Disorders of consciousness (DOC) occur in severe cases of neurological disease and acquired brain injury, spanning the continuum from complete unresponsiveness (vegetative state) to partial conscious awareness with only erratic voluntary behavioral responses (minimally conscious state). Assessing the patient’s level of awareness of self and their environment through behavioral evaluation is notoriously difficult and may lead to misdiagnosis if residual cognitive function goes undetected. A number of studies (Di et al., 2007; Staffen et al., 2008; Coleman et al., 2007; Qin et al., 2010) applying brain-imaging methods to measure brain activity associated with processing self-referential stimuli (stimuli related to the self) have found similar responses between patients with DOC and healthy volunteers. The present study involved a unique pediatric patient with comorbid quadriplegia and non-communicative impaired awaress who underwent fMRI to explore brain activity associated with the auditory presentation of personally relevant language stimuli: the subject’s own name (SON) and a familiar voice (FV). Activation was observed in the left tranverse temporal gyrus across all auditory stimuli. Presentation of the SON revealed activation in the left ventromedial prefrontal cortex (vMPFC) and right dorsolateral prefrontal cortex (DLPFC) and presentation of the FV revealed activation in the left supramarginal gyrus. These findings provide evidence of preserved brain activity in this patient during the presentation of self-referential stimuli and therefore support the application of functional neuroimaging methods to detect residual brain activity in pediatric patients who display impaired awareness.

Electroencephalography and functional magnetic resonance are two different methods for measuring of neural activity. EEG signals have excellent time resolution, fMRI scans capture records of brain activity in excellent spatial resolution. It is assumed that the joint analysis can take advantage of both methods simultaneously. Statistical Parametric Mapping (SPM8) is freely available software which serves to automatic analysis of fMRI data estimated with general linear model. It is not possible to estimate automatic EEG–fMRI analysis with it. Therefore software EEG Regressor Builder was created during master thesis. It preprocesses EEG signals into EEG regressors which are loaded with program SPM8 where joint EEG–fMRI analysis is estimated in general linear model. EEG regressors consist of vectors of temporal changes in absolute or relative power values of EEG signal in the specified frequency bands from selected electrodes due to periods of fMRI acquisition of individual images. The software is tested on the simultaneous EEG-fMRI data of a visual oddball experiment. EEG regressors are calculated for temporal changes in absolute and relative EEG power values in three frequency bands of interest ( 8-12Hz, 12-20Hz a 20-30Hz) from the occipital electrodes (O1, O2 and Oz). Three types of test analyzes is performed. Data from three individuals is examined in the first. Accuracy of results is evaluated due to the possibilities of setting of calculation method of regressor. Group analysis of data from twenty-two healthy patients is performed in the second. Group EEG regressors analysis is realized in the third through the correlation matrix due to the specified type of power and frequency band outside of the general linear model.