We observed the steady-state visually evoked potential(SSVEP) from a healthy subject using a compact quad-channel potassium spin exchange relaxation-free(SERF) optically pumped magnetometer(OPM). To this end, 30 s of ...We observed the steady-state visually evoked potential(SSVEP) from a healthy subject using a compact quad-channel potassium spin exchange relaxation-free(SERF) optically pumped magnetometer(OPM). To this end, 30 s of data were collected, and SSVEP-related magnetic responses with signal intensity ranging from 150 fT to 300 f T were observed for all four channels. The corresponding signal to noise ratio(SNR) was in the range of 3.5–5.5. We then used different channels to operate the sensor as a gradiometer. In the specific case of detecting SSVEP, we noticed that the short channel separation distance led to a strongly diminished gradiometer signal. Although not optimal for the case of SSVEP detection, this set-up can prove to be highly useful for other magnetoencephalography(MEG) paradigms that require good noise cancellation.Considering its compactness, low cost, and good performance, the K-SERF sensor has great potential for biomagnetic field measurements and brain-computer interfaces(BCI).展开更多
Brain oscillations are vital to cognitive functions,while disrupted oscillatory activity is linked to various brain disorders.Although high-frequency neural oscillations(>1 Hz)have been extensively studied in cogni...Brain oscillations are vital to cognitive functions,while disrupted oscillatory activity is linked to various brain disorders.Although high-frequency neural oscillations(>1 Hz)have been extensively studied in cognition,the neural mechanisms underlying low-frequency hemodynamic oscillations(LFHO)<1 Hz have not yet been fully explored.One way to examine oscillatory neural dynamics is to use a facial expression(FE)paradigm to induce steady-state visual evoked potentials(SSVEPs),which has been used in electroencephalography studies of high-frequency brain oscillation activity.In this study,LFHO during SSVEP-inducing periodic flickering stimuli presentation were inspected using functional near-infrared spectroscopy(fNIRS),in which hemodynamic responses in the prefrontal cortex were recorded while participants were passively viewing dynamic FEs flickering at 0.2 Hz.The fast Fourier analysis results demonstrated that the power exhibited monochronic peaks at 0.2 Hz across all channels,indicating that the periodic events successfully elicited LFHO in the prefrontal cortex.More importantly,measurement of LFHO can effectively distinguish the brain activation difference between different cognitive conditions,with happy FE presentation showing greater LFHO power than neutral FE presentation.These results demonstrate that stimuli flashing at a given frequency can induce LFHO in the prefrontal cortex,which provides new insights into the cognitive mechanisms involved in slow oscillation.展开更多
In recent years, Brain Computer Interface (BCI) systems based on Steady-State Visual Evoked Potential (SSVEP) have received much attention. This study tries to develop a SSVEP based BCI system that can control a wheel...In recent years, Brain Computer Interface (BCI) systems based on Steady-State Visual Evoked Potential (SSVEP) have received much attention. This study tries to develop a SSVEP based BCI system that can control a wheelchair prototype in five different positions including stop position. In this study four different flickering frequencies in low frequency region were used to elicit the SSVEPs and were displayed on a Liquid Crystal Display (LCD) monitor using Lab-VIEW. Four stimuli colors, green, red, blue and violet were used to investigate the color influence in SSVEPs. The Electroencephalogram (EEG) signals recorded from the occipital region were segmented into 1 second window and features were extracted by using Fast Fourier Transform (FFT). One-Against-All (OAA), a popular strategy for multiclass SVM, is used to classify SSVEP signals. During stimuli color comparison SSVEP with violet color showed higher accuracy than that with green, red and blue stimuli.展开更多
