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Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), EEG-fMRI, combines the complementary properties of scalp EEG ...

McGill University

Focal cortical dysplasia (FCD) is able to generate an intrinsic pathological EEG activity characterized by a continuous or near-continuous spiking. Different patterns of discharge were described. We examined quantitatively the distribution of the intracerebral FCD patterns in relation to sleep in order to investigate whether this activity is independent of thalamocortical influences.

Sleep influences the intracerebral EEG pattern of focal cortical dysplasia.

Intracranial electroencephalography (EEG), performed presurgically in patients with drug-resistant and difficult-to-localize focal epilepsy, samples only a small fraction of brain tissue and thus requires strong hypotheses regarding the possible localization of the epileptogenic zone. EEG/fMRI (functional magnetic resonance imaging), a noninvasive tool resulting in hemodynamic responses, could contribute to the generation of these hypotheses. This study assessed how these responses, despite their interictal origin, predict the seizure-onset zone (SOZ).

The hemodynamic response to interictal epileptic discharges localizes the seizure-onset zone.

It has been reported that interictal epileptic discharges (IEDs) recorded in temporal regions on scalp EEG are unlikely to originate from mesial temporal structures. However, EEG-fMRI sometimes show mesial temporal activation. We hypothesized that BOLD activation in the temporal neocortex is weaker than in the mesial structures, reflecting the fact that propagated activity has less metabolic demand than the original discharge.

Temporal lobe spikes: EEG-fMRI contributions to the "mesial vs. lateral" debate.

Structural and functional imaging studies in focal epilepsy often reveal distributed regions of abnormality. These are interpreted as representing the existence of epileptic networks, but the presence of actual neuronal interactions between these regions has not been demonstrated. We sought to determine whether the distributed hemodynamic responses often seen in functional magnetic resonance imaging (fMRI) studies of scalp interictal epileptic discharges (IEDs) actually correspond to synchronized neuronal activities when examining the intracerebral electroencephalogram (iEEG) at distant nodes of the network.

Epileptic networks in action: Synchrony between distant hemodynamic responses.

Presurgical evaluation that can precisely delineate the epileptogenic zone (EZ) is one important step for successful surgical resection treatment of refractory epilepsy patients. The noninvasive EEG-fMRI recording technique combined with general linear model (GLM) analysis is considered an important tool for estimating the EZ. However, the manual marking of interictal epileptic discharges (IEDs) needed in this analysis is challenging and time-consuming because the quality of the EEG recorded inside the scanner is greatly deteriorated compared to the usual EEG obtained outside the scanner. This is one of main impediments to the widespread use of EEG-fMRI in epilepsy. We propose a deep learning based semi-automatic IED detector that can find the candidate IEDs in the EEG recorded inside the scanner which resemble sample IEDs marked in the EEG recorded outside the scanner. The manual marking burden is greatly reduced as the expert need only edit candidate IEDs. The model is trained on data from 30 patients. Validation of IEDs detection accuracy on another 37 consecutive patients shows our method can improve the median sensitivity from 50.0% for the previously proposed template-based method to 84.2%, with false positive rate as 5 events/min. Reproducibility validation on 15 patients is applied to evaluate if our method can produce similar hemodynamic response maps compared with the manual marking ground truth results. We explore the concordance between the maximum hemodynamic response and the intracerebral EEG defined EZ and find that both methods produce similar percentage of concordance (76.9%, 10 out of 13 patients, electrode was absent in the maximum hemodynamic response in two patients). This tool will make EEG-fMRI analysis more practical for clinical usage.

DeepIED: An epileptic discharge detector for EEG-fMRI based on deep learning.

To determine whether the maximum hemodynamic response to scalp interictal epileptic discharges (IEDs) corresponds to the region where IEDs originate and from where they propagate.

The spike onset zone: The region where epileptic spikes start and from where they propagate.

Optimal performance depends in part on the ability to inhibit the automatic processing of irrelevant information and also on the adjusting the level of control from one trial to the next. In this study, we investigated the spatio-temporal neural correlates of cognitive control using simultaneous functional magnetic resonance imaging and electroencephalography, while 22 participants (10 women) performed a numerical Stroop task. We investigated the spatial and temporal dynamic of the conflict adaptation effects (i.e., reduced interference on items that follow an incongruent stimulus compared to after a congruent stimulus). Joint independent component analysis linked the N200 component to activation of anterior cingulate cortex (ACC) and the conflict slow potential to widespread activations within the fronto-parietal executive control network. Connectivity analyses with psychophysiological interactions and dynamic causal modeling demonstrated coordinated engagement of the cognitive control network after the processing of an incongruent item, and this was correlated with better behavioral performance. Our results combined high spatial and temporal resolution to propose the following network of conflict adaptation effect and specify the time course of activation within this model: first, the anterior insula and inferior frontal gyrus are activated when incongruence is detected. These regions then signal the need for higher control to the ACC, which in turn activates the fronto-parietal executive control network to improve the performance on the next trial.

Spatio-temporal patterns of cognitive control revealed with simultaneous electroencephalography and functional magnetic resonance imaging.

We hypothesized that the number of interictal epileptic discharges (IEDs) during scan and their spatial extent are contributing factors in obtaining appropriate activations that reveal the seizure onset zone (SOZ) in EEG-fMRI.

Widespread interictal epileptic discharge more likely than focal discharges to unveil the seizure onset zone in EEG-fMRI.

A vast network involving the nodules and overlying cortices is believed to be responsible for the epileptogenicity in gray matter heterotopia with multiple nodules, which often associated with difficult-to-treat epilepsy. We sought to determine if functional magnetic resonance imaging (fMRI) could detect internodular functional connectivity (FC), and if this connectivity reflects an actual synchronized neuronal activity and partakes in epileptogenicity.

Internodular functional connectivity in heterotopia-related epilepsy.

We present a rare patient clinically suspected to have mixed idiopathic generalized and focal epilepsy, which was supported by BOLD pattern based on EEG-fMRI. A 37-year-old female with three types of refractory seizures starting at age six - tonic with breathing difficulties and confusion, generalized tonic-clonic, and focal with brief impairment of awareness and versive head movement, initially thought to represent atypical absences - was evaluated by EEG-fMRI. She was also shown to have three types of interictal epileptic discharges: generalized spike or polyspikes and slow waves, and left fronto-temporal and right fronto-temporal discharges. We assessed BOLD activation and deactivation for each type. For generalized patterns, the BOLD activation and deactivation were typical of that seen in primary generalized epilepsy. Whereas maximum activation for left fronto-temporal EEG patterns was observed in the left superior frontal gyrus and posterior superior temporal gyrus, maximum activation for right fronto-temporal patterns was bilateral in the right posterior middle temporal gyrus and left posterior middle temporal gyrus. The EEG-fMRI results suggested that the patient had both refractory idiopathic generalized and focal epilepsy, and not a generalized epilepsy originating from a focus.

Natalja Zazubovits

Montreal Neurological Institute and Hospital

McGill University

Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI

Natalja Zazubovits

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McGill University

Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI

Montreal Neurological Institute and Hospital