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OBJECTIVE: Sleep is an active process with an important role in memory. Epilepsy patients often display a disturbed sleep architecture, with consequences on cognition. We aimed to investigate the effect of sleep on cortical networks' organization.METHODS: We analyzed cortico-cortical evoked responses elicited by single pulse electrical stimulation (SPES) using intracranial depth electrodes in 25 patients with drug-resistant focal epilepsy explored using stereo-EEG. We applied the SPES protocol during wakefulness and NREM - N2 sleep. We analyzed 31,710 significant responses elicited by 799 stimulations covering most brain structures, epileptogenic or non-epileptogenic. We analyzed effective connectivity between structures using a graph-theory approach.RESULTS: Sleep increases excitability in the brain, regardless of epileptogenicity. Local and distant connections are differently modulated by sleep, depending on the tissue epileptogenicity. In non-epileptogenic areas, frontal lobe connectivity is enhanced during sleep. There is increased connectivity between the hippocampus and temporal neocortex, while perisylvian structures are disconnected from the temporal lobe. In epileptogenic areas, we found a clear interhemispheric difference, with decreased connectivity in the right hemisphere during sleep.CONCLUSIONS: Sleep modulates brain excitability and reconfigures functional brain networks, depending on tissue epileptogenicity.SIGNIFICANCE: We found specific patterns of information flow during sleep in physiologic and pathologic structures, with possible implications for cognition.

The operculum, defined as the cortex adjacent to the insula, is a large structure encompassing three lobes, with a recognized role in a variety of neurologic and psychiatric conditions. Its complex functions include sensory, motor, autonomic and cognitive processing. In humans, these are extended with the addition of language. These functions are implemented by highly specialized neuronal populations and their widespread connections, which our study aims at mapping in detail. We studied a group of 31 patients that were explored with intracranial electrodes during the pre-surgical workup for drug-resistant epilepsy. We have selected the subset of contacts implanted in non-epileptogenic opercular cortex and we analyzed the neurophysiological and behavioral responses to direct electrical stimulation. The functional mapping was performed by applying 1 Hz and 50 Hz electrical stimulation on 252 contact pairs and recording the threshold for evoking clinical effects. The effective connectivity was assessed using cortico-cortical evoked potentials elicited by single-pulse electrical stimulation in a subset of 19 patients. The locations of the effects grouped in twelve distinct semiological classes were analyzed. The most frequent effects evoked by stimulation of the frontal operculum were language related (29%). The Rolandic area produced most often oropharyngeal symptoms (47%), the parietal operculum produced somatosensory effects (67%), while the temporal evoked auditory (58%) semiology. The connectivity pattern was complex, with these structures having widespread ipsilateral and contralateral projections. The local connections between the opercular subregions and with the insula, as well as with more distant areas like the cingulate gyrus, were distinguished by strength and between-subjects consistency. In conclusion, we demonstrate specific opercular functionality, distinct from the one of the insular cortex. The study is complemented by a literature review on the opercular functional connectome in human and non-human primates.

Objective To perform a side-by-side comparison of two epileptogenicity biomarkers, high frequency oscillations (HFOs) and delayed responses (DRs), as a result of single-pulse electrical stimulation. Methods We have recorded stimulation-evoked HFOs and DRs in 16 epileptic patients undergoing presurgical evaluation using the stereoelectroencephalographic method. To evaluate converging and complementary information provided by the biomarkers, we analyzed them individually and for logical “and”/“or” combinations between them. 3D maps of the biomarkers’ distributions by recording location (inbound maps) and by stimulation location (outbound maps) were created to analyze their relationship with the epileptogenic structures. Results HFOs occur less frequently than DRs, by 18.7%, when counting by recording contacts, and more frequently, by 7.4%, when counting by stimulation contacts. 40.6% of the contacts exhibiting HFOs also exhibit DRs, and 44.1% of the contacts exhibiting DRs also exhibit HFOs. When combining biomarkers, there was a tradeoff between increased seizure onset zone (SOZ) sensitivity, from 21.3% to 73%, and decreased specificity, from 87.2% to 34.3%. Conclusions There is a moderate similarity in the information provided by the DRs and HFOs. Significance The biomarkers complement each other, but there is a tradeoff between different metrics for SOZ localization.

