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Dynamic functional connectivity and graph theory metrics in a rat model of temporal lobe epilepsy reveal a preference for brain states with a lower functional connectivity, segregation and integration

Emma Christiaen (UGent) , Marie-Gabrielle Goossens (UGent) , Benedicte Descamps (UGent) , Lars Emil Larsen (UGent) , Paul Boon (UGent) , Robrecht Raedt (UGent) and Christian Vanhove (UGent)
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Abstract
Epilepsy 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 patients with epilepsy. This longitudinal study investigated changes in dynamic functional connectivity (dFC) and network topology during the development of epilepsy using the intraperitoneal kainic acid (IPKA) rat model of temporal lobe epilepsy (TLE). Resting state functional magnetic resonance images (rsfMRI) of 20 IPKA animals and 7 healthy control animals were acquired before and 1, 3, 6, 10 and 16 weeks after status epilepticus (SE) under medetomidine anaesthesia using a 7 T MRI system. Starting from 17 weeks post-SE, hippocampal EEG was recorded to determine the mean daily seizure frequency of each animal. Dynamic FC was assessed by calculating the correlation matrices between fMRI time series of predefined regions of interest within a sliding window of 50 s using a step length of 2 s. The matrices were classified into 6 FC states, each characterized by a correlation matrix, using k-means clustering. In addition, several time-variable graph theoretical network metrics were calculated from the time-varying correlation matrices and classified into 6 states of functional network topology, each characterized by a combination of network metrics. Our results showed that FC states with a lower mean functional connectivity, lower segregation and integration occurred more often in IPKA animals compared to control animals. Functional connectivity also became less variable during epileptogenesis. In addition, average daily seizure frequency was positively correlated with percentage dwell time (i.e. how often a state occurs) in states with high mean functional connectivity, high segregation and integration, and with the number of transitions between states, while negatively correlated with percentage dwell time in states with a low mean functional connectivity, low segregation and low integration. This indicates that animals that dwell in states of higher functional connectivity, higher segregation and higher integration, and that switch more often between states, have more seizures.
Keywords
Resting state functional MRI, Temporal lobe epilepsy, Intraperitoneal kainic acid rat model, Dynamic functional connectivity, Sliding window analysis, NETWORKS, SEIZURES, FMRI

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MLA
Christiaen, Emma, et al. “Dynamic Functional Connectivity and Graph Theory Metrics in a Rat Model of Temporal Lobe Epilepsy Reveal a Preference for Brain States with a Lower Functional Connectivity, Segregation and Integration.” NEUROBIOLOGY OF DISEASE, vol. 139, 2020, doi:10.1016/j.nbd.2020.104808.
APA
Christiaen, E., Goossens, M.-G., Descamps, B., Larsen, L. E., Boon, P., Raedt, R., & Vanhove, C. (2020). Dynamic functional connectivity and graph theory metrics in a rat model of temporal lobe epilepsy reveal a preference for brain states with a lower functional connectivity, segregation and integration. NEUROBIOLOGY OF DISEASE, 139. https://doi.org/10.1016/j.nbd.2020.104808
Chicago author-date
Christiaen, Emma, Marie-Gabrielle Goossens, Benedicte Descamps, Lars Emil Larsen, Paul Boon, Robrecht Raedt, and Christian Vanhove. 2020. “Dynamic Functional Connectivity and Graph Theory Metrics in a Rat Model of Temporal Lobe Epilepsy Reveal a Preference for Brain States with a Lower Functional Connectivity, Segregation and Integration.” NEUROBIOLOGY OF DISEASE 139. https://doi.org/10.1016/j.nbd.2020.104808.
Chicago author-date (all authors)
Christiaen, Emma, Marie-Gabrielle Goossens, Benedicte Descamps, Lars Emil Larsen, Paul Boon, Robrecht Raedt, and Christian Vanhove. 2020. “Dynamic Functional Connectivity and Graph Theory Metrics in a Rat Model of Temporal Lobe Epilepsy Reveal a Preference for Brain States with a Lower Functional Connectivity, Segregation and Integration.” NEUROBIOLOGY OF DISEASE 139. doi:10.1016/j.nbd.2020.104808.
Vancouver
1.
Christiaen E, Goossens M-G, Descamps B, Larsen LE, Boon P, Raedt R, et al. Dynamic functional connectivity and graph theory metrics in a rat model of temporal lobe epilepsy reveal a preference for brain states with a lower functional connectivity, segregation and integration. NEUROBIOLOGY OF DISEASE. 2020;139.
IEEE
[1]
E. Christiaen et al., “Dynamic functional connectivity and graph theory metrics in a rat model of temporal lobe epilepsy reveal a preference for brain states with a lower functional connectivity, segregation and integration,” NEUROBIOLOGY OF DISEASE, vol. 139, 2020.
@article{8650254,
  abstract     = {Epilepsy 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 patients with epilepsy. This longitudinal study investigated changes in dynamic functional connectivity (dFC) and network topology during the development of epilepsy using the intraperitoneal kainic acid (IPKA) rat model of temporal lobe epilepsy (TLE). Resting state functional magnetic resonance images (rsfMRI) of 20 IPKA animals and 7 healthy control animals were acquired before and 1, 3, 6, 10 and 16 weeks after status epilepticus (SE) under medetomidine anaesthesia using a 7 T MRI system. Starting from 17 weeks post-SE, hippocampal EEG was recorded to determine the mean daily seizure frequency of each animal. Dynamic FC was assessed by calculating the correlation matrices between fMRI time series of predefined regions of interest within a sliding window of 50 s using a step length of 2 s. The matrices were classified into 6 FC states, each characterized by a correlation matrix, using k-means clustering. In addition, several time-variable graph theoretical network metrics were calculated from the time-varying correlation matrices and classified into 6 states of functional network topology, each characterized by a combination of network metrics. Our results showed that FC states with a lower mean functional connectivity, lower segregation and integration occurred more often in IPKA animals compared to control animals. Functional connectivity also became less variable during epileptogenesis. In addition, average daily seizure frequency was positively correlated with percentage dwell time (i.e. how often a state occurs) in states with high mean functional connectivity, high segregation and integration, and with the number of transitions between states, while negatively correlated with percentage dwell time in states with a low mean functional connectivity, low segregation and low integration. This indicates that animals that dwell in states of higher functional connectivity, higher segregation and higher integration, and that switch more often between states, have more seizures.},
  articleno    = {104808},
  author       = {Christiaen, Emma and Goossens, Marie-Gabrielle and Descamps, Benedicte and Larsen, Lars Emil and Boon, Paul and Raedt, Robrecht and Vanhove, Christian},
  issn         = {0969-9961},
  journal      = {NEUROBIOLOGY OF DISEASE},
  keywords     = {Resting state functional MRI,Temporal lobe epilepsy,Intraperitoneal kainic acid rat model,Dynamic functional connectivity,Sliding window analysis,NETWORKS,SEIZURES,FMRI},
  language     = {eng},
  pages        = {18},
  title        = {Dynamic functional connectivity and graph theory metrics in a rat model of temporal lobe epilepsy reveal a preference for brain states with a lower functional connectivity, segregation and integration},
  url          = {http://dx.doi.org/10.1016/j.nbd.2020.104808},
  volume       = {139},
  year         = {2020},
}

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