Evidence map›Paper›PMID 22134477›Full record

ReviewPsychopharmacology2012

Reversal learning as a measure of impulsive and compulsive behavior in addictions.

Alicia Izquierdo, J David Jentsch

Open access · greenAbstract readReview
In one paragraph

Review in Psychopharmacology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 182 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
182citing papers in PubMed, 1 pooled it
12.4field-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

182 citing papers in PubMed, 1 synthesis or guideline pooled it, 298 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Trial
  5. Trial
  6. Trial
  7. Trial
  8. Trial
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

122 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

2 authors at 2 institutions in 1 country.

Alicia IzquierdoDepartment of Psychology, California State University, Los Angeles, 5151 State University Drive, Los Angeles, CA 90032, USA. aizquie@calstatela.edu
J David Jentsch
California State University Los Angeles · USUniversity of California, Los Angeles · US

Funding

Research Initiative for Scientific Enhancement (RISE)R25GM061331 · NIGMS · CALIFORNIA STATE UNIVERSITY LOS ANGELES · PI FOSTER, KRISHNA L · 2000 to 2021
$33.1M
Translational Research to Enhance Cognitive ControlP50MH077248 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI MCCRACKEN, JAMES T. · 2006 to 2011
$9.2M
NEUROCHEMISTRY OF MODAFINIL-MA INTERACTION IN RAT BRAINP20DA022539 · NIDA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LONDON, EDYTHE DANICK · 2006 to 2009
$2.9M
Translational Models of Memory and Cognitive Control (Component 5 of 8)RL1MH083270 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI JENTSCH, J. DAVID · 2007 to 2011
$2.6M
Consortium for Neuropsychiatric Phenomics-Coordinating Center (1 of 8)UL1DE019580 · NIDCR · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BILDER, ROBERT M · 2008 to 2011
$1.9M
Methamphetamine effect on cognitive flexibilitySC2MH087974 · NIMH · CALIFORNIA STATE UNIVERSITY LOS ANGELES · PI IZQUIERDO, ALICIA · 2009 to 2011
$432k
NIDA NIH HHS P20 DA022539NIDA NIH HHS P20-DA022539NIDCR NIH HHS UL1 DE019580NIDCR NIH HHS UL1-DE019580NIGMS NIH HHS R25 GM061331NIGMS NIH HHS R25 GM61331NIMH NIH HHS 1SC2MH087974NIMH NIH HHS P50 MH077248NIMH NIH HHS P50-MH077248NIMH NIH HHS RL1 MH083270NIMH NIH HHS RL1-MH083270NIMH NIH HHS SC2 MH087974
6 · The paper itself

Abstract

backgroundOur ability to measure the cognitive components of complex decision-making across species has greatly facilitated our understanding of its neurobiological mechanisms. One task in particular, reversal learning, has proven valuable in assessing the inhibitory processes that are central to executive control. Reversal learning measures the ability to actively suppress reward-related responding and to disengage from ongoing behavior, phenomena that are biologically and descriptively related to impulsivity and compulsivity. Consequently, reversal learning could index vulnerability for disorders characterized by impulsivity such as proclivity for initial substance abuse as well as the compulsive aspects of dependence.

objectiveThough we describe common variants and similar tasks, we pay particular attention to discrimination reversal learning, its supporting neural circuitry, neuropharmacology and genetic determinants. We also review the utility of this task in measuring impulsivity and compulsivity in addictions.

methodsWe restrict our review to instrumental, reward-related reversal learning studies as they are most germane to addiction.

conclusionThe research reviewed here suggests that discrimination reversal learning may be used as a diagnostic tool for investigating the neural mechanisms that mediate impulsive and compulsive aspects of pathological reward-seeking and -taking behaviors. Two interrelated mechanisms are posited for the neuroadaptations in addiction that often translate to poor reversal learning: frontocorticostriatal circuitry dysregulation and poor dopamine (D2 receptor) modulation of this circuitry. These data suggest new approaches to targeting inhibitory control mechanisms in addictions.

Indexed as

Behavior, AddictiveBiogenic MonoaminesBrainCompulsive BehaviorDecision MakingHumansImpulsive BehaviorInhibition, PsychologicalModels, NeurologicalNeural PathwaysReversal LearningBiogenic Monoamines

Identifiers

PMID22134477
PMCPMC3249486
OpenAlexW1976029693

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.