Visual-spatial attention is an essential brain function that enables us to select and preferentially process high priority information in the visual fields. Several brain areas have been shown to participate in the control of spatial attention in humans, but little is known about the underlying selection mechanisms. Non-invasive scalp recordings of event-related potentials (e.r.ps) in humans have shown that attended visual stimuli are preferentially selected as early as 80-90 ms after stimulus onset, but current e.r.p. methods do not permit a precise localization of the participating cortical areas. In this study we combined neuroimaging (positron emission tomography) with e.r.p. recording in order to describe both the cortical anatomy and time course of attentional selection processes. Together these methods showed that visual inputs from attended locations receive enhanced processing in the extrastriate cortex (fusiform gyrus) at 80-130 ms after stimulus onset. These findings reinforce early selection models of attention.

Using magnetoencephalography (MEG), we compared the processing of sinusoidal tones in the auditory cortex of 12 non-musicians, 12 professional musicians and 13 amateur musicians. We found neurophysiological and anatomical differences between groups. In professional musicians as compared to non-musicians, the activity evoked in primary auditory cortex 19-30 ms after stimulus onset was 102% larger, and the gray matter volume of the anteromedial portion of Heschl's gyrus was 130% larger. Both quantities were highly correlated with musical aptitude, as measured by psychometric evaluation. These results indicate that both the morphology and neurophysiology of Heschl's gyrus have an essential impact on musical aptitude.

Review and analysis of continuous EEG recordings may be impeded by physiological artifacts such as blinks, eye movements, or cardiac activity. Spatial filters based on artifact and brain signal topographies can remove artifacts completely without distortion of relevant brain activity. The authors describe the basic principle of artifact correction by spatial filtering and they review different approaches to estimate artifact and brain signal topographies. The main focus is on the preselection approach, which is fast enough to be applied while paging through the segments of a digital EEG recording. Examples of real EEG segments, containing epileptic seizure activity or interictal spikes contaminated by artifacts, show that spatial filtering by preselection can be a useful tool during EEG review. Advantages and disadvantages of the different spatial filter approaches are discussed.

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