Adil Deniz Duru

Simultaneous EEG/fMRI Analysis of the Resonance Phenomena in Steady-State Visual Evoked Responses:

The stability of the steady-state visual evoked potentials (SSVEPs) across trials and subjects makes them a suitable tool for the investigation of the visual system. The reproducible pattern of the frequency characteristics of SSVEPs shows a global amplitude maximum around 10 Hz and additional local maxima around 20 and 40 Hz, which have been argued to represent resonant behavior of damped neuronal oscillators. Simultaneous electroencephalogram/functional magnetic resonance imaging (EEG/fMRI) measurement allows testing of the resonance hypothesis about the frequency-selective increases in SSVEP amplitudes in human subjects, because the total synaptic activity that is represented in the fMRI-Blood Oxygen Level Dependent (fMRI-BOLD) response would not increase but get synchronized at the resonance frequency. For this purpose, 40 healthy volunteers were visually stimulated with flickering light at systematically varying frequencies between 6 and 46 Hz, and the correlations between SSVEP amplitudes and the BOLD responses were computed. The SSVEP frequency characteristics of all subjects showed 3 frequency ranges with an amplitude maximum in each of them, which roughly correspond to alpha, beta and gamma bands of the EEG. The correlation maps between BOLD responses and SSVEP amplitude changes across the different stimulation frequencies within each frequency band showed no significant correlation in the alpha range, while significant correlations were obtained in the primary visual area for the beta and gamma bands. This non-linear relationship between the surface recorded SSVEP amplitudes and the BOLD responses of the visual cortex at stimulation frequencies around the alpha band supports the view that a resonance at the tuning frequency of the thalamo-cortical alpha oscillator in the visual system is responsible for the global amplitude maximum of the SSVEP around 10 Hz. Information gained from the SSVEP/fMRI analyses in the present study might be extrapolated to the EEG/fMRI analysis of the transient event-related potentials (ERPs) in terms of expecting more reliable and consistent correlations between EEG and fMRI responses, when the analyses are carried out on evoked or induced oscillations (spectral perturbations) in separate frequency bands instead of the time-domain ERP peaks.

Assessment of surgeon's stress level and alertness using EEG during laparoscopic simple nephrectomy

Laparoscopic simple nephrectomy (LSN) is an accepted treatment modality for nonfunctioning kidneys. Besides decreased postoperative morbidity, LSN is an advantage with decreased analgesic requirements and convalescence. LSN is a highly stressful operation, and the procedure requires high concentration level and experience. Emotions recognized from Electroencephalogram (EEG) may lead to detect the real emotions of the human. In this study, we proposed a subject-dependent stress level detection from EEG using the (Fpz beta/alpha) ratio to recognize high and low dominance levels of feelings based on the 2D Valence-Arousal model. The stress level of the surgeon is monitored via EEG during the operation. The most stressful phase of LSN and its change over time are determined using wireless EEG headset with real-time measurements. The aim here is to monitor and utilize objective information on the mental effort and stress demanded.

Implementation of Low Resolution Electro-Magnetic Tomography with fMRI Statistical Maps on Realistic Head Models

Functional neuroimaging studies can be performed by combining the modalities of fMRI and Electroencephalography because of their complementary properties. The main advantage of EEG imaging among other modalities is the high temporal resolution while fMRI has high spatial resolution. So, usage of these procedures is going to help us to gain more information about the functional organization of the brain. In this study, changes in the relationship between steady state visual evoked potentials (SSVEP) generators and BOLD responses during visual stimulation have been systematically studied with 5 stimulus presentation rates (2, 4, 6, 8,10) between 2-10 Hz. fMRI Analysis was carried out using statistical parametric mapping (SPM). The result of fMRI analysis is used as a localization mask for SSVEP localization process. SSVEP generators are localized using low resolution electro magnetic tomography (LORETA) which is implemented on a realistic head model. Then, for each stimulus frequency voxel by voxel correlation values of the active regions are computed.

Neuroimaging of Event Related Brain Potentials (ERP) using fMRI and Dipole Source Reconstruction

Neuroimaging is an essential tool for the diagnosis of cognitive brain disorders along with the EEG measurements. EEG and fMRI are the two crucial modalities which reflect the functional activity inside the brain. EEG is easy to apply and provides high temporal resolution but has poor spatial resolution. Contrarily, fMRI has a higher spatial resolution while having a poor temporal resolution. In this study, multi modal data sets obtained from Event Related fMRI and EEG measurements are analyzed using SPM and LORETA based dipole source reconstruction techniques, respectively. It has been demonstrated that the generator of N170 component of ERP which is located at superior temporal region is in agreement with the SPM results of fMRI. The results imply that the joint use of fMRI and ERP data helps identifying the physiological and hemodynamic correlates of face recognition by estimating the underlying functional activity in a fine temporal and spatial resolution.

