Processing of EEG Signals for Study of Coupling in Brain Regions for Eyes Open and Eyes Closed Conditions

This paper deals with processing the EEG signals obtained from 16 spatially arranged electrodes to measure coupling or synchrony between the frontal, parietal, occipital and temporal lobes of the cerebrum under the eyes open and eyes closed conditions. This synchrony was measured using magnitude squared coherence, Short Time Fourier Transform and wavelet based coherences. We found a pattern in the time-frequency coherence as we moved from the nasion to the inion of the subject's head. The coherence pattern obtained from the wavelet approach was found to be far more capable of picking up peaks in coherence with respect to frequency when compared to the regular Fourier based coherence. We detected high synchrony between frontal polar electrodes that is missing in coherence plots between other electrode pairs. The study has potential applications in healthcare.

A Bacterial Foraging Optimization and Learning Automata Based Feature Selection for Motor Imagery EEG Classification

Selection of relevant features is an open problem in Brain-computer interfacing (BCI) research. Sometimes, features extracted from brain signals are high dimensional which in turn affects the accuracy of the classifier. Selection of the most relevant features improves the performance of the classifier and reduces the computational cost of the system. In this study, we have used a combination of Bacterial Foraging Optimization and Learning Automata to determine the best subset of features from a given motor imagery electroencephalography (EEG) based BCI dataset. Here, we have employed Discrete Wavelet Transform to obtain a high dimensional feature set and classified it by Distance Likelihood Ratio Test. Our proposed feature selector produced an accuracy of 80.291% in 216 seconds.

Dissecting neural circuits for vision in nonhuman primates using fMRI-guided electrophysiology and optogenetics

The visual system is a remarkable platform that evolved to solve difficult computational problems such as detection, recognition, and classification of objects. Of great interest is the face-processing network, a sub-system buried deep in the temporal lobe, dedicated for analyzing specific type of objects (faces). In this thesis, I focus on the problem of face detection by the face-processing network. Insights obtained from years of developing computer-vision algorithms to solve this task have suggested that it may be efficiently and effectively solved by detection and integration of local contrast features. Does the brain use a similar strategy? To answer this question, I embark on a journey that takes me through the development and optimization of dedicated tools for targeting and perturbing deep brain structures. Data collected using MR-guided electrophysiology in early face-processing regions was found to have strong selectivity for contrast features, similar to ones used by artificial systems. While individual cells were tuned for only a small subset of features, the population as a whole encoded the full spectrum of features that are predictive to the presence of a face in an image. Together with additional evidence, my results suggest a possible computational mechanism for face detection in early face processing regions. To move from correlation to causation, I focus on adopting an emergent technology for perturbing brain activity using light: optogenetics. While this technique has the potential to overcome problems associated with the de-facto way of brain stimulation (electrical microstimulation), many open questions remain about its applicability and effectiveness for perturbing the non-human primate (NHP) brain. In a set of experiments, I use viral vectors to deliver genetically encoded optogenetic constructs to the frontal eye field and faceselective regions in NHP and examine their effects side-by-side with electrical microstimulation to assess their effectiveness in perturbing neural activity as well as behavior. Results suggest that cells are robustly and strongly modulated upon light delivery and that such perturbation can modulate and even initiate motor behavior, thus, paving the way for future explorations that may apply these tools to study connectivity and information flow in the face processing network.

What Can the Brain Teach Us about Winemaking? An fMRI Study of Alcohol Level Preferences

Over the last few decades, wine makers have been producing wines with a higher alcohol content, assuming that they are more appreciated by consumers. To test this hypothesis, we used functional magnetic imaging to compare reactions of human subjects to different types of wine, focusing on brain regions critical for flavor processing and food reward. Participants were presented with carefully matched pairs of high- and low- alcohol content red wines, without informing them of any of the wine attributes. Contrary to expectation, significantly greater activation was found for low- alcohol than for high- alcohol content wines in brain regions that are sensitive to taste intensity, including the insula as well as the cerebellum. Wines were closely matched for all physical attributes except for alcohol content, thus we interpret the preferential response to the low- alcohol content wines as arising from top-down modulation due to the low alcohol content wines inducing greater attentional exploration of aromas and flavours. The findings raise intriguing possibilities for objectively testing hypotheses regarding methods of producing a highly complex product such as wine.

Accurate real-time feedback of surface EMG during fMRI.

Real-time acquisition of EMG during functional MRI (fMRI) provides a novel method of controlling motor experiments in the scanner using feedback of EMG. Because of the redundancy in the human muscle system, this is not possible from recordings of joint torque and kinematics alone, because these provide no information about individual muscle activation. This is particularly critical during brain imaging because brain activations are not only related to joint torques and kinematics but are also related to individual muscle activation. However, EMG collected during imaging is corrupted by large artifacts induced by the varying magnetic fields and radio frequency (RF) pulses in the scanner. Methods proposed in literature for artifact removal are complex, computationally expensive, and difficult to implement for real-time noise removal. We describe an acquisition system and algorithm that enables real-time acquisition for the first time. The algorithm removes particular frequencies from the EMG spectrum in which the noise is concentrated. Although this decreases the power content of the EMG, this method provides excellent estimates of EMG with good resolution. Comparisons show that the cleaned EMG obtained with the algorithm is, like actual EMG, very well correlated with joint torque and can thus be used for real-time visual feedback during functional studies.

