کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6821427 | 1434048 | 2018 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
The contribution of the contingent negative variation (CNV) to goal maintenance
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب رفتاری
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چکیده انگلیسی
The dot pattern expectancy (DPX) task has been strongly recommended as a measure of goal maintenance, which is impaired in schizophrenia patients. The current event-related potential (ERP) study was designed mainly to identify the ERP component that could represent the goal maintenance process of the DPX task as indexed by the error rate of the BX vs. AY (EBX-AY). We focused our analysis on the cue-phased contingent negative variation (CNV) and found a significant association between the EBX-AY and the amplitude of the difference wave of cue B vs. cue A (CNVB-A) (for CP3, β = â 0.262, P = 0.001; for CPZ, β = â 0.184, P = 0.025; for CP4, β = â 0.201, P = 0.015). Lower EBX-AY (better goal maintenance) was correlated with larger CNVB-A. Further analysis found a significant association between the error rate of AY condition (EAY) and the amplitude of CNVA (for CP3, β = â 0.180, P = 0.029; for CPZ, β = â 0.184, P = 0.024; for CP4, β = â 0.208, P = 0.011) and a significant association between the error rate of BX condition (EBX) and the amplitude of CNVB-A (for CP3, β = â 0.198, P = 0.016; for CPZ, β = â 0.165, P = 0.043; for CP4, β = â 0.151, P = 0.066), but not the amplitude of the CNVB (all P > 0.05). All these results together suggested that the cue-phased CNV could be used to represent the goal maintenance process. Future research needs to verify these results with schizophrenia patients.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Schizophrenia Research - Volume 195, May 2018, Pages 372-377
Journal: Schizophrenia Research - Volume 195, May 2018, Pages 372-377
نویسندگان
Aihua Shen, Wan Zhao, Bingqian Han, Qiumei Zhang, Zhifang Zhang, Xiongying Chen, Jinguo Zhai, Min Chen, Boqi Du, Xiaoxiang Deng, Feng Ji, Chuanyue Wang, Yu-Tao Xiang, Hongjie Wu, Qi Dong, Chuansheng Chen, Jun Li,