Simultaneous invasive and non-invasive recordings in humans: a novel Rosetta stone for deciphering brain activity.

Simultaneous noninvasive and invasive electrophysiological recordings provide a unique opportunity to achieve a comprehensive understanding of human brain activity, much like a Rosetta stone for human neuroscience. In this review we focus on the increasingly-used powerful combination of intracranial electroencephalography (iEEG) with scalp electroencephalography (EEG) or magnetoencephalography (MEG). We first provide practical insight on how to achieve these technically challenging recordings. We then provide examples from clinical research on how simultaneous recordings are advancing our understanding of epilepsy. This is followed by the illustration of how human neuroscience and methodological advances could benefit from these simultaneous recordings. We conclude with a call for open data sharing and collaboration, while ensuring neuroethical approaches and argue that only with a true collaborative approach the promises of simultaneous recordings will be fulfilled.

Identification of Early Hippocampal Dynamics during Recognition Memory with Independent Component Analysis.

The hippocampus is generally considered to have relatively late involvement in recognition memory, its main electrophysiological signature being between 400 and 800 ms after stimulus onset. However, most electrophysiological studies have analyzed the hippocampus as a single responsive area, selecting only a single-site signal exhibiting the strongest effect in terms of amplitude. These classical approaches may not capture all the dynamics of this structure, hindering the contribution of other hippocampal sources that are not located in the vicinity of the selected site. We combined intracerebral electroencephalogram recordings from epileptic patients with independent component analysis during a recognition memory task involving the recognition of old and new images. We identified two sources with different responses emerging from the hippocampus: a fast one (maximal amplitude at ∼250 ms) that could not be directly identified from raw recordings and a latter one, peaking at ∼400 ms. The former component presented different amplitudes between old and new items in 6 out of 10 patients. The latter component had different delays for each condition, with a faster activation (∼290 ms after stimulus onset) for recognized items. We hypothesize that both sources represent two steps of hippocampal recognition memory, the faster reflecting the input from other structures and the latter the hippocampal internal processing. Recognized images evoking early activations would facilitate neural computation in the hippocampus, accelerating memory retrieval of complementary information. Overall, our results suggest that the hippocampal activity is composed of several sources with an early activation related to recognition memory.

Towards an electroencephalographic measure of awareness based on the reactivity of oscillatory macrostates to hearing a subject's own name.

We proposed that the brain's electrical activity is composed of a sequence of alternating states with repeating topographic spectral distributions on scalp electroencephalogram (EEG), referred to as oscillatory macrostates. The macrostate showing the largest decrease in the probability of occurrence, measured as a percentage (reactivity), during sensory stimulation was labelled as the default EEG macrostate (DEM). This study aimed to assess the influence of awareness on DEM reactivity (DER). We included 11 middle cerebral artery ischaemic stroke patients with impaired awareness having a median Glasgow Coma Scale (GCS) of 6/15 and a group of 11 matched healthy controls. EEG recordings were carried out during auditory 1 min stimulation epochs repeating either the subject's own name (SON) or the SON in reverse (rSON). The DEM was identified across three SON epochs alternating with three rSON epochs. Compared with the patients, the DEM of controls contained more posterior theta activity reflecting source dipoles that could be mapped in the posterior cingulate cortex. The DER was measured from the 1 min quiet baseline preceding each stimulation epoch. The difference in mean DER between the SON and rSON epochs was measured by the salient EEG reactivity (SER) theoretically ranging from -100% to 100%. The SER was 12.4 ± 2.7% (Mean ± standard error of the mean) in controls and only 1.3 ± 1.9% in the patient group (P < 0.01). The patient SER decreased with the Glasgow Coma Scale. Our data suggest that awareness increases DER to SON as measured by SER.

Functional Enhancement and Characterization of an Electrophysiological Mapping Electrode Probe with Carbonic, Directional Macrocontacts.

