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fMRI temporal clustering analysis in patients with frequent interictal epileptiform discharges: comparison with EEG-driven analysis

Hamandi, Khalid, Salek Haddadi, A., Liston, A., Laufs, H., Fish, D. R. and Lemieux, L. 2005. fMRI temporal clustering analysis in patients with frequent interictal epileptiform discharges: comparison with EEG-driven analysis. NeuroImage 26 (1) , pp. 309-316.

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Abstract

Temporal clustering analysis (TCA) is an exploratory data-driven technique that has been proposed for the analysis of resting fMRI to localise epileptiform activity without need for simultaneous EEG. Conventionally, fMRI of epileptic activity has been limited to those patients with subtle clinical events or frequent interictal epileptiform EEG discharges, requiring simultaneous EEG recording, from which a linear model is derived to make valid statistical inferences from the fMRI data. We sought to evaluate TCA by comparing the results with those of EEG correlated fMRI in eight selected cases. Cases were selected with clear epileptogenic localisation or lateralisation on the basis of concordant EEG and structural MRI findings, in addition to concordant activations seen on EEG-derived fMRI analyses. In three, areas of activation were seen with TCA but none corresponding to the electro-clinical localisation or activations obtained with EEG driven analysis. Temporal clusters were closely coincident with times of maximal head motion. We feel this is a serious confound to this approach and recommend that interpretation of TCA that does not address motion and physiological noise be treated with caution. New techniques to localise epileptogenic activity with fMRI alone require validation with an appropriate independent measure. In the investigation of interictal epileptiform activity, this is best done with simultaneous EEG recording.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Medicine
MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Subjects: R Medicine > R Medicine (General)
Publisher: Elsevier
ISSN: 1053-8119
Last Modified: 04 Jun 2017 08:43
URI: http://orca-mwe.cf.ac.uk/id/eprint/83487

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