1. What Does an Epileptiform Spike Look Like in MEG? Comparison Between Coincident EEG and MEG Spikes
- Author
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Jan C. de Munck, António Martins da Silva, Geertjan Huiskamp, Fernando H. Lopes da Silva, Ilonka Manshanden, José Maria Fernandes, Demetrios N. Velis, and João Paulo Cunha
- Subjects
Adult ,Male ,genetic structures ,Physiology ,Models, Neurological ,Electroencephalography ,EEG-fMRI ,behavioral disciplines and activities ,Brain mapping ,Coincident ,Physiology (medical) ,medicine ,Humans ,Cerebral Cortex ,Brain Mapping ,Communication ,Epilepsy ,medicine.diagnostic_test ,business.industry ,Orientation (computer vision) ,musculoskeletal, neural, and ocular physiology ,Magnetoencephalography ,Signal Processing, Computer-Assisted ,Pattern recognition ,Neurophysiology ,Electrodes, Implanted ,nervous system ,Neurology ,Female ,Spike (software development) ,Neurology (clinical) ,Artificial intelligence ,business ,Psychology ,psychological phenomena and processes - Abstract
Recent investigations suggest that there are differences between the characteristics of EEG and MEG epileptiform spikes. The authors performed an objective characterization of the morphology of epileptiform spikes recorded simultaneously in both EEG and MEG to determine whether they present the same morphologic characteristics. Based on a stepwise approach, the authors performed a computer analysis of EEG and MEG of a set of coincident epileptiform transients selected by a senior clinical neurophysiologist in recordings of three patients with drug-resistant epilepsy. A computer-based algorithm was applied to extract parameters that could be used to describe quantitatively the morphology of the transients, followed by a statistical comparison over the extracted metrics of the EEG and MEG waveforms. EEG and MEG coincident events were statistically different with respect to several morphologic characteristics, such as duration, sharpness, and shape. The differences found appear to be a consequence of MEG signals not being influenced by volume propagation through the tissues with different conductivities that surround the brain, compared with EEG, and of the different orientation of the underlying dipolar sources. The results indicate that visual inspection of MEG spikes and automatic spike-detector algorithms should use criteria adapted to the specific characteristics of the MEG, and not simply those used on conventional EEG.
- Published
- 2005
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