Cited by 3Neural and Behavioral Psychology StudiesAnxiety, Depression, Psychometrics, Treatment, Cognitive ProcessesMental Health and Psychiatry

Addressing altered anticipation as a transdiagnostic target through computational psychiatry

Open access
Sepúlveda, Pradyumna, Aitsahalia, Ines, Kumar, Krishan, Atkin, Tobias, Iigaya, Kiyohito·2025·Biological Psychiatry Cognitive Neuroscience and Neuroimaging

Abstract

Anticipation of future experiences is a crucial cognitive function impacted in various psychiatric conditions. Despite significant research advancements, the mechanisms that underlie altered anticipation remain poorly understood, and effective targeted treatments are largely lacking. In this review, we propose an integrated computational psychiatry approach to addressing these challenges. We begin by outlining how altered anticipation presents across different psychiatric conditions, including schizophrenia, major depressive disorder, anxiety disorders, substance use disorders, and eating disorders, and summarizing the insights that have been gained from extensive research using self-report scales and task-based neuroimaging despite notable limitations. Then, we explore how emerging computational modeling approaches, such as reinforcement learning and anticipatory utility theory, could overcome these limitations and offer deeper insights into underlying mechanisms and individual variations. We propose that integrating these interdisciplinary methodologies can offer comprehensive transdiagnostic insights, aiding the discovery of new therapeutic targets and advancing precision psychiatry.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.bpsc.2025.02.014

Cites

187 of 187 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Altered-anticipation and anticipatory-utility frameworks propose that attenuated precision on reward-error signals may reduce anticipatory pleasure and motivational drive.

    “Recent altered-anticipation and anticipatory-utility frameworks propose that such attenuated precision on reward-error signals may reduce anticipatory pleasure and motivational drive (35).”

    From Predictive coding and neurocomputational psychiatry: a mechanistic framework for understanding mental disorders (2026) · cites this paper as [35]

    The Computational modeling approaches section (page not available) says prediction errors from advance reward information boost anticipatory utility, supporting the proposed link to anticipatory pleasure. It does not describe attenuated precision on reward-error signals or say that such attenuation reduces motivational drive. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. [126]Sutton RS, Barto AG. Reinforcement Learning, second edition: An Introduction. MIT Press; 2018. 549 p.

Authors
Sepúlveda, P., Aitsahalia, I., Kumar, K., Atkin, T., & Iigaya, K.
Affiliations
Columbia University Irving Medical Center (US)
Corresponding author
  • Sepúlveda, Pradyumna
  • Iigaya, Kiyohito
Venue
Biological Psychiatry Cognitive Neuroscience and Neuroimaging
Publisher
Elsevier BV
Published
2025-09
Volume
10
Issue
9
Pages
903-917
ISSN
2451-9022 (ISSN-L)
OpenAlex
W4408223864
Cited by
3
References
186
Citations by year
2026: 2 · 2025: 1
FWCI
0.19
Type
journal article
Language
en
Open access
Locations
  • Biological Psychiatry Cognitive Neuroscience and Neuroimaging (acceptedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • OSF Preprints (OSF Preprints) (submittedVersion, cc-by)
Funders
  • NIH (R01MH136214)
  • NSF (2022342390)
  • Leon Levy Foundation
  • National Alliance for Research on Schizophrenia and Depression
  • Brain and Behavior Research Foundation
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
  • Social Sciences › Arts and Humanities › Philosophy › Mental Health and Psychiatry
Keywords
anticipation, computational psychiatry, transdiagnostic mechanisms, reinforcement learning, schizophrenia, major depressive disorder, anxiety disorders, substance use disorders, eating disorders, precision psychiatry, therapeutic target
MeSH terms
Mental Disorders, Brain, Humans, Psychiatry, Anticipation, Psychological

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review