Evidence map›Paper›PMID 30341621›Full record

ReviewCognitive, affective & behavioral neuroscience2019

Deconstructing value-based decision making via temporally selective manipulation of neural activity: Insights from rodent models.

Caitlin A Orsini, Caesar M Hernandez, Jennifer L Bizon, Barry Setlow

Open access · bronzeAbstract readReview
In one paragraph

Review in Cognitive, affective & behavioral neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

15 citing papers in PubMed, 26 citations in OpenAlex.

  1. Trial
  2. Review
  3. Circuit and Cell-Specific Contributions to Decision Making Involving Risk of Explicit Punishment in Male and Female Rats.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
    Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Reward/Punishment-Based Decision Making in Rodents.Current protocols in neuroscience · 2020
    Article
  14. Article
  15. Reward systems, cognition, and emotion: Introduction to the special issue.Cognitive, affective & behavioral neuroscience · 2019
    Article
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

4 authors at 2 institutions in 1 country.

Caitlin A OrsiniDepartment of Psychiatry, University of Florida College of Medicine, P.O. Box 100256, Gainesville, FL, 32610-0256, USA. orsini@ufl.edu.
Caesar M HernandezDepartment of Neuroscience, University of Florida, Gainesville, FL, 32610, USA.
Jennifer L BizonDepartment of Psychiatry, University of Florida College of Medicine, P.O. Box 100256, Gainesville, FL, 32610-0256, USA.
Barry SetlowDepartment of Psychiatry, University of Florida College of Medicine, P.O. Box 100256, Gainesville, FL, 32610-0256, USA.
Florida College · USUniversity of Florida · US

Funding

Neural Mechanisms of Cognitive Decline in AgingR01AG029421 · NIA · UNIVERSITY OF FLORIDA · PI BIZON, JENNIFER LYNN · 2007 to 2018
$3.1M
Decision making and basolateral amygdala dysfunction in agingRF1AG060778 · NIA · UNIVERSITY OF FLORIDA · PI BIZON, JENNIFER LYNN, FRAZIER, CHARLES J · 2018 to 2018
$3.0M
Risk taking and cocaine use: interactions, mechanisms, and therapeutic targetsR01DA036534 · NIDA · UNIVERSITY OF FLORIDA · PI SETLOW, BARRY · 2015 to 2019
$1.7M
Neural circuits and mechanisms underlying maladaptive risk-taking following cocaine self-administrationR00DA041493 · NIDA · UNIVERSITY OF TEXAS AT AUSTIN · PI ORSINI, CAITLIN ANNE · 2019 to 2021
$745k
Neural circuits and mechanisms underlying maladaptive risk-taking following cocaine self-administrationK99DA041493 · NIDA · UNIVERSITY OF FLORIDA · PI ORSINI, CAITLIN ANNE · 2017 to 2018
$232k
NIA NIH HHS R01 AG029421NIA NIH HHS RF1 AG060778NIDA NIH HHS K99 DA041493NIDA NIH HHS R00 DA041493NIDA NIH HHS R01 DA036534
6 · The paper itself

Abstract

The ability to choose among options that differ in their rewards and costs (value-based decision making) has long been a topic of interest for neuroscientists, psychologists, and economists alike. This is likely because this is a cognitive process in which all animals (including humans) engage on a daily basis, be it routine (which road to take to work) or consequential (which graduate school to attend). Studies of value-based decision making (particularly at the preclinical level) often treat it as a uniform process. The results of such studies have been invaluable for our understanding of the brain substrates and neurochemical systems that contribute to decision making involving a range of different rewards and costs. Value-based decision making is not a unitary process, however, but is instead composed of distinct cognitive operations that function in concert to guide choice behavior. Within this conceptual framework, it is therefore important to consider that the known neural substrates supporting decision making may contribute to temporally distinct and dissociable components of the decision process. This review will describe this approach for investigating decision making, drawing from published studies that have used techniques that allow temporal dissection of the decision process, with an emphasis on the literature in animal models. The review will conclude with a discussion of the implications of this work for understanding pathological conditions that are characterized by impaired decision making.

Indexed as

Models, AnimalRewardAnimalsBasolateral Nuclear ComplexCorpus StriatumDecision MakingHumansMesencephalonPrefrontal CortexRodentiaAmygdalaDecision makingDopamineOptogeneticsPrefrontal cortex

Identifiers

PMID30341621
PMCPMC6472996
OpenAlexW2895991016

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.