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In this paper, we present the design and performance of a portable, arbitrary waveform, multichannel constant current electrotactile stimulator that costs less than $30 in components. The stimulator consists of a stimulation controller and power supply that are less than half the size of a credit card and can produce ±15 mA at ±150 V. The design is easily extensible to multiple independent channels...
The effect of high frequency repetitive transcranial magnetic stimulation (rTMS) with a subthreshold intensity on hemodynamic response in brain cortices (both motor and prefrontal cortices) was investigated using the functional near infrared spectroscopy (fNIRS) technique. FNIRS signals of the motor and prefrontal cortices were acquired in healthy volunteers (n=7) at rest and during rTMS intervention...
Visual prosthesis based on penetrative optic nerve (ON) stimulation is an alternative approach to partially restore visual function. As one of the most important factors, pulse shape of electrical stimulus is a major consideration in the design of ON visual prosthesis. Animal experiments showed that the evoked responses in visual cortex (V1) to ON electrical stimulation are dependent on the stimulus...
Regenerative peripheral-nerve interfaces are a novel method for integrating with the peripheral nervous system. These devices have the potential to isolate and transduce both afferent (sensory) and efferent (motor) neural signals to produce fine control of advanced prosthetics. We have developed a novel regenerative device comprised of microfabricated polyimide electrode threads supported by a hydrogel...
Mitigating pathological synchrony of neurons in basal ganglia networks was considered as one of the potential mechanisms of deep brain stimulation (DBS) in treating Parkinson's disease. Motivated by reducing the energy of external stimuli, optimal control strategies are presented to regulate DBS waveform so as to mitigate synchronous oscillations of neural networks with fewer energy expenditure. In...
In Motor Imagery literature, performance predictors are commonly divided in four categories: personal, psychological, anatomical and neurophysiological. However these predictors are limited to inter-subjects changes. To overcome this limitation and evaluate intra-subjects performance, we tried to combine two groups of these measures: psychological and neurophysiological. As neurophysiological variables...
Satellite glial cells (SGCs) are supporting cells enveloping and isolating soma of neurons in sensory ganglia such as dorsal root ganglion (DRG) in the peripheral nervous system. Recent studies have shown that they are involved in intercellular communication between neuronal somata within ganglia in chronic pain and inflammatory conditions. One hypothesis proposed for this communication is via release...
In support of a method for nonlinear modeling of cortical connectivity, an innovation in evolutionary processing is reported. By a strategic modification to the crossover and mutation operators within the NSGA-II genetic algorithm, the number of generations required to achieve optimal nonlinear regressor models with 99.9% confidence is reduced by 52%.
We developed a technique showing that non stationarities in EEG signal carry information about cognition. This technique was successfully tested in two different databases: a working memory database, and an Alzheimer disease database. We also provide evidence suggesting that EEG might not be even piecewise stationary. Therefore, as changes between different stationary regimes are linked to transitions...
Decoding intended movement trajectory from neural activity is crucial for developing neuroprosthetic devices. In this study, we propose a processing framework to combine different information from two types of neural activities: action potentials (spikes) and local field potentials (LFPs). For this purpose, we proposed a stacked generalization approach based on recurrent neural network to enhance...
In order to understand brain mechanisms and functionalities, neural probes with electrode arrays are incorporated into mice and Local Field Potentials (LFP) are recorded indicating the activities of groups of neurons. Next, the brain activity can be analyzed in terms of Current Source Density (CSD), which are computed via the LFP. In this paper, we propose the analysis of the somatosensory cortex...
Sparse Bayesian Learning (SBL) is a widely used framework which helps us to deal with two basic problems of machine learning, to avoid overfitting of the model and to incorporate prior knowledge into it. In this work, multiple linear regression models under the SBL framework are used for the problem of multiclass classification when multiple subjects are available. As a case study, we apply our method...
Brain-machine interface (BMI) can be used to control robotic arm to assist paralysis people improving their quality of life. However process control of objects grasping is still a complex task for BMI users. High efficiency and accuracy is hard to achieve in objects grasping process even after extensive training. An important reason is lack of sufficient feedback information for performing the closed-loop...
Visual fixation is an item of the Coma Recovery Scale-Revised (CRS-R), it is difficult to be detected by clinicians using the behavioral scales because of fluctuations of arousal level and the presence of motor impairment in disorders of consciousness (DOC) patients. Brain-computer interfaces (BCIs), which directly detect brain response without any behavioral expression, can be used to evaluate a...
The ability to allow subjects, including paralyzed patients, to perform a task using brain-computer interfaces has seen a rapid and growing success. Surprisingly, however, it is still not known how far such performance can be improved - especially in cases of long term amputation where both efferent and afferent functions are abolished and may lead to deterioration of the relevant brain representations...
Denoising, noise or interferences are removed from recorded signal to enhance the signal-to-noise ratio (SNR), is a crucial and ubiquitous step in the procedure of signal processing, especially for neurophysiological signal. This step facilitates following processing, such as feature extraction, classification, and data analyses. Conventional methods are based on the principle of separating noise...
Electrocorticogram (ECoG) based Brain-Computer Interfaces (BCI) provide finer spatial resolution and improved signal-to-noise ratio than its noninvasive counterpart, Electroencephalogram (EEG). This remarkable feature allows for processing in higher spectral bands in order to elucidate more spatially localized encoding mechanisms. We propose an automatic, fully data-driven method to extract relevant...
In P300 speller brain-computer interface (BCI), the stimulus sequence is presented to subject for several rounds to achieve reliable P300 detection. Traditionally, the number of rounds is fixed and relatively large (e.g., 15 in the Wadsworth Dataset of BCI Competition 2005), which results in low information transfer rate. In order to improve the speed of character recognition without affecting the...
Stroke can be defined as a sudden onset of neurological deficits caused by a focal injury to the central nervous system from a vascular cause. In ischemic stroke (∼87% of all strokes) and transient ischemic attack (TIA), the blood vessel carrying blood to the brain is blocked causing deficit in the glucose supply - the main energy source. Here, neurovascular coupling (NVC) mechanism links neural activity...
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