Journal of Pediatric Epilepsy 2016; 05(01): 011-017
DOI: 10.1055/s-0035-1567848
Original Article
Georg Thieme Verlag KG Stuttgart · New York

Default Mode Network in a Small Cohort of Children with Abnormal Brain MRIs

Michael A. Bush
1   Department of Radiology, Nationwide Children's Hospital, The Ohio State University, Columbus, Ohio, United States
,
James W. Murakami
1   Department of Radiology, Nationwide Children's Hospital, The Ohio State University, Columbus, Ohio, United States
› Author Affiliations
Further Information

Publication History

29 January 2015

12 March 2015

Publication Date:
19 November 2015 (online)

Abstract

Resting state networks (RSNs) are functionally connected brain networks identified as correlated low-frequency fluctuations in blood oxygenation level dependent (BOLD) signal. One common network, the default mode network (DMN), is deactivated during performance of demanding tasks such as some language and memory tests. The DMN can also be isolated as an RSN using independent component analysis (ICA) on data acquired from subjects at rest. The vast majority of research has focused on the DMN as visualized in subjects or patients with structurally normal brains. To see if the DMN could be identified in patients with structurally abnormal brains encountered daily in routine clinical practice, we compared the DMN identified by both techniques in 14 pediatric seizure patients undergoing routine eloquent cortex mapping with functional magnetic resonance imaging (fMRI). We successfully isolated the DMN as areas of deactivation during a semantic word generation task. We also employed temporal concatenation to combine four task-based fMRI exams from each patient. The composite dataset was then studied with ICA to isolate the DMN, as an RSN, from each patient. We found that the DMN demonstrated by the two techniques was very similar with two exceptions. The two techniques appear to display slightly different aspects of the DMN. The ability to reliably and retrospectively identify the DMN using RSN analysis in patients with large brain abnormalities and seizures may provide another avenue to study these patients and their treatments.