From Sound Perception to Automatic Detection of Schizophrenia: An EEG-Based Deep Learning Approach.
From Sound Perception to Automatic Detection of Schizophrenia: An EEG-Based Deep Learning Approach.
复制标题
DOI：
10.3389/fpsyt.2021.813460
复制
发表时间：
2021
影响因子：
4.7
通讯作者：
Silva CA
中科院分区：
文献类型：
--
作者：
Barros C;Roach B;Ford JM;Pinheiro AP;Silva CA
Deep learning techniques have been applied to electroencephalogram (EEG) signals, with promising applications in the field of psychiatry. Schizophrenia is one of the most disabling neuropsychiatric disorders, often characterized by the presence of auditory hallucinations. Auditory processing impairments have been studied using EEG-derived event-related potentials and have been associated with clinical symptoms and cognitive dysfunction in schizophrenia. Due to consistent changes in the amplitude of ERP components, such as the auditory N100, some have been proposed as biomarkers of schizophrenia. In this paper, we examine altered patterns in electrical brain activity during auditory processing and their potential to discriminate schizophrenia and healthy subjects. Using deep convolutional neural networks, we propose an architecture to perform the classification based on multi-channels auditory-related EEG single-trials, recorded during a passive listening task. We analyzed the effect of the number of electrodes used, as well as the laterality and distribution of the electrical activity over the scalp. Results show that the proposed model is able to classify schizophrenia and healthy subjects with an average accuracy of 78% using only 5 midline channels (Fz, FCz, Cz, CPz, and Pz). The present study shows the potential of deep learning methods in the study of impaired auditory processing in schizophrenia with implications for diagnosis. The proposed design can provide a base model for future developments in schizophrenia research.
登录
查看更多内容
影响因子：
64.8
作者：
Harris CR;Millman KJ;van der Walt SJ;Gommers R;Virtanen P;Cournapeau D;Wieser E;Taylor J;Berg S;Smith NJ;Kern R;Picus M;Hoyer S;van Kerkwijk MH;Brett M;Haldane A;Del Río JF;Wiebe M;Peterson P;Gérard-Marchant P;Sheppard K;Reddy T;Weckesser W;Abbasi H;Gohlke C;Oliphant TE
通讯作者：
Oliphant TE
影响因子：
4.7
作者：
Mazer P;Macedo I;Paiva TO;Ferreira-Santos F;Pasion R;Barbosa F;Almeida P;Silveira C;Cunha-Reis C;Marques-Teixeira J
通讯作者：
Marques-Teixeira J
多样性何时有助于分类集成的泛化？
影响因子：
11.8
作者：
Bian, Yijun;Chen, Huanhuan
通讯作者：
Chen, Huanhuan
影响因子：
6.6
作者：
Ford, Judith M.;Palzes, Vanessa A.;Mathalon, Daniel H.
通讯作者：
Mathalon, Daniel H.
影响因子：
4.5
作者：
Freedman, Robert;Olsen-Dufour, Amanda M.;Olincy, Ann
通讯作者：
Olincy, Ann