The maximum length sequence (m-sequence) has been successfully used to study the linear/nonlinear components of auditory evoked potential (AEP) with rapid stimulation. However, more study is needed to evaluate the effect of the m-sequence order in terms of the noise attenuation performance. This study aimed to address this issue using response-free electroencephalogram (EEG) and EEGs with nonlinear AEPs. We examined the noise attenuation ratios to evaluate the noise variation for the calculations of superimposed averaging and cross-correlation, respectively, which constitutes the main process in the deconvolution method using the dataset of spontaneous EEGs to simulate the cases of different orders (order 5 to 12) of m-sequences. And an experiment using m-sequences of order 7 and 9 was performed in true cases with substantial linear and nonlinear AEPs. The results demonstrate that the noise attenuation ratio is well agreed with the theoretical value derived from the properties of m-sequences on the random noise condition. The comparison of waveforms for AEP components from two m-sequences showed high similarity suggesting the insensitivity of AEP to the m-sequence order. This study provides a more comprehensive solution to the selection of m-sequences which will facilitate the feasible application on the nonlinear AEP with m-sequence method.
ObjectiveTo study whether the pattern visual evoked potential (P-VEP) under different spatial frequency in patients with multiple sclerosis (MS) is different from normal people. MethodsP-VEP examination under high (15') and low (60') spatial frequency was performed on 18 MS patients (36 eyes) treated in our department from September 2011 to April 2012 and 20 normal volunteers (40 eyes). Then, we analyzed the difference between the two groups under the above-mentioned two kinds of spatial frequency. ResultsThe latency of P100 of P-VEP under high spatial frequency in MS patients was (120.50±13.04) ms which was significantly different from (109.21±5.38) ms of normal volunteers (P < 0.05). The latency of P100 of P-VEP under low spatial frequency in MS patients was (109.57±12.87) ms, which was also significantly different from (103.31±5.45) ms of normal volunteers (P < 0.05). The amplitude of P100 of P-VEP under high spatial frequency in MS patients was (9.17±5.69)μV and it was significantly lower than that[(15.69±8.45)μv] of normal volunteers (P < 0.05). The amplitude of P100 of P-VEP under low spatial frequency in MS patients was (11.93±16.75)μV and it was not significantly different from normal volunteers[(13.47±9.24μV)]. Based on different corrected vision, the MS patients were divided into two groups (vision≥1.0 and vision < 1.0). For patients with vision≥1.0, the latency of P100 and the amplitude of P100 of P-VEP under high spatial frequency was (113.43±8.28) ms and (12.94±5.46)μV; the latency of P100 and the amplitude of P100 of P-VEP under low spatial frequency was (111.13±11.50) ms and (11.57±5.60)μV. For patients with vision < 1.0, the latency of P100 and the amplitude of P100 of P-VEP under high spatial frequency was (126.69±13.49) ms and (5.87±3.43)μV; the latency of P100 and the amplitude of P100 of P-VEP under low spatial frequency was (108.26±14.11) ms and (12.24±5.82)μV. There was no significant difference in the latency and amplitude of P100 under low spatial frequency between the two groups with different corrected vision (P > 0.05), but the latency and amplitude of P100 under high spatial frequency were both significantly different between those two groups (P < 0.05). ConclusionsCompared with normal people, MS patients feature latency delay and amplitude reduction of the P-VEP, which was more severe under high spatial frequency. P-VEP under high spatial frequency may become an important evidence to evaluate visual function of MS patients.
Steady-state visual evoked potential (SSVEP) has been widely used in the research of brain-computer interface (BCI) system in recent years. The advantages of SSVEP-BCI system include high classification accuracy, fast information transform rate and strong anti-interference ability. Most of the traditional researches induce SSVEP responses in low and middle frequency bands as control signals. However, SSVEP in this frequency band may cause visual fatigue and even induce epilepsy in subjects. In contrast, high-frequency SSVEP-BCI provides a more comfortable and natural interaction despite its lower amplitude and weaker response. Therefore, it has been widely concerned by researchers in recent years. This paper summarized and analyzed the related research of high-frequency SSVEP-BCI in the past ten years from the aspects of paradigm and algorithm. Finally, the application prospect and development direction of high-frequency SSVEP were discussed and prospected.
ObjectiveTo evaluate the differences of visual evoked potentials (amplitudes and latency) between cerebral palsy (CP) children and normal children. MethodsThis study involved fourteen children aged from 4 to 7 years with CP (monoplegia) between 2009 and 2013. Another 14 normal children aged from 5 to 9 years treated in the Department of Ophthalmology in West China Hospital during the same period were regarded as the control group. Both eyes of all the participants were examined by multifocal visual evoked potential (mfVEP). The mfVEP examination results were recorded, and amplitude and latency were analyzed. First, we analyzed the differences of amplitudes and latency time between monoplegia children and children in the control group. Second, gross motor function classification system (GMFCS) was used to classify the fourteen monoplegia children among whom there were five GMFCS Ⅰ patients and nine GMFCS Ⅱ patients. The differences of mfVEP were analyzed between the two GMFCS groups. ResultsThe amplitude and latency of mfVEP in children with CP showed gradual changes similar to those in the normal children. The amplitudes were decreasing and the latencies were delaying from the first eccentricity to the sixth eccentricity. The amplitudes in children with CP were lower than those in the control group in the first to the third eccentricities for both eyes (P＜0.05), and latency of left eye was delayed in the first eccentricity in children with CP (P=0.045). No difference was found between the two GMFCS groups (P>0.05) except the amplitude of the first eccentricity (P=0.043). ConclusionsThe results of mfVEP show significant differences of amplitude and latency between CP and normal children, suggesting the existence of visual pathway impairments in cerebral palsy children. The results of mfVEP can provide an objective basis of visual impairments for cerebral palsy children.
