The Role of EEG-fMRI in Studying Cognitive Network Alterations in Epilepsy

Electroencephalography derived connectivity informing epilepsy surgical planning: Towards clinical applications and future perspectives

Epilepsy is one of the most diffused neurological disorders, affecting 50 million people worldwide. Around 30% of patients have drug-resistant epilepsy (DRE), defined as failure of at least two tolerated antiseizure medications (ASMs) to achieve sustained seizure freedom. Brain surgery is an effective therapeutic approach in this group, hinging on the accurate localization of the epileptic focus. The latter task is complex and requires multimodal investigation methods. Epilepsy is also a network disorder and represents one of the best application scenarios of methods leveraging brain functional organization at large scales. Connectivity analysis represents a promising tool for improving surgical assessment, enabling better identification of candidates who could benefit the most from epilepsy surgery. The scalp electroencephalography (EEG) is the most relevant tool to characterize epileptic activity. The EEG has benefited significantly from technological advancement across the last decades. Firstly, electrical source imaging (ESI) allows the reconstruction of electrical activity detected by EEG at the cortex level; secondly, functional connectivity (FC) allows the assessment of functional dependencies across brain areas. The EEG has therefore expanded potential applications in the localization and characterization of the epileptogenic network for surgical planning. As the translation of these methods in clinical practice is little discussed in the literature, we reviewed the investigations using EEG-derived FC. We showed that the FC-informed identification of the epileptic networks improves the localization precision in focal epilepsy. We discussed the heterogeneity in the results and methodology preventing prompt research-to-clinic translation. We finally provided practical suggestions for promoting the applicability of FC-based research in real clinical practice, looking for future research.

Clinical Usefulness of Simultaneous Electroencephalography and Functional Magnetic Resonance Imaging in Children With Focal Epilepsy

Background and Purpose

The current study analyzed the interictal epileptiform discharge (IED)-related hemodynamic response and aimed to determine the clinical usefulness of simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) in defining the epileptogenic zone (EZ) in children with focal epilepsy.

Methods

Patients with focal epilepsy showing IEDs on conventional EEG were evaluated using EEG-fMRI. Statistical analyses were performed using the times of spike as events modeled with multiple hemodynamic response functions. The area showing the most significant t-value for blood-oxygen-level-dependent (BOLD) changes was compared with the presumed EZ. Moreover, BOLD responses between -9 and +9 s around the spike times were analyzed to track the hemodynamic response patterns over time.

Results

Half (n=13) of 26 EEG-fMRI investigations of 19 patients were successful. Two patients showed 2 different types of spikes, resulting in 15 analyses. The maximum BOLD response was concordant with the EZ in 11 (73.3%) of the 15 analyses. In 10 (66.7%) analyses, the BOLD response localized the EZs more specifically. Focal BOLD responses in the EZs occurred before IEDs in 11 analyses and were often widespread after IEDs. Hemodynamic response patterns were consistent in the same epilepsy syndrome or when repeating the investigation in the same patients.

Conclusions

EEG-fMRI can provide additional information for localizing the EZ in children with focal epilepsy, and also reveal the pathogenesis of pediatric epilepsy by evaluating the patterns in the hemodynamic response across time windows of IEDs.

EEG-fMRI of epileptiform discharges: non-invasive investigation of the whole brain

Simultaneous EEG-fMRI is a unique and non-invasive method for investigating epileptic activity. Interictal epileptiform discharge-related EEG-fMRI provides cortical and subcortical blood oxygen level-dependent (BOLD) signal changes specific to epileptic discharges. As a result, EEG-fMRI has revealed insights into generators and networks involved in epileptic activity in different types of epilepsy, demonstrating-for instance-the implication of the thalamus in human generalized spike and wave discharges and the role of the Default Mode Network (DMN) in absences and focal epilepsy, and proposed a mechanism for the cortico-subcortical interactions in Lennox-Gastaut syndrome discharges. EEG-fMRI can find deep sources of epileptic activity not available to scalp EEG or MEG and provides critical new information to delineate the epileptic focus when considering surgical treatment or electrode implantation. In recent years, methodological advances, such as artifact removal and automatic detection of events have rendered this method easier to implement, and its clinical potential has since been established by evidence of the impact of BOLD response on clinical decision-making and of the relationship between concordance of BOLD responses with extent of resection and surgical outcome. This review presents the recent developments in EEG-fMRI methodology and EEG-fMRI studies in different types of epileptic disorders as follows: EEG-fMRI acquisition, gradient and pulse artifact removal, statistical analysis, clinical applications, pre-surgical evaluation, altered physiological state in generalized genetic epilepsy, and pediatric EEG-fMRI studies.

