EEG - fMRI: Physiological Basis, Technique, and Applications by Arno Villringer, Christoph Mulert, Louis Lemieux (auth.),

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By Arno Villringer, Christoph Mulert, Louis Lemieux (auth.), Christoph Mulert, Louis Lemieux (eds.)

Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are vitally important and complementary modalities considering that fMRI bargains excessive spatial answer whereas EEG offers an instantaneous dimension of neuronal task with excessive temporal solution. curiosity within the integration of those sorts of information is transforming into quickly because it supplies to yield very important new insights into human mind job, as has already happened relating to epilepsy. certainly, it sort of feels yes that built-in EEG-fMRI will play an expanding function in neuroscience and within the scientific research of varied mind problems. This e-book discusses extensive all points of EEG-fMRI, together with physiological rules and technical and methodological matters equivalent to EEGartefact aid equipment, snapshot caliber, and information research options. unique attention is given to all capability purposes, essentially within the fields of sleep learn, cognitive neuroscience, and medical neurology and psychiatry. the entire authors are well-known specialists within the box, and the textual content is supported through a variety of informative illustrations.

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Extra resources for EEG - fMRI: Physiological Basis, Technique, and Applications

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5 times larger. Many minicolumns are bound together by short-range horizontal connections, and thus form what has been denominated cortical columns or cortical modules (Mountcastle 1997). One column in the somatic sensory cortex contains about 80 minicolumns and is roughly hexagonal with a width of about 300–400 mm (Favorov and Diamond 1990). These estimates can be used to give a rough answer to the question formulated above.

G. fMRI) or again by a combination of the two (EEG–fMRI). EEG usually provides the time or state marker in imaging studies of spontaneous brain activity: this is the EEG-derived hypothesis-driven approach to fMRI analysis. The paradigmatic example for the latter is the study of the haemodynamic correlates of epileptic spikes (Warach et al. 1996; Lemieux et al. 2001a, b; Krakow et al. 2001a, b). Again, one dataset (EEG) is used as a predictor of vascular changes in fMRI, PET or NIRS data. A similar situation is the assessment of vascular correlates of spontane­ ous changes in EEG rhythms, which can only be achieved by simultaneous studies (Goldman et al.

The frequency of this network beta2 rhythm appears to depend on the magnitude of the M current, a non-­inactivating potassium current found in many neuronal cell types that can be modulated by a large array of receptor types, including muscarinic cholinergic receptors, in IB interneurons. These findings suggest the possibility that a normally occurring cortical network oscillation involved in motor control could be generated largely or entirely by nonsynaptic mechanisms. According to these authors, higher beta2 frequency oscillations occur mainly during the anticipatory period leading up to a movement in response to a sensory cue.

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