A core component of psychological therapy causes adaptive changes in computational learning mechanisms.

Computational psychiatry distancing emotion regulation psychotherapy reinforcement learning

Journal

Psychological medicine
ISSN: 1469-8978
Titre abrégé: Psychol Med
Pays: England
ID NLM: 1254142

Informations de publication

Date de publication:
08 Jun 2023
Historique:
medline: 8 6 2023
pubmed: 8 6 2023
entrez: 8 6 2023
Statut: aheadofprint

Résumé

Cognitive distancing is an emotion regulation strategy commonly used in psychological treatment of various mental health disorders, but its therapeutic mechanisms are unknown. 935 participants completed an online reinforcement learning task involving choices between pairs of symbols with differing reward contingencies. Half (49.1%) of the sample was randomised to a cognitive self-distancing intervention and were trained to regulate or 'take a step back' from their emotional response to feedback throughout. Established computational ( Cognitive distancing improved task performance, including when participants were later tested on novel combinations of symbols without feedback. Group differences in computational model-derived parameters revealed that cognitive distancing resulted in clearer representations of option values (estimated 0.17 higher inverse temperatures). Simultaneously, distancing caused increased sensitivity to negative feedback (estimated 19% higher loss learning rates). Exploratory analyses suggested this resulted from an evolving shift in strategy by distanced participants: initially, choices were more determined by expected value differences between symbols, but as the task progressed, they became more sensitive to negative feedback, with evidence for a difference strongest by the end of training. Adaptive effects on the computations that underlie learning from reward and loss may explain the therapeutic benefits of cognitive distancing. Over time and with practice, cognitive distancing may improve symptoms of mental health disorders by promoting more effective engagement with negative information.

Sections du résumé

BACKGROUND BACKGROUND
Cognitive distancing is an emotion regulation strategy commonly used in psychological treatment of various mental health disorders, but its therapeutic mechanisms are unknown.
METHODS METHODS
935 participants completed an online reinforcement learning task involving choices between pairs of symbols with differing reward contingencies. Half (49.1%) of the sample was randomised to a cognitive self-distancing intervention and were trained to regulate or 'take a step back' from their emotional response to feedback throughout. Established computational (
RESULTS RESULTS
Cognitive distancing improved task performance, including when participants were later tested on novel combinations of symbols without feedback. Group differences in computational model-derived parameters revealed that cognitive distancing resulted in clearer representations of option values (estimated 0.17 higher inverse temperatures). Simultaneously, distancing caused increased sensitivity to negative feedback (estimated 19% higher loss learning rates). Exploratory analyses suggested this resulted from an evolving shift in strategy by distanced participants: initially, choices were more determined by expected value differences between symbols, but as the task progressed, they became more sensitive to negative feedback, with evidence for a difference strongest by the end of training.
CONCLUSIONS CONCLUSIONS
Adaptive effects on the computations that underlie learning from reward and loss may explain the therapeutic benefits of cognitive distancing. Over time and with practice, cognitive distancing may improve symptoms of mental health disorders by promoting more effective engagement with negative information.

Identifiants

pubmed: 37288530
doi: 10.1017/S0033291723001587
pii: S0033291723001587
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-11

Subventions

Organisme : Wellcome Trust
ID : 206691
Pays : United Kingdom

Auteurs

Quentin Dercon (Q)

MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
UCL Institute of Mental Health, University College London, London, UK.

Sara Z Mehrhof (SZ)

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

Timothy R Sandhu (TR)

MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
Department of Psychology, University of Cambridge, Cambridge, UK.

Caitlin Hitchcock (C)

MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australia.

Rebecca P Lawson (RP)

MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
Department of Psychology, University of Cambridge, Cambridge, UK.

Diego A Pizzagalli (DA)

Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA.

Tim Dalgleish (T)

MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
Cambridgeshire and Peterborough NHS Foundation Trust, Cambridgeshire, UK.

Camilla L Nord (CL)

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

Classifications MeSH