Electrophysiological mapping (EM) using acute electrode probes is a common procedure performed during functional neurosurgery. Due to their constructive specificities, the EM probes are lagging in innovative enhancements. This work addressed complementing a clinically employed EM probe with carbonic and circumferentially segmented macrocontacts that are operable both for neurophysiological sensing ("recording") of local field potentials (LFP) and for test stimulation. This paper illustrates in-depth the development that is based on the direct writing of functional materials. The unconventional fabrication processes were optimized on planar geometry and then transferred to the cylindrically thin probe body. We report and discuss the constructive concept and architecture of the probe, characteristics of the electrochemical interface deduced from voltammetry and chronopotentiometry, and the results of in vitro and in vivo recording and pulse stimulation tests. Two- and three-directional macrocontacts were added on probes having shanks of 550 and 770 µm diameters and 10-23 cm lengths. The graphitic material presents a ~2.7 V wide, almost symmetric water electrolysis window, and an ultra-capacitive charge transfer. When tested with clinically relevant 150 µs biphasic current pulses, the interfacial polarization stayed safely away from the water window for pulse amplitudes up to 9 mA (135 µC/cm2). The in vivo experiments on adult rat models confirmed the high-quality sensing of LFPs. Additionally, the in vivo-prevailing increase in the electrode impedance and overpotential are discussed and modeled by an ionic mobility-reducing spongiform structure; this restricted diffusion model gives new applicative insight into the in vivo-uprisen stimulation overpotential.

Organization of the epileptogenic zone and signal analysis at seizure onset in patients with drug-resistant epilepsy due to focal cortical dysplasia with mTOR pathway gene mutations-An SEEG study.

Epilepsy surgery in genetic drug-resistant epilepsy is a debated subject as more histological and molecular data are available. We retrospectively collected data from focal drug-resistant epilepsy patients that underwent stereoelectroencephalography (SEEG) invasive recordings. Patients with nonlesional brain imaging or in whom a first epilepsy surgery failed to control seizures were selected. We computed and displayed the intracranial ictal onset activity pattern on structural imaging. Patients underwent epilepsy gene panel testing, next generation sequencing-NGS. Of 113 patients, 13 underwent genetic testing, and in 6 patients, a mechanistic target of rapamycin pathway gene germline mutation (mTOR) was identified. Brain imaging was nonlesional except for one patient in whom two abnormalities suggestive of focal cortical dysplasia (FCD) were found. Patients underwent tailored brain surgery based on SEEG data, tissue analysis revealed FCD and postsurgical outcome was favorable. Our findings are similar to previous case series suggesting that epilepsy surgery can be a treatment option in patients with mTOR pathway mutation. In patients with mTOR pathway mutation, the postsurgical outcome is favorable if complete resection of the epileptogenic zone is performed. Electrophysiological seizure onset patterns in FCDs associated with mTOR pathway mutations display low-voltage fast activity as previously described.

Studying memory processes at different levels with simultaneous depth and surface EEG recordings.

Investigating cognitive brain functions using non-invasive electrophysiology can be challenging due to the particularities of the task-related EEG activity, the depth of the activated brain areas, and the extent of the networks involved. Stereoelectroencephalographic (SEEG) investigations in patients with drug-resistant epilepsy offer an extraordinary opportunity to validate information derived from non-invasive recordings at macro-scales. The SEEG approach can provide brain activity with high spatial specificity during tasks that target specific cognitive processes (e.g., memory). Full validation is possible only when performing simultaneous scalp SEEG recordings, which allows recording signals in the exact same brain state. This is the approach we have taken in 12 subjects performing a visual memory task that requires the recognition of previously viewed objects. The intracranial signals on 965 contact pairs have been compared to 391 simultaneously recorded scalp signals at a regional and whole-brain level, using multivariate pattern analysis. The results show that the task conditions are best captured by intracranial sensors, despite the limited spatial coverage of SEEG electrodes, compared to the whole-brain non-invasive recordings. Applying beamformer source reconstruction or independent component analysis does not result in an improvement of the multivariate task decoding performance using surface sensor data. By analyzing a joint scalp and SEEG dataset, we investigated whether the two types of signals carry complementary information that might improve the machine-learning classifier performance. This joint analysis revealed that the results are driven by the modality exhibiting best individual performance, namely SEEG.

