ArticleeLife2020
A circuit mechanism for decision-making biases and NMDA receptor hypofunction.
Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 28 citations in OpenAlex.
- Premature commitment to uncertain decisions during human NMDA receptor hypofunction.Nature communications · 2022Trial
- Habenula-ventral tegmental area functional coupling and risk aversion in humans.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Disentangling sources of variability in decision-making.Nature reviews. Neuroscience · 2025Review
- Effects of Ketamine on Frontoparietal Interactions in a Rule-Based Antisaccade Task in Macaque Monkeys.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Decision-Making, Pro-variance Biases and Mood-Related Traits.Computational psychiatry (Cambridge, Mass.) · 2024Article
- Understanding mental health through computers: An introduction to computational psychiatry.Frontiers in psychiatry · 2023Review
- The promise of a model-based psychiatry: building computational models of mental ill health.The Lancet. Digital health · 2022Review
- Article
- Aberrant maturation and connectivity of prefrontal cortex in schizophrenia-contribution of NMDA receptor development and hypofunction.Molecular psychiatry · 2022Review
- Understanding Motor Abnormalities in Psychiatric Disorders as Altered Sensorimotor Processing.Biological psychiatry global open science · 2021Article
- Article
- A Diversity of Intrinsic Timescales Underlie Neural Computations.Frontiers in neural circuits · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
Decision-making biases can be features of normal behaviour, or deficits underlying neuropsychiatric symptoms. We used behavioural psychophysics, spiking-circuit modelling and pharmacological manipulations to explore decision-making biases during evidence integration. Monkeys showed a pro-variance bias (PVB): a preference to choose options with more variable evidence. The PVB was also present in a spiking circuit model, revealing a potential neural mechanism for this behaviour. To model possible effects of NMDA receptor (NMDA-R) antagonism on this behaviour, we simulated the effects of NMDA-R hypofunction onto either excitatory or inhibitory neurons in the model. These were then tested experimentally using the NMDA-R antagonist ketamine, a pharmacological model of schizophrenia. Ketamine yielded an increase in subjects' PVB, consistent with lowered cortical excitation/inhibition balance from NMDA-R hypofunction predominantly onto excitatory neurons. These results provide a circuit-level mechanism that bridges across explanatory scales, from the synaptic to the behavioural, in neuropsychiatric disorders where decision-making biases are prominent.
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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.