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Automated Affect Detection in Deep Brain Stimulation for Obsessive-Compulsive Disorder: A Pilot Study

机译:强迫症深部脑刺激的自动影响检测:一项初步研究

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摘要

Automated measurement of affective behavior in psychopathology has been limited primarily to screening and diagnosis. While useful, clinicians more often are concerned with whether patients are improving in response to treatment. Are symptoms abating, is affect becoming more positive, are unanticipated side effects emerging? When treatment includes neural implants, need for objective, repeatable biometrics tied to neurophysiology becomes especially pressing. We used automated face analysis to assess treatment response to deep brain stimulation (DBS) in two patients with intractable obsessive-compulsive disorder (OCD). One was assessed intraoperatively following implantation and activation of the DBS device. The other was assessed three months post-implantation. Both were assessed during DBS on and o conditions. Positive and negative valence were quantified using a CNN trained on normative data of 160 non-OCD participants. Thus, a secondary goal was domain transfer of the classifiers. In both contexts, DBS-on resulted in marked positive affect. In response to DBS-off, affect flattened in both contexts and alternated with increased negative affect in the outpatient setting. Mean AUC for domain transfer was 0.87. These findings suggest that parametric variation of DBS is strongly related to affective behavior and may introduce vulnerability for negative affect in the event that DBS is discontinued.
机译:精神病理学中情感行为的自动测量主要限于筛查和诊断。尽管有用,但临床医生更多地关注患者是否对治疗有所改善。症状是否减轻,影响变得更积极,是否出现了意料之外的副作用?当治疗包括神经植入物时,对与神经生理学相关的客观,可重复的生物统计的需求就变得尤为紧迫。我们使用自动化面部分析来评估两名顽固性强迫症(OCD)患者对深部脑刺激(DBS)的治疗反应。在植入和激活DBS装置后进行了术中评估。另一个在植入后三个月进行评估。两者均在DBS上和其他条件下进行了评估。使用在160名非OCD参与者的规范化数据中受过训练的CNN量化正价和负价。因此,第二个目标是分类器的域转移。在这两种情况下,DBS-on都产生了明显的积极影响。为了应对DBS-off,在两种情况下影响趋于平缓,在门诊患者中交替增加负面影响。域转移的平均AUC为0.87。这些发现表明,DBS的参数变化与情感行为密切相关,并且在DBS停止使用时可能会带来负面影响的脆弱性。

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