Download Clinical Electrophysiology of the Somatosensory Cortex: A by Christoph Baumgartner PDF

By Christoph Baumgartner

The medical electrophysiology of the human somatosensory cortex was once investigated with a mixed procedure utilizing cortical stimulations and somatosensory evoked responses on electrocorticography, scalp-EEG, and magnetoencephalography, a brand new neurophysiological procedure. The spatiotemporal constitution of the evoked reaction was once studied with novel biophysical modeling thoughts which allowed identity of the three-d intracerebral situation, time job, and interplay of the neuronal assets in human somatosensory cortex. hence, new points at the practical anatomy of the human somatosensory cortex should be elicited. additionally, the somatotopy of the hand somatosensory cortex used to be investigated. Clinically, the result of comparability of the various concepts can enhance the non-invasive localization standards for fundamental motor and somatosensory cortex that is very important in sufferers present process neurosurgical approaches adjoining to relevant fissure.

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Extra resources for Clinical Electrophysiology of the Somatosensory Cortex: A Combined Study Using Electrocorticography, Scalp-EEG, and Magnetoencephalography

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Some authors have even suggested that the skull and scalp are virtually transparent to magnetic fields [162, 198, 199]. This results in a better spatial resolution of MEG compared to scalp-EEG and magnetic field maxima are about one third closer to each other than electrical potential maxima (Figs. 4C) [69]. Electric and magnetic fields are oriented perpendicular to each other. Thus, the directions of highest sensitivity - usually the direction between the field maxima - are orthogonal to each other [69, 162] (Figs.

Motor, sensory, and speech cortex, and to record interictal as well as ictal epileptiform discharges to exactly localize the seizure focus.

Multiple source modeling yielded dipoles in the anterior and midtemporal region 26 mm and 38 mm beneath the scalp. e. the spike and the slow wave, were generated by two spatially distinct neuronal populations. Both PCA (Fig. 5E) and multiple source modeling (Fig. 51) could reproduce the actual data set (Fig. 5A) very closely and explained over 85% of the data variance. Analogous to the previous example, results ofPCA and multiple dipole modeling were similar, but not identical. 9. 1. Limitations of Principal Component Analysis PCA is a statistical technique with no relation to the underlying brain physiology.

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