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神经周期性紊乱可预测强迫症患者接受深部脑刺激后的临床反应。

Disruption of neural periodicity predicts clinical response after deep brain stimulation for obsessive-compulsive disorder.

机构信息

Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA.

Department of Electrical & Computer Engineering, Rice University, Houston, TX, USA.

出版信息

Nat Med. 2024 Oct;30(10):3004-3014. doi: 10.1038/s41591-024-03125-0. Epub 2024 Jul 12.

Abstract

Recent advances in surgical neuromodulation have enabled chronic and continuous intracranial monitoring during everyday life. We used this opportunity to identify neural predictors of clinical state in 12 individuals with treatment-resistant obsessive-compulsive disorder (OCD) receiving deep brain stimulation (DBS) therapy ( NCT05915741 ). We developed our neurobehavioral models based on continuous neural recordings in the region of the ventral striatum in an initial cohort of five patients and tested and validated them in a held-out cohort of seven additional patients. Before DBS activation, in the most symptomatic state, theta/alpha (9 Hz) power evidenced a prominent circadian pattern and a high degree of predictability. In patients with persistent symptoms (non-responders), predictability of the neural data remained consistently high. On the other hand, in patients who improved symptomatically (responders), predictability of the neural data was significantly diminished. This neural feature accurately classified clinical status even in patients with limited duration recordings, indicating generalizability that could facilitate therapeutic decision-making.

摘要

近年来,手术神经调节技术的进步使得我们能够在日常生活中对颅内进行慢性、持续监测。我们利用这一机会,在接受深部脑刺激(DBS)治疗的 12 名治疗抵抗性强迫症(OCD)患者(NCT05915741)中,确定了临床状态的神经预测因子。我们基于五名患者初始队列中腹侧纹状体区域的连续神经记录开发了我们的神经行为模型,并在另外七名患者的独立队列中进行了测试和验证。在 DBS 激活之前,处于最明显症状状态时,θ/α(9 Hz)功率表现出明显的昼夜节律模式和高度的可预测性。在持续性症状(无反应者)的患者中,神经数据的可预测性保持一致地高。另一方面,在症状明显改善的患者(有反应者)中,神经数据的可预测性显著降低。即使在记录时间有限的患者中,这种神经特征也能准确地分类临床状态,表明具有普遍性,这可能有助于治疗决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b38f/11485242/b0a025080670/41591_2024_3125_Fig1_HTML.jpg

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