TY  - JOUR
PY  - 2021//
TI  - Neural mechanisms of human decision-making
JO  - Cognitive, affective and behavioral neuroscience
A1  - Nair, Ananta
A1  - Krueger, Kai
A1  - Herd, Seth
A1  - Mollick, Jessica
A1  - O'Reilly, Randall
SP  - ePub
EP  - ePub
VL  - ePub
IS  - ePub
N2  - 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.<p />  <p>Language: en</p>
LA  - en
SN  - 1530-7026
UR  - http://dx.doi.org/10.3758/s13415-020-00842-0
ID  - ref1
ER  -