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Electroencephalography (EEG) signals are spatio-temporal. EEG has very good temporal resolution but typically doesn't possess high spatial resolution. The surface Laplacian enhances the spatial resolution and selectivity of the surface electrical activity. Concentric ring electrodes have been shown to estimate the surface Laplacian directly with significantly better spatial resolution than conventional...
This paper presents an application of wavelet filtering to single-trial P300 component analysis. The objective of this study is to introduce a new method for analyzing the P300 component, when performing a given cognitive task, in this case, a two-choice reaction time task. The discrete wavelet transform with Daubechies wavelet is employed to detect the presence of P300 in individual trials. Wavelet...
The following topics are dealt: time-frequency analysis; functional magnetic resonance imaging; cancer drug delivery; glucose sensor and diabetics control; neural computing; EEG; biomechanics; biomedical information network; health care environment; optical coherence tomography; medical diagnostics device; image-guided surgery; radiation therapy; laparoscopy; circadian rhythms; rehabilitation techniques;...
We describe a two-frequency diffuse optical tomographic (DOT) imaging and EEG recording system suitable for the study of real-time hemodynamic and neural activities in freely moving rats. The system uses a bundle of 16 optical fibers that both deliver light and capture its reemission. This bundle runs in parallel with a cable carrying EEG signals from 16 microelectrodes. Both data collection arrays...
We describe a two-frequency diffuse optical tomographic (DOT) imaging and EEG recording system suitable for the study of real-time hemodynamic and neural activities in freely moving rats. The system uses a bundle of 16 optical fibers that both deliver light and capture its reemission. This bundle runs in parallel with a cable carrying EEG signals from 16 microelectrodes. Both data collection arrays...
A motor imagery based brain-computer interface (BCI) translates the subject's motor intention into a control signal. For this BCI system, most algorithms are based on power changes of mu and beta rhythms. In this paper, we employ the measurement of phase synchrony to investigate the activities of the supplementary motor area (SMA) and primary motor area (M1) during left/right hand movement imagery...
A motor imagery based brain-computer interface (BCI) translates the subject's motor intention into a control signal. For this BCI system, most algorithms are based on power changes of mu and beta rhythms. In this paper, we employ the measurement of phase synchrony to investigate the activities of the supplementary motor area (SMA) and primary motor area (M1) during left/right hand movement imagery...
The timing of a behavioral response, such as a button press in reaction to a visual stimulus, is highly variable across trials. In this paper we describe a methodology for single-trial analysis of electroencephalography (EEG) which can be used to reduce the error in the estimation of the timing of the behavioral response and thus reduce the error in estimating the onset time of the stimulus. We consider...
The timing of a behavioral response, such as a button press in reaction to a visual stimulus, is highly variable across trials. In this paper we describe a methodology for single-trial analysis of electroencephalography (EEG) which can be used to reduce the error in the estimation of the timing of the behavioral response and thus reduce the error in estimating the onset time of the stimulus. We consider...
In this study, we introduced a new index, namely overlap index, to quantify the spatial resolution of cortical activity for muscle coordination based on the measurement of EEG-EMG coherence during a motor task. By applying this index on 4 control and 4 hemisphere chronic stroke subjects we successfully identified that there is a significantly increased overlap between biceps brachii at the elbow and...
In this study, we introduced a new index, namely overlap index, to quantify the spatial resolution of cortical activity for muscle coordination based on the measurement of EEG-EMG coherence during a motor task. By applying this index on 4 control and 4 hemisphere chronic stroke subjects we successfully identified that there is a significantly increased overlap between biceps brachii at the elbow and...
Non invasive brain-computer interfaces (BCI) allow people to communicate by modulating features of their electroencephalogram (EEG). Spatiotemporal filtering has a vital role in multi-class, EEG based BCI. In this study, we used a novel combination of principle component analysis, independent component analysis and dipole source localization to design a spatiotemporal multiple source tuning (SPAMSORT)...
Non invasive brain-computer interfaces (BCI) allow people to communicate by modulating features of their electroencephalogram (EEG). Spatiotemporal filtering has a vital role in multi-class, EEG based BCI. In this study, we used a novel combination of principle component analysis, independent component analysis and dipole source localization to design a spatiotemporal multiple source tuning (SPAMSORT)...
The electroencephalogram (EEG) consists of an underlying background process with superimposed transient nonstationarities such as epileptic spikes (ESs). The detection of ESs in the EEG is of particular importance in the diagnosis of epilepsy. In this paper a new approach for detecting ESs in EEG recordings is presented. It is based on a time-varying autoregressive model (TVAR) that makes use of the...
The electroencephalogram (EEG) consists of an underlying background process with superimposed transient nonstationarities such as epileptic spikes (ESs). The detection of ESs in the EEG is of particular importance in the diagnosis of epilepsy. In this paper a new approach for detecting ESs in EEG recordings is presented. It is based on a time-varying autoregressive model (TVAR) that makes use of the...
Assessment of brain connectivity among different brain areas during cognitive or motor tasks is a crucial problem in neuroscience today. Aim of this work is to use a neural mass model to assess the effect of various connectivity patterns in the power spectral density (PSD) of cortical EEG, and investigate the possibility to derive connectivity circuits from real EEG data. To this end, a model of an...
Assessment of brain connectivity among different brain areas during cognitive or motor tasks is a crucial problem in neuroscience today. Aim of this work is to use a neural mass model to assess the effect of various connectivity patterns in the power spectral density (PSD) of cortical EEG, and investigate the possibility to derive connectivity circuits from real EEG data. To this end, a model of an...
For the multimodal functional neuroimaging combining fMRI and EEG, it is of significance to correct the distortion due to the fMRI-EEG mismatches, which arise from the fundamental difference between brain electric and hemodynamic activities. In the present study, we proposed a novel two-step approach (referred to as "Twomey algorithm") for the fMRI-constrained cortical source imaging. In...
For the multimodal functional neuroimaging combining fMRI and EEG, it is of significance to correct the distortion due to the fMRI-EEG mismatches, which arise from the fundamental difference between brain electric and hemodynamic activities. In the present study, we proposed a novel two-step approach (referred to as "Twomey algorithm") for the fMRI-constrained cortical source imaging. In...
An accurate and robust electroencephalogram (EEG) source localization algorithm would be a definite asset for the surgical treatment of patients with epilepsy. Due to the underdetermined nature of the EEG inverse problem, a variety of algorithms with unique constraints and assumptions are applied to select the current dipole source distribution that best accounts for the scalp recordings. We investigated...
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