Evidence map›Paper›PMID 24391601›Full record

ReviewFrontiers in psychiatry2013

A computational hypothesis for allostasis: delineation of substance dependence, conventional therapies, and alternative treatments.

Yariv Z Levy, Dino J Levy, Andrew G Barto, Jerrold S Meyer

Abstract readReview
In one paragraph

Review in Frontiers in psychiatry, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. A Control Theory Model of Smoking.Methods report (RTI Press) · 2017
    Article
  5. 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

4 authors.

Yariv Z LevySchool of Computer Science, University of Massachusetts Amherst , Amherst, MA , USA.
Dino J LevyRecanati Faculty of Management, Tel-Aviv University , Tel-Aviv , Israel ; Sagol School of Neuroscience, Tel-Aviv University , Tel-Aviv , Israel.
Andrew G BartoSchool of Computer Science, University of Massachusetts Amherst , Amherst, MA , USA ; Neuroscience and Behavior Program, University of Massachusetts Amherst , Amherst, MA , USA.
Jerrold S MeyerDepartment of Psychology, University of Massachusetts Amherst , Amherst, MA , USA ; Neuroscience and Behavior Program, University of Massachusetts Amherst , Amherst, MA , USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The allostatic theory of drug abuse describes the brain's reward system alterations as substance misuse progresses. Neural adaptations arising from the reward system itself and from the antireward system provide the subject with functional stability, while affecting the person's mood. We propose a computational hypothesis describing how a virtual subject's drug consumption, cognitive substrate, and mood interface with reward and antireward systems. Reward system adaptations are assumed interrelated with the ongoing neural activity defining behavior toward drug intake, including activity in the nucleus accumbens, ventral tegmental area, and prefrontal cortex (PFC). Antireward system adaptations are assumed to mutually connect with higher-order cognitive processes occurring within PFC, orbitofrontal cortex, and anterior cingulate cortex. The subject's mood estimation is a provisional function of reward components. The presented knowledge repository model incorporates pharmacokinetic, pharmacodynamic, neuropsychological, cognitive, and behavioral components. Patterns of tobacco smoking exemplify the framework's predictive properties: escalation of cigarette consumption, conventional treatments similar to nicotine patches, and alternative medical practices comparable to meditation. The primary outcomes include an estimate of the virtual subject's mood and the daily account of drug intakes. The main limitation of this study resides in the 21 time-dependent processes which partially describe the complex phenomena of drug addiction and involve a large number of parameters which may underconstrain the framework. Our model predicts that reward system adaptations account for mood stabilization, whereas antireward system adaptations delineate mood improvement and reduction in drug consumption. This investigation provides formal arguments encouraging current rehabilitation therapies to include meditation-like practices along with pharmaceutical drugs and behavioral counseling.

Indexed as

allostasisantireward system adaptationsdrug additiondrug intake predictionknowledge repository modelmoodmultiscale computational modelreward system adaptations

Identifiers

PMID24391601
PMCPMC3868344

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Registered trials

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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.