Jiajia Yang

Enhancing performance of a motor imagery based brain–computer interface by incorporating electrical stimulation-induced SSSEP

OBJECTIVE We proposed a novel simultaneous hybrid brain-computer interface (BCI) by incorporating electrical stimulation into a motor imagery (MI) based BCI system. The goal of this study was to enhance the overall performance of an MI-based BCI. In addition, the brain oscillatory pattern in the hybrid task was also investigated. APPROACH 64-channel electroencephalographic (EEG) data were recorded during MI, selective attention (SA) and hybrid tasks in fourteen healthy subjects. In the hybrid task, subjects performed MI with electrical stimulation which was applied to bilateral median nerve on wrists simultaneously. MAIN RESULTS The hybrid task clearly presented additional steady-state somatosensory evoked potential (SSSEP) induced by electrical stimulation with MI-induced event-related desynchronization (ERD). By combining ERD and SSSEP features, the performance in the hybrid task was significantly better than in both MI and SA tasks, achieving a ~14% improvement in total relative to the MI task alone and reaching ~89% in mean classification accuracy. On the contrary, there was no significant enhancement obtained in performance while separate ERD feature was utilized in the hybrid task. In terms of the hybrid task, the performance using combined feature was significantly better than using separate ERD or SSSEP feature. SIGNIFICANCE The results in this work validate the feasibility of our proposed approach to form a novel MI-SSSEP hybrid BCI outperforming a conventional MI-based BCI through combing MI with electrical stimulation.

Abnormal EEG Complexity and Functional Connectivity of Brain in Patients with Acute Thalamic Ischemic Stroke

Ischemic thalamus stroke has become a serious cardiovascular and cerebral disease in recent years. To date the existing researches mostly concentrated on the power spectral density (PSD) in several frequency bands. In this paper, we investigated the nonlinear features of EEG and brain functional connectivity in patients with acute thalamic ischemic stroke and healthy subjects. Electroencephalography (EEG) in resting condition with eyes closed was recorded for 12 stroke patients and 11 healthy subjects as control group. Lempel-Ziv complexity (LZC), Sample Entropy (SampEn), and brain network using partial directed coherence (PDC) were calculated for feature extraction. Results showed that patients had increased mean LZC and SampEn than the controls, which implied the stroke group has higher EEG complexity. For the brain network, the stroke group displayed a trend of weaker cortical connectivity, which suggests a functional impairment of information transmission in cortical connections in stroke patients. These findings suggest that nonlinear analysis and brain network could provide essential information for better understanding the brain dysfunction in the stroke and assisting monitoring or prognostication of stroke evolution.

Emotion recognition based on EEG changes in movie viewing

EEG-based emotion recognition has received increasing attention in advanced human-computer interaction, where the choice of independent variables to discriminate emotions from the frequency range of EEG and electrode locations is not very self-evident, thus this work tried to find the correlation between the emotional states and both EEG frequency ranges and EEG channels. 12 healthy volunteers were emotionally elicited by movie clips to experience five basic emotional states of neutral, happy, sad, tense and disgust states. Fisher discriminant ratio (FDR) was employed to find the discriminative bands and electrodes with statistical differences. Finally, a support vector machine (SVM) with 5-fold cross validation was performed. Average recognition rates have achieved 93.31% and 85.39% for two feature sets.

An online hybrid brain-computer interface combining multiple physiological signals for webpage browse

The hybrid brain computer interface (hBCI) could provide higher information transfer rate than did the classical BCIs. It included more than one brain-computer or human-machine interact paradigms, such as the combination of the P300 and SSVEP paradigms. Research firstly constructed independent subsystems of three different paradigms and tested each of them with online experiments. Then we constructed a serial hybrid BCI system which combined these paradigms to achieve the functions of typing letters, moving and clicking cursor, and switching among them for the purpose of browsing webpages. Five subjects were involved in this study. They all successfully realized these functions in the online tests. The subjects could achieve an accuracy above 90% after training, which met the requirement in operating the system efficiently. The results demonstrated that it was an efficient system capable of robustness, which provided an approach for the clinic application.The hybrid brain computer interface (hBCI) could provide higher information transfer rate than did the classical BCIs. It included more than one brain-computer or human-machine interact paradigms, such as the combination of the P300 and SSVEP paradigms. Research firstly constructed independent subsystems of three different paradigms and tested each of them with online experiments. Then we constructed a serial hybrid BCI system which combined these paradigms to achieve the functions of typing letters, moving and clicking cursor, and switching among them for the purpose of browsing webpages. Five subjects were involved in this study. They all successfully realized these functions in the online tests. The subjects could achieve an accuracy above 90% after training, which met the requirement in operating the system efficiently. The results demonstrated that it was an efficient system capable of robustness, which provided an approach for the clinic application.