Simultaneous EEG-fMRI: What Have We Learned and What Does the Future Hold?

Simultaneous EEG-fMRI has developed into a mature measurement technique in the past 25 years. During this time considerable technical and analytical advances have been made, enabling valuable scientific contributions to a range of research fields. This review will begin with an introduction to the measurement principles involved in EEG and fMRI and the advantages of combining these methods. The challenges faced when combining the two techniques will then be considered. An overview of the leading application fields where EEG-fMRI has made a significant contribution to the scientific literature and emerging applications in EEG-fMRI research trends is then presented.

Structural and functional motor-network disruptions predict selective action-concept deficits: Evidence from frontal lobe epilepsy

Built on neurodegenerative lesions models, the disrupted motor grounding hypothesis (DMGH) posits that motor-system alterations selectively impair action comprehension. However, major doubts remain concerning the dissociability, neural signatures, and etiological generalizability of such deficits. Few studies have compared action-concept outcomes between disorders affecting and sparing motor circuitry, and none has examined their multimodal network predictors via data-driven approaches. Here, we first assessed action- and object-concept processing in patients with frontal lobe epilepsy (FLE), patients with posterior cortex epilepsy (PCE), and healthy controls. Then, we examined structural and functional network signatures via diffusion tensor imaging and resting-state connectivity measures. Finally, we used these measures to predict behavioral performance with an XGBoost machine learning regression algorithm. Relative to controls, FLE (but not PCE) patients exhibited selective action-concept deficits together with structural and functional abnormalities along motor networks. The XGBoost model reached a significantly large effect size only for action-concept outcomes in FLE, mainly predicted by structural (cortico-spinal tract, anterior thalamic radiation, uncinate fasciculus) and functional (M1-parietal/supramarginal connectivity) motor networks. These results extend the DMGH, suggesting that action-concept deficits are dissociable markers of frontal/motor (relative to posterior) disruptions, directly related to the structural and functional integrity of motor networks, and traceable beyond canonical movement disorders.

Hippocampal atrophy and quantitative EEG markers in mild cognitive impairment in temporal lobe epilepsy versus extra-temporal lobe epilepsy

OBJECTIVE

Cognitive impairment in temporal lobe epilepsy is widely acknowledged as one of the most well-known comorbidities. This study aimed to explore cognitive impairment and to determine the potential clinical, radiological, and quantitative electroencephalography markers for cognitive impairment in temporal lobe epilepsy patients versus extra-temporal lobe epilepsy.

METHODS

Forty-five patients with temporal lobe epilepsy and forty-five patients with extra-temporal lobe epilepsy were recruited for an administered digit span test, verbal fluency test, mini-mental state examination, digital symbol test, and Montreal cognitive assessment. Also, they were subjected to magnetic resonance imaging assessment for hippocampal atrophy and a quantitative electroencephalography assessment for electroencephalography markers (median frequency, peak frequency, and the alpha-to-theta ratio).

RESULTS

Patients with extra-temporal lobe epilepsy showed non-significant higher epilepsy durations and a higher frequency of seizures. Temporal lobe epilepsy patients showed a more statistically significant family history of epilepsy (37.7%), more history of febrile convulsions (13.3%), higher hippocampal atrophy (17.8%), and lower cognitive scales, especially mini-mental state examination and Montreal cognitive assessment; lower digital symbol test, verbal fluency test, and backward memory of digit span test. Also, temporal lobe epilepsy patients had a strong negative correlation with electroencephalography markers: median frequency, peak frequency, and the alpha-to-theta ratio (r =  - 0.68, P < 0.005 and r =  - 0.64, P < 0.005 and r =  - 0.66, P < 0.005 respectively).