Musicogenic seizures in temporal lobe epilepsy: Case reports based on ictal source localization analysis.

Musicogenic epilepsy is a rare form of reflex epilepsy in which seizures are provoked by music. Different musicogenic stimuli have been identified: pleasant/unpleasant music or specific musical patterns. Several etiologies have been uncovered, such as focal cortical dysplasia, autoimmune encephalitis, tumors, or unspecific gliosis. In this article, we report two patients with musicogenic seizures. The first patient was diagnosed with structural temporal lobe epilepsy. Her seizures were elicited by music that she liked. Interictal and ictal video-electroencephalography (video-EEG) and signal analysis using independent component analysis revealed the right temporal lobe seizure onset extending over the neocortical regions. The patient underwent right temporal lobectomy (including the amygdala, the head, and the body of the hippocampus) and faced an Engel IA outcome 3 years post-surgery. The second patient was diagnosed with autoimmune temporal lobe epilepsy (GAD-65 antibodies). Her seizures were triggered by contemporary hit radio songs without any personal emotional significance. Interictal and ictal video-electroencephalography (video-EEG) and independent component analysis highlighted the left temporal lobe seizure onset extending over the neocortical regions. Intravenous immunoglobulin therapy was initiated, and the patient became seizure-free at 1 year. In conclusion, musicogenic seizures may be elicited by various auditory stimuli, the presence or absence of an emotional component offering an additional clue for the underlying network pathophysiology. Furthermore, in such cases, the use of independent component analysis of the scalp EEG signals proves useful in revealing the location of the seizure generator, and our findings point toward the temporal lobe, both mesial and neocortical regions.

Cingulate Cortex: Anatomy, Structural and Functional Connectivity.

SUMMARY: The cingulate cortex is a paired brain region located on the medial wall of each hemisphere. This review explores the anatomy as well as the structural and functional connectivity of the cingulate cortex underlying essential roles this region plays in emotion, autonomic, cognitive, motor control, visual-spatial processing, and memory.

A comparison of uni- and multi-variate methods for identifying brain networks activated by cognitive tasks using intracranial EEG.

Cognitive tasks are commonly used to identify brain networks involved in the underlying cognitive process. However, inferring the brain networks from intracranial EEG data presents several challenges related to the sparse spatial sampling of the brain and the high variability of the EEG trace due to concurrent brain processes. In this manuscript, we use a well-known facial emotion recognition task to compare three different ways of analyzing the contrasts between task conditions: permutation cluster tests, machine learning (ML) classifiers, and a searchlight implementation of multivariate pattern analysis (MVPA) for intracranial sparse data recorded from 13 patients undergoing presurgical evaluation for drug-resistant epilepsy. Using all three methods, we aim at highlighting the brain structures with significant contrast between conditions. In the absence of ground truth, we use the scientific literature to validate our results. The comparison of the three methods' results shows moderate agreement, measured by the Jaccard coefficient, between the permutation cluster tests and the machine learning [0.33 and 0.52 for the left (LH) and right (RH) hemispheres], and 0.44 and 0.37 for the LH and RH between the permutation cluster tests and MVPA. The agreement between ML and MVPA is higher: 0.65 for the LH and 0.62 for the RH. To put these results in context, we performed a brief review of the literature and we discuss how each brain structure's involvement in the facial emotion recognition task.

