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Electroencephalography (EEG) processing methods mostly focus on extracting its spectral or spatial features, which are proven to discriminate bilateral hand movement, hand movement directions and speed. The focus of current study is to explore EEG time-domain features that represent neural correlates of hand movement execution speed. In this paper, we propose autocorrelation analysis of EEG and features...
Major depressive disorder (MDD) is associated with excessive self-focus and a tendency to engage in self-reflection. Women are more inclined to form negative thoughts when facing problems such as social rejection. The neuroimaging studies addressing MDD females are still rare. The medial prefrontal cortex, a central node of anterior default mode network (DMN), plays an important role in the pathophysiology...
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...
Current Brain Computer Interface (BCI) systems are limited by relying on neuronal spikes and decoding limited to kinematics only. For a BCI system to be practically useful, it should be able to decode brain information on a continuous basis with low latency. This study investigates if force can be decoded from local field potentials (LFP) recorded with deep brain electrodes located at the Subthalamic...
Recently, we proposed a musculoskeletal model to simultaneously predict motion along metacarpophalangeal (MCP) and wrist flexion/extension degrees-of-freedom (DOFs) from surface electromyography (EMG) signals. Since wrist pronation/supination is also functionally important, we extended the musculoskeletal model to simultaneously estimate wrist pronation/supination in addition to wrist and MCP flexion/extension...
Schizophrenia is a severe psychiatric disorder that affects individuals across the course of their lifetime. Neurocognitive deficits are a typical characteristic of this disorder and are prominent in many cognitive domains including attention and fluency. Despite the recognized importance, patient cognition is rarely monitored as a regular part of treatment and even then, only with behavioral metrics...
We present here a browser-based application for visualizing patterns of connectivity in 3D stacked data matrices with large numbers of pairwise relations. Visualizing a connectivity matrix, looking for trends and patterns, and dynamically manipulating these values is a challenge for scientists from diverse fields, including neuroscience and genomics. In particular, high-dimensional neural data include...
Recently, SSVEP detection from EEG signals has attracted the interest of the research community, leading to a number of well-tailored methods, such as Canonical Correlation Analysis (CCA) and a number of variants. Despite their effectiveness, due to their strong dependence on the correct calculation of correlations, these methods may prove to be inadequate in front of potential deficiency in the number...
Multi-target stimulus coding plays an important role in a steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI). In conventional SSVEP-based BCIs, a large interval between two neighboring stimulus frequencies is often used to improve classification accuracy. Although recent progresses in stimulus coding and target identification methods that have significantly improved...
Functional intrinsic brain networks (IBNs) has been widely studied due to its close relationship to different brain functions and diseases. In these studies, linear metrics, e.g., correlation, have been commonly used in identifying brain networks, especially on functional magnetic resonance imaging (fMRI) data. However, nonlinear mechanism is believed to exist in forming brain networks. In the present...
Grasping objects is one of the most important hand utilisation in everyday life. Due to neuromuscular ailments or injury, some people are unable to move their hands. Though myoelectrically controlled prostheses are widely available in the market, they require some muscle based control points which are hardly available for many. Motor Imagination (MI) controlled prostheses will surpass this shortcomings...
To study the metabolic changes following amputation, we investigated the metabolite concentrations in the secondary somatosensory cortex and thalamus from twenty-three upper limb amputees and sixteen age-matched healthy controls using proton magnetic resonance spectroscopy (MRS). The ratios of major metabolites to the creatine (Cr) peak were quantified to indicate metabolite levels. Compared with...
Generalized linear models (GLMs) are useful tools to capture the characteristic features of spiking neurons; however, the long-term prediction of an autoregressive GLM inferred through maximum likelihood (ML) can be subject to runway self-excitation. We explain here that this runaway excitation is a consequence of the one-step-ahead ML inference used in estimating the parameters of the GLM. Alternatively,...
In this paper, we compared the performance of a number of Diffusion Tensor Imaging (DTI) pre-processing tools on a dataset of chronic subcortical stroke patients during rehabilitation exercise. In the comparison, acquired Diffusion-Weighted Images (DWI) are pre-processed by different pipelines, which compose of different DTI pre-processing tools, independently. And a DTI measure, FA (fractional anisotropy),...
Transcranial Magnetic Stimulation (TMS) treatments have been employed in hospitals. Conventional figure-8 coils can only stimulate a highly localized area, and it is difficult to stimulate specific points accurately without an infrared camera system that is large and expensive. To ease patients' burden, we suggest home treatment with a smaller driving circuit and a smaller positioning system that...
Visual brain-computer interfaces (BCIs) have achieved great progress in speed recently. But the problem of visual fatigue caused by intense flashes poses a great challenge in designing practical systems for long-term use. A direct way to improve visual comfort is to reduce the stimulus contrast. But it could also weaken the featured evoked potentials, which would bring a negative impact on system...
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