Jann, Kay; Koenig, Thomas; Dierks, Thomas; Boesch, Chris; Federspiel, Andrea (2010). Association of individual resting state EEG alpha frequency and cerebral blood flow. NeuroImage, 51(1), pp. 365-72. San Diego, Calif.: Elsevier 10.1016/j.neuroimage.2010.02.024
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Cognitive task performance differs considerably between individuals. Besides cognitive capacities, attention might be a source of such differences. The individual's EEG alpha frequency (IAF) is a putative marker of the subject's state of arousal and attention, and was found to be associated with task performance and cognitive capacities. However, little is known about the metabolic substrate (i.e. the network) underlying IAF. Here we aimed to identify this network. Correlation of IAF with regional Cerebral Blood Flow (rCBF) in fifteen young healthy subjects revealed a network of brain areas that are associated with the modulation of attention and preparedness for external input, which are relevant for task execution. We hypothesize that subjects with higher IAF have pre-activated task-relevant networks and thus are both more efficient in the task-execution, and show a reduced fMRI-BOLD response to the stimulus, not because the absolute amount of activation is smaller, but because the additional activation by processing of external input is limited due to the higher baseline.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > University Psychiatric Services > University Hospital of Psychiatry and Psychotherapy > Psychiatric Neurophysiology [discontinued] 04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic, Interventional and Paediatric Radiology > DCR Magnetic Resonance Spectroscopy and Methodology (AMSM) |
UniBE Contributor: |
Jann, Kay, König, Thomas, Dierks, Thomas, Boesch, Christoph Hans, Federspiel, Andrea |
ISSN: |
1053-8119 |
Publisher: |
Elsevier |
Language: |
English |
Submitter: |
Factscience Import |
Date Deposited: |
04 Oct 2013 14:07 |
Last Modified: |
02 Mar 2023 23:20 |
Publisher DOI: |
10.1016/j.neuroimage.2010.02.024 |
PubMed ID: |
20156573 |
Web of Science ID: |
000276480200038 |
BORIS DOI: |
10.7892/boris.219 |
URI: |
https://boris.unibe.ch/id/eprint/219 (FactScience: 196949) |