Asymmetric representation of aversive prediction errors in Pavlovian threat conditioning.

Ojala, Karita E; Tzovara, Athina; Poser, Benedikt A; Lutti, Antoine; Bach, Dominik R (2022). Asymmetric representation of aversive prediction errors in Pavlovian threat conditioning. NeuroImage, 263, p. 119579. Elsevier 10.1016/j.neuroimage.2022.119579

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Survival in biological environments requires learning associations between predictive sensory cues and threatening outcomes. Such aversive learning may be implemented through reinforcement learning algorithms that are driven by the signed difference between expected and encountered outcomes, termed prediction errors (PEs). While PE-based learning is well established for reward learning, the role of putative PE signals in aversive learning is less clear. Here, we used functional magnetic resonance imaging in humans (21 healthy men and women) to investigate the neural representation of PEs during maintenance of learned aversive associations. Four visual cues, each with a different probability (0, 33, 66, 100%) of being followed by an aversive outcome (electric shock), were repeatedly presented to participants. We found that neural activity at omission (US-) but not occurrence of the aversive outcome (US+) encoded PEs in the medial prefrontal cortex. More expected omission of aversive outcome was associated with lower neural activity. No neural signals fulfilled axiomatic criteria, which specify necessary and sufficient components of PE signals, for signed PE representation in a whole-brain search or in a-priori regions of interest. Our results might suggest that, different from reward learning, aversive learning does not involve signed PE signals that are represented within the same brain region for all conditions.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Institute of Computer Science (INF) > Cognitive Computational Neuroscience (CCN)
08 Faculty of Science > Institute of Computer Science (INF)

UniBE Contributor:

Tzovara, Athina

Subjects:

000 Computer science, knowledge & systems
500 Science > 510 Mathematics

ISSN:

1095-9572

Publisher:

Elsevier

Language:

English

Submitter:

Pubmed Import

Date Deposited:

24 Aug 2022 13:59

Last Modified:

13 Mar 2024 13:16

Publisher DOI:

10.1016/j.neuroimage.2022.119579

PubMed ID:

35995374

Uncontrolled Keywords:

aversive prediction errors axiomatic conditions fMRI reinforcement learning threat learning

BORIS DOI:

10.48350/172251

URI:

https://boris.unibe.ch/id/eprint/172251

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