Dimensionality and Ramping: Signatures of Sentence Integration in the Dynamics of Brains and Deep Language Models.

A sentence is more than the sum of its words: its meaning depends on how they combine with one another. The brain mechanisms underlying such semantic composition remain poorly understood. To shed light on the neural vector code underlying semantic composition, we introduce two hypotheses: (1) the intrinsic dimensionality of the space of neural representations should increase as a sentence unfolds, paralleling the growing complexity of its semantic representation; and (2) this progressive integration should be reflected in ramping and sentence-final signals. To test these predictions, we designed a dataset of closely matched normal and jabberwocky sentences (composed of meaningless pseudo words) and displayed them to deep language models and to 11 human participants (5 men and 6 women) monitored with simultaneous MEG and intracranial EEG. In both deep language models and electrophysiological data, we found that representational dimensionality was higher for meaningful sentences than jabberwocky. Furthermore, multivariate decoding of normal versus jabberwocky confirmed three dynamic patterns: (1) a phasic pattern following each word, peaking in temporal and parietal areas; (2) a ramping pattern, characteristic of bilateral inferior and middle frontal gyri; and (3) a sentence-final pattern in left superior frontal gyrus and right orbitofrontal cortex. These results provide a first glimpse into the neural geometry of semantic integration and constrain the search for a neural code of linguistic composition.SIGNIFICANCE STATEMENT Starting from general linguistic concepts, we make two sets of predictions in neural signals evoked by reading multiword sentences. First, the intrinsic dimensionality of the representation should grow with additional meaningful words. Second, the neural dynamics should exhibit signatures of encoding, maintaining, and resolving semantic composition. We successfully validated these hypotheses in deep neural language models, artificial neural networks trained on text and performing very well on many natural language processing tasks. Then, using a unique combination of MEG and intracranial electrodes, we recorded high-resolution brain data from human participants while they read a controlled set of sentences. Time-resolved dimensionality analysis showed increasing dimensionality with meaning, and multivariate decoding allowed us to isolate the three dynamical patterns we had hypothesized.

Modification of brain conductivity in human focal epilepsy: A model-based estimation from stereoelectroencephalography.

OBJECTIVE: We have developed a novel method for estimating brain tissue electrical conductivity using low-intensity pulse stereoelectroencephalography (SEEG) stimulation coupled with biophysical modeling. We evaluated the hypothesis that brain conductivity is correlated with the degree of epileptogenicity in patients with drug-resistant focal epilepsy. METHODS: We used bipolar low-intensity biphasic pulse stimulation (.2 mA) followed by a postprocessing pipeline for estimating brain conductivity. This processing is based on biophysical modeling of the electrical potential induced in brain tissue between the stimulated contacts in response to pulse stimulation. We estimated the degree of epileptogenicity using a semi-automatic method quantifying the dynamic of fast discharge at seizure onset: the epileptogenicity index (EI). We also investigated how the location of stimulation within specific anatomical brain regions or within lesional tissue impacts brain conductivity. RESULTS: We performed 1034 stimulations of 511 bipolar channels in 16 patients. We found that brain conductivity was lower in the epileptogenic zone (EZ; unpaired median difference = .064, p < .001) and inversely correlated with the epileptogenic index value (p < .001, Spearman rho = -.32). Conductivity values were also influenced by anatomical site, location within lesion, and delay between SEEG electrode implantation and stimulation, and had significant interpatient variability. Mixed model multivariate analysis showed that conductivity is significantly associated with EI (F = 13.45, p < .001), anatomical regions (F = 5.586, p < .001), delay since implantation (F = 14.71, p = .003), and age at SEEG (F = 6.591, p = .027), but not with the type of lesion (F = .372, p = .773) or the delay since last seizure (F = 1.592, p = .235). SIGNIFICANCE: We provide a novel model-based method for estimating brain conductivity from SEEG low-intensity pulse stimulations. The brain tissue conductivity is lower in EZ as compared to non-EZ. Conductivity also varies significantly across anatomical brain regions. Involved pathophysiological processes may include changes in the extracellular space (especially volume or tortuosity) in epileptic tissue.

Stereo-EEG-based ictal functional connectivity in patients with periventricular nodular heterotopia-related epilepsy.