The present study investigated the allocation of spatial attention using steady-state visual evoked potentials(SSVEPs).The SSVEP is elicited in visual cortical areas by a repetitive flicker having the same fundamental...The present study investigated the allocation of spatial attention using steady-state visual evoked potentials(SSVEPs).The SSVEP is elicited in visual cortical areas by a repetitive flicker having the same fundamental frequency as the driving stimulus.Two flickers were applied with the letter stream presented in the center of the monitor and the distractor presented on either the left or right side of the target.Participants were instructed to detect the target letter in the letter stream.The distance of the two flickers was manipulated.The results show that the amplitudes of the SSVEPs elicited by the distractor were enhanced when it was in the closest position and suppressed when it was at a farther distance.But the amplitudes rebounded at the farthest distance.Meanwhile,the SSVEP elicited by the target flicker remained stable independent of the distance of the distractor.Thus,the present study indicates that focused attention involves neural suppression surrounding the classic "spotlight",and the SSVEP paradigms open new avenues for studying the attentional suppression mechanism.展开更多
This study explored methods for improving the performance of Steady-State Visual Evoked Potential(SSVEP)-based Brain-Computer Interfaces(BCI), and introduced a new analytical method to quantitatively analyze and refle...This study explored methods for improving the performance of Steady-State Visual Evoked Potential(SSVEP)-based Brain-Computer Interfaces(BCI), and introduced a new analytical method to quantitatively analyze and reflect the characteristics of SSVEP. We focused on the effect of the pre-stimulation paradigm on the SSVEP dynamic models and the dynamic response process of SSVEP, and performed a comparative analysis of three pre-stimulus paradigms(black, gray, and white). Four dynamic models with different orders(second-and third-order)and with and without a zero point were used to fit the SSVEP envelope. The zero-pole analytical method was adopted to conduct quantitative analysis on the dynamic models, and the response characteristics of SSVEP were represented by zero-pole distribution characteristics. The results of this study indicated that the pre-stimulation paradigm affects the characteristics of SSVEP, and the dynamic models had good fitting abilities with SSVEPs under various types of pre-stimulation. Furthermore, the zero-pole characteristics of the models effectively characterize the damping coefficient, oscillation period, and other SSVEP characteristics. The comparison of zeros and poles indicated that the gray pre-stimulation condition corresponds to a lower damping coefficient, thus showing its potential to improve the performance of SSVEP-BCIs.展开更多
基金Project supported by the National Key Research and Development Program of China(Grant Nos.2016YFA0300600 and 2016YFA0301500)the Strategic Priority Research Program of Chinese Academy of Sciences(Grant Nos.XDB07030000 and XDBS32000000)+1 种基金the National Natural Science Foundation of China(Grant Nos.11474347 and 31730039)the Fund from the Ministry of Science and Technology of China(Grant No.2015CB351701)
文摘We observed the steady-state visually evoked potential(SSVEP) from a healthy subject using a compact quad-channel potassium spin exchange relaxation-free(SERF) optically pumped magnetometer(OPM). To this end, 30 s of data were collected, and SSVEP-related magnetic responses with signal intensity ranging from 150 fT to 300 f T were observed for all four channels. The corresponding signal to noise ratio(SNR) was in the range of 3.5–5.5. We then used different channels to operate the sensor as a gradiometer. In the specific case of detecting SSVEP, we noticed that the short channel separation distance led to a strongly diminished gradiometer signal. Although not optimal for the case of SSVEP detection, this set-up can prove to be highly useful for other magnetoencephalography(MEG) paradigms that require good noise cancellation.Considering its compactness, low cost, and good performance, the K-SERF sensor has great potential for biomagnetic field measurements and brain-computer interfaces(BCI).
基金University of Macao,Nos.MYRG2019-00082-FHS and MYRG2018-00081-FHSMacao Science and Technology Development Fund,No.FDCT 025/2015/A1 and FDCT 0011/2018/A1.
