From Sound Perception to Automatic Detection of Schizophrenia: An EEG-Based Deep Learning Approach.

ABSTRACT: 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 n

SUBMITTER: Barros C 

PROVIDER: S-EPMC8892210 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature