Evidence map›Paper›PMID 35317408›Full record

ArticleBiological psychiatry global open science2021

Task-general efficiency of evidence accumulation as a computationally-defined neurocognitive trait: Implications for clinical neuroscience.

Alexander Weigard, Chandra Sripada

Open access · goldAbstract read
In one paragraph

Article in Biological psychiatry global open science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
5.7field-weighted citation impact, top 4% of its field
1 · What the graph read from 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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 40 citations in OpenAlex.

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  9. Model-based analysis of stop-signal data reveals robust neural and clinical correlates of evidence accumulation but not inhibition.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
    Article
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  12. From symptom-based heterogeneity to mechanism-based profiling in youth ADHD: the promise of computational psychiatry.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
    Review
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  17. Neurophysiology of Perceptual Decision-Making and Its Alterations in Attention-Deficit Hyperactivity Disorder.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Alexander WeigardDepartment of Psychiatry, University of Michigan.
Chandra SripadaDepartment of Psychiatry, University of Michigan.
University of Michigan · US

Funding

MULTIDISCIPLINARY ALCOHOLISM RESEARCH TRAINING PROGRAMT32AA007477 · NIAAA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Maureen A. Walton · 1990 to 2026
$7.4M
Impulsivity as Immaturity: Mapping Dysmaturation of the Brain's Control Architecture in Youth Externalizing PsychopathologyR01MH107741 · NIMH · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SRIPADA, CHANDRA SEKHAR · 2015 to 2019
$2.3M
NIAAA NIH HHS T32 AA007477NIMH NIH HHS R01 MH107741
6 · The paper itself

Abstract

Quantifying individual differences in higher-order cognitive functions is a foundational area of cognitive science that also has profound implications for research on psychopathology. For the last two decades, the dominant approach in these fields has been to attempt to fractionate higher-order functions into hypothesized components (e.g., "inhibition", "updating") through a combination of experimental manipulation and factor analysis. However, the putative constructs obtained through this paradigm have recently been met with substantial criticism on both theoretical and empirical grounds. Concurrently, an alternative approach has emerged focusing on parameters of formal computational models of cognition that have been developed in mathematical psychology. These models posit biologically plausible and experimentally validated explanations of the data-generating process for cognitive tasks, allowing them to be used to measure the latent mechanisms that underlie performance. One of the primary insights provided by recent applications of such models is that individual and clinical differences in performance on a wide variety of cognitive tasks, ranging from simple choice tasks to complex executive paradigms, are largely driven by efficiency of evidence accumulation (EEA), a computational mechanism defined by sequential sampling models. This review assembles evidence for the hypothesis that EEA is a central individual difference dimension that explains neurocognitive deficits in multiple clinical disorders and identifies ways in which in this insight can advance clinical neuroscience research. We propose that recognition of EEA as a major driver of neurocognitive differences will allow the field to make clearer inferences about cognitive abnormalities in psychopathology and their links to neurobiology.

Indexed as

cognitive controldiffusion modelexecutive functionlinear ballistic accumulatormathematical psychologytransdiagnostic risk

Identifiers

PMID35317408
PMCPMC8936715
OpenAlexW3138189545

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.