Study On The SSVEP's Application In Brain-Computer Interface And Cognitive Task

The genesis of SSVEP isn't clear till now, and often explained by loop-loop feedback or wave theories. SSVEP is used mainly in two hands, one is in studying of cognitive task, the other is in Brain-Computer Interface (BCI). In this paper, we'll discuss the fundamental theory about SSVEP and its application, and there include the contents below.1). From studying the SSVEP evoked by a pulse stimulus of 10 Hz with different duty-cycle, we found that the amplitude of SSVEP was the biggest one when the duty-cycle was about 0.4.2). From using the red, green or blue flicker to stimulate the eyes of subjects separately under the same luninance, we found that the distribution of SSVEP was similar under each situation, while the intensities of them were different, the SSVEP evoked by the blue flicker was the biggest one, that evoked by the red flicker was smaller than that evoked by the blue flicker, while that evoked by the green flicker was the smallest one.3). We use the flickers in different frequency band to evoke the SSVEP separately or simultaneously, from studying the SSVEP amplitude and distribution under these situations, it is found that there is no clear interaction between these networks when activated simultaneously, in other word, these networks are independent from each other.4). Because of the different lighting theory for different type stimulator, the spectum of the flickers are different too. Although the stimulating frequency and luminance are the same, the evoked SSVEPs are different from each other. From using different type stimulators in different frequency band, it is found that the SSVEP evoked by the LED flicker is the strongest one, while the fundamental frequency in SSVEP evoked by the CRT and LCD flicker is similar to each other, although the difference of the harmonics is significant.5). When using power spectrum (PS) method to extract SSVEP within a relative long time period, the influence by the potential mental activity can be eliminated to some extent, and a relative high accuracy but low transfer rate can be obtained. When using the stability coefficient (SC) method introduced here, which was obtained by Wavelet Analysis, the influence in a relative short time period by the noise can be eliminated greatly, which could further result in a relative high accuracy and transfer rate in a SSVEP-based BCI system.6). In order to compare the influence on the different frequency SSVEP by a same cognitive task, we use two frequencies in different band to evoke SSVEP, and make the subject execute the same memory task. From comparing the SSVEP under two situations, it is found that the influence on the different frequency SSVEP by the same task is similar to each other, while that on the low frequency is more clear and stable than that on the high frequency.7). From studying the SSVEP amplitudes with attention or without attention, it is found that the SSVEP amplitude is improved with attention, while this influence is clearer for the low frequency than for the high frequency. This result supports the theory of selection early about attention.8). The subject was asked to finish a same memory task repetitively, and the ERP of this task was obtained by the traditional average method. Then the subject was asked to execute the same memory task repetitively under the flicker stimulus, and a method named Steady-State Probe Topography (SSPT) was used to extract the SSVEP. From comparing the ERP and SSVEP, it is found that the ERP can modulate the amplitude of SSVEP, and this modulation is clear in the regions where two kinds of signals are both strong.