Functional connectivity changes in patients with absence epilepsy studied using resting-state functional MRI

Epilepsy-related functional brain network alterations are already present at an early age in the GAERS rat model of genetic absence epilepsy

Introduction

Genetic Absence Epilepsy Rats from Strasbourg (GAERS) represent a model of genetic generalized epilepsy. The present longitudinal study in GAERS and age-matched non-epileptic controls (NEC) aimed to characterize the epileptic brain network using two functional measures, resting state-functional magnetic resonance imaging (rs-fMRI) and manganese-enhanced MRI (MEMRI) combined with morphometry, and to investigate potential brain network alterations, following long-term seizure activity.

Methods

Repeated rs-fMRI measurements at 9.4 T between 3 and 8 months of age were combined with MEMRI at the final time point of the study. We used graph theory analysis to infer community structure and global and local network parameters from rs-fMRI data and compared them to brain region-wise manganese accumulation patterns and deformation-based morphometry (DBM).

Results

Functional connectivity (FC) was generally higher in GAERS when compared to NEC. Global network parameters and community structure were similar in NEC and GAERS, suggesting efficiently functioning networks in both strains. No progressive FC changes were observed in epileptic animals. Network-based statistics (NBS) revealed stronger FC within the cortical community, including regions of association and sensorimotor cortex, and with basal ganglia and limbic regions in GAERS, irrespective of age. Higher manganese accumulation in GAERS than in NEC was observed at 8 months of age, consistent with higher overall rs-FC, particularly in sensorimotor cortex and association cortex regions. Functional measures showed less similarity in subcortical regions. Whole brain volumes of 8 months-old GAERS were higher when compared to age-matched NEC, and DBM revealed increased volumes of several association and sensorimotor cortex regions and of the thalamus.

Discussion

rs-fMRI, MEMRI, and volumetric data collectively suggest the significance of cortical networks in GAERS, which correlates with an increased fronto-central connectivity in childhood absence epilepsy (CAE). Our findings also verify involvement of basal ganglia and limbic regions. Epilepsy-related network alterations are already present in juvenile animals. Consequently, this early condition seems to play a greater role in dynamic brain function than chronic absence seizures.

Predicting the therapeutic response to valproic acid in childhood absence epilepsy through electroencephalogram analysis using machine learning

Childhood absence epilepsy (CAE) is a common type of idiopathic generalized epilepsy, manifesting as daily multiple absence seizures. Although seizures in most patients can be adequately controlled with first-line antiseizure medication (ASM), approximately 25 % of patients respond poorly to first-line ASM. In addition, an accurate method for predicting first-line medication responsiveness is lacking. We used the quantitative electroencephalogram (QEEG) features of patients with CAE along with machine learning to predict the therapeutic effects of valproic acid in this population. We enrolled 25 patients with CAE from multiple medical centers. Twelve patients who required additional medication for seizure control or who were shifted to another ASM and 13 patients who achieved seizure freedom with valproic acid within 6 months served as the nonresponder and responder groups. Using machine learning, we analyzed the interictal background EEG data without epileptiform discharge before ASM. The following features were analyzed: EEG frequency bands, Hjorth parameters, detrended fluctuation analysis, Higuchi fractal dimension, Lempel-Ziv complexity (LZC), Petrosian fractal dimension, and sample entropy (SE). We applied leave-one-out cross-validation with support vector machine, K-nearest neighbor (KNN), random forest, decision tree, Ada boost, and extreme gradient boosting, and we tested the performance of these models. The responders had significantly higher alpha band power and lower delta band power than the nonresponders. The Hjorth mobility, LZC, and SE values in the temporal, parietal, and occipital lobes were higher in the responders than in the nonresponders. Hjorth complexity was higher in the nonresponders than in the responders in almost all the brain regions, except for the leads FP1 and FP2. Using KNN classification with theta band power in the temporal lobe yielded optimal performance, with sensitivity of 92.31 %, specificity of 76.92 %, accuracy of 84.62 %, and area under the curve of 88.46 %.We used various EEG features along with machine learning to accurately predict whether patients with CAE would respond to valproic acid. Our method could provide valuable assistance for pediatric neurologists in selecting suitable ASM.

Different circuitry dysfunction in drug-naive patients with juvenile myoclonic epilepsy and juvenile absence epilepsy

RATIONALE

Juvenile myoclonic epilepsy (JME) and juvenile absence epilepsy (JAE) are generalized epileptic syndromes presenting in the same age range. To explore whether uneven network dysfunctions may underlie the two different phenotypes, we examined drug-naive patients with JME and JAE at the time of their earliest presentation.

METHODS

Patients were recruited based on typical JME (n = 23) or JAE (n = 18) presentation and compared with 16 age-matched healthy subjects (HS). We analyzed their awake EEG signals by Partial Directed Coherence and graph indexes.

RESULTS

Out-density and betweenness centrality values were different between groups. With respect to both JAE and HS, JME showed unbalanced out-density and out-strength in alpha and beta bands on central regions and reduced alpha out-strength from fronto-polar to occipital regions, correlating with photosensitivity. With respect to HS, JAE showed enhanced alpha out-density and out-strength on fronto-polar regions. In gamma band, JAE showed reduced Global/Local Efficiency and Clustering Coefficient with respect to HS, while JME showed more scattered values.

CONCLUSIONS

Our data suggest that regional network changes in alpha and beta bands underlie the different presentation distinguishing JME and JAE resulting in motor vs non-motor seizures characterizing these two syndromes. Conversely, impaired gamma-activity within the network seems to be a non-local marker of defective inhibition.