Nodular heterotopia (NH)-related drug-resistant epilepsy is challenging due to the deep location of the NH and the complexity of the underlying epileptogenic network. Using ictal stereo-electroencephalography (SEEG) and functional connectivity (FC) analyses in 14 patients with NH-related drug-resistant epilepsy, we aimed to determine the leading structure during seizures. For this purpose, we compared node IN and OUT strength between bipolar channels inside the heterotopia and inside gray matter, at the group level and at the individual level. At seizure onset, the channels within NH belonging to the epileptogenic and/or propagation network showed higher node OUT-strength than the channels within the gray matter (p = .03), with higher node OUT-strength than node IN-strength (p = .03). These results are in favor of a "leading" role of NH during seizure onset when involved in the epileptogenic- or propagation-zone network (50% of patients). However, when looking at the individual level, no significant difference between NH and gray matter was found, except for one patient (in two of three seizures). This result confirms the heterogeneity and the complexity of the epileptogenic network organization in NH and the need for SEEG exploration to characterize more precisely patient-specific epileptogenic network organization.

Permutation entropy-derived parameters to estimate the epileptogenic zone network.

OBJECTIVE: Quantification of the epileptogenic zone network (EZN) most frequently implies analysis of seizure onset. However, important information can also be obtained from the postictal period, characterized by prominent changes in the EZN. We used permutation entropy (PE), a measure of signal complexity, to analyze the peri-ictal stereoelectroencephalography (SEEG) signal changes with emphasis on the postictal state. We sought to determine the best PE-derived parameter (PEDP) for identifying the EZN. METHODS: Several PEDPs were computed retrospectively on SEEG-recorded seizures of 86 patients operated on for drug-resistant epilepsy: mean baseline preictal entropy, minimum ictal entropy, maximum postictal entropy, the ratio between the maximum postictal and the minimum ictal entropy, and the ratio between the maximum postictal and the baseline preictal entropy. The performance of each biomarker was assessed by comparing the identified epileptogenic contacts or brain regions against the EZN defined by clinical analysis incorporating the Epileptogenicity Index and the connectivity epileptogenicity index methods (EZNc), using the receiver-operating characteristic and precision-recall. RESULTS: The ratio between the maximum postictal and the minimum ictal entropy (defined as the Permutation Entropy Index [PEI]) proved to be the best-performing PEDP to identify the EZNC . It demonstrated the highest area under the curve (AUC) and F1 score at the contact level (AUC 0.72; F1 0.39) and at the region level (AUC 0.78; F1 0.47). PEI values gradually decreased between the EZN, the propagation network, and the non-involved regions. PEI showed higher performance in patients with slow seizure-onset patterns than in those with fast seizure-onset patterns. The percentage of resected epileptogenic regions defined by PEI was significantly correlated with surgical outcome. SIGNIFICANCE: PEI is a promising tool to improve the delineation of the EZN. PEI combines ease and robustness in a routine clinical setting with high sensitivity for seizures without fast activity at seizure onset.

Psychiatric complications following SEEG-guided radiofrequency thermocoagulations in patients with drug-resistant epilepsy.

SEEG-guided radiofrequency thermocoagulation (RF-TC) in the epileptogenic regions is a therapeutic option for patients with drug-resistant focal epilepsy who may have or not indication for epilepsy surgery. The most common adverse events of RF-TC are seizures, headaches, somatic pain, and sensory-motor deficits. If RF-TC could lead to psychiatric complications is unknown. In the present study, seven out of 164 patients (4.2 %) experienced psychiatric decompensation with or without memory deterioration after RF-TC of bilateral or unilateral amygdala and hippocampus. The appearance of symptoms was either acute, subacute, or chronic and the symptoms were either transient or lasted for several months. Common features among these patients were female sex, mesial temporal epilepsy, and a pre-existing history of psychological distress and memory dysfunction. Our study highlights the possibility of neuropsychiatric deterioration in specific patients following SEEG-guided RF-TC, despite its rarity.

Comparison of beamformer and ICA for dynamic connectivity analysis: A simultaneous MEG-SEEG study.