CONCLUSION

Cognitive impairment in patients with temporal lobe epilepsy was correlated with hippocampal atrophy and quantitative electroencephalography abnormalities, especially peak frequency, median frequency, and alpha-to-theta ratio that could be used alone for the identification of early cognitive impairment.

TRIAL REGISTRATION

Clinicaltrials.gov: NCT04376671.

In vivo calcium imaging reveals disordered interictal network dynamics in epileptic stxbp1b zebrafish

STXBP1 mutations are associated with encephalopathy, developmental delay, intellectual disability, and epilepsy. While neural networks are known to operate at a critical state in the healthy brain, network behavior during pathological epileptic states remains unclear. Examining activity during periods between well-characterized ictal-like events (i.e., interictal period) could provide a valuable step toward understanding epileptic networks. To study these networks in the context of STXBP1 mutations, we combine a larval zebrafish model with in vivo fast confocal calcium imaging and extracellular local field potential recordings. Stxbp1b mutants display transient periods of elevated activity among local clusters of interacting neurons. These network "cascade" events were significantly larger in size and duration in mutants. At mesoscale resolution, cascades exhibit neurodevelopmental abnormalities. At single-cell scale, we describe spontaneous hyper-synchronized neuronal ensembles. That calcium imaging reveals uniquely disordered brain states during periods between pathological ictal-like seizure events is striking and represents a potential interictal biomarker.

Recent Advances in Neuroimaging of Epilepsy

Human neuroimaging has had a major impact on the biological understanding of epilepsy and the relationship between pathophysiology, seizure management, and outcomes. This review highlights notable recent advancements in hardware, sequences, methods, analyses, and applications of human neuroimaging techniques utilized to assess epilepsy. These structural, functional, and metabolic assessments include magnetic resonance imaging (MRI), positron emission tomography (PET), and magnetoencephalography (MEG). Advancements that highlight non-invasive neuroimaging techniques used to study the whole brain are emphasized due to the advantages these provide in clinical and research applications. Thus, topics range across presurgical evaluations, understanding of epilepsy as a network disorder, and the interactions between epilepsy and comorbidities. New techniques and approaches are discussed which are expected to emerge into the mainstream within the next decade and impact our understanding of epilepsies. Further, an increasing breadth of investigations includes the interplay between epilepsy, mental health comorbidities, and aberrant brain networks. In the final section of this review, we focus on neuroimaging studies that assess bidirectional relationships between mental health comorbidities and epilepsy as a model for better understanding of the commonalities between both conditions.

Topography-Related EEG-fMRI in Surgically Confirmed Epileptic Foci: A Comparison to Spike-Related EEG-fMRI in Clinical Practice

EEG-fMRI has gained increasing importance in epilepsy pre-surgical diagnosis. However, 40-70% of EEG-fMRI recordings in patients lack interictal epileptiform discharges (IEDs) during the scan, which could be overcome by detecting matching topography maps. We tried to validate this method in clinical settings taking various electroclinical factors into consideration. Eleven patients who had undergone EEG-fMRI during pre-surgical evaluation for drug-resistant epilepsy and who had had clinical long-term video-EEG were studied. Spike-related blood oxygen level-dependent (BOLD) maps were created using IEDs occurring during the EEG-fMRI scan. Separate maps were then generated from IEDs marked on the clinical long-term EEG recordings, which were averaged to produce topographical IED maps and correlated with the EEGs recorded inside the scanner yielding a correlation coefficient time course. Epileptogenic zones were defined by an expert panel during pre-surgical evaluation and validated by an epilepsy surgery resulting in a good outcome. Both techniques' performance was evaluated according to factors including arousal during IED recording, IED topography and lateralization, lesion type, and localization. Topography-related EEG-fMRI yielded more specific results compared to the spike-related method. Superficial lesion location and ipsilateral IED seem to result in a higher concordance of BOLD maps. The polarity of BOLD responses may be lesion-dependent, and both positive and negative BOLD changes may be associated with the irritative zone. Topography-related EEG-fMRI may show improved specificity especially for superficial lesions producing ipsilateral spikes. This method can be used as an alternative either in the absence of spikes during the simultaneous EEG-fMRI acquisition or to sharpen a diffusely activated BOLD-map.

