Maria Centeno

Network Connectivity in Epilepsy: Resting State fMRI and EEG–fMRI Contributions

There is a growing body of evidence pointing toward large-scale networks underlying the core phenomena in epilepsy, from seizure generation to cognitive dysfunction or response to treatment. The investigation of networks in epilepsy has become a key concept to unlock a deeper understanding of the disease. Functional imaging can provide valuable information to characterize network dysfunction; in particular resting state fMRI (RS-fMRI), which is increasingly being applied to study brain networks in a number of diseases. In patients with epilepsy, network connectivity derived from RS-fMRI has found connectivity abnormalities in a number of networks; these include the epileptogenic, cognitive and sensory processing networks. However, in majority of these studies, the effect of epileptic transients in the connectivity of networks has been neglected. EEG–fMRI has frequently shown networks related to epileptic transients that in many cases are concordant with the abnormalities shown in RS studies. This points toward a relevant role of epileptic transients in the network abnormalities detected in RS-fMRI studies. In this review, we summarize the network abnormalities reported by these two techniques side by side, provide evidence of their overlapping findings, and discuss their significance in the context of the methodology of each technique. A number of clinically relevant factors that have been associated with connectivity changes are in turn associated with changes in the frequency of epileptic transients. These factors include different aspects of epilepsy ranging from treatment effects, cognitive processes, or transition between different alertness states (i.e., awake–sleep transition). For RS-fMRI to become a more effective tool to investigate clinically relevant aspects of epilepsy it is necessary to understand connectivity changes associated with epileptic transients, those associated with other clinically relevant factors and the interaction between them, which represents a gap in the current literature. We propose a framework for the investigation of network connectivity in patients with epilepsy that can integrate epileptic processes that occur across different time scales such as epileptic transients and disease duration and the implications of this approach are discussed.

The effect of topiramate on cognitive fMRI

Summary Purpose Topiramate (TPM) is known to cause language impairment in healthy volunteers and patients with epilepsy. We assessed the effects of TPM on functional language networks in both patients with focal epilepsies and healthy controls using functional magnetic resonance imaging (fMRI). Methods We obtained fMRI data in 24 controls and 35 patients with frontal lobe epilepsy using a simple verbal fluency (VF) paradigm. Eight of the 35 patients were treated with TPM in polytherapy. We compared cognitive task related activations and de-activations in patients taking TPM with patients taking other AEDs and healthy controls. In a longitudinal pilot study with VF-fMRI paradigm, we studied two patients with focal epilepsies twice, prior to starting and on stable doses of TPM, two patients twice, before and after tapering TPM completely and two healthy controls twice, before and after single doses of 200 mg TPM. Key findings Cross sectional analyses of VF-fMRI showed a reduction in the task-related deactivation of the default mode network (DMN) in patients taking TPM. The longitudinal study corroborated these findings as both chronic administration and a single dose of TPM were associated with impaired categorical verbal fluency and disruption of task-related deactivations. Significance Similar neuropsychological and fMRI findings in patients and healthy controls indicate a specific effect of TPM in default mode network areas that may be essential components of the language network. Our preliminary data suggest a mechanism by which TPM impairs cognitive processing during language function and highlights the sensitivity of fMRI to detect the effects of AEDs on cognitive brain networks.

Levetiracetam reduces abnormal network activations in temporal lobe epilepsy

Objective: We used functional MRI (fMRI) and a left-lateralizing verbal and a right-lateralizing visual-spatial working memory (WM) paradigm to investigate the effects of levetiracetam (LEV) on cognitive network activations in patients with drug-resistant temporal lobe epilepsy (TLE). Methods: In a retrospective study, we compared task-related fMRI activations and deactivations in 53 patients with left and 54 patients with right TLE treated with (59) or without (48) LEV. In patients on LEV, activation patterns were correlated with the daily LEV dose. Results: We isolated task- and syndrome-specific effects. Patients on LEV showed normalization of functional network deactivations in the right temporal lobe in right TLE during the right-lateralizing visual-spatial task and in the left temporal lobe in left TLE during the verbal task. In a post hoc analysis, a significant dose-dependent effect was demonstrated in right TLE during the visual-spatial WM task: the lower the LEV dose, the greater the abnormal right hippocampal activation. At a less stringent threshold (p < 0.05, uncorrected for multiple comparisons), a similar dose effect was observed in left TLE during the verbal task: both hippocampi were more abnormally activated in patients with lower doses, but more prominently on the left. Conclusions: Our findings suggest that LEV is associated with restoration of normal activation patterns. Longitudinal studies are necessary to establish whether the neural patterns translate to drug response. Classification of evidence: This study provides Class III evidence that in patients with drug-resistant TLE, levetiracetam has a dose-dependent facilitation of deactivation of mesial temporal structures.

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity.

FIACH: A biophysical model for automatic retrospective noise control in fMRI

Different noise sources in fMRI acquisition can lead to spurious false positives and reduced sensitivity. We have developed a biophysically-based model (named FIACH: Functional Image Artefact Correction Heuristic) which extends current retrospective noise control methods in fMRI. FIACH can be applied to both General Linear Model (GLM) and resting state functional connectivity MRI (rs-fcMRI) studies. FIACH is a two-step procedure involving the identification and correction of non-physiological large amplitude temporal signal changes and spatial regions of high temporal instability. We have demonstrated its efficacy in a sample of 42 healthy children while performing language tasks that include overt speech with known activations. We demonstrate large improvements in sensitivity when FIACH is compared with current methods of retrospective correction. FIACH reduces the confounding effects of noise and increases the studys power by explaining significant variance that is not contained within the commonly used motion parameters. The method is particularly useful in detecting activations in inferior temporal regions which have proven problematic for fMRI. We have shown greater reproducibility and robustness of fMRI responses using FIACH in the context of task induced motion. In a clinical setting this will translate to increasing the reliability and sensitivity of fMRI used for the identification of language lateralisation and eloquent cortex. FIACH can benefit studies of cognitive development in young children, patient populations and older adults.

