Sichuan jingshen weisheng (Jun 2024)

Research progress on electroencephalography in the prediction of efficacy and therapeutic mechanism for anxiety disorders

  • Yuan Danfeng,
  • Yang Xiangyun,
  • Li Zhanjiang

DOI
https://doi.org/10.11886/scjsws20231002002
Journal volume & issue
Vol. 37, no. 3
pp. 270 – 276

Abstract

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Anxiety disorders are characterized by high prevalence and recurrence rate. Selective serotonin reuptake inhibitors (SSRIs) and cognitive behavioral therapy (CBT) are recommended as first-line treatments for anxiety disorders, while some patients do not response to either of these treatments. Therefore, exploring the neurobiological mechanisms associated with treatment response and valuable prognostic marker is of great value in guiding clinical decision making. Previous studies have reported an altered electroencephalogram (EEG) pattern in patients with anxiety disorders after treatment, and revealed a correlation between baseline EEG and treatment response, suggesting that EEG is of great value in predicting the treatment response in anxiety disorders. The purpose of this article is to delineate findings from a systematic review of the literature investigating the EEG signal in prognostic prediction and exploration of neurobiological mechanisms, so as to provide electrophysiological evidence for individualized treatment of anxiety disorders. Results of this review show that patients responding more strongly to negative emotional stimuli before treatment are more likely to benefit from SSRIs and CBT. After the CBT, no statistical difference is found in the amplitude of error-related negativity (ERN) and P1 component between pre- and post- procedure measurements, suggesting that CBT may not reduce anxiety symptoms by improving attention bias and behavioral monitoring. EEG indicators related to emotion perception under negative emotional stimuli at baseline, such as late positive potential (LPP), may be promising markers for predicting response to treatment in anxiety disorders. [Funded by the Science and Technology Innovation 2030-Major Project of "Brain Science and Brain-like Research" (number, 2021ZD0202004); Capital Health Development Scientific Research Project (number, 2020-1-2121)]

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