ROC-based estimates of neural-behavioral covariations using matched filters.
Neural Comput
; 26(8): 1667-89, 2014 Aug.
Article
em En
| MEDLINE
| ID: mdl-24877731
ABSTRACT
Correlations between responses in visual cortex and perceptual performance help draw a functional link between neural activity and visually guided behavior. These correlations are commonly derived with ROC-based neural-behavioral covariances (referred to as choice or detect probability) using boxcar analysis windows. Although boxcar windows capture the covariation between neural activity and behavior during steady-state stimulus presentations, they are not optimized to capture these correlations during short time-varying visual inputs. In this study, we implemented a matched-filter technique, combined with cross-validation, to improve the estimation of ROC-based neural-behavioral covariance under short and dynamic stimulus conditions. We show that this approach maximizes the area under the ROC curve and converges to the true neural-behavioral covariance using a Poisson spiking model. We also demonstrate that the matched filter, combined with cross-validation, reveals the dynamics of the neural-behavioral covariations of individual MT neurons during the detection of a brief motion stimulus.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Lobo Temporal
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Comportamento de Escolha
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Detecção de Sinal Psicológico
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Modelos Neurológicos
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Percepção de Movimento
Tipo de estudo:
Prognostic_studies
Limite:
Animals
Idioma:
En
Ano de publicação:
2014
Tipo de documento:
Article