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In this paper, autoregressive modeling technique and neural network based modeling techniques are used to model and simulate electroencephalogram (EEG) signals. EEG signal modeling is used as a tool to identify pathophysiological EEG changes potentially useful in clinical diagnosis. The normal, background and epileptic EEG signals are modeled and the dynamical properties of the actual and modeled...
This paper attempts to make use of Brain Computer Interface (BCI) in implementing an application called the Media Communication Center for the paralyzed people. The application is based on the event-related potential called P300 to perform button selections on media and communication programs such as the mp3 player, video player, photo gallery and e-book. One of the key issues in such system is the...
The Directed Transfer Function (DTF) and the Partial Directed Coherence (PDC) are frequency-domain estimators, based on the multivariate autoregressive modelling (MVAR) of time series, that are able to describe interactions between cortical areas in terms of the concept of Granger causality. However, the classical estimation of these methods requires the stationary of the signals. In this way, transient...
We have proposed a new ictal source analysis approach by combining a spatio-temporal source localization approach, and causal interaction estimation technique. The FINE approach is used to identify neural electrical sources from spatio-temporal scalp-EEGs. The Granger causality estimation uses source waveforms estimated by FINE to characterize the causal interaction between the neural electrical sources...
Auditory evoked potentials (AEPs) have been recorded at high stimulus rates during sleep using continuous loop averaging deconvolution (CLAD) sequences. AEP transient signals are obtained via frequency domain deconvolution of overlapped responses. Simultaneous acquisition of auditory brainstem response (ABR), middle latency response (MLR), and long latency response (LLR) is obtained at an average...
Localization of the cognitive activity in the brain is one of the major problems in neuroscience. Current techniques for neuro-imaging are based on functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and event related potential (ERP) recordings. The highest temporal resolution is achieved by ERP, which is crucial for temporal localization of activities. However, the spatial...
Binocular rivalry is a visual perceptual phenomenon which occurs when two incongruent stimuli are viewed by a subject through each eye, but only one of them is perceived at a time, with a switch in perception every few seconds, which reflects the alternation of perceptual dominance. To investigate the correlation between contrast-related perception and neural activities, the subjects' EEGs were recorded...
Artifact removal is an essential part in electroencephalogram (EEG) recording and the raw EEG signals require preprocessing before feature extraction. In this work, we implemented three filtering methods and demonstrated their effects on the performance of different classifiers. Bandpass digital filtering, median filtering and facet method are three preprocessing approaches investigated in this paper...
In this paper, autoregressive modeling technique and neural network based modeling techniques are used to model and simulate electroencephalogram (EEG) signals. EEG signal modeling is used as a tool to identify pathophysiological EEG changes potentially useful in clinical diagnosis. The normal, background and epileptic EEG signals are modeled and the dynamical properties of the actual and modeled...
The issue of subject-specific parameter selection in an electroencephalogram (EEG)-based brain-computer interface (BCI) is tackled in this paper. Hjorth- and Barlow-based feature extraction procedures (FEPs) are investigated along with linear discriminant analysis (LDA) for classification. These are well-known nonparametric FEPs but their simplicity prevents them from matching the performance of more...
The skull is a tissue with a widely controversial range of conductivity values. This article correlates live skull conductivity measurements with post mortem conductivity measurements with a scaling factor ranging between 2.5 and 4. The scaling factor is validated by a mathematical model that determines the skull conductivity using saline and cerebrospinal fluid (CSF) conductivities and correlated...
In the analysis of epileptic electroencephalographic (EEG) and magnetoencephalography (MEG) data, spike separation is diagnostically important because localization of epileptic focus often depends on accurate extraction of spiky activity from the raw data. In this paper, we present a method to automatically extract spikes using the wavelet transform combined with morphological filtering based on a...
This paper attempts to make use of brain computer interface (BCI) in implementing an application called the media communication center for the paralyzed people. The application is based on the event-related potential called P300 to perform button selections on media and communication programs such as the mp3 player, video player, photo gallery and e-book. One of the key issues in such system is the...
An epileptic seizure detector's performance definitely depends on features extraction and selection. In this study, we present the short-time average magnitude difference function (sAMDF) as a computationally efficient feature to distinguish seizures from EEG and it is compared with the frequently used curve length. We also suggest using a subspace based approach for feature selection that exploits...
In binocular rivalry, a subject views two incongruent stimuli through each eye but consciously perceives only one stimulus at a time, with a switch in perceptual dominance every a few seconds. To locate the fusiform face area (FFA) which is a face-selective region, thirteen subjects are recorded with a 64-channel electroencephalograph while experiencing binocular rivalry. A face image flickering at...
Brain-computer interfaces (BCIs) aim to provide an alternative channel for paralyzed patients to communicate with external world. Reducing the time needed for the initial calibration is one important objective in P300 based BCI research. In this paper, the training time is reduced by a semi-supervised learning approach. A model is trained by small training set first. The on-line test data with predicted...
This work proposes a mathematical approach for combining event-related potentials (ERPs) and functional magnetic resonance images (fMRI). Data were separately recorded during the same event-related experimental design, consisting of visually presented single letters and non-alphabetic symbols, that had to be either simply observed (passive condition) or read aloud (active condition). This protocol...
A neural mass model of interacting macro-columns is stimulated to reproduce unisensory, auditory and visually evoked potentials and multisensory (concurrent audiovisual) evoked potentials. These were elicited from patients conducting a reaction response task and recorded from intracranial electrodes placed on the parietal lobe. Important features of this model include inhibitory and excitatory feedback...
Epileptic patients often show interictal epileptic discharges (IED's) in the electroencephalogram (EEG) recorded between seizures. This epileptiform activity is in many cases related to the location of the seizure onset, and is believed to reflect the frequency of the seizures. We present a fully automated technique that is able to extract the IED's from the EEG, despite the obscuring artifacts. The...
A laboratory simulation has been devised for use in developing and testing physiologic monitoring systems' performance in the presence of electrosurgical interference. This facilitated the development through iterative optimization of an EEG based parameter whose performance is improved during electrosurgery. The system was found to have an improvement of 94% in response to electrosurgery interference...
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