Cargando…

Bridging Neural and Computational Viewpoints on Perceptual Decision-Making

Sequential sampling models have provided a dominant theoretical framework guiding computational and neurophysiological investigations of perceptual decision-making. While these models share the basic principle that decisions are formed by accumulating sensory evidence to a bound, they come in many f...

Descripción completa

Detalles Bibliográficos
Autores principales: O’Connell, Redmond G., Shadlen, Michael N., Wong-Lin, KongFatt, Kelly, Simon P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Applied Science Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6215147/
https://www.ncbi.nlm.nih.gov/pubmed/30007746
http://dx.doi.org/10.1016/j.tins.2018.06.005
Descripción
Sumario:Sequential sampling models have provided a dominant theoretical framework guiding computational and neurophysiological investigations of perceptual decision-making. While these models share the basic principle that decisions are formed by accumulating sensory evidence to a bound, they come in many forms that can make similar predictions of choice behaviour despite invoking fundamentally different mechanisms. The identification of neural signals that reflect some of the core computations underpinning decision formation offers new avenues for empirically testing and refining key model assumptions. Here, we highlight recent efforts to explore these avenues and, in so doing, consider the conceptual and methodological challenges that arise when seeking to infer decision computations from complex neural data.