Abstract
The ability to use environmental stimuli to predict impending harm
is critical for survival. Such predictions should be available as
early as they are reliable. In pavlovian conditioning, chains of
successively earlier predictors are studied in terms of higher-order
relationships, and have inspired computational theories such as temporal
difference learning1. However, there is at present no adequate neurobiological
account of how this learning occurs. Here, in a functional magnetic
resonance imaging (fMRI) study of higher-order aversive conditioning,
we describe a key computational strategy that humans use to learn
predictions about pain. We show that neural activity in the ventral
striatum and the anterior insula displays a marked correspondence
to the signals for sequential learning predicted by temporal difference
models. This result reveals a flexible aversive learning process
ideally suited to the changing and uncertain nature of real-world
environments. Taken with existing data on reward learning2, our results
suggest a critical role for the ventral striatum in integrating complex
appetitive and aversive predictions to coordinate behaviour.
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