Evolution of Functional Connectivity of Brain Networks and Their Dynamic Interaction in Temporal Lobe Epilepsy

Abstract

This study presents a cross-sectional investigation of functional networks in temporal lobe epilepsy (TLE) as they evolve over years of disease. Networks of interest were identified based on a priori hypotheses: the network of seizure propagation ipsilateral to the seizure focus, the same regions contralateral to seizure focus, the cross hemisphere network of the same regions, and a cingulate midline network. Resting functional magnetic resonance imaging data were acquired for 20 min in 12 unilateral TLE patients, and 12 age- and gender-matched healthy controls. Functional changes within and between the four networks as they evolve over years of disease were quantified by standard measures of static functional connectivity and novel measures of dynamic functional connectivity. The results suggest an initial disruption of cross-hemispheric networks and an increase in static functional connectivity in the ipsilateral temporal network accompanying the onset of TLE seizures. As seizures progress over years, the static functional connectivity across the ipsilateral network diminishes, while dynamic functional connectivity measures show the functional independence of this ipsilateral network from the network of midline regions of the cingulate declines. This implies a gradual breakdown of the seizure onset and early propagation network involving the ipsilateral hippocampus and temporal lobe as it becomes more synchronous with the network of regions responsible for secondary generalization of the seizures, a process that may facilitate the spread of seizures across the brain. Ultimately, the significance of this evolution may be realized in relating it to symptoms and treatment outcomes of TLE.

Functional connectivity homogeneity correlates with duration of temporal lobe epilepsy

“…The network structure in TLE appears to also undergo progression and reorganization over time [41]. Prior work using seed based functional connectivity analysis has revealed reduced functional independence of the presumed ipsilateral ictal network from midline networks in TLE [42], which may also indicate progressive homogenization (less independence) over time using a different analysis approach. This reduced independence may also be the reason for the observed progressive increase in cross-hippocampal connectivity with longer duration in TLE [43].…”

Resting-state functional connectivity in epilepsy

“…of altered functional organization varying with age of seizure onset has been demonstrated through rsFC [4,21,22]. A recent study by Morgan et al [21] showed that there is an initial disruption of cross-hemispheric networks and an increase in static functional connectivity in the ipsilateral temporal network accompanying the onset of TLE seizures.…”

“…A recent study by Morgan et al [21] showed that there is an initial disruption of cross-hemispheric networks and an increase in static functional connectivity in the ipsilateral temporal network accompanying the onset of TLE seizures. As seizures progress over years, functional connectivity declines within both a static ipsilateral network and a dynamic midline (e.g., cingulate) network; however, these networks appear to be independent of each other.…”

Methods and Considerations for Dynamic Analysis of Functional MR Imaging Data

“…Such metrics have been demonstrated as promising biomarkers for distinguishing between states 27,29 , or between patients and healthy controls 61–64 .…”

“…Investigators have pursued DFC methods in a wide variety of brain disorders, including schizophrenia 38,131,132133134 , bipolar disorder 131 , autism spectrum disorder 135,136 , major depression, mild cognitive impairment 137138 , Alzheimer’s disease 139 and dementia with Lewy bodies 95 , post-traumatic stress disorder 78 , epilepsy 61,140 and multiple sclerosis, among others 79 . Encouragingly, these studies have begun to suggest that dynamic features are more sensitive or specific than static connectivity in differentiating between healthy and control populations.…”