Evidence map›Paper›PMID 26072028›Full record

ReviewNeuroscience and biobehavioral reviews2015

Neural mechanisms regulating different forms of risk-related decision-making: Insights from animal models.

Caitlin A Orsini, David E Moorman, Jared W Young, Barry Setlow, Stan B Floresco

Open access · greenAbstract readReview
In one paragraph

Review in Neuroscience and biobehavioral reviews, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
93citing papers in PubMed, 1 pooled it
8.7field-weighted citation impact, top 1% 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

93 citing papers in PubMed, 1 synthesis or guideline pooled it, 159 citations in OpenAlex.

  1. Pooled it
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  8. Review
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  11. Developmental Shifts in Amygdala Function.Current topics in behavioral neurosciences · 2025
    Review
  12. Article
  13. Article
  14. Review
  15. Sex differences in sensitivity to dopamine receptor manipulations of risk-based decision making in rats.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
    Article
  16. Article
  17. Article
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  19. Review
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33 more citing papers are in PubMed but not listed here.

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

5 authors at 5 institutions in 2 countries.

Caitlin A OrsiniDepartment of Psychiatry and Center for Addiction Research and Education, University of Florida College of Medicine, Gainesville, FL, United States.
David E MoormanDepartment of Psychological and Brain Sciences, University of Massachusetts, Amherst, MA, United States.
Jared W YoungDepartment of Psychiatry, University of California San Diego, United States; VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States.
Barry SetlowDepartment of Psychiatry and Center for Addiction Research and Education, University of Florida College of Medicine, Gainesville, FL, United States.
Stan B FlorescoDepartment of Psychology and Brain Research Center, University of British Columbia, Vancouver, BC, Canada. Electronic address: floresco@psych.ubc.ca.
Florida College · USMental Illness Research, Education and Clinical Centers · USUniversity of British Columbia · CAUniversity of Florida · USUniversity of Massachusetts Amherst · US

Funding

A model organism of brain circuitry and behavioral switching for bipolar disorderR01MH104344 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI YOUNG, JARED WILLIAM · 2014 to 2017
$1.7M
Neural mechanism of enduring cocaine effects on impulsive choiceR01DA024671 · NIDA · UNIVERSITY OF FLORIDA · PI SETLOW, BARRY · 2009 to 2013
$1.4M
Role of Prefrontal Networks in Addiction EndophenotypesR21DA032005 · NIDA · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI MOORMAN, DAVID E · 2011 to 2012
$356k
CIHR MOP 89861NIDA NIH HHS R01 DA024671NIDA NIH HHS R01-DA024671NIDA NIH HHS R21 DA032005NIDA NIH HHS R21-DA032005NIMH NIH HHS R01 MH104344NIMH NIH HHS R01-MH104344
6 · The paper itself

Abstract

Over the past 20 years there has been a growing interest in the neural underpinnings of cost/benefit decision-making. Recent studies with animal models have made considerable advances in our understanding of how different prefrontal, striatal, limbic and monoaminergic circuits interact to promote efficient risk/reward decision-making, and how dysfunction in these circuits underlies aberrant decision-making observed in numerous psychiatric disorders. This review will highlight recent findings from studies exploring these questions using a variety of behavioral assays, as well as molecular, pharmacological, neurophysiological, and translational approaches. We begin with a discussion of how neural systems related to decision subcomponents may interact to generate more complex decisions involving risk and uncertainty. This is followed by an overview of interactions between prefrontal-amygdala-dopamine and habenular circuits in regulating choice between certain and uncertain rewards and how different modes of dopamine transmission may contribute to these processes. These data will be compared with results from other studies investigating the contribution of some of these systems to guiding decision-making related to rewards vs. punishment. Lastly, we provide a brief summary of impairments in risk-related decision-making associated with psychiatric disorders, highlighting recent translational studies in laboratory animals.

Indexed as

Risk-TakingTranslational Research, BiomedicalAnimalsBrainDecision MakingHumansDecision makingDopamineLateral habenulaManiaNucleus accumbensPrefrontal cortexPunishmentUncertainty

Identifiers

PMID26072028
PMCPMC7913606
OpenAlexW2214549810

What OpenQuestion holds

Textmetadata
LicenceTDM
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.