title: Physical connections between different SSVEP neural networks.
abstract: This work investigates the mechanism of the Steady-State Visual Evoked Potential (SSVEP). One theory suggests that different SSVEP neural networks exist whose strongest response are located in different frequency bands. This theory is based on the fact that there are similar SSVEP frequency-amplitude response curves in these bands. Previous studies that employed simultaneous stimuli of different frequencies illustrated that the distribution of these networks were similar, but did not discuss the physical connection between them. By comparing the SSVEP power and distribution under a single-eye stimulus and a simultaneous, dual-eye stimulus, this work demonstrates that the distributions of different SSVEP neural networks are similar to each other and that there should be physical overlapping between them. According to the band-pass filter theory in a signal transferring channel, which we propose in this work for the first time, there are different amounts of neurons that are involved under repetitive stimuli of different frequencies and that the response intensity of each neuron is similar to each other so that the total response (i.e., the SSVEP) that is observed from the scalp is different.
authors.affiliation: School of Computer Science and Engineering, University of Electronic Science and Technology of China, ChengDu, 610054, China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, ChengDu, 610054, China.
authors.forename: Zhenghua
authors.initials: Z
authors.lastname: Wu
mesh_terms: D004569:Electroencephalography; D005074:Evoked Potentials, Visual / Q000502:physiology*; D006801:Humans; D009474:Neurons / Q000502:physiology*; D009799:Ocular Physiological Phenomena; D010775:Photic Stimulation / Q000379:methods*; D017949:Retinal Cone Photoreceptor Cells / Q000502:physiology; D017948:Retinal Rod Photoreceptor Cells / Q000502:physiology