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Nat Neurosci. 2014 Nov;17(11):1607-12. doi: 10.1038/nn.3832. Epub 2014 Oct 5.

Representation of aversive prediction errors in the human periaqueductal gray.

Author information

1
1] Department of Psychology and Neuroscience, University of Colorado, Boulder, Boulder, Colorado, USA. [2] PERFORM Centre, Concordia University, Montreal, Quebec, Canada.
2
Department of Psychology, Columbia University, New York, New York, USA.
3
Center for Neural Science, New York University, New York, New York, USA.
4
Department of Psychology and Neuroscience, University of Colorado, Boulder, Boulder, Colorado, USA.
5
1] Department of Psychology, Columbia University, New York, New York, USA. [2] Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

Abstract

Pain is a primary driver of learning and motivated action. It is also a target of learning, as nociceptive brain responses are shaped by learning processes. We combined an instrumental pain avoidance task with an axiomatic approach to assessing fMRI signals related to prediction errors (PEs), which drive reinforcement-based learning. We found that pain PEs were encoded in the periaqueductal gray (PAG), a structure important for pain control and learning in animal models. Axiomatic tests combined with dynamic causal modeling suggested that ventromedial prefrontal cortex, supported by putamen, provides an expected value-related input to the PAG, which then conveys PE signals to prefrontal regions important for behavioral regulation, including orbitofrontal, anterior mid-cingulate and dorsomedial prefrontal cortices. Thus, pain-related learning involves distinct neural circuitry, with implications for behavior and pain dynamics.

PMID:
25282614
PMCID:
PMC4213247
DOI:
10.1038/nn.3832
[Indexed for MEDLINE]
Free PMC Article

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