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A new method of detecting somatosensory evoked potentials (SSEP) is proposed using a time-frequency based windowing to enhance the signal to noise ratio (SNR) of the recorded SSEP signals. A sequential computation of maxima and minima was then used to find the location of characteristic positive and negative peaks of the SSEP. The algorithm rejects trials with high peak value as they are corrupted...
It has been hypothesized that propriospinal neurons (PNs) in the C3-C4 spinal cord mediates cortical motor commands to the peripheral muscles during tremor in patients with Parkinson's disease (PD). However, there has been no direct evidence so far to support the role of PN in transmitting tremor commands. In this paper, we report the positive correlation of cutaneous afferents with reduction in tremor...
The robustness of myo-electric prosthesis usage is largely influenced by user performance, where psychological factors (i.e. cognitive-skills, motor-skills and psychological status — such as motivation, will, and stress) play a prominent role. These factors become more important the more degrees of freedom (DOF) a multifunctional prosthesis provides. Despite the large amount of research efforts during...
This paper presents a novel computer-aided system for assisting schizophrenia (SZ) diagnosis. Power Spectral Density Ratios (PSDRs) covering 7 brain regions and 5 frequency sub-bands are extracted as features, from single-trial magnetoencephalography (MEG) recorded while subjects read sentence stimuli silently. A two-stage feature selection algorithm combining F-score and Adaptive Boosting (Adaboost)...
Brain-Computer Interfaces (BCI) can provide innovative solutions beyond the medical domain. In human research, visuospatial attention is often assessed from shifts in head or gaze orientation. However in some critical situations, these behavioral features can be dissociated from covert attention processes and brain features may indicate more reliably the spatial focus of attention. In this context,...
Working memory (WM) refers to the short-term maintenance of information with higher cognitive functions. Recent researches show that local field potentials (LFPs) and spikes as different modes of neural signals encode WM respectively. There is a growing interest in how these two signals encode WM in coordination. The aim of this study is to investigate spike-LFP coupling coding WM via joint entropy...
In this paper we present a linear dynamical system to model the ongoing neural response, measured by EEG, while a listener is selectively attending a speech stream that is presented in a mixture. In our state-space formulation, the latent state variables represent the activity of the underlying neural substrates and the ongoing neural dynamics are captured by a multivariate autoregressive model with...
The chemical, mechanical, and electrochemical attributes of the Parylene sheath electrode (PSE) were evaluated following a post-fabrication thermoforming process to determine its impact on both the polymer and thin film platinum materials. The three-dimensional conical shape of the PSE was formed via thermal molding of a surface micromachined Parylene C microchannel using a custom shape-forming microwire...
Many efforts have been directed towards the characterization of nature and meaning of neural motor commands in persons with or without hand amputation. Microneurography is a well-established tool for afferent recordings, which could be potentially employed for a deeper understanding of hand motor control during manipulation tasks. Furthermore, it could hopefully enhance the assessment of users' capability...
In this study, we analyzed intracranial EEG (iEEG) recorded via subdural grid electrodes from patients with extratemporal lobe epilepsy, measuring interelectrode wavelet phase coherence (WPC), between neighbouring and distant cortical areas, during interictal and ictal activity. As several studies have explored phase coherence in the epileptic brain, in relation to lower rhythms (< 80 Hz), we have...
This study introduces a novel data-driven approach for constructing large-scale functional brain networks. These networks are constructed by converting raw functional magnetic resonance imaging data into graphs using independent components analysis (ICA). Empirical evaluations were performed using data collected from three sites, which are part of a pediatric epilepsy consortium. The test data contained...
Izhikevich model of a neuron allows for simulation of spiking pattern that mimics known biological subtypes. When a current within a range typical for biological experiments is injected into the cell the firing pattern produced in the simulation is close to that observed biologically. However, once these neurons are embedded into a network, the level of depolarization is controlled only by the synaptic...
Modifications to the Body Schema refers to the idea that the brain's mapping can be extended to include an external device. Recent research has shown how Brain-Machine Interfaces (BMIs) can be thought of an extension of this concept. While most BMI work has focused on the cortex in relation to this idea, here we study the striatum to see how the actions of a robotic arm are represented in a deep brain...
Inter-user variability of brain activity patterns makes it necessary to obtain a user-specific configuration for optimal performance of a brain-computer interface (BCI). Setting up or adjusting a BCI requires a certain amount of data for the computation of spatial filters, selection of suitable features (e.g., frequency bands), and classifier training. Taking advantage of the spatial and spectral...
The primary aim of this study was to select the optimal feature subset for discrimination of three dimensions of emotions (arousal, valence, liking) from subjects using electroencephalogram (EEG) signals. The EEG signals were collected from 25 channels on 21 healthy subjects whilst they were watching movie segments with emotional content. The band power values extracted from eleven frequency bands,...
Common Spatial Patterns (CSP) is a widely used spatial filtering method for electroencephalogram (EEG)-based brain computer interface (BCI). It is a supervised technique that needs subject specific training data. Due to the non-stationary nature of EEG, EEG signal may exhibit significant inter- and intra-subject variation. Consequently, spatial filters learned from one subject may not perform well...
Brain-Computer Interfaces (BCI) can be utilized to control a variety of devices, such as screen cursors, wheelchairs and robots. Noninvasive EEG-based BCI is an effective, albeit somewhat non-intuitive method. Gaze-based interfaces provide more natural and intuitive interfaces. However, they suffer from the Midas Touch problem, where targets and functions are unintentionally selected because a gaze-only...
For the development of efficient Brain Computer Interfaces (BCIs), recognizing when the system reacts erroneously to a user's input is a much desired functionality. In this paper, we investigate a system for the recognition of error potentials from single-trial Electroencephalography (EEG). Our focus here is the development of a system using only limited calibration data from the test subject, while...
Over the past few years, optical neural stimulation using optogenetics has drawn much attention in neuroscience and biomedical engineering communities because of its many advantages over electrical stimulation. Despite significant amount of studies regarding the effects of optical stimulation on neural activities, the influence of optical stimulation on a large neural population is overlooked. Neuronal...
Multiple single-units recorded from chronically-implanted microelectrode arrays frequently exhibit variability in their spike waveform features and firing characteristics, making it challenging to ascertain the identity of recorded neurons across days. In this study, we present a fast and efficient algorithm that tracks multiple single-units, recorded in a nonhuman primate performing brain control...
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