we seek to identify those stimulus features and the corresponding patterns of neural activity that are most
reliably coupled. We use an extension of reverse-correlation methods based on canonical correlation analysis. The resulting population receptive fields span the
subspace of stimuli that is most informative about the population response. We evaluate our approach using both neuronal models and multi-electrode recordings from rabbit retinal ganglion cells. We show how the model can be extended to capture nonlinear stimulus-response relationships using kernel canonical correlation analysis, which makes it possible to test different coding mechanisms. Our technique can also be used to calculate receptive fields from multi-dimensional neural measurements such as those obtained from dynamic imaging methods.

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 日付: 2008-09
 出版の状態: 出版
 ページ: -
 出版情報: -
 目次: -
 査読: -
 識別子（DOI, ISBNなど）: BibTex参照ID: 4738
 学位: -

関連イベント

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イベント名: Twenty-First Annual Conference on Neural Information Processing Systems (NIPS 2007)
開催地: Vancouver, BC, Canada
開始日・終了日: 2007-12-03 - 2007-12-06

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出版物 1

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出版物名: Advances in Neural Information Processing Systems 20: 21st Annual Conference on Neural Information Processing Systems 2007
種別: 会議論文集
 著者・編者:
Platt, C, 編集者
Koller, D, 編集者
Singer, Y, 編集者
Roweis, ST, 編集者
所属:
-
出版社, 出版地: Red Hook, NY, USA : Curran
ページ: - 巻号: - 通巻号: - 開始・終了ページ: 969 - 976 識別子（ISBN, ISSN, DOIなど）: ISBN: 978-1-605-60352-0