Motor and emotional facial features in parietal lobe seizures: an ictal functional connectivity study using SEEG

Objectives: Parietal lobe epilepsy is one of the rarest types and patients with this form of epilepsy report multiple subjective symptoms during ictal manifestation. Specific facial coupling of emotion and motor symptoms may take various forms, such as pouting and disgust or smiling. We aimed to highlight brain structures and the network involved during ictal grimacing in parietal lobe seizures. Methods: In this study, we report two patients with drug-resistant epilepsy, with seizure onset located in the inferior parietal lobule and a semiology characterized by ictal grimacing. Patients were explored with intracranial electrodes using the stereo-electroencephalographic method. Time-frequency and functional connectivity (a non-linear regression method based on the h² correlation coefficient) signal analyses were performed time-locked to ictal grimace. For both patients, using spectral analysis, we were able to confirm that the bipolar channels, localized at the level of the inferior parietal lobule, were involved in the seizure onset zone, exhibiting a high frequency discharge. Results: The first patient presented with ictal pouting and disgust and the second with smiling/laughter. Connectivity analysis highlighted two different networks responsible for seizure semiology, consisting of grimacing with different emotional expression. The inferior parietal lobule, connected mainly to the anterior insula, dorsal-lateral prefrontal cortex and frontal operculum were responsible for the typical grimace associated with disgust. Furthermore, the inferior parietal lobule, basal temporal structures, superior temporal gyrus, orbitofrontal cortex and temporal pole were involved in smiling and laughter. Significance: It is of great significance for epileptologists to know that the same seizure onset zone in the inferior parietal lobule can generate contrasting facial expressions, smiling/laughter and pouting/disgust, by engaging different epileptogenic networks; the temporo-basal-orbitofrontal and insulo-opercular networks, respectively.

Magnetoencephalography can reveal deep brain network activities linked to memory processes.

Recording from deep neural structures such as hippocampus noninvasively and yet with high temporal resolution remains a major challenge for human neuroscience. Although it has been proposed that deep neuronal activity might be recordable during cognitive tasks using magnetoencephalography (MEG), this remains to be demonstrated as the contribution of deep structures to MEG recordings may be too small to be detected or might be eclipsed by the activity of large-scale neocortical networks. In the present study, we disentangled mesial activity and large-scale networks from the MEG signals thanks to blind source separation (BSS). We then validated the MEG BSS components using intracerebral EEG signals recorded simultaneously in patients during their presurgical evaluation of epilepsy. In the MEG signals obtained during a memory task involving the recognition of old and new images, we identified with BSS a putative mesial component, which was present in all patients and all control subjects. The time course of the component selectively correlated with stereo-electroencephalography signals recorded from hippocampus and rhinal cortex, thus confirming its mesial origin. This finding complements previous studies with epileptic activity and opens new possibilities for using MEG to study deep brain structures in cognition and in brain disorders.

A method to assess the default EEG macrostate and its reactivity to stimulation.

OBJECTIVE: The default mode network (DMN) is deactivated by stimulation. We aimed to assess the DMN reactivity impairment by routine EEG recordings in stroke patients with impaired consciousness. METHODS: Binocular light flashes were delivered at 1 Hz in 1-minute epochs, following a 1-minute baseline (PRE). The EEG was decomposed in a series of binary oscillatory macrostates by topographic spectral clustering. The most deactivated macrostate was labeled the default EEG macrostate (DEM). Its reactivity (DER) was quantified as the decrease in DEM occurrence probability during stimulation. A normalized DER index (DERI) was calculated as DER/PRE. The measures were compared between 14 healthy controls and 32 comatose patients under EEG monitoring following an acute stroke. RESULTS: The DEM was mapped to the posterior DMN hubs. In the patients, these DEM source dipoles were 3-4 times less frequent and were associated with an increased theta activity. Even in a reduced 6-channel montage, a DER below 6.26% corresponding to a DERI below 0.25 could discriminate the patients with sensitivity and specificity well above 80%. CONCLUSION: The method detected the DMN impairment in post-stroke coma patients. SIGNIFICANCE: The DEM and its reactivity to stimulation could be useful to monitor the DMN function at bedside.

Imaging the effective networks associated with cortical function through intracranial high-frequency stimulation.

