Choosing between equally valued options is a common conundrum, for which classical decision theories predicted a prolonged response time (RT). This contrasts with the notion that an optimal decision maker in a stable environment should make fast and random choices, as the outcomes are indifferent. Here, we characterize the neurocognitive processes underlying such voluntary decisions by integrating cognitive modelling of behavioral responses and EEG recordings in a probabilistic reward task. Human participants performed binary choices between pairs of unambiguous cues associated with identical reward probabilities at different levels. Higher reward probability accelerated RT, and participants chose one cue faster and more frequent over the o...
During perceptual decision-making tasks, centroparietal electroencephalographic (EEG) potentials rep...
International audienceMost decisions that we make build upon multiple streams of sensory evidence an...
Optimal decision making in complex environments requires dynamic learning from unexpected events. To...
Choosing between equally valued options is a common conundrum, for which classical decision theories...
Sequential sampling decision-making models have been successful in accounting for reaction time (RT)...
Humans (as well as animals) have an inherent tendency to seek out rewards and to avoid punishments. ...
The cognitive process and time course of quick human decision making was evaluated using reaction ti...
Decision-making in an uncertain environment is driven by two major needs: exploring the environment ...
BACKGROUND: Recent neuroimaging studies suggest that value-based decision-making may rely on mechani...
Deciding how long to keep waiting for future rewards is a nontrivial problem, especially when the ti...
<div><p>Understanding the cognitive and neural processes that underlie human decision making require...
Perceptual decision making is believed to be driven by the accumulation of sensory evidence followin...
Thesis: Ph. D. in Biomedical Engineering, Harvard-MIT Program in Health Sciences and Technology, 201...
Single-unit animal studies have consistently reported decision-related activity mirroring a process ...
At any given moment, the human brain receives a barrage of noisy sensory signals that convey importa...
During perceptual decision-making tasks, centroparietal electroencephalographic (EEG) potentials rep...
International audienceMost decisions that we make build upon multiple streams of sensory evidence an...
Optimal decision making in complex environments requires dynamic learning from unexpected events. To...
Choosing between equally valued options is a common conundrum, for which classical decision theories...
Sequential sampling decision-making models have been successful in accounting for reaction time (RT)...
Humans (as well as animals) have an inherent tendency to seek out rewards and to avoid punishments. ...
The cognitive process and time course of quick human decision making was evaluated using reaction ti...
Decision-making in an uncertain environment is driven by two major needs: exploring the environment ...
BACKGROUND: Recent neuroimaging studies suggest that value-based decision-making may rely on mechani...
Deciding how long to keep waiting for future rewards is a nontrivial problem, especially when the ti...
<div><p>Understanding the cognitive and neural processes that underlie human decision making require...
Perceptual decision making is believed to be driven by the accumulation of sensory evidence followin...
Thesis: Ph. D. in Biomedical Engineering, Harvard-MIT Program in Health Sciences and Technology, 201...
Single-unit animal studies have consistently reported decision-related activity mirroring a process ...
At any given moment, the human brain receives a barrage of noisy sensory signals that convey importa...
During perceptual decision-making tasks, centroparietal electroencephalographic (EEG) potentials rep...
International audienceMost decisions that we make build upon multiple streams of sensory evidence an...
Optimal decision making in complex environments requires dynamic learning from unexpected events. To...