Analysis of correlation between white matter changes and functional responses in thalamic stroke: a DTI & EEG study

Diffusion tensor imaging (DTI) allows in vivo structural brain mapping and detection of microstructural disruption of white matter (WM). One of the commonly used parameters for grading the anisotropic diffusivity in WM is fractional anisotropy (FA). FA value helps to quantify the directionality of the local tract bundle. Therefore, FA images are being used in voxelwise statistical analyses (VSA). The present study used Tract-Based Spatial Statistics (TBSS) of FA images across subjects, and computes the mean skeleton map to detect voxelwise knowledge of the tracts yielding to groupwise comparison. The skeleton image illustrates WM structure and shows any changes caused by brain damage. The microstructure of WM in thalamic stroke is investigated, and the VSA results of healthy control and thalamic stroke patients are reported. It has been shown that several skeleton regions were affected subject to the presence of thalamic stroke (FWE, p < 0.05). Furthermore the correlation of quantitative EEG (qEEG) scores and neurophysiological tests with the FA skeleton for the entire test group is also investigated. We compared measurements that are related to the same fibers across subjects, and discussed implications for VSA of WM in thalamic stroke cases, for the relationship between behavioral tests and FA skeletons, and for the correlation between the FA maps and qEEG scores.Results obtained through the regression analyses did not exceed the corrected statistical threshold values for multiple comparisons (uncorrected, p < 0.05). However, in the regression analysis of FA values and the theta band activity of EEG, cingulum bundle and corpus callosum were found to be related. These areas are parts of the Default Mode Network (DMN) where DMN is known to be involved in resting state EEG theta activity. The relation between the EEG alpha band power values and FA values of the skeleton was found to support the cortico-thalamocortical cycles for both subject groups. Further, the neurophysiological tests including Benton Face Recognition (BFR), Digit Span test (DST), Warrington Topographic Memory test (WTMT), California Verbal Learning test (CVLT) has been regressed with the FA skeleton maps for both subject groups. Our results corresponding to DST task were found to be similar with previously reported findings for working memory and episodic memory tasks. For the WTMT, FA values of the cingulum (right) that plays a role in memory process was found to be related with the behavioral responses. Splenium of corpus callosum was found to be correlated for both subject groups for the BFR.

Analysis of brain electrical topography by spatio-temporal wavelet decomposition

Currently, the Functional Magnetic Resonance Imaging (fMRI), Positron Emission Tomography (PET), and Electroencephalography (EEG) recordings are the major techniques of neuroimaging. The EEG with its highest temporal resolution is still a crucial measurement for localization of activities arising from the electrical behaviour of the brain. A scalp topographic map for an EEG may be a superposition of several simpler subtopographic maps, each resulting from an individual electrical source located at a certain depth. Furthermore, this source may have a temporal characteristic as an oscillation or a rhythm that extends in a certain time window which has been a basis of assumption for the time-frequency analysis methods. A method for the spatio-temporal wavelet decomposition of multichannel EEG data is proposed which facilitates the localization of electrical sources separate and/or overlapping on a continuum of time, frequency and space domains. The subtopographic maps asociated with each of these individual components are then used in the MUSIC source localization algorithm. The validations are performed on simulated EEG data. Spatio-temporal wavelet decomposition as a preprocessing method improves the source localization by simplifying the topographic data formed by the superposition of EEG generators, having possible combinations of temporal, frequency and/or spatial overlappings. Spatio-temporal analysis of EEG will help enhance the accuracy of dipole source reconstruction in neuroimaging.

A comparative study of localization approaches to EEG source imaging

The EEG inverse problem of reconstructing the neural electrical current that produced a given measurement is ill-posed and many different source configurations can yield the same scalp potentials. In this study, we compared localizing capabilities or three EEG inverse algorithms: MUSIC, LORETA and Bayesian MCMC method. Simulations on a realistic head model show that comparing to MUSIC and LORETA, the computational power of MCMC methods offers a flexible and robust tool for EEG source imaging.

Source Localization of Subtopographic Brain Maps for Event Related Potentials (ERP)

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 resolution of scalp topography for ERP is low. There is a severe limitation for the parametric inverse solution algorithms that they can only perform well for the temporally uncorrelated sources. In this study, a spatial decomposition method is proposed to separate the temporally correlated sources using their topographies prior to their localization

Investigating neural efficiency of elite karate athletes during a mental arithmetic task using EEG

Neural efficiency is proposed as one of the neural mechanisms underlying elite athletic performances. Previous sports studies examined neural efficiency using tasks that involve motor functions. In this study we investigate the extent of neural efficiency beyond motor tasks by using a mental subtraction task. A group of elite karate athletes are compared to a matched group of non-athletes. Electroencephalogram is used to measure cognitive dynamics during resting and increased mental workload periods. Mainly posterior alpha band power of the karate players was found to be higher than control subjects under both tasks. Moreover, event related synchronization/desynchronization has been computed to investigate the neural efficiency hypothesis among subjects. Finally, this study is the first study to examine neural efficiency related to a cognitive task, not a motor task, in elite karate players using ERD/ERS analysis. The results suggest that the effect of neural efficiency in the brain is global rather than local and thus might be contributing to the elite athletic performances. Also the results are in line with the neural efficiency hypothesis tested for motor performance studies.

Bayesian EEG Dipole Source Localization using SA-RJMCMC on Realistic Head Model

In this study, electroencephalography (EEG) inverse problem is formulated using Bayesian inference. The posterior probability distribution of current sources is sampled by Markov Chain Monte Carlo (MCMC) methods. Sampling algorithm is designed by combining Reversible Jump (RJ) which permits trans-dimensional iterations and Simulated Annealing (SA), a heuristic to escape from local optima. Two different approaches to EEG inverse problem, Equivalent Current Dipole (ECD) and Distributed Linear Imaging (DLI) are combined in terms of probability. EEG inverse problem is solved with this probabilistic approach using simulated data on a realistic head model. Localization errors are computed. Comparing to Multiple Signal Classification algorithm (MUSIC) and Low-Resolution Electromagnetic Tomography (LORETA), using MCMC methods with a Bayesian approach is useful for solving the EEG inverse problem.