Objective The purpose of this study was to evaluate if focal cortical dysplasia (FCD) co‐localization to cortical functional networks is associated with the temporal distribution of epilepsy onset in FCD. Methods International (20 center), retrospective cohort from the Multi‐Centre Epilepsy Lesion Detection (MELD) project. Patients included if >3 years old, had 3D pre‐operative T1 magnetic resonance imaging (MRI; 1.5 or 3 T) with radiologic or histopathologic FCD after surgery. Images processed using the MELD protocol, masked with 3D regions‐of‐interest (ROI), and co‐registered to fsaverage_sym (symmetric template). FCDs were then co‐localized to 1 of 7 distributed functional cortical networks. Negative binomial regression evaluated effect of FCD size, network, histology, and sulcal depth on age of epilepsy onset. From this model, predictive age of epilepsy onset was calculated for each network. Results Three hundred eighty‐eight patients had median age seizure onset 5 years (interquartile range [IQR] = 3–11 years), median age at pre‐operative scan 18 years (IQR = 11–28 years). FCDs co‐localized to the following networks: limbic (90), default mode (87), somatomotor (65), front parietal control (52), ventral attention (32), dorsal attention (31), and visual (31). Larger lesions were associated with younger age of onset (p = 0.01); age of epilepsy onset was associated with dominant network (p = 0.04) but not sulcal depth or histology. Sensorimotor networks had youngest onset; the limbic network had oldest age of onset (p values <0.05). Interpretation FCD co‐localization to distributed functional cortical networks is associated with age of epilepsy onset: sensory neural networks (somatomotor and visual) with earlier onset, and limbic latest onset. These variations may reflect developmental differences in synaptic/white matter maturation or network activation and may provide a biological basis for age‐dependent epilepsy onset expression. ANN NEUROL 2022;92:503–511

No abstract

Background and Objectives:Task-fMRI is a clinical tool for language lateralization, but has limitations, and cannot provide information about network-level plasticity. Additional methods are needed to improve the precision of presurgical language mapping. We investigate language resting-state functional connectivity(RS fMRI;FC) in typically developing children and children with epilepsy. Our objectives were to: 1)Understand how FC components differ between typically developing (TD) children and those with epilepsy. 2)Elucidate how the location of disease (frontal/temporal epilepsy foci) effects FC. 3)Investigate the relationship between age and FC.Methods:Sample includes 55 TD children (mean age 12 years, range 7-18, and 31 patients with focal epilepsy (mean age 13) with same range. All subjects underwent RS fMRI. Using a bilateral canonical language map as target, vertex wise intra-hemispheric FC map and inter-hemispheric FC map for each subject were computed and thresholded at top 10% to compute an FC laterality index (FCLI;((L-R)/(L+R)) of the frontal and temporal regions for both integration (intra-hemispheric FC; FCLIi) and segregation (Inter-hemispheric FC; FCLIs) maps.Results:We found FC differences in the developing language network based on disease, seizure foci location, and age. Frontal and Temporal FCLIi was different between groups (t(84)=2.82, p<.01; t(84)=4.68, p<.01, respectively). Frontal epilepsy foci had the largest differences from TD (Cohen’s D Frontal FCLIi=0.84, FCLIs=0.51; Temporal FCLIi=1.29). Development and disease have opposing influences on the laterality of FC based on groups. In the frontal foci group, FCLIi decreased with age (r=-0.42), whereas in the temporal foci group FCLIi increased with age (r=0.40). Within the epilepsy group, increases in right frontal integration FCLI relates to increased right frontal task activation in our mostly left language dominant group (r=.52, p<.01). Language network connectivity is associated with higher verbal intelligence in children with epilepsy (r=.45, p<.05).Discussion:These findings lend preliminary evidence that FC reflects network plasticity in the form of adaptation and compensation, or the ability to recruit support and reallocate resources within and outside of the traditional network to compensate for disease. FC expands on task-based fMRI and provides complementary and potentially useful information about the language network that is not captured using task-based fMRI alone.