Investigating inhibition deficit in schizophrenia using task-modulated brain networks
Investigating inhibition deficit in schizophrenia using task-modulated brain networks
复制标题
使用任务调制的大脑网络研究精神分裂症的抑制缺陷
DOI：
10.1007/s00429-020-02078-7
复制
发表时间：
2020-04
影响因子：
3.1
通讯作者：
Bharat Biswal
中科院分区：
文献类型：
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作者：
Yang Hang;Di Xin;Gong Qiyong;Sweeney John;Bharat Biswal
精神分裂症患者在诸如停止信号任务等条件下表现出抑制缺陷。与健康对照组相比，停止信号反应时间（SSRT）始终较长，并伴有右额下回的脑激活减少。然而，关于分布式大脑网络如何支持反应抑制功能，以及这种网络是否在精神分裂症中发生改变，在很大程度上是未知的。我们分析了44名精神分裂症患者和44名匹配对照的停止信号任务的功能性MRI数据，并进行了全脑心理生理相互作用分析以获得任务调制连接性（TMC）。采用支持向量分类法对精神分裂症患者进行分类，并采用支持向量回归法探讨TMC与SSRT等行为指标之间的关系。精神分裂症组TMC减少，主要涉及额顶网络，TMC增加，与感觉运动网络有关。此外，TMC只能成功预测对照组的SSRT，进一步表明精神分裂症异常的任务调制。最后，我们比较了不同类型度量的分类和预测结果，即，TMC、任务独立连接性（TIC）、任务功能连接性（TFC）和静息状态功能连接性（RSFC）。TMC在行为预测中表现更好，而TIC在分类中表现更好。TFC和RSFC具有与TIC相似的分类和预测性能。目前的研究结果提供了新的见解，改变脑功能整合的反应抑制精神分裂症，并建议不同类型的连接措施是互补的，更好地了解大脑网络及其变化。
Schizophrenia subjects have shown deficits of inhibition in conditions such as a stop signal task. The stop signal response time (SSRT) is consistently longer compared with healthy controls, and is accompanied by decreased brain activations in the right inferior frontal gyrus. However, as to how the response inhibition function is supported by distributed brain networks, and whether such networks are altered in schizophrenia are largely unknown. We analyzed functional MRI data of a stop signal task from 44 schizophrenia patients and 44 matched controls, and performed whole-brain psychophysiological interaction analysis to obtain task-modulated connectivity (TMC). Support vector classification was used to classify schizophrenia, and support vector regression was applied to explore the relationships between TMC and behavior indexes, such as SSRT. Schizophrenia group showed a decreased TMC pattern which mainly involved the fronto-parietal network, and increased TMC related to the sensorimotor network. Moreover, TMC could only successfully predict SSRT in the control group, further suggesting an abnormal task modulation in schizophrenia. Lastly, we compared the classification and prediction results from different types of measures, i.e., TMC, task-independent connectivity (TIC), task-functional connectivity (TFC), and resting-state functional connectivity (RSFC). TMC performed better in the behavior predictions, while TIC performed better in the classification. TFC and RSFC had similar classification and prediction performance as TIC. The current results provide new insights into the altered brain functional integration underlying response inhibition in schizophrenia, and suggest that different types of connectivity measures are complementary for a better understanding of brain networks and their alterations.
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影响因子：
5.7
作者：
Pereira F;Mitchell T;Botvinick M
通讯作者：
Botvinick M
影响因子：
3.5
作者：
Touroutoglou A;Andreano JM;Barrett LF;Dickerson BC
通讯作者：
Dickerson BC
影响因子：
6.6
作者：
Kraguljac, Nina Vanessa;White, David Matthew;Lahti, Adrienne Carol
通讯作者：
Lahti, Adrienne Carol
DOI：
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发表时间：
2006
影响因子：
11.1
作者：
R. Cho;R. Konecky;C. Carter
通讯作者：
R. Cho;R. Konecky;C. Carter
影响因子：
4.4
作者：
通讯作者：
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