Open AccessFunctional coupling of simultaneous electrical and metabolic activity in the human brain
Author(s) -
Oakes Terrence R.,
Pizzagalli Diego A.,
Hendrick Andrew M.,
Horras Katherine A.,
Larson Christine L.,
Abercrombie Heather C.,
Schaefer Stacey M.,
Koger John V.,
Davidson Richard J.
Publication year - 2004
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.20004
Subject(s) - voxel , electroencephalography , positron emission tomography , human brain , cerebral blood flow , brain activity and meditation , psychology , neuroscience , neuroimaging , nuclear magnetic resonance , functional magnetic resonance imaging , pattern recognition (psychology) , artificial intelligence , physics , computer science , medicine , cardiology , cognitive psychology
Abstract The relationships between brain electrical and metabolic activity are being uncovered currently in animal models using invasive methods; however, in the human brain this relationship remains not well understood. In particular, the relationship between noninvasive measurements of electrical activity and metabolism remains largely undefined. To understand better these relations, cerebral activity was measured simultaneously with electroencephalography (EEG) and positron emission tomography using [ 18 f]‐fluoro‐2‐deoxy‐ D ‐glucose (PET‐FDG) in 12 normal human subjects during rest. Intracerebral distributions of current density were estimated, yielding tomographic maps for seven standard EEG frequency bands. The PET and EEG data were registered to the same space and voxel dimensions, and correlational maps were created on a voxel‐by‐voxel basis across all subjects. For each band, significant positive and negative correlations were found that are generally consistent with extant understanding of EEG band power function. With increasing EEG frequency, there was an increase in the number of positively correlated voxels, whereas the lower α band (8.5–10.0 Hz) was associated with the highest number of negative correlations. This work presents a method for comparing EEG signals with other more traditionally tomographic functional imaging data on a 3‐D basis. This method will be useful in the future when it is applied to functional imaging methods with faster time resolution, such as short half‐life PET blood flow tracers and functional magnetic resonance imaging. Hum. Brain Mapping 21:257–270, 2004. © 2004 Wiley‐Liss, Inc.