Statistical learning shapes pain perception and prediction independently of external cues

Author:

Onysk Jakub12ORCID,Gregory Nicholas1,Whitefield Mia1,Jain Maeghal1,Turner Georgia13,Seymour Ben45ORCID,Mancini Flavia1ORCID

Affiliation:

1. Computational and Biological Learning Unit, Department of Engineering, University of Cambridge

2. Applied Computational Psychiatry Lab, Max Planck Centre for Computational Psychiatry and Ageing Research, Queen Square Institute of Neurology and Mental Health Neuroscience Department, Division of Psychiatry, University College London

3. MRC Cognition and Brain Sciences Unit, University of Cambridge

4. Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, Headington

5. Center for Information and Neural Networks (CiNet)

Abstract

The placebo and nocebo effects highlight the importance of expectations in modulating pain perception, but in everyday life we don’t need an external source of information to form expectations about pain. The brain can learn to predict pain in a more fundamental way, simply by experiencing fluctuating, non-random streams of noxious inputs, and extracting their temporal regularities. This process is called statistical learning. Here, we address a key open question: does statistical learning modulate pain perception? We asked 27 participants to both rate and predict pain intensity levels in sequences of fluctuating heat pain. Using a computational approach, we show that probabilistic expectations and confidence were used to weigh pain perception and prediction. As such, this study goes beyond well-established conditioning paradigms associating non-pain cues with pain outcomes, and shows that statistical learning itself shapes pain experience. This finding opens a new path of research into the brain mechanisms of pain regulation, with relevance to chronic pain where it may be dysfunctional.

Funder

Medical Research Council

Wellcome Trust

Versus Arthritis

IITP

University of Cambridge Research Computing Service

NIHR Oxford Health BRC

Publisher

eLife Sciences Publications, Ltd

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