Steady-state visual evoked potential (SSVEP) is one of the commonly used control signals in brain-computer interface (BCI) systems. The SSVEP-based BCI has the advantages of high information transmission rate and short training time, which has become an important branch of BCI research field. In this review paper, the main progress on frequency recognition algorithm for SSVEP in past five years are summarized from three aspects, i.e., unsupervised learning algorithms, supervised learning algorithms and deep learning algorithms. Finally, some frontier topics and potential directions are explored.
Algorithms ; Brain-Computer Interfaces ; Electroencephalography/methods* ; Evoked Potentials, Visual ; Photic Stimulation

Brain-computer interface (BCI) can be summarized as a system that uses online brain information to realize communication between brain and computer. BCI has experienced nearly half a century of development, although it now has a high degree of awareness in the public, but the application of BCI in the actual scene is still very limited. This collection invited some BCI teams in China to report their efforts to promote BCI from laboratory to real scene. This paper summarizes the main contents of the invited papers, and looks forward to the future of BCI.
Brain ; Brain-Computer Interfaces ; China ; Electroencephalography ; Laboratories ; User-Computer Interface

Bacomics is a unified framework for the interactions of the brain and the outside world, integrating the subject, method, and application mode of brain-apparatus conversation. This article divides the brain-apparatus conversation modes from the perspective of biological and non-biological apparatus, including the brain-biological organ interaction (BAC-1), brain-external non-living equipment and environment interaction (BAC-2), and the fusion agents of these two interactions (BAC-3), and explains the ways and potential applications in different modes.
Brain

Objective: Abnormalities of static brain activity have been reported in schizophrenia, but it remains to be clarified the temporal variability of intrinsic brain activities in schizophrenia and how atypical antipsychotics affect it. Methods: We employed a resting-state functional magnetic resonance imaging (rs-fMRI) and a sliding-window analysis of dynamic amplitude of low-frequency fluctuation (dALFF) to evaluate the dynamic brain activities in schizophrenia (SZ) patients before and after 8-week antipsychotic treatment. Twenty-six schizophrenia individuals and 26 matched healthy controls (HC) were included in this study. Results: Compared with HC, SZ showed stronger dALFF in the right inferior temporal gyrus (ITG.R) at baseline. After medication, the SZ group exhibited reduced dALFF in the right middle occipital gyrus (MOG.R) and increased dALFF in the left superior frontal gyrus (SFG.L), right middle frontal gyrus (MFG.R), and right inferior parietal lobule (IPL.R). Dynamic ALFF in IPL.R was found to significant negative correlate with the Scale for the Assessment of Negative Symptoms (SANS) scores at baseline. Conclusion Our results showed dynamic intrinsic brain activities altered in schizophrenia after short term antipsychotic treatment. The findings of this study support and expand the application of dALFF method in the study of the pathological mechanism in psychosis in the future.

Adolescent ; Decision Making ; Emotions ; Humans

Objective We utilized a joint independent component analysis (Joint ICA), a novel method that combined rs?fMRI and DTI information, to describe comprehensive characteristics of brain functional activities and microstructural changes in the continuum of AD. Methods We employed a Joint ICA to calculate ALFF maps of fMRI data and FA maps of DTI data and fuse them in healthy controls (n=68), SCD (n=35), amnesic MCI (n=47) and AD (n=31). Besides, we applied one way ANOVA to detect the significant differences of joint components among groups, while controlling the age, gender, education, head motion, volumes of gray matter, white matter and CSF. Partial correlation analysis was used to test the relationships between joint ICs and cognitive measures. Results The results showed that there was no inner?group difference in HC and SCD groups (F=14.16, P<0.05). Compared to HC, SCD and AD groups, the ALFF component of aMCI group showed higher values in the bilateral cerebellum, bilateral precuneus, bilateral angular gyrus, bilateral frontal gyrus, bilateral temporal areas, thalamus and left insula. And in these regions, the ALFF of AD group was lower than HC. For the FA component map, same differences were found in the corpus callosum and limbic system. Furthermore, positive partial correlation between the IC weights and Mini?Mental State Examination (MMSE) scores was also found (r=0.29, P<0.01). Conclusions Multi?modal evaluation of AD has been implemented by using Joint ICA analysis of fMRI?DTI, which would contribute to early prediction, diagnosis, and even effective intervention in AD. These findings could help to explain the underlying mechanism of the disease progression.