OBJECTIVE: To investigate functional coupling between brain networks using spectral changes induced by single-pulse electric stimulation (SPES).METHOD: We analyzed 20 patients with focal epilepsy, implanted with depth electrodes. SPES was applied to each pair of adjacent contacts, and responses were recorded from all other contacts. The mean response amplitude value was quantified in three time-periods after stimulation (10-60, 60-255, 255-500ms) for three frequency-ranges (Gamma, Ripples, Fast-Ripples), and compared to baseline. A total of 30,755 responses were analyzed, taking into consideration three dichotomous pairs: stimulating in primary sensory areas (S1-V1) vs. outside them, to test the interaction in physiologic networks; stimulating in seizure onset zone (SOZ) vs. non-SOZ, to test pathologic interactions; recording in default mode network (DMN) vs. non-DMN.RESULTS: Overall, we observed an early excitation (10-60ms) and a delayed inhibition (60-500ms). More specifically, in the delayed period, stimulation in S1-V1 produced a higher gamma-inhibition in the DMN, while stimulation in the SOZ induced a higher inhibition in the epilepsy-related higher frequencies (Ripples and Fast-Ripples).CONCLUSION: Physiologic and pathologic interactions can be assessed using spectral changes induced by SPES.SIGNIFICANCE: This is a promising method for connectivity studies in patients with drug-resistant focal epilepsy.

The cingulate cortex is part of the limbic system. Its function and connectivity are organized in a rostro-caudal and ventral-dorsal manner which was addressed by various other studies using rather coarse cortical parcellations. In this study, we aim at describing its function and connectivity using invasive recordings from patients explored for focal drug-resistant epilepsy. We included patients that underwent stereo-electroencephalographic recordings using intracranial electrodes in the University Emergency Hospital Bucharest between 2012 and 2019. We reviewed all high frequency stimulations (50 ​Hz) performed for functional mapping of the cingulate cortex. We used two methods to characterize brain connectivity. Effective connectivity was inferred based on the analysis of cortico-cortical potentials (CCEPs) evoked by single pulse electrical stimulation (SPES) (15 ​s inter-pulse interval). Functional connectivity was estimated using the non-linear regression method applied to 60 ​s spontaneous electrical brain signal intervals. The effective (stimulation-evoked) and functional (non-evoked) connectivity analyses highlight brain networks in a different way. While non-evoked connectivity evidences areas having related activity, often in close proximity to each other, evoked connectivity highlights spatially extended networks. To highlight in a comprehensive way the cingulate cortex’s network, we have performed a bi-modal connectivity analysis that combines the resting-state broadband h2 non-linear correlation with cortico-cortical evoked potentials. We co-registered the patient’s anatomy with the fsaverage FreeSurfer template to perform the automatic labeling based on HCP-MMP parcellation. At a group level, connectivity was estimated by averaging responses over stimulated/recorded or recorded sites in each pair of parcels. Finally, for multiple regions that evoked a clinical response during high frequency stimulation, we combined the connectivity of individual pairs using maximum intensity projection. Connectivity was assessed by applying SPES on 2094 contact pairs and recording CCEPs on 3580 contacts out of 8582 contacts of 660 electrodes implanted in 47 patients. Clinical responses elicited by high frequency stimulations in 107 sites (pairs of contacts) located in the cingulate cortex were divided in 10 groups: affective, motor behavior, motor elementary, versive, speech, vestibular, autonomic, somatosensory, visual and changes in body perception. Anterior cingulate cortex was shown to be connected to the mesial temporal, orbitofrontal and prefrontal cortex. In the middle cingulate cortex, we located affective, motor behavior in the anterior region, and elementary motor and somatosensory in the posterior part. This region is connected to the prefrontal, premotor and primary motor network. Finally, the posterior cingulate was shown to be connected with the visual areas, mesial and lateral parietal and temporal cortex.