Magnetoencephalography (MEG) is a powerful tool for estimating brain connectivity with both good spatial and temporal resolution. It is particularly helpful in epilepsy to characterize non-invasively the epileptic networks. However, using MEG to map brain networks requires solving a difficult inverse problem that introduces uncertainty in the activity localization and connectivity measures. Our goal here was to compare independent component analysis (ICA) followed by dipole source localization and the linearly constrained minimum-variance beamformer (LCMV-BF) for characterizing regions with interictal epileptic activity and their dynamic connectivity. After a simulation study, we compared ICA and LCMV-BF results with intracerebral EEG (stereotaxic EEG, SEEG) recorded simultaneously in 8 epileptic patients, which provide a unique 'ground truth' to which non-invasive results can be confronted. We compared the signal time courses extracted applying ICA and LCMV-BF on MEG data to that of SEEG, both for the actual signals and the dynamic connectivity computed using cross-correlation (evolution of links in time). With our simulations, we illustrated the different effect of the temporal and spatial correlation among sources on the two methods. While ICA was more affected by the temporal correlation but robust against spatial configurations, LCMV-BF showed opposite behavior. Moreover, ICA seems more suited to retrieve the simulated networks. In case of real patient data, good MEG/SEEG correlation and good localization were obtained in 6 out of 8 patients. In 4 of them ICA had the best performance (higher correlation, lower localization distance). In terms of dynamic connectivity, the evolution in time of the cross-correlation links could be retrieved in 5 patients out of 6, however, with more variable results in terms of correlation and distance. In two patients LCMV-BF had better results than ICA. In one patient the two methods showed equally good outcomes, and in the remaining two patients ICA performed best. In conclusion, our results obtained by exploiting simultaneous MEG/SEEG recordings suggest that ICA and LCMV-BF have complementary qualities for retrieving the dynamics of interictal sources and their network interactions.

Complications of Intracranial Multimodal Monitoring for Neurocritical Care: A Systematic Review and Meta-Analysis.

Intracranial multimodal monitoring (iMMM) is increasingly used for neurocritical care. However, concerns arise regarding iMMM invasiveness considering limited evidence in its clinical significance and safety profile. We conducted a synthesis of evidence regarding complications associated with iMMM to delineate its safety profile. We performed a systematic review and meta-analysis (PROSPERO Registration Number: CRD42021225951) according to the Preferred Reporting Items for Systematic Review and Meta-Analysis and Peer Review of Electronic Search Strategies guidelines to retrieve evidence from studies reporting iMMM use in humans that mention related complications. We assessed risk of bias using the Newcastle-Ottawa Scale and funnel plots. The primary outcomes were iMMM complications. The secondary outcomes were putative risk factors. Of the 366 screened articles, 60 met the initial criteria and were further assessed by full-text reading. We included 22 studies involving 1206 patients and 1434 iMMM placements. Most investigators used a bolt system (85.9%) and a three-lumen device (68.8%), mainly inserting iMMM into the most injured hemisphere (77.9%). A total of 54 postoperative intracranial hemorrhages (pooled rate of 4%; 95% confidence interval [CI] 0-10%; I2 86%, p < 0.01 [random-effects model]) was reported, along with 46 misplacements (pooled rate of 6%; 95% CI 1-12%; I2 78%, p < 0.01) and 16 central nervous system infections (pooled rate of 0.43%; 95% CI 0-2%; I2 64%, p < 0.01). We found 6 system breakings, 18 intracranial bone fragments, and 5 cases of pneumocephalus. Currently, iMMM systems present a similar safety profile as intracranial devices commonly used in neurocritical care. Long-term outcomes of prospective studies will complete the benefit-risk assessment of iMMM in neurocritical care. Consensus-based reporting guidelines on iMMM use are needed to bolster future collaborative efforts.

Latest Views on the Mechanisms of Action of Surgically Implanted Cervical Vagal Nerve Stimulation in Epilepsy.

