Reviewer #2 (Public Review): Direct observation of the neural computations underlying a single decision
Year: 2023
Type: peer-review
Abstract: Neurobiological investigations of perceptual decision-making have furnished the first glimpse of a flexible cognitive process at the level of single neurons (; ). Neurons in the parietal and prefrontal cortex (; ; ; ) are thought to represent the accumulation of noisy evidence, acquired over time, leading to a decision. Neural recordings averaged over many decisions have provided support for the deterministic rise in activity to a termination bound (). Critically, it is the unobserved stochastic component that is thought to confer variability in both choice and decision time (). Here, we elucidate this drift-diffusion-like signal on individual decisions by recording simultaneously from hundreds of neurons in the lateral intraparietal cortex (LIP). We show that a single scalar quantity derived from the weighted sum of the population activity represents a combination of deterministic drift and stochastic diffusion. Moreover, we provide direct support for the hypothesis that this drift-diffusion signal is the quantity responsible for the variability in choice and reaction times. The population-derived signals rely on a small subset of neurons with response fields that overlap the choice targets. These neurons represent the integral of noisy evidence from direction-selective neurons within LIP itself. This parsimonious architecture would escape detection by state-space analyses, absent a clear hypothesis.
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W4387578933