Elissaios Karageorgiou
Former Member of the Brain Sciences CenterBrain Sciences Center (BSC)

Publications

  1. Canonical correlation analysis of Synchronous Neural InteractionsSynchronous Neural Interactions (SNI)Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG. and cognitive deficits in Alzheimer's dementia Journal of Neural Engineering (2012, August) Karageorgiou E, Lewis S, McCarten JR, Leuthold A, Hemmy LS, McPherson SE, Rottunda SJ, Rubins D, & Georgopoulos AP
  2. Neuropsychological Testing and Structural Magnetic Resonance ImagingStructural Magnetic Resonance Imaging (sMRI)Performed to assess gray-matter volume. The data are acquired using a Philips 3T Achieva XL magnet with a SENSE 8 channel head coil. Approximately 500,000 voxels per brain are analyzed. In the first analysis, the volume of about 100 separate brain regions is calculated using FreeSurfer software (www.surfer.nmr.mgh.harvard. edu). This provides a coarse-grain, volumetric analysis of areas of the brain. In the second analysis, called voxel-based morphometry, the density of each voxel is assessed for a fine-grain analysis of each area.5 Typically, gray-matter volume decreases with age but at rates that are different for different people, for different areas of the brain, and for men and women. In that sense, one can talk about "gray-matter age" versus chronological age. A person may be 68 years old but have the gray-matter volume of a 50-year-old. Defining brain age based on measurements (as contrasted with chronological age) is a pervasive theme in this project. as Diagnostic Biomarkers Early in the Course of Schizophrenia and Related Psychoses Neuroinformatics (2011, December) Karageorgiou E, Schulz SC, Gollub RL, Andreasen NC, Ho BC, Lauriello J, Calhoun VD, Bockholt, Sponheim S, & Georgopoulos AP
  3. Cortical processing of tactile stimuli applied in quick succession across the fingertips: temporal evolution of dipole sources revealed by magnetoencephalography Experimental Brain Research (2008, August) Karageorgiou E, Koutlas I, Alonso A, Leuthold A, Lewis S, & Georgopoulos AP
  4. P2-027: Association of cognitive deficits with SNISynchronous Neural Interactions (SNI)Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG. as revealed by magnetoencephalography: A canonical correlation analysis Alzheimer's & Dementia (2008, July) Karageorgiou E, Lewis S, McCarten JR, Leuthold A, Hemmy LS, McPherson SE, Rottunda SJ, & Georgopoulos AP
  5. Representations of Voluntary Arm Movements in the Motor Cortex and Their Transformations Understanding events: How humans see, represent, and act on events (2008, May) Georgopoulos AP, & Karageorgiou E
  6. Neurostatistics: applications, challenges and expectations Statistics in Medicine (2008, February) Georgopoulos AP, & Karageorgiou E
  7. SNISynchronous Neural Interactions (SNI)Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG. assessed by magnetoencephalography: a functional biomarker for brain disorders Journal of Neural Engineering (2007, August) Georgopoulos AP, Karageorgiou E, Leuthold A, Lewis S, Lynch J, Alonso A, Aslam Z, Carpenter A, Georgopoulos A, Hemmy LS, Koutlas I, Langheim F, McCarten JR, McPherson SE, Pardo J, Pardo P, Parry GJ, Rottunda SJ, Segal BM, Sponheim S, Stanwyck JJ, Stephane M, & Westermeyer JJ