Body awareness is the result of sensory integration in the posterior parietal cortex; however, other brain structures are part of this process. Our goal is to determine how the cingulate cortex is involved in the representation of our body. We retrospectively selected patients with drug‐resistant epilepsy, explored by stereo‐electroencephalography, that had the cingulate cortex sampled outside the epileptogenic zone. The clinical effects of high‐frequency electrical stimulation were reviewed and only those sites that elicited changes related to body perception were included. Connectivity of the cingulate cortex and other cortical structures was assessed using the h (2) coefficient, following a nonlinear regression analysis of the broadband EEG signal. Poststimulation changes in connectivity were compared between two sets of stimulations eliciting or not eliciting symptoms related to body awareness (interest and control groups). We included 17 stimulations from 12 patients that reported different types of body perception changes such as sensation of being pushed toward right/left/up, one limb becoming heavier/lighter, illusory sensation of movement, sensation of pressure, sensation of floating or detachment of one hemi‐body. High‐frequency stimulation in the cingulate cortex (1 anterior, 15 middle, 1 posterior part) elicits body perception changes, associated with a decreased connectivity of the dominant posterior insula and increased coupling between other structures, located particularly in the nondominant hemisphere.

In the context of the human brain, the term "connectivity" can refer to structural, functional or effective connectivity. Intracranial electrical stimulation is perhaps the most direct way of investigating the effective connectivity. We propose a method of mapping the effective connectivity, revealed by the electrical stimulation of brain structures, over the structural connectome (SC), obtained through diffusion spectrum imaging (DSI), to form a structural-effective connectome (SEC). A number of 24 patients with refractory epilepsy were implanted with depth electrodes for pre-surgical evaluation. Effective connectivity was assessed by analyzing the responses to single pulse electrical stimulation (SPES). Stimulation pulses having variable amplitude were applied to each pair of adjacent contacts and responses evoked by stimulation were recorded from other contacts located in other brain areas. Early responses (10-110 ms) on the stimulation-activated contacts located outside the epileptogenic zone were averaged for each patient, resulting in a patient-level physiological effective connectome (EC). The population level EC is computed by averaging the connections of the individual ECs, on a structure by structure basis. A fiber activation factor is used to weight the number of fibers connecting a pair of structures in the SC by its corresponding normalized EC value. The resulting number of effectively activated fibers describes the directional connection strength between two structures in the SEC. A physiological SEC comprising directional connections between 70 segmented brain areas in both hemispheres, was obtained by inclusion of structures outside the epileptogenic zone only. Over the entire structure set, the Spearman's correlation coefficient ρ between the number of fibers extracted from the DSI Atlas and the normalized RMS responses to SPES was ρ=0.21 (p0.001), while Kendall's tau coefficients ranged -0.52-0.44 (p0.05). The physiological structural-effective connectomics approach we have introduced can be applied for the creation of a whole-brain connectivity atlas that can be used as a reference tool for differential analysis of altered versus normal brain connectivity in epileptic patients.

Highlights • New method for stimulation artifact removal from cortico-cortical evoked potentials. • The method is based on electrical modeling of tissue-electrode interface. • It allows disambiguation of time-locked physiological responses and artifacts. • Method validation is based on synthetic and experimental data., Background Effective connectivity can be explored using direct electrical stimulations in patients suffering from drug-resistant focal epilepsies and investigated with intracranial electrodes. Responses to brief electrical pulses mimic the physiological propagation of signals and manifest as cortico-cortical evoked potentials (CCEP). The first CCEP component is believed to reflect direct connectivity with the stimulated region but the stimulation artifact, a sharp deflection occurring during a few milliseconds, frequently contaminates it. New method In order to recover the characteristics of early CCEP responses, we developed an artifact correction method based on electrical modeling of the electrode–tissue interface. The biophysically motivated artifact templates are then regressed out of the recorded data as in any classical template-matching removal artifact methods. Results Our approach is able to make the distinction between the physiological responses time-locked to the stimulation pulses and the non-physiological component. We tested the correction on simulated CCEP data in order to quantify its efficiency for different stimulation and recording parameters. We demonstrated the efficiency of the new correction method on simulations of single trial recordings for early responses contaminated with the stimulation artifact. The results highlight the importance of sampling frequency for an accurate analysis of CCEP. We then applied the approach to experimental data. Comparison with existing method The model-based template removal was compared to a correction based on the subtraction of the averaged artifact. Conclusions This new correction method of stimulation artifact will enable investigators to better analyze early CCEP components and infer direct effective connectivity in future CCEP studies.

