Topic: motivational salience network

Asymmetry in choice patterns across rewarding and punishing contexts has long been observed in behavioural economics. Within existing theories of reinforcement learning, the mechanistic account of these behavioural differences is still debated. We propose that motivational salience - the degree of bottom-up attention attracted by a stimulus with relation to motivational value - offers a potential mechanism to modulate stimulus value updating and decision policy. In a probabilistic reversal learning task, we identified post-feedback signals from EEG and pupillometry that captured differential a