Evidence map›Paper›PMID 23151990›Full record

ArticleHuman brain mapping2014

Stochastic dynamic causal modeling of working memory connections in cocaine dependence.

Liangsuo Ma, Joel L Steinberg, Khader M Hasan, Ponnada A Narayana, Larry A Kramer, F Gerard Moeller

Open access · greenAbstract read
In one paragraph

Article in Human brain mapping, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
1.3field-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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
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  18. Modeling Causal Relationship Between Brain Regions Within the Drug-Cue Processing Network in Chronic Cocaine Smokers.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2015
    Article
  19. Article
  20. Review
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

6 authors at 1 institution in 1 country.

Liangsuo MaDepartment of Psychiatry and Behavioral Sciences, University of Texas Health Science Center, Houston, Texas.
Joel L Steinberg
Khader M Hasan
Ponnada A Narayana
Larry A Kramer
F Gerard Moeller
The University of Texas Health Science Center at Houston · US

Funding

Translational MR Imaging in Cocaine Pharmacotherapy DevelopmentP50DA009262 · NIDA · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI GREEN, CHARLES EDWARD · 1994 to 2014
$26.9M
Serotonin, Impulsivity, and Substance AbuseK02DA000403 · NIDA · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI MOELLER, FREDERICK GERARD · 2000 to 2011
$1.2M
NIDA NIH HHS K02 DA000403NIDA NIH HHS K02 DA00403NIDA NIH HHS #P50 DA009262NIDA NIH HHS P50 DA009262
6 · The paper itself

Abstract

Although reduced working memory brain activation has been reported in several brain regions of cocaine-dependent subjects compared with controls, very little is known about whether there is altered connectivity of working memory pathways in cocaine dependence. This study addresses this issue by using functional magnetic resonance imaging-based stochastic dynamic causal modeling (DCM) analysis to study the effective connectivity of 19 cocaine-dependent subjects and 14 healthy controls while performing a working memory task. Stochastic DCM is an advanced method that has recently been implemented in SPM8 that can obtain improved estimates, relative to deterministic DCM, of hidden neuronal causes before convolution with the hemodynamic response. Thus, stochastic DCM may be less influenced by the confounding effects of variations in blood oxygen level-dependent response caused by disease or drugs. Based on the significant regional activation common to both groups and consistent with previous working memory activation studies, seven regions of interest were chosen as nodes for DCM analyses. Bayesian family level inference, Bayesian model selection analyses, and Bayesian model averaging (BMA) were conducted. BMA showed that the cocaine-dependent subjects had large differences compared with the control subjects in the strengths of prefrontal-striatal modulatory (B matrix) DCM parameters. These findings are consistent with altered cortical-striatal networks that may be related to reduced dopamine function in cocaine dependence. As far as we are aware, this is the first between-group DCM study using stochastic methodology.

Indexed as

Models, StatisticalAdultBayes TheoremBrainCocaine-Related DisordersConnectomeFemaleHumansMagnetic Resonance ImagingMaleMemory, Short-TermMiddle AgedNeostriatumPrefrontal CortexYoung Adultaddictioncocaine dependencedynamic causal modelingeffective connectivitystochastic DCMworking memory

Identifiers

PMID23151990
PMCPMC4440319
OpenAlexW1563275472

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.