Blindfold learning of an accurate neural metric.
Proc Natl Acad Sci U S A
; 115(13): 3267-3272, 2018 03 27.
Article
em En
| MEDLINE
| ID: mdl-29531065
ABSTRACT
The brain has no direct access to physical stimuli but only to the spiking activity evoked in sensory organs. It is unclear how the brain can learn representations of the stimuli based on those noisy, correlated responses alone. Here we show how to build an accurate distance map of responses solely from the structure of the population activity of retinal ganglion cells. We introduce the Temporal Restricted Boltzmann Machine to learn the spatiotemporal structure of the population activity and use this model to define a distance between spike trains. We show that this metric outperforms existing neural distances at discriminating pairs of stimuli that are barely distinguishable. The proposed method provides a generic and biologically plausible way to learn to associate similar stimuli based on their spiking responses, without any other knowledge of these stimuli.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
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Encéfalo
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Potenciais de Ação
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Aprendizagem
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Modelos Neurológicos
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Rede Nervosa
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Neurônios
Limite:
Humans
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article