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  Neurometric function analysis of population codes

Berens, P., Gerwinn, S., Ecker, A., & Bethge, M. (2010). Neurometric function analysis of population codes. In Y. Bengio, D. Schuurmans, J. Lafferty, C. Williams, & A. Culotta (Eds.), Advances in Neural Information Processing Systems 22 (pp. 90-98). Red Hook, NY, USA: Curran.

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 Urheber:
Berens, P1, 2, Autor           
Gerwinn, S1, 2, Autor           
Ecker, AS1, 2, Autor           
Bethge, M1, 2, Autor           
Affiliations:
1Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Zusammenfassung: The relative merits of different population coding schemes have mostly been analyzed in the framework of stimulus reconstruction using Fisher Information. Here, we consider the case of stimulus discrimination in a two alternative forced choice paradigm and compute neurometric functions in terms of the minimal discrimination error and the Jensen-Shannon information to study neural population codes.
We first explore the relationship between minimum discrimination error, Jensen-Shannon Information and Fisher Information and show that the discrimination framework is more informative about the coding accuracy than Fisher Information as it defines an error for any pair of possible stimuli. In particular, it includes Fisher Information as a special case. Second, we use the framework to study population codes of angular variables. Specifically, we assess the impact of different noise correlations structures on coding accuracy in long versus short decoding
time windows. That is, for long time window we use the common Gaussian noise approximation. To address the case of short time windows we analyze the Ising model with identical noise correlation structure. In this way, we provide a new rigorous framework for assessing the functional consequences of noise correlation structures for the representational accuracy of neural population codes that is in particular applicable to short-time population coding.

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 Datum: 2010-04
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: BibTex Citekey: 6076
 Art des Abschluß: -

Veranstaltung

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Titel: 23rd Annual Conference on Neural Information Processing Systems (NIPS 2009)
Veranstaltungsort: Vancouver, BC, Canada
Start-/Enddatum: 2009-12-07 - 2009-12-10

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Titel: Advances in Neural Information Processing Systems 22
Genre der Quelle: Konferenzband
 Urheber:
Bengio, Y, Herausgeber
Schuurmans, D, Herausgeber
Lafferty, J, Herausgeber
Williams, C, Herausgeber
Culotta, A, Herausgeber
Affiliations:
-
Ort, Verlag, Ausgabe: Red Hook, NY, USA : Curran
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 90 - 98 Identifikator: ISBN: 978-1-615-67911-9