Brain temporal complexity in explaining the therapeutic and cognitive effects of seizure therapy
Brain temporal complexity in explaining the therapeutic and cognitive effects of seizure therapy
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DOI：
10.1093/brain/awx030
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发表时间：
2017-04-01
期刊：
影响因子：
14.5
通讯作者：
Daskalakis, Zafiris J.
中科院分区：
文献类型：
--
作者：
Farzan, Faranak;Atluri, Sravya;Daskalakis, Zafiris J.
全世界有超过3.5亿人患有抑郁症，其中三分之一的人对药物有抗药性。癫痫治疗仍然是抑郁症最有效的治疗方法，即使许多治疗失败。癫痫治疗的效用是有限的，由于其认知副作用和耻辱。癫痫治疗的生物学靶点仍然未知，阻碍了具有可比疗效的新治疗方法的设计。癫痫发作影响通过脑电图观察到的大脑时间动态。这种动态性反映了分布式大脑网络中丰富的信息处理，有助于情感和认知过程。我们研究了癫痫发作治疗通过调节大脑时间动态影响情绪（抑郁症状）和认知的假设。我们获得了34例患者（年龄= 46.0 +/- 14.0，21名女性）接受两种类型的癫痫治疗-电休克治疗或磁癫痫治疗的静息态脑电图。我们使用多尺度熵来量化癫痫治疗前后大脑时间动力学的复杂性。我们发现，精细时间尺度的复杂性降低强调了对两种癫痫治疗的成功治疗反应。顶枕叶和中央脑区精细时间尺度复杂性的更大降低与抑郁症状的更大改善显著相关。粗时间尺度复杂性的增加与包括自传体记忆在内的认知能力的下降有关。这些发现是区域和时间尺度特定的。也就是说，在精细的时间尺度上，枕骨区域（例如O-2电极或右枕极）的复杂性变化仅与抑郁症状的变化相关，而与认知的变化无关，并且与顶中央区（例如，大脑半球）的复杂性变化相关。G.在较粗的时间尺度上，Pz电极或顶内沟和经顶沟）仅与认知变化相关，而与抑郁症状无关。最后，复杂性的区域和时间尺度特异性变化分别以良好（80%）和极好（95%）的准确性将抗抑郁药和癫痫治疗的认知反应分类。在这项研究中，我们发现了一个新的癫痫治疗的生物学靶点：大脑静息态动力学的复杂性。脑静息状态动力学复杂性的区域和时间尺度依赖性变化是癫痫发作治疗反应的一种新的机制标志物，可解释与该治疗相关的抗抑郁反应和认知变化。这一标志物在指导新一代抗抑郁治疗的设计方面具有巨大的潜力。
Over 350 million people worldwide suffer from depression, a third of whom are medication-resistant. Seizure therapy remains the most effective treatment in depression, even when many treatments fail. The utility of seizure therapy is limited due to its cognitive side effects and stigma. The biological targets of seizure therapy remain unknown, hindering design of new treatments with comparable efficacy. Seizures impact the brains temporal dynamicity observed through electroencephalography. This dynamicity reflects richness of information processing across distributed brain networks subserving affective and cognitive processes. We investigated the hypothesis that seizure therapy impacts mood (depressive symptoms) and cognition by modulating brain temporal dynamicity. We obtained resting-state electroencephalography from 34 patients (age = 46.0 +/- 14.0, 21 females) receiving two types of seizure treatments-electroconvulsive therapy or magnetic seizure therapy. We used multi-scale entropy to quantify the complexity of the brain's temporal dynamics before and after seizure therapy. We discovered that reduction of complexity in fine timescales underlined successful therapeutic response to both seizure treatments. Greater reduction in complexity of fine timescales in parieto-occipital and central brain regions was significantly linked with greater improvement in depressive symptoms. Greater increase in complexity of coarse timescales was associated with greater decline in cognition including the autobiographical memory. These findings were region and timescale specific. That is, change in complexity in occipital regions (e.g. O-2 electrode or right occipital pole) at fine timescales was only associated with change in depressive symptoms, and not change in cognition, and change in complexity in parieto-central regions (e. g. Pz electrode or intra and transparietal sulcus) at coarser timescale was only associated with change in cognition, and not depressive symptoms. Finally, region and timescale specific changes in complexity classified both antidepressant and cognitive response to seizure therapy with good (80%) and excellent (95%) accuracy, respectively. In this study, we discovered a novel biological target of seizure therapy: complexity of the brain resting state dynamics. Region and timescale dependent changes in complexity of the brain resting state dynamics is a novel mechanistic marker of response to seizure therapy that explains both the antidepressant response and cognitive changes associated with this treatment. This marker has tremendous potential to guide design of the new generation of antidepressant treatments.