Objectives Intracranial direct electrical stimulation (iDES) uses different parameters for mapping the epileptogenic and functional areas in patients with drug-resistant epilepsy. We aim at finding the common factor driving the electrographic responses to various iDES protocols reported in the literature. Methods We recorded early responses to single-pulse iDES in 11 subjects undergoing stereoelectroencephalographic presurgical evaluation. We systematically explored the role of several pulse parameters in evoking responses: monophasic versus biphasic pulses, current intensity, and pulse duration. We performed a correlation and regression analysis between responses to different protocols by amplitude, duration, and charge per phase. Results Regression analysis revealed that the responses were similar for the same charge per phase, regardless of their pulse duration and amplitude. Over eighty percent (82.8%) of the responses to variable pulse duration biphasic stimulation and between 58.6% and 81.9% of the responses to monophasic stimulation, depending on pulse polarity, were correlated to the responses evoked by the variable amplitude biphasic protocol, when expressing stimulus strength in terms of charge per phase. Conclusions Regardless of the combination of different stimulation currents, it is the underlying charge per phase parameter that determines the magnitude of the responses to single-pulse electrical stimulation. Significance Our results provide a unifying method for comparing iDES protocols.

Objective Epilepsy is characterized by transient alterations in brain synchronization resulting in seizures with a wide spectrum of manifestations. Seizure severity and risks for patients depend on the evolution and spread of the hypersynchronous discharges. With standard visual inspection and pattern classification, this evolution could not be predicted early on. It is still unclear to what degree the seizure onset zone determines seizure severity. Such information would improve our understanding of ictal epileptic activity and the existing electroencephalogram (EEG)-based warning and intervention systems, providing specific reactions to upcoming seizure types. We investigate the possibility of predicting the future development of an epileptic seizure during the first seconds of recordings after their electrographic onset. Methods Based on intracranial EEG recordings of 493 ictal events from 26 patients with focal epilepsy, a set of 25 time and frequency domain features was computed using nonoverlapping 1-second time windows, from the first 3, 5, and 10 seconds of ictal EEG. Three random forest classifiers were trained to predict the future evolution of the seizure, distinguishing between subclinical events, focal onset aware and impaired awareness, and focal to bilateral tonic-clonic seizures. Results Results show that early seizure type prediction is possible based on a single EEG channel located in the seizure onset zone with correct prediction rates of 76.2 ± 14.5% for distinguishing subclinical electrographic events from clinically manifest seizures, 75 ± 16.8% for distinguishing focal onset seizures that are or are not bilateral tonic-clonic, and 71.4 ± 17.2% for distinguishing between focal onset seizures with or without impaired awareness. All predictions are above the chance level (P Significance These findings provide the basis for developing systems for specific early warning of patients and health care providers, and for targeting EEG-based closed-loop intervention approaches to electrographic patterns with a high inherent risk to become clinically manifest.

Objectives By analyzing the responses to intracranial electrical stimulation we aim at im-proving the localization of the seizure onset zone (SOZ) and the connectivity between different areas. Methods Our center uses a set of traditional and innovative advanced analysis methods for stereo-EEG signals recorded using depth electrodes. We analyze stimulation-evoked activity in time-frequency domain to detect inter-ictal epileptogenicity biomarkers like high-frequency oscillations (HFO, f > 80 Hz) and delayed responses (DR, t > 100 ms). Results of the different quantitative EEG analyses are represented as 3-D maps superimposed with patient’s anatomy, as visible on various imaging modalities, and their evolution in time is shown as movies. Cortico-cortical evoked potentials (CCEP) based on early responses (t = 10–110 ms) to single-pulse intracranial stimulation are used to calculate functional connectivity between cortical areas. Results Biomarker response maps and effective connectomes were calculated in a population of 24 patients undergoing presurgical evaluation for drug-resistant epilepsy. The sensitivity with respect to SOZ of HFOs was higher than the one of the DR by both response and stimulation location, whereas the specificity of the DRs was higher by the lo-cation of the stimulation. Discussion Despite variable sensitivity and specificity of the biomarkers, the positive pre-diction level of these biomarkers is less than 30%, taken separately or in combination. Conclusions Analysis of responses to intracranial electrical stimulation can contribute to the identification of the epileptogenic networks and for delineating the epileptogenic are-as. Significance We illustrate the value of using multiple advanced signal analysis techniques.