Studies have shown that the clinical manifestation of patients with neuropsychiatric disorders might be related to the abnormal connectivity of brain functions. Psychogenic non-epileptic seizures (PNES) are different from the conventional epileptic seizures due to the lack of the expected electroencephalographically epileptic changes in central nervous system, but are related to the presence of significant psychological factors. Diagnosis of PNES remains challenging. We found in the present work that the connectivity between the frontal and parieto-occipital in PNES was weaker than that of the controls by using network analysis based on electroencephalogram (EEG) signals. In addition, PNES were recognized by using the network properties as linear discriminant nalysis (LDA) input and classification accuracy was 85%. This study may provide a feasible tool for clinical diagnosis of PNES.
Brain ; physiopathology ; Electroencephalography ; Epilepsy ; Humans ; Seizures ; diagnosis

Objective To investigate the clinical efficacy of transarterial chemoembolization (TACE) combined with sorafenib for the treatment of inoperable hepatocellular carcinoma (HCC), and to discuss the influence of treatment interval on the survival time. Methods During the period from July 2008 to May 2011 at authors’ hospital, a total of 50 patients with inoperable HCC were treated with TACE together with sorafenib. The treatment intervals between each TACE procedure were recorded. The results were analyzed. Results Up to Dec. 31, 2011, the median follow-up time of the 50 patients was 310 days. The mean interval between TACE treatments was 69 days before the combination treatment was employed , while the mean interval was 112 days after the combination treatment started , and the longest interval was 648 days. Conclusion Combination treatment TACE with sorafenib can remarkably prolong the treatment interval in patients with inoperable HCC, thus the patient can get more survival benefits.

Objective To investigate the application of C- arm CT imaging technique in evaluating the efficacy of transarterial chemoembolization(TACE) for hepatocellular carcinoma(HCC). Methods During the period from Sep. 2012 to Mar. 2013 at authors’ hospital, C- arm CT scanning was employed during the performance of TACE in 80 patients with HCC. The residual active tumor lesions, Lipiodol deposition and the embolization of the feeding arteries after TACE therapy were assessed by C- arm CT plain scan images and the images of early artery phase and parenchymal phase, as well as the post- processing images. The efficacy of TACE was thus evaluated. Results A total of 139 hepatic tumors were detected in 80 patients by C- arm CT imaging. C- arm CT scanning performed immediately after TACE showed that satisfactory result was obtained in 128 lesions of 75 patients(128/139, 92.9%). Fewer, medium and more residual active tumors were seen in 78, 29 and 21 lesions respectively, while dense, moderate and thin Lipiodol deposition was seen in 64, 39 and 25 lesions respectively. After TACE therapy obvious decrease in blood supply was demonstrated in 101 lesions, while no obvious decrease in blood supply was seen in 27 lesions. Conclusion C- arm CT scanning after TACE for patients with HCC can conveniently, accurately and comprehensively reveal the residual active tumors, Lipiodol deposition and embolization status of feeding arteries. Therefore, this technique should be regarded as an important means to evaluate the efficacy of TACE.

Neurofeedback, as an alternative treatment method of behavioral medicine, is a technique which translates the electroencephalogram (EEG) signals to styles as sounds or animation to help people understand their own physical status and learn to enhance or suppress certain EEG signals to regulate their own brain functions after several repeated trainings. This paper develops a neurofeedback system on the foundation of brain-computer interface technique. The EEG features are extracted through real-time signal process and then translated to feedback information. Two feedback screens are designed for relaxation training and attention training individually. The veracity and feasibility of the neurofeedback system are validated through system simulation and preliminary experiment.
Brain-Computer Interfaces ; Electroencephalography ; Female ; Humans ; Neurofeedback