Dynamic functional connectivity and graph theory metrics in a rat model of temporal lobe epilepsy

IntroductionEpilepsy is a neurological disorder characterized by recurrent epileptic seizures. The involvement of abnormal functional brain networks in the development of epilepsy and its comorbidities has been demonstrated by electrophysiological and neuroimaging studies in epilepsy patients1. In this longitudinal resting state functional MRI (rsfMRI) study, changes in dynamic functional connectivity (dFC) and network topology during epileptogenesis were investigated using the intraperitoneal kainic acid (IPKA) rat model of temporal lobe epilepsy (TLE).Subjects and Methods24 adult male Sprague-Dawley rats were used. 17 were i.p. injected with kainic acid according to the protocol of Hellier et al. (1998)2, resulting in status epilepticus (SE), and 7 with saline (controls). Before and 5 times post-SE, rsfMRI scans were acquired on a 7T system. Correlation between fMRI timeseries was calculated within a sliding window of 50s with a 2s step length. The resulting correlation matrices were classified into 6 states using k-means clustering. For all time-varying correlation matrices, graph theoretical metrics were calculated and classified into 6 states of network topology. Percentage dwell time in and number of transitions between each state were calculated and their correlation with seizure frequency, based on hippocampal EEG recordings, was assessed. Results and DiscussionThe 6 states of FC were sorted from highest to lowest mean value. Percentage dwell time in State 1, 2 and 3 was significantly lower in the IPKA group compared to controls, while dwell time in State 5 and 6 was significantly higher. A significant effect of time post-SE could be found in the IPKA group, where a significant decrease in dwell time in State 1, 2, 3 and 4 and increase in State 5 and 6 could be observed during epileptogenesis (Fig. 1A). The number of transitions was significantly lower in the IPKA group compared to controls and decreased significantly during epileptogenesis in the IPKA group (Fig. 1B). Seizure frequency was positively correlated with dwell time in State 2 one week post-SE and in State 4 16 weeks post-SE, and negatively with dwell time in State 5 one week post-SE and State 6 16 weeks post-SE (Fig. 2). The number of transitions 16 weeks post-SE was positively correlated with seizure frequency. Similar results were obtained for the states of network topology.ConclusionStates with a lower mean FC occurred more often in IPKA animals compared to controls. FC became less variable during epileptogenesis, which might be related to cognitive problems. Seizure frequency was positively correlated with dwell time in states with high FC and number of transitions between states, indicating that dwelling in states of higher FC and more switching between states seem to increase the probability that seizures are generated.IntroductionEpilepsy is a neurological disorder characterized by recurrent epileptic seizures. The involvement of abnormal functional brain networks in the development of epilepsy and its comorbidities has been demonstrated by electrophysiological and neuroimaging studies in epilepsy patients1. In this longitudinal resting state functional MRI (rsfMRI) study, changes in dynamic functional connectivity (dFC) and network topology during epileptogenesis were investigated using the intraperitoneal kainic acid (IPKA) rat model of temporal lobe epilepsy (TLE).Subjects and Methods24 adult male Sprague-Dawley rats were used. 17 were i.p. injected with kainic acid according to the protocol of Hellier et al. (1998)2, resulting in status epilepticus (SE), and 7 with saline (controls). Before and 5 times post-SE, rsfMRI scans were acquired on a 7T system. Correlation between fMRI timeseries was calculated within a sliding window of 50s with a 2s step length. The resulting correlation matrices were classified into 6 states using k-means clustering. For all time-varying correlation matrices, graph theoretical metrics were calculated and classified into 6 states of network topology. Percentage dwell time in and number of transitions between each state were calculated and their correlation with seizure frequency, based on hippocampal EEG recordings, was assessed. Results and DiscussionThe 6 states of FC were sorted from highest to lowest mean value. Percentage dwell time in State 1, 2 and 3 was significantly lower in the IPKA group compared to controls, while dwell time in State 5 and 6 was significantly higher. A significant effect of time post-SE could be found in the IPKA group, where a significant decrease in dwell time in State 1, 2, 3 and 4 and increase in State 5 and 6 could be observed during epileptogenesis (Fig. 1A). The number of transitions was significantly lower in the IPKA group compared to controls and decreased significantly during epileptogenesis in the IPKA group (Fig. 1B). Seizure frequency was positively correlated with dwell time in State 2 one week post-SE and in State 4 16 weeks post-SE, and negatively with dwell time in State 5 one week post-SE and State 6 16 weeks post-SE (Fig. 2). The number of transitions 16 weeks post-SE was positively correlated with seizure frequency. Similar results were obtained for the states of network topology.ConclusionStates with a lower mean FC occurred more often in IPKA animals compared to controls. FC became less variable during epileptogenesis, which might be related to cognitive problems. Seizure frequency was positively correlated with dwell time in states with high FC and number of transitions between states, indicating that dwelling in states of higher FC and more switching between states seem to increase the probability that seizures are generated.C