Abstracts

Cognitive networks in Lennox-Gastaut Syndrome show impaired within-network integration and between-network segregation

Abstract number : 3.228
Submission category : 5. Neuro Imaging
Year : 2015
Submission ID : 2328291
Source : www.aesnet.org
Presentation date : 12/7/2015 12:00:00 AM
Published date : Nov 13, 2015, 12:43 PM

Authors :
Aaron Warren, David Abbott, David Vaughan, Graeme Jackson, John Archer

Rationale: Lennox-Gastaut Syndrome (LGS) is an epileptic encephalopathy associated with intractable seizures and severe cognitive impairment. The precise cause of impaired cognition is poorly understood. Using functional MRI and concurrent electroencephalography (EEG-fMRI), we recently demonstrated that transient epileptic discharges in LGS are expressed simultaneously through multiple brain networks that normally underlie distinct cognitive functions (Epilepsia, 2014; 55(8); 1245-54). However, the ongoing behavior of these brain networks in LGS, during periods with and without epileptic activity, remains unknown. Here, we aimed to a) compare functional interactions within and between key cognitive brain networks in LGS patients and a group of healthy controls, and b) compare network interactions in LGS patients during periods with and without scalp-recorded epileptic activity.Methods: EEG-fMRI was performed in 15 LGS patients (8 females; mean age 28.7±10.6 years) and 17 healthy controls (6 females; 27.6±6.6 years). Resting-state fMRI data were acquired for 25 mins using a 3T scanner. fMRI data were pre-processed to remove spurious signal changes caused by motion and physiological noise. Common networks of brain activity (each represented by a spatial map and a timecourse of signal changes) were determined from the fMRI data using group independent components analysis (group ICA). Functional interactions between seven cognitive networks were explored by calculating the Pearson’s correlation coefficient between each pair of network timecourses. Network correlation strengths were compared between patients and controls using a multivariate analysis of covariance. Additionally, in a subset of 6 LGS patients, we used within-sample t-tests to compare network correlation strengths during fMRI periods when epileptic discharges were present (discharge-affected) or absent (discharge-unaffected) on each patient’s simultaneous EEG recording. All results were corrected for multiple comparisons using the false-discovery rate (with q=0.05).Results: Relative to controls, patients showed a) significantly stronger interactions between networks involved in distinct cognitive functions, including networks involved in internally-oriented attention (default-mode network [DMN]) and externally-oriented attention (visuospatial attention network), and b) significantly weaker interactions within networks involved in related cognitive functions, including anterior and posterior regions of the DMN (Figure 1). The within-sample comparison of network interactions in LGS during discharge-affected and discharge-unaffected periods revealed no significant differences.Conclusions: Functional interactions between cognitive networks are abnormal in LGS. Patients show a failure of within-network integration and between-network segregation. Network interactions are similar during periods with and without epileptic activity, suggesting that abnormal network behavior persists throughout the interictal state.
Neuroimaging