Motor co-activation in siblings of patients with juvenile myoclonic epilepsy: an imaging endophenotype?

In juvenile myoclonic epilepsy (JME), myoclonic jerks are often triggered by cognitive effort. Wandschneider et al. report co-activation of the motor and prefrontal cognitive networks in unaffected siblings, similar to that previously reported in patients themselves. This co-activation could constitute a heritable marker for further genetic studies of JME.

Epileptic networks are strongly connected with and without the effects of interictal discharges

Epilepsy is increasingly considered as the dysfunction of a pathologic neuronal network (epileptic network) rather than a single focal source. We aimed to assess the interactions between the regions that comprise the epileptic network and to investigate their dependence on the occurrence of interictal epileptiform discharges (IEDs).

Optimising EEG-fMRI for Localisation of Focal Epilepsy in Children

Background Early surgical intervention in children with drug resistant epilepsy has benefits but requires using tolerable and minimally invasive tests. EEG-fMRI studies have demonstrated good sensitivity for the localization of epileptic focus but a poor yield although the reasons for this have not been systematically addressed. While adults EEG-fMRI studies are performed in the “resting state”; children are commonly sedated however, this has associated risks and potential confounds. In this study, we assessed the impact of the following factors on the tolerability and results of EEG-fMRI in children: viewing a movie inside the scanner; movement; occurrence of interictal epileptiform discharges (IED); scan duration and design efficiency. This work’s motivation is to optimize EEG-fMRI parameters to make this test widely available to paediatric population Methods Forty-six children with focal epilepsy and 20 controls (6–18) underwent EEG-fMRI. For two 10 minutes sessions subjects were told to lie still with eyes closed, as it is classically performed in adult studies (“rest sessions”), for another two sessions, subjects watched a child friendly stimulation i.e. movie (“movie sessions”). IED were mapped with EEG-fMRI for each session and across sessions. The resulting maps were classified as concordant/discordant with the presumed epileptogenic focus for each subject. Findings Movement increased with scan duration, but the movie reduced movement by ~40% when played within the first 20 minutes. There was no effect of movie on the occurrence of IED, nor in the concordance of the test. Ability of EEG-fMRI to map the epileptogenic region was similar for the 20 and 40 minute scan durations. Design efficiency was predictive of concordance. Conclusions A child friendly natural stimulus improves the tolerability of EEG-fMRI and reduces in-scanner movement without having an effect on IED occurrence and quality of EEG-fMRI maps. This allowed us to scan children as young as 6 and obtain localising information without sedation. Our data suggest that ~20 minutes is the optimal length of scanning for EEG-fMRI studies in children with frequent IED. The efficiency of the fMRI design derived from spontaneous IED generation is an important factor for producing concordant results.

Interictal activity is an important contributor to abnormal intrinsic network connectivity in paediatric focal epilepsy.

Patients with focal epilepsy have been shown to have reduced functional connectivity in intrinsic connectivity networks (ICNs), which has been related to neurocognitive development and outcome. However, the relationship between interictal epileptiform discharges (IEDs) and changes in ICNs remains unclear, with evidence both for and against their influence. EEG‐fMRI data was obtained in 27 children with focal epilepsy (mixed localisation and aetiologies) and 17 controls. A natural stimulus task (cartoon blocks verses blocks where the subject was told “please wait”) was used to enhance the connectivity within networks corresponding to ICNs while reducing potential confounds of vigilance and motion. Our primary hypothesis was that the functional connectivity within visual and attention networks would be reduced in patients with epilepsy. We further hypothesized that controlling for the effects of IEDs would increase the connectivity in the patient group. The key findings were: (1) Patients with mixed epileptic foci showed a common connectivity reduction in lateral visual and attentional networks compared with controls. (2) Having controlled for the effects of IEDs there were no connectivity differences between patients and controls. (3) A comparison within patients revealed reduced connectivity between the attentional network and basal ganglia associated with interictal epileptiform discharges. We also found that the task activations were reduced in epilepsy patients but that this was unrelated to IED occurrence. Unexpectedly, connectivity changes in ICNs were strongly associated with the transient effects of interictal epileptiform discharges. Interictal epileptiform discharges were shown to have a pervasive transient influence on the brains functional organisation. Hum Brain Mapp 38:221–236, 2017.

Clinical language fMRI with real-time monitoring in temporal lobe epilepsy: Online processing methods

The increasing demand for clinical fMRI data has resulted in a need to translate research methods to clinical use. Referrals for language lateralization prior to epilepsy surgery are becoming more common, but time constraints make this unachievable in many busy neuroimaging departments. This study examines whether a single covert verbal fluency paradigm with real-time monitoring and online processing (BrainWave) could replace conventional offline processing (SPM) for the purpose of establishing expressive language dominance prior to epilepsy surgery. We analyzed language fMRI results of 30 patients (17 female; 24 right‐handed; median age: 30.5) with temporal lobe epilepsy. Concordance between visual assessment of SPM and BrainWave was 92.8%. Lateralization indices correlated closely with visual assessments of lateralization with a concordance of 85.7%. BrainWave provided a real-time, fast and accurate display of language lateralization easily applied in a clinical setting using only online image processing.