Financial gain- and loss-related BOLD signals in the human ventral tegmental area and substantia nigra pars compacta

Neural Representation of Valenced and Generic Probability and Uncertainty

Representing the probability and uncertainty of outcomes facilitates adaptive behavior by allowing organisms to prepare in advance and devote attention to relevant events. Probability and uncertainty are often studied only for valenced (appetitive or aversive) outcomes, raising the question of whether the identified neural machinery also processes the probability and uncertainty of motivationally neutral outcomes. Here, we aimed to dissociate valenced from valence-independent (i.e., generic) probability (p; maximum at p = 1) and uncertainty (maximum at p = 0.5) signals using human neuroimaging. In a Pavlovian task (n = 41; 19 females), different cues predicted appetitive, aversive, or neutral liquids with different probabilities (p = 0, p = 0.5, p = 1). Cue-elicited motor responses accelerated, and pupil sizes increased primarily for cues that predicted valenced liquids with higher probability. For neutral liquids, uncertainty rather than probability tended to accelerate cue-induced responding and decrease pupil size. At the neural level, generic uncertainty signals were limited to the occipital cortex, while generic probability also activated the anterior ventromedial prefrontal cortex. These generic probability and uncertainty signals contrasted with cue-induced responses that only encoded the probability and uncertainty of valenced liquids in medial prefrontal, insular, and occipital cortices. Our findings show a behavioral and neural dissociation of generic and valenced signals. Thus, some parts of the brain keep track of motivational charge while others do not, highlighting the need and usefulness of characterizing the exact nature of learned representations.

Instructed motivational states bias reinforcement learning and memory formation

Motivation influences goals, decisions, and memory formation. Imperative motivation links urgent goals to actions, narrowing the focus of attention and memory. Conversely, interrogative motivation integrates goals over time and space, supporting rich memory encoding for flexible future use. We manipulated motivational states via cover stories for a reinforcement learning task: The imperative group imagined executing a museum heist, whereas the interrogative group imagined planning a future heist. Participants repeatedly chose among four doors, representing different museum rooms, to sample trial-unique paintings with variable rewards (later converted to bonus payments). The next day, participants performed a surprise memory test. Crucially, only the cover stories differed between the imperative and interrogative groups; the reinforcement learning task was identical, and all participants had the same expectations about how and when bonus payments would be awarded. In an initial sample and a preregistered replication, we demonstrated that imperative motivation increased exploitation during reinforcement learning. Conversely, interrogative motivation increased directed (but not random) exploration, despite the cost to participants' earnings. At test, the interrogative group was more accurate at recognizing paintings and recalling associated values. In the interrogative group, higher value paintings were more likely to be remembered; imperative motivation disrupted this effect of reward modulating memory. Overall, we demonstrate that a prelearning motivational manipulation can bias learning and memory, bearing implications for education, behavior change, clinical interventions, and communication.

Financial gain- and loss-related BOLD signals in the human ventral tegmental area and substantia nigra pars compacta

Neurons in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNC) play central roles in reward-related behaviours. Nonhuman animal studies suggest that these neurons also process aversive events. However, our understanding of how the human VTA and SNC responds to such events is limited and has been hindered by the technical challenge of using functional magnetic resonance imaging (fMRI) to investigate a small structure where the signal is particularly vulnerable to physiological noise. Here we show, using methods optimized specifically for the midbrain (including high-resolution imaging, a novel registration protocol, and physiological noise modelling), a BOLD (blood-oxygen-level dependent) signal to both financial gain and loss in the VTA and SNC, along with a response to nil outcomes that are better or worse than expected in the VTA. Taken together, these findings suggest that the human VTA and SNC are involved in the processing of both appetitive and aversive financial outcomes in humans.