Journal of Affective Disorders Reports (Jan 2022)

Alteration of segregation of brain systems in the severe depressive disorder after electroconvulsive therapy

  • Xiaopeng Hu,
  • Min Zhao,
  • Yang Ma,
  • YiJun Ge,
  • Huiguang He,
  • Shengpei Wang,
  • Yingfeng Qian

Journal volume & issue
Vol. 7
p. 100299

Abstract

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Background: Severe depressive disorder (SDD) has been characterized by abnormal brain activity and interactions across the whole-brain functional networks. Electroconvulsive therapy (ECT) has been considered as an effective and rapid treatment for SDD. However, whether ECT may enhance the dysconnectivity between brain networks to achieve antidepressant effects is still largely unknown. Methods: Resting-state functional magnetic resonance imaging was acquired from 25 SDD participants (9M/16F, age: 34.32±9.69) before and after ECT treatments (9M/16F, age: 34.32±9.69), along with 25 sex-and age-matched healthy controls (9M/16F, age: 24.72±8.16). Then, large-scale functional brain network of each participant was constructed and divided into ten functional systems. Finally, the topology properties across ten systems, including with- and between-system connectivity, system-segregation and participation coefficient, were assessed and analyzed between SDD patients and controls. Results: Our results showed ECT can enhance the reduced functional connectivity (FC) of default model network (DMN) and frontal-parietal network (FPN) in SDD patients. In particular, after ECT, not only the FC within DMN and FPN was strengthened, but also the FC between DMN/FPN with subcortical network (SUB) and visual network was significantly increased. These above connectives of DMN and FPN were significantly reduced in before-ECT SDD compared to healthy controls and were closely related to clinical scores of depression. Conclusion: Our findings indicated the enhanced interactions in with- and between-systems of DMN and FPN may contributed to the ECT response in SDD patients. And These findings provide novel and important insights into the neurobiological mechanisms underlying depression, even ECT.

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