SSVEP Response Is Related to Functional Brain Network Topology Entrained by the Flickering Stimulus

Abstract

Previous studies have shown that the brain network topology correlates with the cognitive function. However, few studies have investigated the relationship between functional brain networks that process sensory inputs and outputs. In this study, we focus on steady-state paradigms using a periodic visual stimulus, which are increasingly being used in both brain-computer interface (BCI) and cognitive neuroscience researches. Using the graph theoretical analysis, we investigated the relationship between the topology of functional networks entrained by periodic stimuli and steady state visually evoked potentials (SSVEP) using two frequencies and eleven subjects. First, the entire functional network (Network 0) of each frequency for each subject was constructed according to the coherence between electrode pairs. Next, Network 0 was divided into three sub-networks, in which the connection strengths were either significantly (positively for Network 1, negatively for Network 3) or non-significantly (Network 2) correlated with the SSVEP responses. Our results revealed that the SSVEP responses were positively correlated to the mean functional connectivity, clustering coefficient, and global and local efficiencies, while these responses were negatively correlated with the characteristic path length of Networks 0, 1 and 2. Furthermore, the strengths of these connections that significantly correlated with the SSVEP (both positively and negatively) were mainly found to be long-range connections between the parietal-occipital and frontal regions. These results indicate that larger SSVEP responses correspond with better functional network topology structures. This study may provide new insights for understanding brain mechanisms when using SSVEPs as frequency tags.

Dietary Carotenoids Lutein and Zeaxanthin Change Brain Activation in Older Adult Participants: A Randomized, Double‐Masked, Placebo‐Controlled Trial

“…Increased neural activity, reflected in increased response power in the SSVEP, is known to correlate with increases in functional connectivity and efficiency in the topological organization of the neural networks that are entrained by the eliciting stimulus. [43] Our results are consistent with the hypothesis that L and Z, like a number of other exogenous factors, may exert a direct effect on the neural circuitry of the brain.…”

Steady-state BOLD Response to Higher-order Cognition Modulates Low-Frequency Neural Oscillations

“…Because of these significant advantages, the SSEP is extremely useful in examining basic cognition such as visual attention (Morgan, Hansen, & Hillyard, 1996), working memory (Ellis, Silberstein, & Nathan, 2006), neurological disorders (Uhlhaas & Singer, 2006;Krishnan et al, 2005), and other sensation processes (Nangini, Ross, Tam, & Graham, 2006;Plourde, 2006). However, it is difficult to examine low-frequency neural oscillations and higher-order cognition with SSEPs because of the required high frequency of stimuli presentation (Zhang, Xu, Huang, Cheng, & Yao, 2013;Regan, 1989).…”

The study of brain networks driven by steady‐state visual evoked potentials

“…The preliminary result in this article indicated that visually driven functional networks of the brain may have distinct spatial distributions across different cortical areas with characteristic frequencies. Zhang et al suggested that larger SSVEP responses correspond with better functional network topology structures (Zhang et al, ). From our results, the network patterns expressing as the distribution of C and L together which two determine the effectiveness of networks is responsible for the phenomenon of SSVEP three subsystems.…”