Bridging Neural and Computational Viewpoints on Perceptual Decision-Making.

摘要: Sequential sampling models have provided a dominant theoretical framework guiding computational and neurophysiological investigations of perceptual decision-making. While these share the basic principle that decisions are formed by accumulating sensory evidence to bound, they come in many forms can make similar predictions choice behaviour despite invoking fundamentally different mechanisms. The identification neural signals reflect some core computations underpinning decision formation offers new avenues for empirically testing refining key model assumptions. Here, we highlight recent efforts explore and, so doing, consider conceptual methodological challenges arise when seeking infer from complex data.