The Neurophysiological Biomarker Toolbox for pre-clinical EEG/MEG research

Simon-Shlomo Poil, Klaus Linkenkaer-Hansen
Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), VU University Amsterdam, The Netherlands.

Introduction Eyes-closed rest EEG/MEG is used for assessing the functional state of the brain in pre-clinical research—typically in terms of disease influences on neuronal oscillation frequency, amplitude, or coherence. However, neuronal oscillations fluctuate considerably in time and amplitude and this is not captured by the classical analyses.

The study of spatial and temporal dimensions of neuronal processing requires different correlation analyses. Coordination of anatomically distributed activity (parallel processing) may be studied by computing correlations between neuronal signals from different brain areas (Cross-correlations). In contrast, coordination of brain activity over time (serial processing) may be studied by computing auto-correlations in neuronal signals within a single brain area (Auto-correlations). See Figure.

Methods The MATLAB-based “Neurophysiological Biomarker Toolbox” (or NBT) provides algorithms for characterizing the temporal structure of ongoing oscillations. (see our webpage)

Results Using the NBT, we have observed a prominent decrease in auto-correlations in early-stage Alzheimer’s disease (Montez & Poil et al., PNAS, 2009). See Figure.

Conclusions The temporal structure of ongoing oscillations may be important for brain function and its quantitative analysis provides an important insight into the functional organization of the brain in pre-clinical research using resting-state EEG/MEG. We invite collaborators to use our NBT toolbox.

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Keywords Ongoing oscillations, MEG, EEG, biomarkers, Alzheimer’s disease

(abstract: ONWA annual PhD-meeting 2009)