Brain Network Analysis for Auditory Disease: A Twofold Study

Publication date: Available online 11 April 2019Source: NeurocomputingAuthor(s): Pei-Zhen Li, Ling Huang, Chang-Dong Wang, Chuan Li, Jian-Huang LaiAbstractTinnitus is the phantom perception of sound and can have negative effect on the quality of life. Sudden deafness is generally defined as sensorineural hearing loss of 30 dB or greater over at least three contiguous audiometric frequencies and within a three-day period, which is usually unilateral and can be associated with tinnitus. The exact pathogenesis of such auditory diseases is still unknown, and alterations in the functional connectivity of the brain network are suspected to involve one possible pathogenesis. Scalp electroencephalogram (EEG) analysis is a common approach to capture brain neural activity. This paper conducts a twofold study in terms of brain network analysis for auditory diseases based on EEG data. Specifically, the brain network is constructed in view of the phase lag index (PLI) between signals. The unsupervised study is first conducted via the unsupervised network community detection algorithm. The goal is to reveal the underlying characteristics of functional connectivity concerning subjects with and without auditory diseases from the brain network perspective. The second study is the supervised learning. A new strategy termed FBA (Features from Brain Areas) is proposed to abstract each brain network as a feature vector and the supervised classification method, i.e., Support Vector Machine (SVM) i...
Source: Neurocomputing - Category: Neuroscience Source Type: research