Models, movements, and minds: bridging the gap between decision making and action

Abstract

Decision making is a fundamental cognitive function, which not only determines our day‐to‐day choices but also shapes the trajectories of our movements, our lives, and our societies. While immense progress has been made in recent years on our understanding of the mechanisms underlying decision making, research on this topic is still largely split into two halves. Good‐based models largely state that decisions are made between representations of abstract value associated with available options; while action‐based models largely state that decisions are made at the level of action representations. These models are further divided between those that state that a decision is made before an action is specified, and those that regard decision making as an evolving process that continues until movement completion. Here, we review computational models, behavioral findings, and results from neural recordings associated with these frameworks. In synthesizing this literature, we submit that decision making is best understood as a continuous, graded, and distributed process that traverses a landscape of behaviorally relevant options, from their presentation until movement completion. Identifying and understanding the intimate links between decision making and action processing has important implications for the study of complex, goal‐directed behaviors such as social communication, and for elucidating the underlying mechanisms by which decisions are formed.

Individual difference in serial dependence results from opposite influences of perceptual choices and motor responses

“…Moreover, in our previous study, we found a behavioral oscillation of ∼10 Hz for motor response bias in perceptual decision making (Zhang, Morrone, & Alais, 2019). All these findings support an action-based decision-making theory, wherein perceptual evaluation of sensory evidence and movement planning are parallel (Cisek & Kalaska, 2010;Wispinski, Gallivan, & Chapman, 2018). If motor responses do not necessarily reflect perceptual choices, it is not clear whether the serial dependence on the previous response observed in many studies is an action-independent effect or a motor-related bias.…”

Decision making in slow and rapid reaching: Sacrificing success to minimize effort

“…Yet, it is clear from our goal keeper example that decisions exist on a continuum, and strong interconnections must exist between the cognitive systems that drive strategic decisions and sensorimotor control. During the last decade there has been a considerable increase in research attempting to bridge the gap between cognition and sensorimotor systems (for review see Gallivan, Chapman, Wolpert, & Flanagan, 2018;Wispinski, Gallivan, & Chapman, 2018).…”

Reaching for known unknowns: Rapid reach decisions accurately reflect the future state of dynamic probabilistic information

“…Behavioural measures such as reaction time, accuracy, and movement trajectories are often thought to index the same internal cognitive processes (31). However, these behaviors are measured at different times.…”

“…One tool for assessing dynamic cognitive states is to analyze the shape of movement trajectories (4,(23)(24)(25)(26)(27)(28)(29)(30)(31). Hand or computer mouse trajectories can reflect the deliberation of external information, such as random dot motion stimuli (4, 5), number magnitude (32,33), or word processing (28).…”