Direct electrical stimulation (DES) is considered to be the gold standard for mapping cortical function. A careful mapping of the eloquent cortex is key to successful resective or ablative surgeries, with a minimal postoperative deficit, for treatment of drug-resistant epilepsy. There is accumulating evidence suggesting that not only local, but also remote activations play an equally important role in evoking clinical effects. By introducing a new intracranial stimulation paradigm and signal analysis methodology allowing to disambiguate EEG responses from stimulation artifacts we highlight the spatial extent of the networks associated with clinical effects. Our study includes 26 patients that underwent stereoelectroencephalographic investigations for drug-resistant epilepsy, having 337 depth electrodes with 4,351 contacts sampling most brain structures. The routine high-frequency electrical stimulation protocol for eloquent cortex mapping was altered in a subtle way, by alternating the polarity of the biphasic pulses in a train, causing the splitting the spectral lines of the artifactual components, exposing the underlying tissue response. By performing a frequency-domain analysis of the EEG responses during DES we were able to capture remote activations and highlight the effect's network. By using standard intersubject averaging and a fine granularity HCP-MMP parcellation, we were able to create local and distant connectivity maps for 614 stimulations evoking specific clinical effects. The clinical value of such maps is not only for a better understanding of the extent of the effects' networks guiding the invasive exploration, but also for understanding the spatial patterns of seizure propagation given the timeline of the seizure semiology.

Network of autoscopic hallucinations elicited by intracerebral stimulations of periventricular nodular heterotopia: An SEEG study.

Periventricular nodular heterotopias (PVNH) are areas of neurons abnormally located in the white matter that might be involved in physiological cortical functions. Autoscopic hallucinations are changes in self-consciousness determined by a mismatch in integration of multiple sensory inputs. Our goal is to highlight the brain network involved in generation of autoscopic hallucination elicited by electrical stimulation of a PVNH in a drug resistant epilepsy patient. Our patient was explored using stereo-electroencephalography with electrodes covering the right posterior temporal PVNH and the adjacent cortex. Direct electrical high frequency stimulation of the PVNH elicited autoscopic hallucinations mainly involving the face and upper trunk. We then used multiple modalities to determine brain connectivity: single pulse electrical stimulation of the PVNH and stimulation-evoked potentials were used to highlight resting state effective connectivity. High-frequency stimulation using alternating polarity pulses enabled us to identify the network involved, time-locked to the clinical effect and to map symptom-related effective connectivity. Functional connectivity using a non-linear regression method was used to determine dependencies between different cortical regions following the stimulation. Finally, structural connectivity was highlighted using deterministic fiber tracking. Multi-modal connectivity analysis identified a network involving the PVNH, occipital and temporal neocortex, fusiform gyrus and parietal cortex.

Extracting seizure onset from surface EEG with independent component analysis: Insights from simultaneous scalp and intracerebral EEG.

The success of stereoelectroencephalographic (SEEG) investigations depends crucially on the hypotheses on the putative location of the seizure onset zone. This information is derived from non-invasive data either based on visual analysis or advanced source localization algorithms. While source localization applied to interictal spikes recorded on scalp is the classical method, it does not provide unequivocal information regarding the seizure onset zone. Raw ictal activity contains a mixture of signals originating from several regions of the brain as well as EMG artifacts, hampering direct input to the source localization algorithms. We therefore introduce a methodology that disentangles the various sources contributing to the scalp ictal activity using independent component analysis and uses equivalent current dipole localization as putative locus of ictal sources. We validated the results of our analysis pipeline by performing long-term simultaneous scalp - intracerebral (SEEG) recordings in 14 patients and analyzing the wavelet coherence between the independent component encoding the ictal discharge and the SEEG signals in 8 patients passing the inclusion criteria. Our results show that invasively recorded ictal onset patterns, including low-voltage fast activity, can be captured by the independent component analysis of scalp EEG. The visibility of the ictal activity strongly depends on the depth of the sources. The equivalent current dipole localization can point to the seizure onset zone (SOZ) with an accuracy that can be as high as 10 mm for superficially located sources, that gradually decreases for deeper seizure generators, averaging at 47 mm in the 8 analyzed patients. Independent component analysis is therefore shown to have a promising SOZ localizing value, indicating whether the seizure onset zone is neocortical, and its approximate location, or located in mesial structures. That may contribute to a better crafting of the hypotheses used as basis of the stereo-EEG implantations.

