ReviewNature neuroscience2016
Computational psychiatry as a bridge from neuroscience to clinical applications.
Review in Nature neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 469 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Computational Psychiatric Approach for Prognosis of Medication-Resistant Depression
Prediction of the Therapeutic Response in Depression Based on an Early Neuro-computational Modeling Assessment of Motivation
Who cites it
469 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The hierarchical taxonomy of psychopathology and the search for neurobiological substrates of mental illness: A systematic review and roadmap for future research.Journal of psychopathology and clinical science · 2024Pooled it
- Prior Expectations of Volatility Following Psychotherapy for Delusions: A Randomized Clinical Trial.JAMA network open · 2025Trial
- Individualized Functional Brain System Topologies and Major Depression: Relationships Among Patch Sizes and Clinical Profiles and Behavior.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2024Trial
- A core component of psychological therapy causes adaptive changes in computational learning mechanisms.Psychological medicine · 2024Trial
- Repetitive negative thinking is associated with conflict-related neural activity that modulates evidence accumulation.Journal of mood and anxiety disorders · 2026Article
- Dynamical system modeling in schizophrenia: a narrative review of computational psychiatry frameworks.Dialogues in clinical neuroscience · 2026Review
- The 'UPIC' cohort: a nationwide prospective study of mental health among adolescents and young adults in Sweden - a study protocol.BMJ open · 2026Article
- Temporal Dynamics of Reward Dysfunction in Psychiatric Disorders: Memory-Derived Value, Incentive Salience, Hedonic Impact, and Value Updating.Biological psychiatry global open science · 2026Review
- Decomposing response inhibition: A POMDP model.PLoS computational biology · 2026Article
- Rapid and reliable computational markers of decision-making for predicting daily smoking behavior and smoking cessation treatment outcomes.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Article
- Digital bioethics: exploring an emerging field.Medicine, health care, and philosophy · 2026Article
- Animal Models for Drug Discovery in Schizophrenia: A Critical View from a Clinical Perspective.Pharmaceutical medicine · 2026Review
- Effort and substance use: differentiating tobacco use through reinforcement learning of effort based decision making.Journal of computational neuroscience · 2026Article
- The choice-wide behavioral association study: data-driven identification of interpretable behavioral components.Nature communications · 2026Article
- Artificial Intelligence in Psychiatry: Five Decades of Progress and Persistent Translational Challenges.Psychiatric research and clinical practice · 2026Article
- Mood computational mechanisms underlying increased risk behavior in adolescent suicidal patients.eLife · 2026Article
- Computational mechanisms of learning and forgetting differentiate affective and substance use disorders.Molecular psychiatry · 2026Article
- Understanding anxiety through uncertainty quantification.British journal of psychology (London, England : 1953) · 2026Article
- The recoverability, reliability, and generalizability of reward processing parameters and relation to mental health symptoms.Psychological medicine · 2026Article
- Longitudinal analysis of decision-making deficits in binge-eating disorders using drift diffusion modeling.Appetite · 2026Article
409 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Translating advances in neuroscience into benefits for patients with mental illness presents enormous challenges because it involves both the most complex organ, the brain, and its interaction with a similarly complex environment. Dealing with such complexities demands powerful techniques. Computational psychiatry combines multiple levels and types of computation with multiple types of data in an effort to improve understanding, prediction and treatment of mental illness. Computational psychiatry, broadly defined, encompasses two complementary approaches: data driven and theory driven. Data-driven approaches apply machine-learning methods to high-dimensional data to improve classification of disease, predict treatment outcomes or improve treatment selection. These approaches are generally agnostic as to the underlying mechanisms. Theory-driven approaches, in contrast, use models that instantiate prior knowledge of, or explicit hypotheses about, such mechanisms, possibly at multiple levels of analysis and abstraction. We review recent advances in both approaches, with an emphasis on clinical applications, and highlight the utility of combining them.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.