Mostrar el registro sencillo del ítem
dc.contributor.author
Eyherabide, Hugo Gabriel
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.contributor.author
Samengo, Ines
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.date.available
2017-06-06T20:20:55Z
dc.date.issued
2013-11
dc.identifier.citation
Eyherabide, Hugo Gabriel; Samengo, Ines; When and why noise correlations are important in neural decoding; Society For Neuroscience; Journal Of Neuroscience; 33; 45; 11-2013; 17921-17936
dc.identifier.issn
0270-6474
dc.identifier.uri
http://hdl.handle.net/11336/17629
dc.description.abstract
Information may be encoded both in the individual activity of neurons and in the correlations between their activities. Understanding whether knowledge of noise correlations is required to decode all the encoded information is fundamental for constructing computational models, brain–machine interfaces, and neuroprosthetics. If correlations can be ignored with tolerable losses of information, the readout of neural signals is simplified dramatically. To that end, previous studies have constructed decoders assuming that neurons fire independently and then derived bounds for the information that is lost. However, here we show that previous bounds were not tight and overestimated the importance of noise correlations. In this study, we quantify the exact loss of information induced by ignoring noise correlations and show why previous estimations were not tight. Further, by studying the elementary parts of the decoding process, we determine when and why information is lost on a single-response basis. We introduce the minimum decoding error to assess the distinctive role of noise correlations under natural conditions. We conclude that all of the encoded information can be decoded without knowledge of noise correlations in many more situations than previously thought.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Society For Neuroscience
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Neural Correlations
dc.subject
Information Theory
dc.subject
Decoding
dc.subject.classification
Biología
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.subject.classification
Ciencias Biológicas
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.title
When and why noise correlations are important in neural decoding
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2015-10-15T20:01:42Z
dc.journal.volume
33
dc.journal.number
45
dc.journal.pagination
17921-17936
dc.journal.pais
Estados Unidos
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.description.fil
Fil: Eyherabide, Hugo Gabriel. Comisión Nacional de Energía Atómica. Centro Atómico Bariloche; Argentina. Comisión Nacional de Energía Atómica. Gerencia del Area de Energía Nuclear. Instituto Balseiro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: Samengo, Ines. Comisión Nacional de Energía Atómica. Centro Atómico Bariloche; Argentina. Comisión Nacional de Energía Atómica. Gerencia del Area de Energía Nuclear. Instituto Balseiro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.journal.title
Journal Of Neuroscience
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1523/JNEUROSCI.0357-13.2013
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.jneurosci.org/content/33/45/17921
Archivos asociados