Pattern analysis of neuroimaging data reveals novel insights on threat learning and extinction in humans

Augustin C Hennings; Samuel E Cooper; Jarrod A Lewis-Peacock; Joseph E Dunsmoor

doi:10.1016/j.neubiorev.2022.104918

Pattern analysis of neuroimaging data reveals novel insights on threat learning and extinction in humans

Neurosci Biobehav Rev. 2022 Nov:142:104918. doi: 10.1016/j.neubiorev.2022.104918. Epub 2022 Oct 15.

Authors

Augustin C Hennings¹, Samuel E Cooper², Jarrod A Lewis-Peacock³, Joseph E Dunsmoor⁴

Affiliations

¹ Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA; Institute for Neuroscience, University of Texas at Austin, Austin, TX, USA; Department of Psychiatry and Behavioral Sciences, Dell Medical School, University of Texas at Austin, Austin, TX, USA.
² Department of Psychiatry and Behavioral Sciences, Dell Medical School, University of Texas at Austin, Austin, TX, USA.
³ Institute for Neuroscience, University of Texas at Austin, Austin, TX, USA; Department of Psychiatry and Behavioral Sciences, Dell Medical School, University of Texas at Austin, Austin, TX, USA; Center for Learning and Memory, Department of Neuroscience, University of Texas at Austin, Austin, TX, USA; Department of Psychology, University of Texas at Austin, Austin, TX, USA.
⁴ Institute for Neuroscience, University of Texas at Austin, Austin, TX, USA; Department of Psychiatry and Behavioral Sciences, Dell Medical School, University of Texas at Austin, Austin, TX, USA; Center for Learning and Memory, Department of Neuroscience, University of Texas at Austin, Austin, TX, USA. Electronic address: joseph.dunsmoor@austin.utexas.edu.

PMID: 36257347
DOI: 10.1016/j.neubiorev.2022.104918

Abstract

Several decades of rodent neurobiology research have identified a network of brain regions that support Pavlovian threat conditioning and extinction, focused predominately on the amygdala, hippocampus, and medial prefrontal cortex (mPFC). Surprisingly, functional magnetic resonance imaging (fMRI) studies have shown inconsistent evidence for these regions while humans undergo threat conditioning and extinction. In this review, we suggest that translational neuroimaging efforts have been hindered by reliance on traditional univariate analysis of fMRI. Whereas univariate analyses average activity across voxels in a given region, multivariate pattern analyses (MVPA) leverage the information present in spatial patterns of activity. MVPA therefore provides a more sensitive analysis tool to translate rodent neurobiology to human neuroimaging. We review human fMRI studies using MVPA that successfully bridge rodent models of amygdala, hippocampus, and mPFC function during Pavlovian learning. We also highlight clinical applications of these information-sensitive multivariate analyses. In sum, we advocate that the field should consider adopting a variety of multivariate approaches to help bridge cutting-edge research on the neuroscience of threat and anxiety.

Keywords: Amygdala; Extinction; FMRI; Fear; Hippocampus; MPFC; MVPA; Univariate.

Publication types

Review
Research Support, U.S. Gov't, Non-P.H.S.
Research Support, N.I.H., Extramural

MeSH terms

Amygdala / diagnostic imaging
Conditioning, Classical
Extinction, Psychological*
Fear*
Humans
Magnetic Resonance Imaging / methods
Neuroimaging
Prefrontal Cortex / diagnostic imaging

Abstract

Publication types

MeSH terms

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