Accelerated long-term forgetting in focal epilepsy: Do interictal spikes during sleep matter?

Accelerated long-term forgetting (ALF) is a particular form of amnesia mostly encountered in focal epilepsy, particularly in temporal lobe epilepsy. This type of memory loss is characterized by an impairment of long-term consolidation of declarative memory, and its mechanisms remain poorly understood. In particular, the respective contribution of lesion, seizures, interictal epileptic discharges, and sleep is still debated. Here, we provide an overview of the relationships intertwining epilepsy, sleep, and memory consolidation and, based on recent findings from intracranial electroencephalographic recordings, we propose a model of ALF pathophysiology that integrates the differential role of interictal spikes during wakefulness and sleep. This model provides a framework to account for the different timescales at which ALF may occur.

Contributions of left and right anterior temporal lobes to semantic cognition: Evidence from patients with small temporopolar lesions

Decades of research have increased the understanding of the contribution of the anterior temporal lobes (ATLs) to semantic cognition. Nonetheless, whether semantic processing of different types of information show a selective relationship with left and right ATLs, or whether semantic processing in the ATLs is independent of the modality of the input is currently unknown. There exists evidence supporting each of these alternatives. A fundamental objection to these findings is that they were obtained from studies with patients with brain damage affecting extensive regions, sometimes bilaterally. In the current study, we assessed a group of 38 temporal lobe epilepsy (TLE) patients with either left or right small epileptogenic lesions with a battery of commonly used semantic tasks that tested verbal and non-verbal semantic processing. We found that left TLE patients exhibited worse performance than controls on the verbal semantic tasks, as expected, but also on the non-verbal semantic task. On the other hand, performance of the right TLE group did not differ from controls on the non-verbal task, but was worse on a semantic fluency task. When performance between patient groups was compared, we found that left TLE not only did worse than right TLE on the naming task, but also on the non-verbal associative memory task. When considered together, current data do not support a strong view of input modality differences between left and right ATLs. Additionally, they provide evidence indicating that the left and right ATLs do not make similar contributions to a singular functional system for semantic representation.

Graph theory application with functional connectivity to distinguish left from right temporal lobe epilepsy

OBJECTIVE

To investigate the application of graph theory with functional connectivity to distinguish left from right temporal lobe epilepsy (TLE).

METHODS

Alterations in functional connectivity within several brain networks - default mode (DMN), attention (AN), limbic (LN), sensorimotor (SMN) and visual (VN) - were examined using resting-state functional MRI (rs-fMRI). The study accrued 21 left and 14 right TLE as well as 17 nonepileptic control subjects. The local nodal degree, a feature of graph theory, was calculated foreach of the brain networks. Multivariate logistic regression analysis was performed to determine the accuracy of identifying seizure laterality based on significant differences in local nodal degree in the selected networks.

RESULTS

Left and right TLE patients showed dissimilar patterns of alteration in functional connectivity when compared to control subjects. Compared with right TLE, patients with left TLE exhibited greater nodal degree' (i.e. hyperconnectivity) with right superomedial frontal gyrus (in DMN), inferior frontal gyrus pars triangularis (in AN), right caudate and left superior temporal gyrus (in LN) and left paracentral lobule (in SMN), while showing lesser nodal degree (i.e. hypoconnectivity) with left temporal pole (in DMN), right insula (in LN), left supplementary motor area (in SMN), and left fusiform gyrus (in VN). The LN showed the highest accuracy of 82.9% among all considered networks in determining laterality of the TLE. By combinations of local degree attributes in the DMN, AN, LN, and VN, logistic regression analysis demonstrated an accuracy of 94.3% by comparison.

CONCLUSION

Our study demonstrates the utility of graph theory application to brain network analysis as a potential biomarker to assist in the determination of TLE laterality and improve the confidence in presurgical decision-making in cases of TLE.