ObjectiveTo study the relationship between brain white matter fiber occult lesions and P100 wave latency of visual evoked potential (VEP) in neuromyelitis optica (NMO) patients by diffusion tensor imaging (DTI). MethodsTwenty patients with NMO who were treated between July 2008 and April 2009 were selected as the trial group. According to the VEP test, the latency of P100 wave was prolonged, the NMO patients were divided into VEP abnormal group (trial group 1) and VEP normal group (trial group 2). Twenty healthy adult volunteers served as the control group. The DTI examination in brain was done to measure the fractional anisotropy (FA) value of optic nerve (FAn), optic tract (FAt), and optic radiation (FAr);and the mean diffusivity (MD) value of optic nerve (MDn), optic tract (MDt), and optic radiation (MDr). The FA, MD, and P100 wave latency were compared between groups, and the correlation between MD, FA, and P100 wave latency of NMO were analyzed. ResultsIn the 20 NMO patients, 13 patients with VEP had prolonged bilateral P100 wave latency prolongation or no wave (trial group 1), and 7 patients had normal bilateral P100 wave latency (trial group 2). Compared with the trial group 2 and the control group, the FA values were significantly decreased, and the MD values were significantly increased in the trial group 1 (P<0.05). There was no significant difference in the FA and MD values between the trial group 2 and the control group (P>0.05). All FA (FAn, FAt, and FAr) values of each part of NMO patients were negatively correlated with the latency of P100 wave (P<0.05), all MD (MDn, MDt, and MDr) values were positively correlated with the latency of P100 wave (P<0.05). ConclusionDTI could show small pathylogical changes in the white matter fibers of visual pathway, and there is a correlation between DTI and VEP in NMO, suggesting that a more comprehensive assessment to the condition and prognosis can be made through the VEP in the clinical indicators.
Injury of dorsal root ganglia (DRG) may cause sensory and motor dysfunction. In order to investigate the changes of somato-sensory evoked potential (SEP) and histological characteristics of DRG in different causes and different periods of injury, fifty-two rabbits were chosed to build the models. The rabbits were divided into 4 groups: Control group (n = 4); mechanical compressing group (n = 16); inflammatory injury group (n = 16); and treatment group (2% lidocaine with hydroprednisone was administered locally, n = 16). After one to eight weeks, SEP was determined and samples of DRG were obtained to observe the histological and ultrastructural changes every week. The result showed that the gap junction of microvascular endothelium in DRG had been destroyed by the mechanical compression was the major cause of the vessel permeability increasing. The increasing of endothelial pinocytic vesicles transportation and widening of endothelial gap junction were the main causes of inflammatory irritation of DRG. The local infiltration with 2% lidocaine and hydroprednisone could obviously ameliorate inflammatory injury in DRG.
This study investigates a brain-computer interface (BCI) system based on an augmented reality (AR) environment and steady-state visual evoked potentials (SSVEP). The system is designed to facilitate the selection of real-world objects through visual gaze in real-life scenarios. By integrating object detection technology and AR technology, the system augmented real objects with visual enhancements, providing users with visual stimuli that induced corresponding brain signals. SSVEP technology was then utilized to interpret these brain signals and identify the objects that users focused on. Additionally, an adaptive dynamic time-window-based filter bank canonical correlation analysis was employed to rapidly parse the subjects’ brain signals. Experimental results indicated that the system could effectively recognize SSVEP signals, achieving an average accuracy rate of 90.6% in visual target identification. This system extends the application of SSVEP signals to real-life scenarios, demonstrating feasibility and efficacy in assisting individuals with mobility impairments and physical disabilities in object selection tasks.
Objective To study the regulations of visual evoked potential(VEP) changes in 30 patients with multiple sclerosis (MS). Methods VEP were performed in 30 MS patients,and the results were compared with normal subjects. Results The abnormality rate of VEP were 76.7%. 82.6% of patients with abnormal VEP showed clinical visual symptoms; 17.4% among those patients have no clinical visual symptoms. Conclusion The rate of VEP abnormal in MS patients is more high. It may help more in the diagnosis of MS.
In order to investigate the clinical significance of electron-neurogram for evaluating the degree and prognosis of acute traumatic cervical spinal cord injury without fracture or dislocation, electron-neurogram and sensory evoked potential (SEP) of the upper limbs in 4 such cases were recorded from the 3rd to 30th day after the injury. The results showed SEP and MEP could be obtained from every nerve in both upper limbs, and continous monitoring of SEP and MEP could provide valuable data to judge the degree and prognosis of the injury in spinal cord.
Brain-computer interface (BCI) systems based on steady-state visual evoked potential (SSVEP) have become one of the major paradigms in BCI research due to their high signal-to-noise ratio and short training time required by users. Fast and accurate decoding of SSVEP features is a crucial step in SSVEP-BCI research. However, the current researches lack a systematic overview of SSVEP decoding algorithms and analyses of the connections and differences between them, so it is difficult for researchers to choose the optimum algorithm under different situations. To address this problem, this paper focuses on the progress of SSVEP decoding algorithms in recent years and divides them into two categories—trained and non-trained—based on whether training data are needed. This paper also explains the fundamental theories and application scopes of decoding algorithms such as canonical correlation analysis (CCA), task-related component analysis (TRCA) and the extended algorithms, concludes the commonly used strategies for processing decoding algorithms, and discusses the challenges and opportunities in this field in the end.