文摘Brain oscillations are vital to cognitive functions,while disrupted oscillatory activity is linked to various brain disorders.Although high-frequency neural oscillations(>1 Hz)have been extensively studied in cognition,the neural mechanisms underlying low-frequency hemodynamic oscillations(LFHO)<1 Hz have not yet been fully explored.One way to examine oscillatory neural dynamics is to use a facial expression(FE)paradigm to induce steady-state visual evoked potentials(SSVEPs),which has been used in electroencephalography studies of high-frequency brain oscillation activity.In this study,LFHO during SSVEP-inducing periodic flickering stimuli presentation were inspected using functional near-infrared spectroscopy(fNIRS),in which hemodynamic responses in the prefrontal cortex were recorded while participants were passively viewing dynamic FEs flickering at 0.2 Hz.The fast Fourier analysis results demonstrated that the power exhibited monochronic peaks at 0.2 Hz across all channels,indicating that the periodic events successfully elicited LFHO in the prefrontal cortex.More importantly,measurement of LFHO can effectively distinguish the brain activation difference between different cognitive conditions,with happy FE presentation showing greater LFHO power than neutral FE presentation.These results demonstrate that stimuli flashing at a given frequency can induce LFHO in the prefrontal cortex,which provides new insights into the cognitive mechanisms involved in slow oscillation.
文摘In recent years, Brain Computer Interface (BCI) systems based on Steady-State Visual Evoked Potential (SSVEP) have received much attention. This study tries to develop a SSVEP based BCI system that can control a wheelchair prototype in five different positions including stop position. In this study four different flickering frequencies in low frequency region were used to elicit the SSVEPs and were displayed on a Liquid Crystal Display (LCD) monitor using Lab-VIEW. Four stimuli colors, green, red, blue and violet were used to investigate the color influence in SSVEPs. The Electroencephalogram (EEG) signals recorded from the occipital region were segmented into 1 second window and features were extracted by using Fast Fourier Transform (FFT). One-Against-All (OAA), a popular strategy for multiclass SVM, is used to classify SSVEP signals. During stimuli color comparison SSVEP with violet color showed higher accuracy than that with green, red and blue stimuli.
基金supported by the Zhejiang Provincial Natural Science Foundation of China (Y207527)
文摘The present study investigated the allocation of spatial attention using steady-state visual evoked potentials(SSVEPs).The SSVEP is elicited in visual cortical areas by a repetitive flicker having the same fundamental frequency as the driving stimulus.Two flickers were applied with the letter stream presented in the center of the monitor and the distractor presented on either the left or right side of the target.Participants were instructed to detect the target letter in the letter stream.The distance of the two flickers was manipulated.The results show that the amplitudes of the SSVEPs elicited by the distractor were enhanced when it was in the closest position and suppressed when it was at a farther distance.But the amplitudes rebounded at the farthest distance.Meanwhile,the SSVEP elicited by the target flicker remained stable independent of the distance of the distractor.Thus,the present study indicates that focused attention involves neural suppression surrounding the classic "spotlight",and the SSVEP paradigms open new avenues for studying the attentional suppression mechanism.
基金supported by the Key Research and Development Program of Guangdong Province (No. 2018B030339001)the National Key Research and Development Program of China (No. 2017YFB1002505)the National Natural Science Foundation of China (No. 61431007)
文摘This study explored methods for improving the performance of Steady-State Visual Evoked Potential(SSVEP)-based Brain-Computer Interfaces(BCI), and introduced a new analytical method to quantitatively analyze and reflect the characteristics of SSVEP. We focused on the effect of the pre-stimulation paradigm on the SSVEP dynamic models and the dynamic response process of SSVEP, and performed a comparative analysis of three pre-stimulus paradigms(black, gray, and white). Four dynamic models with different orders(second-and third-order)and with and without a zero point were used to fit the SSVEP envelope. The zero-pole analytical method was adopted to conduct quantitative analysis on the dynamic models, and the response characteristics of SSVEP were represented by zero-pole distribution characteristics. The results of this study indicated that the pre-stimulation paradigm affects the characteristics of SSVEP, and the dynamic models had good fitting abilities with SSVEPs under various types of pre-stimulation. Furthermore, the zero-pole characteristics of the models effectively characterize the damping coefficient, oscillation period, and other SSVEP characteristics. The comparison of zeros and poles indicated that the gray pre-stimulation condition corresponds to a lower damping coefficient, thus showing its potential to improve the performance of SSVEP-BCIs.
