Neural Mechanisms of Human Decision-Making

Autor: Randall C. O'Reilly, Jessica Mollick, Ananta Nair, Kai A. Krueger, Seth A. Herd
Rok vydání: 2021
Předmět:
Zdroj: Cognitive, Affective, & Behavioral Neuroscience. 21:35-57
ISSN: 1531-135X
1530-7026
Popis: We present a theory and neural network model of the neural mechanisms underlying human decision-making. We propose a detailed model of the interaction between brain regions, under a proposer-predictor-actor-critic​ ​framework. This theory is based on detailed animal data and theories of action-selection. Those theories are adapted to serial operation to bridge levels of analysis and explain human decision-making. Task-relevant areas of cortex propose a candidate plan using fast, model-free, parallel neural computations. Other areas of cortex and medial temporal lobe can then predict​ likely outcomes of that plan in this situation. This optional prediction- (or model-) based computation can produce better accuracy and generalization, at the expense of speed. Next, linked regions of basal ganglia act​ to accept or reject the proposed plan based on its reward history in similar contexts. If that plan is rejected, the process repeats to consider a new option. The reward-prediction system acts as a critic​ to determine the value of the outcome relative to expectations and produce dopamine as a training signal for cortex and basal ganglia. By operating sequentially and hierarchically, the same mechanisms previously proposed for animal action-selection could explain the most complex human plans and decisions. We discuss explanations of model-based decisions, habitization, and risky behavior based on the computational model.
Databáze: OpenAIRE
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