VEGF attenuates 2-VO induced cognitive impairment and neuronal injury associated with the activation of PI3K/Akt and Notch1 pathway

&NA; Vascular endothelial growth factor (VEGF) has been identified as a potential treatment for effectively improving cognitive function in several neuropathological conditions. However, the underlying mechanism and the relevant downstream protective pathways that are activated in neurons by VEGF remain elusive, especially in chronic global cerebral ischemia. In this study, we intended to investigate the signaling mechanisms of VEGF in cognitive protection and anti‐apoptosis in a rat model of chronic global cerebral ischemia induced by permanent bilateral common carotid artery occlusion (2‐VO). The results showed that intranasal administration of VEGF (72 h post‐ischemia for 6 successive days) caused a significant improvement in the cognitive deficits induced by 2‐VO, accompanied by a reversal of oxidative stress and VEGF depletion in the hippocampus. In addition, VEGF‐treatment decreased the expression of Bax and Caspase‐3, increased the expression of anti‐apoptotic Bcl‐xl and the main protein involved in energy homeostasis AMP‐activated protein kinase (AMPK), which may account for the anti‐apoptotic effects of VEGF. Importantly, VEGF administration upregulated the phosphorylation levels of Akt (pAkt) and PI3K, activated Notch1 pathway in 2‐VO hippocampus. These findings suggested that intranasal administration of VEGF alleviated cognitive impairment induced by 2‐VO injury, and attenuated oxidative damage and neuronal injury in hippocampus associated with the regulation of PI3K/Akt and Notch1 signaling pathway, which might be the underlying mechanisms of VEGF on global chronic cerebral ischemia. HighlightsIntranasal administration of VEGF improved cognitive deficits in 2‐VO rats.VEGF attenuated neuronal and oxidative stress damage in 2‐VO hippocampus.VEGF alleviates neuronal apoptosis via the activation of PI3K/Akt pathway.Notch1 signaling pathway is involved with the cognitive protection of VEGF.

Bombesin attenuated ischemia-induced spatial cognitive and synaptic plasticity impairment associated with oxidative damage

The dysfunction of spatial cognition is a character to various neurological disorders and therapeutic strategy. However, it is limited to known risk factors clinically so far. Gastrin releasing peptide (GRP) signaling is a neuropeptide system mediating emotional memory events. However, the effects of GRP agonist on spatial cognition and hippocampal synaptic plasticity are rarely investigated, especially in pathologic condition. This study was designed to investigate the long-term effects of GRPR agonist, bombesin, against cognitive impairment induced by chronic cerebral ischemia in rats and its possible mechanisms. Our results revealed that bombesin administration (30 μg/kg/day, for 14 continuous days) significantly protected the cognitive and synaptic plasticity impairments as assessed by the Morris water maze and long-term potentiation tests. The mechanism studies demonstrated that bombesin significantly alleviated the decreased activity of total superoxide dismutase (T-SOD), catalase (CAT) and altered the increased the content of malondialdehyde (MDA). Besides, the decreased expression of synapse plasticity-related proteins, calcium- calmodulin- dependent protein kinase II (CaMKII) and synaptophysin (SYP) in the hippocampus were increased with drug treatment. In conclusion, bombesin could protect the oxidative stress and expression of proteins, which were important for synaptic plasticity and cognitive function impairment induced by chronic cerebral ischemia. Our study is presented to provide novel insights into the effects of bombesin on spatial learning and memory, which should be further explored as a potential drug in disorders involving deficits in cognitive function.

Research on Gastroesophageal Reflux Disease Based on Dynamic Features of Ambulatory 24-Hour Esophageal pH Monitoring

Ambulatory 24-hour esophageal pH monitoring has been considered as the gold standard for diagnosing gastroesophageal reflux disease (GERD), and in clinical application, static parameters are widely used, such as DeMeester score. However, a shortcoming of these static variables is their relatively high false negative rate and long recording time required. They may be falsely labeled as nonrefluxers and not appropriately treated. Therefore, it is necessary to seek more accurate and objective parameters to detect and quantify GERD. This paper first describes a new effort that investigated the feasibility of dynamic features of 24-hour pH recording. Wavelet energy, information entropy, and wavelet entropy were estimated for three groups (severe, mild-to-moderate, and normal). The results suggest that wavelet energy and entropy are physiologically meaningful since they differentiated patients with varying degrees of GERD. K-means clustering algorithm was employed to obtain the sensitivity and specificity of new parameters. It is obvious that information entropy goes with the highest sensitivity of 87.3% and wavelet energy has the highest specificity of 97.1%. This would allow a more accurate definition of the best indicators to detect and quantify GERD as well as provide an alternative insight into the early diagnosis of GERD.