Differential roles of human striatum and amygdala in associative learning

Journal name:
Nature Neuroscience
Volume:
14,
Pages:
1250–1252
Year published:
DOI:
doi:10.1038/nn.2904
Received
Accepted
Published online

Although the human amygdala and striatum have both been implicated in associative learning, only the striatum's contribution has been consistently computationally characterized. Using a reversal learning task, we found that amygdala blood oxygen level–dependent activity tracked associability as estimated by a computational model, and dissociated it from the striatal representation of reinforcement prediction error. These results extend the computational learning approach from striatum to amygdala, demonstrating their complementary roles in aversive learning.

At a glance

Figures

  1. Experimental design and behavioral model fit.
    Figure 1: Experimental design and behavioral model fit.

    (a) Experiment timeline illustration. The acquisition phase consisted of presentations of the conditioned stimulus (CS+), which was partially associated with electric shock, and an unconditioned stimulus (CS−) that was not associated with shock. In the reversal phase, the reinforcement contingencies for the original conditioned and unconditioned stimuli were switched. (b) Average SCRs across subjects (red) and the best-fit associability trace (blue).

  2. Neural correlates of associability and prediction error term.
    Figure 2: Neural correlates of associability and prediction error term.

    (a) BOLD activity in the ventral striatum, but not in the amygdala, correlated with prediction error. (b) BOLD activity in the bilateral amygdala, but not in the ventral striatum, correlated with associability regressor (P < 0.05, SVC). The results are shown at uncorrected thresholds to display the full extent of the activation. (c) Differential representations of associability (α) and prediction error (δ) in striatum and amygdala BOLD activity (±s.e.m.) plotted as regression effect sizes (β values, arbitrary units).

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Author information

Affiliations

  1. Department of Psychology, New York University, New York, New York, USA.

    • Jian Li,
    • Elizabeth A Phelps &
    • Nathaniel D Daw
  2. Center for Neural Science, New York University, New York, New York, USA.

    • Jian Li,
    • Elizabeth A Phelps &
    • Nathaniel D Daw
  3. Departments of Psychiatry and Neuroscience, and Friedman Brain Institute, Mt. Sinai School of Medicine, New York, New York, USA.

    • Daniela Schiller
  4. Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, Maryland, USA.

    • Geoffrey Schoenbaum
  5. Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA.

    • Geoffrey Schoenbaum
  6. National Institute on Drug Abuse Intramural Research Program, Baltimore, Maryland, USA.

    • Geoffrey Schoenbaum

Contributions

E.A.P. and D.S. designed the study and conducted the experiment. J.L. and N.D.D. performed the data analysis. J.L., D.S., G.S., E.A.P. and N.D.D. interpreted the data and wrote the manuscript.

Competing financial interests

The authors declare no competing financial interests.

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Supplementary information

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  1. Supplementary Text and Figures (3 MB)

    Supplementary Figures 1–3, Supplementary Tables 1–5 and Supplementary Methods

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