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.
Decision making revolves around weighing potential gains and losses. Research in economic decision making has emphasized that humans exercise disproportionate caution when making explicit choices involving loss. By comparison, research in perceptual decision making has revealed a processing advantage for targets associated with potential gain, though the effects of loss have been explored less systematically. Here, we use a rapid reaching task to measure the relative sensitivity (Experiment 1) and the time course (Experiments 2 and 3) of rapid actions with regard to the reward valence and probability of targets. We show that targets linked to a high probability of gain influence actions about 100 ms earlier than targets associated with equivalent probability and value of loss. These findings are well accounted for by a model of stimulus response in which reward modulates the late, postpeak phase of the activity. We interpret our results within a neural framework of biased competition that is resolved in spatial maps of behavioral relevance. As implied by our model, all visual stimuli initially receive positive activation. Gain stimuli can build off of this initial activation when selected as a target, whereas loss stimuli have to overcome this initial activation in order to be avoided, accounting for the observed delay between valences. Our results bring clarity to the perceptual effects of losses versus gains and highlight the importance of considering the timeline of different biasing factors that influence decisions.
Frequency-dependent brightness enhancement, where a flickering light can appear twice as bright as an equiluminant constant light, has been reported to exist within the alpha (8–12 Hz) band. Could oscillatory neural activity be driving this perceptual effect? Here, in two experiments, human subjects reported which of two flickering stimuli were brighter. Strikingly, 4 Hz stimuli were reported as brighter more than 80% of the time when compared to all other tested frequencies, even though all stimuli were equiluminant and of equal temporal length. Electroencephalography recordings showed that inter-trial phase coherence (ITC) of theta (4 Hz) was: (1) Significantly greater than alpha, contralateral to the flickering stimulus; (2) Enhanced by the presence of a second ipsilateral 4 Hz flickering stimulus; and (3) Uniquely lateralized, unlike the alpha band. Importantly, on trials with two identical stimuli (i.e. 4 Hz vs 4 Hz), the brightness discrimination judgment could be predicted by the hemispheric balance in the amount of 4 Hz ITC. We speculate that the theta rhythm plays a distinct information transfer role, where its ability to share information between hemispheres via entrainment promotes a better processing of visual information to inform a discrimination decision.
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