The effects of pediatric epilepsy on a language connectome

Abstract

This study introduces a new approach for assessing the effects of pediatric epilepsy on a language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI. An auditory word definition decision task paradigm was used to activate the language network for 29 patients and 30 controls. Evaluations illustrated that pediatric epilepsy is associated with a network efficiency reduction. Patients showed a propensity to inefficiently use the whole brain network to perform the language task; whereas, controls seemed to efficiently use smaller segregated network components to achieve the same task. To explain the causes of the decreased efficiency, graph theoretical analysis was performed. The analysis revealed substantial global network feature differences between the patients and controls for the extent of activation network. It also showed that for both subject groups the language network exhibited small-world characteristics; however, the patient's extent of activation network showed a tendency toward randomness. It was also shown that the intensity of activation network displayed ipsilateral hub reorganization on the local level. We finally showed that a clustering scheme was able to fairly separate the subjects into their respective patient or control groups. The clustering was initiated using local and global nodal measurements. Compared to the intensity of activation network, the extent of activation network clustering demonstrated better precision. This ascertained that the network differences presented by the networks were associated with pediatric epilepsy.

Scalp EEG brain functional connectivity networks in pediatric epilepsy

“…The contrast can also be drawn to see if such connectivity maps could enhance the prospects of a diagnosis with the ability to augment other methods seeking a similar goal. Such methods could compare these connectivity maps in relation to specific frequency and temporal features [6,10] or associate them to fMRI data using the connectome, decision functions or PCA [18,54,59] for an optimal classification process. Through the application of developing scalp EEG based connectivity; these initial results did support the hypothesis that pediatric epilepsy disease impacts the connectivity patterns significantly relative to the control population.…”

Neuroimaging correlates of language network impairment and reorganization in temporal lobe epilepsy

“…With respect to language, random network organization and low integration predicted poorer expressive language outcome, explaining 73% of the variance in language decline following both left and right ATL (Doucet, Pustina, et al, 2015). In a study that examined localization-related epilepsy in children, Eddin et al (2014) derived graph theory measures from fMRI data and examined global and local language networks. They found globally decreased efficiency in language network connectivity in pediatric patients when compared to controls.…”

“…While small-world network topology was observed in both the pediatric patients and the control group, network activation in the pediatric epilepsy group was more random. Overall, the control group was observed to efficiently activate a smaller, partitioned network to complete a language task while the pediatric epilepsy group utilized the whole brain for the same task (Eddin et al, 2014). Kellerman et al (2015) similarly found decreased efficiency and organization as well as poor segregation of cognitive network modules in the pediatric epilepsy population (Kellermann, Bonilha, Lin, & Hermann, 2015).…”

Intracranial Volume Estimation and Graph Theoretical Analysis of Brain Functional Connectivity Networks

“…Considering the fact that Epilepsy is a complex disease with multifactorial causes, makes the diagnostic process much more complicated than simply relying on solely model driven knowledge. Furthermore, human brain involves a complex web of neuronal connectivity and discrete anatomical regions that function together to generate brain activity (Lowe, Mock et al 1998;Eddin, Wang et al 2014). …”

“…AD and AC subjects had a neurological and medical evaluation by a physician acoording to the neuropsychological tests (Duara, Loewenstein et al 2010). Structural MRI for pediatric subject groups, PE and PC, were collected by a multisite consortium and repository (Lahlou, Guillen et al 2006)for pediatric epilepsy to study the Age Female/Male PE (n = 13) 13 ± 2.93* 8/5 PC (n = 18) 11 ± 1.26 8/10 AD (n=11) 81 ± 9.31 6/5 AC (n=11) 71 ± 6.21 9/2 effects of pediatric epilepsy on the functionality of the brain as well as on structural impacts (Guillen, Adjouadi et al 2009;Eddin, Wang et al 2014). …”