The study of brain networks driven by steady‐state visual evoked potentials. Issue 2 (June 2015)

• Record Type: Journal Article
• Authors: Yan, Zheng; Lin, Xiaohong; Lin, Chaodong
• Is Part Of: International journal of imaging systems and technology. Volume 25:Issue 2(2015:Jun.)
• Page Start: 165
• Page End: 171
• Publication Date: 2015-06
• Subjects: Imaging systems -- Periodicals; Image processing -- Periodicals; 621.367
• DOI: 10.1002/ima.22133
• Languages: English
• ISSNs: 0899-9457

Abstract

<abstract abstract-type="main"> <title>ABSTRACT</title> <p>In this article, we investigated the brain networks during the steady‐state visual evoked potential (SSVEP) task. Two questions: (1) SSVEP‐driven network structures; and (2) the relationship between SSVEP‐driven networks and stimulus frequencies were studied from a network point of view. Method of directed transfer function was applied to brain active signals recorded from electroencephalography (EEG). The resulting connectivity matrices then were converted to graphs by applying a threshold, so that graph theoretical could be used to analyze the characteristics of SSVEP‐driven networks. The results showed that network connections exist in many scalp locations beyond occipital regions. Different from the outflow areas located mainly around the parietal areas, the inflow areas had a widely distribution pattern including the frontal, temporal, and occipital areas. Furthermore, for a wide range of thresholds, with increasing frequency (7–30 Hz), the distribution of clustering coefficient and characteristic path length presented positive and negative correlation with the three parallel flicker SSVEP subsystems, respectively. The results suggested that a specific frequency may evoke certain SSVEP components more than others, and, therefore, one may generate different evoked potentials which results in different network pattern.</p> </abstract>