Delta EEG Activity in Left Orbitofrontal Cortex in Rats Related to Food Reward and Craving

眶额叶皮质与中脑边缘多巴胺奖赏系统有着复杂的相互纤维联系.先前的研究探讨了药物成瘾过程中眶额叶皮质的脑电活动.在本实验中,将探讨食物奖赏和渴求过程中该皮质的脑电活动.实验采用了两个环境:对照环境和食物刺激相关的环境.首先,训练大鼠在食物刺激相关的环境中吃巧克力花生豆,而后在该环境中设置两种不同的刺激方式:能看到和闻到但不能吃到(渴求实验),或者仍旧可以吃到巧克力花生豆(奖赏实验):同时进行左侧眶额叶皮质的脑电记录.结果发现,在食物刺激相关的环境中大鼠Delta频段(2-4Hz)的脑电活动与食物刺激显著相关,此外,与在对照环境中相比,其相对功率在食物渴求时下降而在食物奖赏时升高.本实验表明,食物相关的奖励可以改变大鼠眶额叶皮质的脑电活动,而且,Delta频段的脑电活动能够作为监测该奖励的一个指标.

EEG activities in the orbitofrontal cortex and dorsolateral prefrontal cortex during the development of morphine dependence, tolerance and withdrawal in rhesus monkeys

Investigating the activities of the prefrontal cortex (PFC) in the process of addiction is valuable for understanding the neural mechanism underlying the impairments of the PFC after drug abuse. However, limited data are obtained from primate animals and few studies analyze Electroencephalogram (EEG) in the gamma band, which plays an important role in cognitive functions. In addition, it is yet unclear whether drug abuse affects the orbitofrontal cortex (OFC) and dorsolateral PFC (DLPFC) - the two most important subregions of the PFC - in similar ways or not. The aim of this study is to address these issues. We recorded EEG in the OFC and DLPFC in three rhesus monkeys. All animals received a course of saline (NaCl 0.9%, 2 ml) injection (5 days) followed by 10 days of morphine injection (every 12 h), and then a further series of saline injection (7 days). A main finding in the present study was that morphine decreased EEG power in all frequency bands in a short period after injection in both the OFC and DLPFC in monkeys. And gamma power decreased not just in short period after morphine injection but lasted to 12 h after injection. Moreover, we found that although the changes in EEG activities in the OFC and DLPFC at 30-35 min after injection were similar, the DLPFC was more sensitive to the effect of morphine than the OFC. (c) 2005 Elsevier B.V. All rights reserved.

Differential effects of ageing on the EEG during pentobarbital and ketamine anaesthesia

Background and objectives: Pentobarbital and ketamine are commonly used in animal experiments, including studies on the effects of ageing on the central nervous system. The electroencephalogram is a sensitive measure of brain activity. The present study i

Simulation of a monolithically integrated CMOS bioamplifier for EEG recordings

A monolithically integrated CMOS bioamplifier is presented in this paper for EEG recording applications. The capacitive-coupled circuit input structure is utilized to eliminate the large and random DC offsets existing in the electrode-tissue interface. Diode-connected NMOS transistors with negative voltage between gate and source are candidates for large resistors necessary to the bioamplifier. A passive BEF (Band Eliminator Filter) can reduce 50 Hz noise disturbance strength by more than 60 dB. A novel analysis approach is given to help determine the noise power spectral density. Simulation results show that the two-stage CMOS bioamplifier in a closed-loop capacitive feedback configuration,provides an AC in-band gain of 39.6 dB, a DC gain of zero, and an input-referred noise of 87 nVrms integrated from 0.01 Hz to 100 Hz.

基于支持向量多分类机的多类复杂手操作EEG信号模式识别

针对用于服务机器人的脑机接口系统中脑电信号模式识别精度不高,不能满足机器人多任务要求的问题,提出一种基于C-支持向量多分类机的多类复杂手操作EEG信号模式识别方法,并将其应用到复杂手操作的EEG信号模式识别试验中,实现一个4类复杂手操作的模式识别,实验结果表明,与之前用BP神经网络进行识别相比,识别率由85%提高到了90%。

空间及言语工作记忆任务的情绪效应：来自ERP/ fMRI的证据

In the present study, based on processing efficiency theory, we used the event-related potentials (ERP) and functional magnetic resonance image (fMRI) techniques to explore the underlying neutral mechanism of influences of negative emotion on three subsystems of working memory, phonological loop、 visuospatial sketh pad and the central executive. The modified DSMT (delayed matching-to-sample task) and n-back tasks were adopted and IAPS (International Affective Picture System) pictures were employed to induce the expected emotional state of subjects. The main results and conclusions obtained in the series of experiments are as the following: 1. In DSM tasks, we found P200 and P300 were reduced by negative emotion in both spatial and verbal tasks, however the increased negative slow wave were only observed in spatial tasks, not in verbal tasks. 2. In n-back tasks, the updating function of WM associated P300 was affected by negative emotion only in spatial tasks, not in verbal tasks. Current density analysis revealed strong current density in the fronto-parietal cortex only in the spatial tasks as well. 3. We adopted fMRI-block design and ROIs analysis, and found significant emotion and task effects in spatial WM-associated right superior parietal cortex; only emotion effect in verbal WM-associated Broca’s area; the interaction effect in attention-associated medial prefrontal area and bilateral inferior parietal cortex. These results implied the negative emotion mainly disturbed the spatial WM-related areas, and the attention control system play a key role in the interaction of spatial WM and negative emotion. 4. to further examine the effects of positive、negative and neutral emotion on tasks with different cognitive loads, the selective effect of emotion on the ERP components of spatial WM was only found in 2-back tasks, not in visual searching tasks. So, firstly the positive emotion as well as negative emotion selectively disturbed on spatial WM in light of the attention resource competition mechanism. Secondly, the selective influences based on the different WM systems, not the properties of spatial and verbal information. At last, the manner of the interaction of emotion and cognition is correlated with the cognitive load.