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Electroencephalogram (EEG) is an important component of the pre-surgical evaluation in the treatment of medically intractable epilepsy. However, clinical EEG uses 19 to 32 electrodes that significantly limits its localization ability. Recent development of dense-array recording techniques has suggested that increased spatial sampling rate improves the accuracy of source localization. In the current...
Neural oscillations are important features in a working central nervous system, facilitating efficient communication across large networks of neurons. To better study the role of these oscillations in various cognitive processes, and to be able to build clinical applications around them, accurate and precise estimations of the instantaneous frequency and phase are required. Here, we present methodology...
We investigate the use of machine learning methods based on the pre-treatment electroencephalograph (EEG) to predict response to repetitive transcranial magnetic stimulation (rTMS), which is a non-pharmacological form of therapy for treating major depressive disorder (MDD). The learning procedure involves the extraction of a large number of candidate features from EEG data, from which a very small...
Platinum microwires, terminated at regular intervals to form a grid of contacts, were used to record electric potentials at the surface of the cerebral cortex in human subjects. The microwire grids were manufactured commercially with 75 μm platinum wire and 1 mm grid spacing, and are FDA approved. Because of their small size and spacing, these grids could be used to explore the scale of spatiotemporal...
Considerable evidences have shown a decrease of neu-ronal activity in the left frontal lobe of depressed patients, but the underlying cortical network is still unclear. The present study intends to investigate the conscious-state brain network patterns in depressed patients compared with control individuals. Cortical functional connectivity is quantified by the partial directed coherence (PDC) analysis...
To control the startup/shutdown of a conventional brain-computer interface (BCI) that is always running for daily use, we proposed and developed a new BCI system called a BCI master switch. We designed it with on/off switching functions by detecting the contingent negative variation (CNV) — related potentials. We chose CNV to improve the single-trial discrimination of user intentions to switch because...
Electrocorticography (ECoG) is an emerging tool to map brain functions in the context of neurosurgical intervention. Previous mapping methods based on the event related power spectrum are prone to noise. To improve the robustness of cortical function mapping, general linear model (GLM), which has been widely used in the analysis of functional magnetic resonance imaging (fMRI) data, is applied to bandpass...
Neuroscientists are becoming interested in the application of computational EEG analysis to the identification of ictal onset zones, however, most studies have focused on the localization of ictal onset zones in focal epilepsy. The present study aimed to estimate the ictal onset zone of Lennox-Gastaut syndrome (LGS) with bilaterally synchronous epileptiform discharges from intracranial electroencephalography...
In the context of drug resistant partial epilepsy, intra-cerebral electrical stimulation (Deep Brain Stimulation) constitutes one of the means of investigation to locate epileptic volume. This exogenous source can then activate the underlying epileptic networks and generate an electrophysiological reaction. The purpose of this work is to estimate and eliminate the overlapping electrical stimulation...
Cortical stimulation (CS) has gained wide attention for its use in augmenting neurological recovery in various conditions. Noninvasive cortical stimulations using transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) are less invasive when delivering the electrical current to the patient's brain, but have several limitations. Direct cortical stimulation (DCS) using...
The goal of this study is to investigate the influence of white matter conductivity anisotropy on the electric field strength induced by electroconvulsive therapy (ECT). We created an anatomically-realistic finite element human head model incorporating tissue heterogeneity and white matter conductivity anisotropy using structural magnetic resonance imaging (MRI) and diffusion tensor MRI data. The...
As epilepsy affects approximately one percent of the world population, electrical stimulation of the brain has recently shown potential for additive seizure control therapy. In this study we applied noninvasive transcranial focal stimulation (TFS) via concentric ring electrodes on the scalp of rats after inducing seizures with pentylenetetrazole (PTZ) to assess the effect of TFS on the electrographic...
Directed influence between multiple channel signal measurements is important for the understanding of large dynamic systems. This research investigates a method to analyze large, complex multi-variable systems using directional flow measure to extract relevant information related to the functional connectivity between different units in the system. The directional flow measure was completed through...
In this paper the replacement of a lost learning function of rats through a computer-based real-time recording and feedback system is shown. In an experiment two recording electrodes and one stimulation electrode were implanted in an anesthetized rat. During a classical-conditioning paradigm, which includes tone and airpuff stimulation, biosignals were recorded and the stimulation events detected...
Electroconvulsive therapy (ECT) is a highly effective treatment for severe depressive disorder. Efficacy and cognitive outcomes have been shown to depend on variations in treatment technique. A high resolution finite element model of a human head was generated from MRI scans and implemented with tissue heterogeneity and an excitable ionic neural model incorporated in the brain. The model was used...
Being noninvasive, low-risk and inexpensive, EEG is a promising methodology in the application of human Brain Computer Interface (BCI) to help those with motor dysfunctions. Here we employed a center-out task paradigm to study the decoding of hand velocity in the EEG recording. We tested the hypothesis using a linear regression model and found a significant correlation between velocity and the low-pass...
In this paper we show a proof of concept for novel automatic seizure onset zone detector. The proposed approach utilizes the Austrian Institute of Technology (AIT) seizure detection system EpiScan extended by a frequency domain source localization module. EpiScan was proven to detect rhythmic epileptoform seizure activity often seen during the early phase of epileptic seizures with reasonable high...
Brain Hyperscanning, i.e. the simultaneous recording of the cerebral activity of different human subjects involved in interaction tasks, is a very recent field of Neuroscience aiming at understanding the cerebral processes generating and generated by social interactions. This approach allows the observation and modeling of the neural signature specifically dependent on the interaction between subjects,...
Efficient methods for Local Field Potential (LFP) signal analysis amenable to interpretation are becoming increasingly relevant. LFP signals are believed, in part, to reflect neural action potential activity, and LFP frequency modulations are linked to spiking events. Furthermore, LFP signals are increasingly accessible in human brain regions previously unreachable due to a proliferation of deep brain...
Advances in neural electrode technology are enabling brain recordings with increasingly fine spatial and temporal resolution. We explore spatio-temporal (ST) patterns of local field potential spikes using a new high-density active electrode array with 500 μm resolution. We record subdural micro-electrocorticographic (μECoG) signals in vivo from a feline model of acute neocortical epileptiform spikes...
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