Objective To investigate how often discharge propagation occurs within the spikes recorded in patients evaluated for epilepsy surgery, and to assess its impact on the accuracy of source imaging. Methods Data were analyzed from 50 consecutive patients who had presurgical workup. Discharge propagation was analyzed using sequential voltage-maps of the averaged spikes, and principal components analysis. When propagation was detected, sources were modeled both at onset and peak. Results Propagation occurred in half of the patients. The median time of propagation between onset and peak was 17 ms. In 60% of the cases with propagation (15/25 patients) this remained in the same sub-lobar area where onset occurred. The accuracy of source imaging in cases of propagating spikes was 67% when only analyzing onset or peak. This was lower as compared to cases without propagation (79%). Combining source imaging at onset and at peak increased the accuracy to 83% for the propagating spikes. Conclusions Propagation occurs often in patients with focal epilepsy, evaluated for surgery. In 40% of the propagating cases, the source of onset and peak were in different sub-lobar regions. Significance For optimal clinical utility, sources should be modeled both at onset and at peak epochs of the spikes.

Pre-surgical assessment and surgical management of frontal epilepsy with normal MRI is often challenging. We present a case of a 33-year-old, right-handed, educated male. During childhood, his seizures presented with mandibular myoclonus and no particular trigger. As a young adult, he developed seizures with a startle component, triggered by unexpected noises. During his ictal episodes, he felt fear and grimaced with sudden head flexion and tonic axial posturing. Similar seizures also occurred without startle. Neuropsychological assessment showed executive dysfunction and verbal memory deficit. The cerebral MRI was normal. Electro-clinical reasoning, investigations performed, the results obtained and follow-up are discussed in detail. [Published with video sequence].

Epileptic seizures are characterized by a rich dynamic spectrum consisting of excessive, abnormal and synchronized firing of neuron ensembles. Such abnormal firing has been quantitatively characterized via power laws in neural avalanches. The term “neural avalanche” has been used to illustrate the excessively amplified neural firing patterns that lead to epileptic seizures. The pattern of amplified firing in neural avalanches betrays a modular signature in the spread of activation across cortical minicolumns. According to this modular approach of epilepsy, the excessive amplification of neural firing in a cortical minicolumn results from a defect within the “inhibitory curtain” surrounding the pyramidal cells. The functional basis of this approach provides insights into potential clinical interventions.

Objective To investigate default-mode network (DMN) deactivation in different types of focal epilepsy by single pulse electric stimulation (SPES). Method We analyzed 18 patients with focal epilepsy (8 frontal, 8 temporal, 2 posterior), implanted with depth electrodes. SPES was applied to each pair of adjacent contacts in seiwure onset zone (SOZ), and responses were recorded from the 10 different DMN-hubs; The responses to SPES in Gamma, Ripple (R) and Fast-Ripple (FR) bands were quantified in a 60–250 ms time-window following each stimulation pulse and compared to baseline. Time of propagation was determined based on N1 latency. These responses were compared across the three epilepsy types. Results Overall, we observed a significant deactivation of the DMN in the upper frequency ranges for all epilepsies (75% drop from baseline for gamma and 93% for R and FR). In the gamma band, the stimulation of frontal SOZs deactivated the ipsilateral posterior cingulate and precuneus significantly more than in the other epilepsy-types, with shorter general latencies of 22, 25 and 23 ms, respectively. Discussion Our results might explain why in prefrontal focal epilepsies and in generalized epilepsies, thought to have a frontal generator, the consciousness is preferentially and significantly impaired. Significance This is a promising method for quantifying the engagement of the consciousness processing areas by the epileptic focus. Detailed illustrations and tables for all 10 DMN-hubs, in all 3 high-frequency bands are provided.