Resting state functional network disruptions in a kainic acid model of temporal lobe epilepsy

Abstract

We studied the graph topological properties of brain networks derived from resting-state functional magnetic resonance imaging in a kainic acid induced model of temporal lobe epilepsy (TLE) in rats. Functional connectivity was determined by temporal correlation of the resting-state Blood Oxygen Level Dependent (BOLD) signals between two brain regions during 1.5% and 2% isoflurane, and analyzed as networks in epileptic and control rats. Graph theoretical analysis revealed a significant increase in functional connectivity between brain areas in epileptic than control rats, and the connected brain areas could be categorized as a limbic network and a default mode network (DMN). The limbic network includes the hippocampus, amygdala, piriform cortex, nucleus accumbens, and mediodorsal thalamus, whereas DMN involves the medial prefrontal cortex, anterior and posterior cingulate cortex, auditory and temporal association cortex, and posterior parietal cortex. The TLE model manifested a higher clustering coefficient, increased global and local efficiency, and increased small-worldness as compared to controls, despite having a similar characteristic path length. These results suggest extensive disruptions in the functional brain networks, which may be the basis of altered cognitive, emotional and psychiatric symptoms in TLE.

Reading in children with drug‐resistant epilepsy was related to functional connectivity in cognitive control regions

“…Consequently, repeated seizures could have led to increased functional connectivity between the amygdala and the prefrontal cortex, as shown in our study. Similar results were shown in a mouse model of temporal lobe epilepsy . Conversely, most studies in humans to date have demonstrated a decrease in functional fronto‐limbic connectivity and this finding has been linked to the increased incidence of mood disorders in patients with temporal lobe epilepsy .…”

Abnormal hippocampal functional network and related memory impairment in pilocarpine‐treated rats

“…A major limitation of our study was the use of anesthetics, which may cause resting state network differences compared to awake animals. Isoflurane has been universally utilized in rodent neuroimaging studies . Some studies demonstrated that although instinct brain networks were still observed at deep levels of anesthesia, brain functional connectivity decreased with increased levels of anesthesia .…”

“…Conversely, in the TLE group of the present study, increased functional connectivity was observed in the visual cortex and mesencephalon to the hippocampal network ( Figure 4B), which is also in agreement with the results from other human neuroimaging studies. 32,33 Interestingly, Gill et al 34 recently revealed a significant increase in functional connectivity within the limbic network and the DMN in KA-treated rats compared to controls. The inconsistent results might have resulted from the choice of rat model.…”

“…Isoflurane has been universally utilized in rodent neuroimaging studies. 19,22,34,37 Some studies demonstrated that although instinct brain networks were still observed at deep levels of anesthesia, brain functional connectivity decreased with increased levels of anesthesia. 37,38 Even so, resting state network analysis based on an awake rat brain or using specific anesthetic with less effect of functional connectivity influence would be more sensitive to detect connectivity changes in the disease model.…”

Deep Transformation Method for Discriminant Analysis of Multi-Channel Resting State fMRI

“…between the various regions of the brain (Yousefnezhad and Zhang 2017). fMRI data have been used to understand the etiopathogenesis of neurological disorders such as Attention Deficit Hyperactivity Disorder (ADHD) (Mahanand, Savitha, and Suresh 2013), autism (Subbaraju et al 2017) and epilepsy (Gill, Mirsattari, and Leung 2017). Studies on the automatic diagnosis of neurological disorders from fMRI data have focused on analyzing the correlations between the regions to find discriminant activities.…”