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Proceedings Paper

Imaging of oscillatory behavior in event-related MEG studies
Author(s): Dimitrios Pantazis; Darren L. Weber; Corby L. Dale; Thomas E. Nichols; Gregory V. Simpson; Richard M. Leahy
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Paper Abstract

Since event-related components in MEG (magnetoencephalography) studies are often buried in background brain activity and environmental and sensor noise, it is a standard technique for noise reduction to average over multiple stimulus-locked responses or “epochs”. However this also removes event-related changes in oscillatory activity that are not phase locked to the stimulus. To overcome this problem, we combine time-frequency analysis of individual epochs with corticallyconstrained imaging to produce dynamic images of brain activity on the cerebral cortex in multiple time-frequency bands. While the SNR in individual epochs is too low to see any but the strongest components, we average signal power across epochs to find event related components on the cerebral cortex in each frequency band. To determine which of these components are statistically significant within an individual subject, we threshold the cortical images to control for false positives. This involves testing thousands of hypotheses (one per surface element and time-frequency band) for significant experimental effects. To control the number of false positives over all tests, we must therefore apply multiplicity adjustments by controlling the familywise error rate, i.e. the probability of one or more false positive detections across the entire cortex. Applying this test to each frequency band produces a set of cortical images showing significant eventrelated activity in each band of interest. We demonstrate this method in applications to high density MEG studies of visual attention.

Paper Details

Date Published: 11 March 2005
PDF: 9 pages
Proc. SPIE 5674, Computational Imaging III, (11 March 2005); doi: 10.1117/12.600607
Show Author Affiliations
Dimitrios Pantazis, Univ. of Southern California (United States)
Darren L. Weber, Univ. of California/San Francisco (United States)
Corby L. Dale, Univ. of California/San Francisco (United States)
Thomas E. Nichols, Univ. of Michigan (United States)
Gregory V. Simpson, Univ. of California/San Francisco (United States)
Richard M. Leahy, Univ. of Southern California (United States)

Published in SPIE Proceedings Vol. 5674:
Computational Imaging III
Charles A. Bouman; Eric L. Miller, Editor(s)

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