Please use this identifier to cite or link to this item: http://ahro.austin.org.au/austinjspui/handle/1/9844
Title: How reliable are fMRI-EEG studies of epilepsy? A nonparametric approach to analysis validation and optimization.
Authors: Waites, Anthony B;Shaw, Marnie E;Briellmann, Regula S;Labate, Angelo;Abbott, David F;Jackson, Graeme D
Affiliation: Brain Research Institute, Austin Health, Heidelberg West, Australia.
Issue Date: 1-Jan-2005
Citation: Neuroimage; 24(1): 192-9
Abstract: Simultaneously acquired functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) data hold great promise for localizing the spatial source of epileptiform events detected in the EEG trace. Despite a number of studies applying this method, there has been no independent and systematic validation of the approach. The present study uses a nonparametric method to show that interictal discharges lead to a blood oxygen level dependent (BOLD) response that is significantly different to that obtained by examining random 'events'. We also use this approach to examine the optimization of analysis strategy for detecting these BOLD responses. Two patients with frequent epileptiform events and a healthy control were studied. The fMRI data for each patient were analyzed using a model derived from the timings of the epileptiform events detected on EEG during fMRI scanning. Twenty sets of random pseudoevents were used to generate a null distribution representing the level of chance correlation between the EEG events and fMRI data. The same pseudoevents were applied to control data. We demonstrate that it is possible to detect blood oxygen level-dependent (BOLD) changes related to interictal discharges with specific and independent knowledge about the reliability of this activation. Biologically generated events complicate the fMRI-EEG experiment. Our proposed validation examines whether identified events have an associated BOLD response beyond chance and allows optimization of analysis strategies. This is an important step beyond standard analysis. It informs clinical interpretation because it permits assessment of the reliability of the connection between interictal EEG events and the BOLD response to those events.
Internal ID Number: 15588610
URI: http://ahro.austin.org.au/austinjspui/handle/1/9844
DOI: 10.1016/j.neuroimage.2004.09.005
URL: http://www.ncbi.nlm.nih.gov/pubmed/15588610
Type: Journal Article
Subjects: Analysis of Variance
Artifacts
Cerebral Cortex.physiopathology
Child
Computer Simulation
Electroencephalography.statistics & numerical data
Epilepsy, Absence.diagnosis.physiopathology
Epilepsy, Generalized.diagnosis.physiopathology
Evoked Potentials.physiology
Female
Humans
Image Enhancement
Image Processing, Computer-Assisted.statistics & numerical data
Magnetic Resonance Imaging.statistics & numerical data
Mathematical Computing
Oxygen.blood
Reference Values
Reproducibility of Results
Statistics as Topic
Statistics, Nonparametric
Appears in Collections:Journal articles

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