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A Conflict Model of Reward-seeking Behavior in Male Rats
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Large-scale network abnormality in behavioral addiction.

Pan Chen1, Junjing Wang2, Guixian Tang1

  • 1Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China.

Journal of Affective Disorders
|March 23, 2024
PubMed
Summary
This summary is machine-generated.

Behavioral addiction (BA) is linked to altered brain network connectivity. This meta-analysis reveals widespread hypo-connectivity within and between key brain networks in individuals with BA.

Keywords:
Behavioral addictionMeta-analysisMultilevel kernel density analysisResting-state functional connectivity

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Area of Science:

  • Neuroscience
  • Psychiatry
  • Computational Biology

Background:

  • Behavioral addiction (BA) presents challenges in understanding its underlying neural mechanisms.
  • Resting-state functional connectivity (rsFC) is a key technique for investigating brain network dysfunction in BA.

Approach:

  • A meta-analysis synthesized data from 56 rsFC studies, including 1755 individuals with BA and 1828 healthy controls (HC).
  • Multilevel kernel density analysis identified patterns of hyper-connectivity and hypo-connectivity within and between large-scale brain networks.

Key Points:

  • Individuals with BA exhibit hypo-connectivity in the fronto-parietal network (FN) and altered connectivity in the ventral attention network (VAN).
  • Disruptions include hypo-connectivity between the FN, VAN, default mode network (DMN), and sensorimotor network (SS).
  • Specific findings include hypo-connectivity between the reward system and the SS, DMN, and VAN.

Conclusions:

  • The findings suggest a model of BA characterized by impaired functional coordination across large-scale brain networks.
  • This research provides a foundation for developing targeted interventions for behavioral addiction.