Accuracy and Safety of Customized Stereotactic Fixtures for Stereoelectroencephalography in Pediatric Patients.

Stereoelectroencephalography (SEEG) in children with intractable epilepsy presents particular challenges. Their thin and partially ossified cranium, specifically in the temporal area, is prone to fracture while attaching stereotactic systems to the head or stabilizing the head in robot's field of action. Postponing SEEG in this special population of patients can have serious consequences, reducing their chances of becoming seizure-free and impacting their social and cognitive development. This study demonstrates the safety and accuracy offered by a frameless personalized 3D printed stereotactic implantation system for SEEG investigations in children under 4 years of age. SEEG was carried out in a 3-year-old patient with drug-resistant focal epilepsy, based on a right temporal-perisylvian epileptogenic zone hypothesis. Fifteen intracerebral electrodes were placed using a StarFix patient-customized stereotactic fixture. The median lateral entry point localization error of the electrodes was 0.90 mm, median lateral target point localization error was 1.86 mm, median target depth error was 0.83 mm, and median target point localization error was 1.96 mm. There were no perioperative complications. SEEG data led to a tailored right temporal-insular-opercular resection, with resulting seizure freedom (Engel IA). In conclusion, patient-customized stereotactic fixtures are a safe and accurate option for SEEG exploration in young children.

Cingulate cortex function and multi-modal connectivity mapped using intracranial stimulation.

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 â€‹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 â€‹s inter-pulse interval). Functional connectivity was estimated using the non-linear regression method applied to 60 â€‹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.

Unsupervised Detection of High-Frequency Oscillations Using Time-Frequency Maps and Computer Vision.

High-frequency oscillations >80 Hz (HFOs) have unique features distinguishing them from spikes and artifactual components that can be well-evidenced in the time-frequency representations. We introduce an unsupervised HFO detector that uses computer-vision algorithms to detect HFO landmarks on two-dimensional (2D) time-frequency maps. To validate the detector, we introduce an analytical model of the HFO based on a sinewave having a Gaussian envelope, for which analytical equations in time-frequency space can be derived, allowing us to establish a direct correspondence between common HFO detection criteria in the time domain with the ones in the frequency domain, used by the computer-vision detection algorithm. The detector identifies potential HFO events on the time-frequency representation, which are classified as true HFOs if criteria regarding the HFO's frequency, amplitude, and duration are met. The detector is validated on simulated HFOs according to the analytical model, in the presence of noise, with different signal-to-noise ratios (SNRs) ranging from -9 to 0 dB. The detector's sensitivity was 0.64 at an SNR of -9 dB, 0.98 at -6 dB, and >0.99 at -3 dB and 0 dB, while its positive prediction value was >0.95, regardless of the SNR. Using the same simulation dataset, our detector is benchmarked against four previously published HFO detectors. The F-measure, a combined metric that takes into account both sensitivity and positive prediction value, was used to compare detection algorithms. Our detector surpassed the other detectors at -6, -3, and 0 dB and had the second best F-score at -9 dB SNR after the MNI detector (0.77 vs. 0.83). The ability to detect HFOs in clinical recordings has been tested on a set of 36 intracranial electroencephalogram (EEG) channels in six patients, with 89% of the detections being validated by two independent reviewers. The results demonstrate that the unsupervised detection of HFOs based on their 2D features in time-frequency maps is feasible and has a performance comparable or better than the most used HFO detectors.

Sleep modulates effective connectivity: A study using intracranial stimulation and recording.

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.

Illusory own body perceptions mapped in the cingulate cortex-An intracranial stimulation study.

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 h2 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.