Early clinical and EEG findings associated with the outcome in childhood absence epilepsy

OBJECTIVES

The objective of this study was to investigate several clinical electroencephalogram (EEG) findings possibly predicting the early response to antiepileptic drugs (AEDs) and the late outcome in children with clinical EEG features fitting the syndromic diagnosis of childhood absence epilepsy (CAE).

METHODS

In 117 untreated patients with typical absences, we analyzed clinical EEG features, and resting EEG activity using partial directed coherence to calculate out- and inflow of cortical oscillations in different regions of interest.

RESULTS

Absences began before 4 years in 12.0%, at 4-9.5 years in 71.8%, and at 10-13 years in 16.2% of the cases. Valproate was started in 91 patients and ethosuximide in 27. With one of AEDs, 77.8% reached seizure control, while the remaining patients needed to switch to the alternative AED. Only 5.9% patients remained drug-resistant. Absences with simple automatisms were the only feature associated with a lack of response to the first AED. Connectivity analysis of resting EEGs showed increased frontal outflow in patients compared with controls, which was significantly greater in the nonresponders to the first AED than in responders. Among the 91 patients followed for 61.2 ± 31.7 months, 14.2% relapsed after a seizure-free period, without differences between the responders to the first or second AED.

CONCLUSIONS

The assessment of electroclinical features provided only minimal prognostic indices. The enhanced outflow of frontal oscillations suggests a circuitry dysfunction significantly greater in the nonresponder to the early treatment. Seizure relapses were rare and comparable in patients who reached seizure freedom with first or second AED, indicating that the resistance to one AED does not influence the outcome.

The epileptic network and cognition: What functional connectivity is teaching us about the childhood epilepsies

Our objective was to summarize and evaluate the rapidly expanding body of literature studying functional connectivity in childhood epilepsy. In the self-limited childhood epilepsies, awareness of cognitive comorbidities has been steadily increasing, and recent advances in our understanding of the network effects of these disorders promise insights into the underlying neurobiology. We reviewed publications addressing functional connectivity in children with epilepsy with an emphasis on studies of children with self-limited childhood epilepsies. The majority of studies have been published in the past 10 years and predominantly examine childhood epilepsy with centrotemporal spikes and childhood absence epilepsy. Cognitive network alterations are commonly observed across the childhood epilepsies. Some of these effects appear to be nonspecific to epilepsy syndrome or even to category of neurological disorder. Other patterns, such as changes in the connectivity of cortical language areas in childhood epilepsy with centrotemporal spikes, provide clues to the underlying cognitive deficits seen in affected children. The literature to date is dominated by general observations of connectivity patterns without a priori hypotheses. These data-driven studies build an important foundation for hypothesis generation and are already providing useful insights into the neuropathology of the childhood epilepsies. Future work should emphasize hypothesis-driven approaches and rigorous clinical correlations to better understand how the knowledge of network alterations can be applied to guidance and treatment for the children in our clinics.

Resting-state functional magnetic resonance imaging: review of neurosurgical applications

Recent research in brain imaging has highlighted the role of different neural networks in the resting state (ie, no task) in which the brain displays spontaneous low-frequency neuronal oscillations. These can be indirectly measured with resting-state functional magnetic resonance imaging, and functional connectivity can be inferred as the spatiotemporal correlations of this signal. This technique has proliferated in recent years and has allowed the noninvasive investigation of large-scale, distributed functional networks. In this review, we give a brief overview of resting-state networks and examine the use of resting-state functional magnetic resonance imaging in neurosurgical contexts, specifically with respect to neurooncology, epilepsy surgery, and deep brain stimulation. We discuss the advantages and disadvantages compared with task-based functional magnetic resonance imaging, the limitations of resting-state functional magnetic resonance imaging, and the emerging directions of this relatively new technology.

Mechanisms regulating neuronal excitability and seizure development following mTOR pathway hyperactivation

The phosphatidylinositol-3-kinase/phosphatase and tensin homolog (PTEN)-mammalian target of rapamycin (mTOR) pathway regulates a variety of neuronal functions, including cell proliferation, survival, growth, and plasticity. Dysregulation of the pathway is implicated in the development of both genetic and acquired epilepsies. Indeed, several causal mutations have been identified in patients with epilepsy, the most prominent of these being mutations in PTEN and tuberous sclerosis complexes 1 and 2 (TSC1, TSC2). These genes act as negative regulators of mTOR signaling, and mutations lead to hyperactivation of the pathway. Animal models deleting PTEN, TSC1, and TSC2 consistently produce epilepsy phenotypes, demonstrating that increased mTOR signaling can provoke neuronal hyperexcitability. Given the broad range of changes induced by altered mTOR signaling, however, the mechanisms underlying seizure development in these animals remain uncertain. In transgenic mice, cell populations with hyperactive mTOR have many structural abnormalities that support recurrent circuit formation, including somatic and dendritic hypertrophy, aberrant basal dendrites, and enlargement of axon tracts. At the functional level, mTOR hyperactivation is commonly, but not always, associated with enhanced synaptic transmission and plasticity. Moreover, these populations of abnormal neurons can affect the larger network, inducing secondary changes that may explain paradoxical findings reported between cell and network functioning in different models or at different developmental time points. Here, we review the animal literature examining the link between mTOR hyperactivation and epileptogenesis, emphasizing the impact of enhanced mTOR signaling on neuronal form and function.