A simple two-stage model predicts response time distributions.
J Physiol
; 587(Pt 16): 4051-62, 2009 Aug 15.
Article
en En
| MEDLINE
| ID: mdl-19564395
ABSTRACT
The neural mechanisms underlying reaction times have previously been modelled in two distinct ways. When stimuli are hard to detect, response time tends to follow a random-walk model that integrates noisy sensory signals. But studies investigating the influence of higher-level factors such as prior probability and response urgency typically use highly detectable targets, and response times then usually correspond to a linear rise-to-threshold mechanism. Here we show that a model incorporating both types of element in series - a detector integrating noisy afferent signals, followed by a linear rise-to-threshold performing decision - successfully predicts not only mean response times but, much more stringently, the observed distribution of these times and the rate of decision errors over a wide range of stimulus detectability. By reconciling what previously may have seemed to be conflicting theories, we are now closer to having a complete description of reaction time and the decision processes that underlie it.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Tiempo de Reacción
/
Corteza Visual
/
Modelos Neurológicos
/
Percepción de Movimiento
/
Red Nerviosa
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Adult
/
Animals
/
Female
/
Humans
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Male
/
Middle aged
Idioma:
En
Revista:
J Physiol
Año:
2009
Tipo del documento:
Article
País de afiliación:
Reino Unido