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Published on: September 19, 2012
Neural Representation of Valenced and Generic Probability and Uncertainty
Jae-Chang Kim1, Lydia Hellrung2, Marcus Grueschow2
1Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, 8006 Zurich, Switzerland jaechang.kim@econ.uzh.ch phil.tobler@econ.uzh.ch.
None:
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.
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