ArticleBiological psychiatry. Cognitive neuroscience and neuroimaging2016
A Roadmap for the Development of Applied Computational Psychiatry.
Article in Biological psychiatry. Cognitive neuroscience and neuroimaging, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
What it found
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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
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Who cites it
53 citing papers in PubMed, 114 citations in OpenAlex.
- Reliability of computational versus noncomputational metrics of working memory and episodic memory in serious mental illness.Journal of psychopathology and clinical science · 2026Article
- The recoverability, reliability, and generalizability of reward processing parameters and relation to mental health symptoms.Psychological medicine · 2026Article
- Early reduction in aversive Pavlovian bias as a mediator of anhedonia improvement during Behavioural Activation in realistic treatment settings.PLoS computational biology · 2026Observational
- Digital mandala coloring as a public mental health tool: psychophysiological benefits and the mediating role of flow in anxiety reduction among university students.Frontiers in public health · 2026Article
- Development and Piloting of Co.Ge.: A Web-Based Digital Platform for Generative and Clinical Cognitive Assessment.Journal of personalized medicine · 2025Article
- Longitudinal evolution of the transdiagnostic prodrome to severe mental disorders: a dynamic temporal network analysis informed by natural language processing and electronic health records.Molecular psychiatry · 2025Article
- A Foraging-Theory-Based Model Captures the Spectrum of Human Behavioral Diversity in Sequential Decision Making.bioRxiv : the preprint server for biology · 2025Article
- Computational Perspectives on Cognition in Anorexia Nervosa: A Systematic Review.Computational psychiatry (Cambridge, Mass.) · 2025Review
- Editorial: Executive functions in psychiatric science, clinical practice and beyond: A Transdiagnostic Window on Functional Heterogeneity.Frontiers in psychiatry · 2025Article
- Increasing the Construct Validity of Computational Phenotypes of Mental Illness Through Active Inference and Brain Imaging.Brain sciences · 2024Review
- Reinforcement-Learning-Informed Queries Guide Behavioral Change.Clinical psychological science : a journal of the Association for Psychological Science · 2024Article
- Revisiting the role of computational neuroimaging in the era of integrative neuroscience.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024Review
- Test-retest reliability of reinforcement learning parameters.Behavior research methods · 2024Article
- Dynamic computational phenotyping of human cognition.Nature human behaviour · 2024Article
- Different components of cognitive-behavioral therapy affect specific cognitive mechanisms.Science advances · 2024Article
- Latent-state and model-based learning in PTSD.Trends in neurosciences · 2024Review
- Closing the loop in psychiatric deep brain stimulation: physiology, psychometrics, and plasticity.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024Review
- Current status, challenges and future prospects in computational psychiatry: a narrative review.Consortium psychiatricum · 2023Review
- Identifying Transdiagnostic Mechanisms in Mental Health Using Computational Factor Modeling.Biological psychiatry · 2023Review
- Reliability of Decision-Making and Reinforcement Learning Computational Parameters.Computational psychiatry (Cambridge, Mass.) · 2023Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 3 countries.
Funding
Abstract
backgroundComputational psychiatry is a burgeoning field that utilizes mathematical approaches to investigate psychiatric disorders, derive quantitative predictions, and integrate data across multiple levels of description. Computational psychiatry has already led to many new insights into the neurobehavioral mechanisms that underlie several psychiatric disorders, but its usefulness from a clinical standpoint is only now starting to be considered.
methodsExamples of computational psychiatry are highlighted, and a phase-based pipeline for the development of clinical computational-psychiatry applications is proposed, similar to the phase-based pipeline used in drug development. It is proposed that each phase has unique endpoints and deliverables, which will be important milestones to move tasks, procedures, computational models, and algorithms from the laboratory to clinical practice.
resultsApplication of computational approaches should be tested on healthy volunteers in Phase I, transitioned to target populations in Phase IB and Phase IIA, and thoroughly evaluated using randomized clinical trials in Phase IIB and Phase III. Successful completion of these phases should be the basis of determining whether computational models are useful tools for prognosis, diagnosis, or treatment of psychiatric patients.
conclusionsA new type of infrastructure will be necessary to implement the proposed pipeline. This infrastructure should consist of groups of investigators with diverse backgrounds collaborating to make computational psychiatry relevant for the clinic.
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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.