BACKGROUND: Vagus nerve stimulation (VNS) is approved as an adjunctive treatment for drug-resistant epilepsy. Although there is a substantial amount of literature aiming at unraveling the mechanisms of action of VNS in epilepsy, it is still unclear how the cascade of events triggered by VNS leads to its antiepileptic effect. OBJECTIVE: In this review, we integrated available peer-reviewed data on the effects of VNS in clinical and experimental research to identify those that are putatively responsible for its therapeutic effect. The topic of transcutaneous VNS will not be covered owing to the current lack of data supporting the differences and commonalities of its mechanisms of action in relation to invasive VNS. SUMMARY OF THE MAIN FINDINGS: There is compelling evidence that the effect is obtained through the stimulation of large-diameter afferent myelinated fibers that project to the solitary tract nucleus, then to the parabrachial nucleus, which in turn alters the activity of the limbic system, thalamus, and cortex. VNS-induced catecholamine release from the locus coeruleus in the brainstem plays a pivotal role. Functional imaging studies tend to point toward a common vagal network that comes into play, made up of the amygdalo-hippocampal regions, left thalamus, and insular cortex. CONCLUSIONS: Even though some crucial pieces are missing, neurochemical, molecular, cellular, and electrophysiological changes occur within the vagal afferent network at three main levels (the brainstem, the limbic system [amygdala and hippocampus], and the cortex). At this final level, VNS notably alters functional connectivity, which is known to be abnormally high within the epileptic zone and was shown to be significantly decreased by VNS in responders. The effect of crucial VNS parameters such as frequency or current amplitude on functional connectivity metrics is of utmost importance and requires further investigation.

Deep Brain Stimulation-Withdrawal Syndrome in Parkinson's Disease: Risk Factors and Pathophysiological Hypotheses of a Life-Threatening Emergency.

BACKGROUND AND OBJECTIVES: Subthalamic nucleus deep brain stimulation (DBS) is the most common therapeutic surgical procedure for patients with Parkinson's disease with motor fluctuations, dyskinesia, or tremor. Routine follow-up of patients allows clinicians to anticipate replacement of the DBS battery reaching the end of its life. Patients who experience a sudden stop of the DBS battery experience a rapid worsening of symptoms unresponsive to high dose of levodopa, in a life-threatening phenomenon called "DBS-withdrawal syndrome." In the current context of the COVID-19 pandemic, in which many surgeries are being deprogrammed, it is of utmost importance to determine to what extent DBS battery replacement surgeries should be considered an emergency. In this study, we attempt to identify risk factors of DBS-withdrawal syndrome and provide new insights about pathophysiological hypotheses. We then elaborate on the optimal approach to avoid and manage such a situation. MATERIALS AND METHODS: We conducted a systematic review of the literature on the subject and reported the cases of 20 patients (including five from our experience) with DBS-withdrawal syndrome, comparing them with 15 undisturbed patients (including three from our experience), all having undergone neurostimulation discontinuation. RESULTS: A long disease duration at battery removal and many years of DBS therapy are the main potential identified risk factors (p < 0.005). In addition, a trend for older age at the event and higher Unified Parkinson's Disease Rating Scale motor score before initial DBS implantation (evaluated in OFF-drug condition) was found (p < 0.05). We discuss several hypotheses that might explain this phenomenon, including discontinued functioning of the thalamic-basal ganglia loop due to DBS-stimulation cessation in a context in which cortical-basal ganglia loop had lost its cortical input, and possible onset of a severe bradykinesia through the simultaneous occurrence of an alpha and high-beta synchronized state. CONCLUSIONS: The patients' clinical condition may deteriorate rapidly, be unresponsive to high dose of levodopa, and become life-threatening. Hospitalization is suggested for clinical monitoring. In the context of the current COVID-19 pandemic, it is important to widely communicate the replacement of DBS batteries reaching the end of their life. More importantly, in cases in which the battery has stopped, there should be no delay in performing replacement as an emergent surgery.

Virtual MEG sensors based on beamformer and independent component analysis can reconstruct epileptic activity as measured on simultaneous intracerebral recordings.

The prevailing gold standard for presurgical determination of epileptogenic brain networks is intracerebral EEG, a potent yet invasive approach. Magnetoencephalography (MEG) is a state-of-the art non-invasive method for investigating epileptiform discharges. However, it is not clear at what level the precision offered by MEG can reach that of SEEG. Here, we present a strategy for non-invasively retrieving the constituents of the interictal network, with high spatial and temporal precision. Our method is based on MEG and a combination of spatial filtering and independent component analysis (ICA). We validated this approach in twelve patients with drug-resistant focal epilepsy, thanks to the unprecedented ground truth provided by simultaneous recordings of MEG and SEEG. A minimum variance adaptive beamformer estimated the source time series and ICA was used to further decompose these time series into network constituents (MEG-ICs), each having a time series (virtual electrode) and a topography (spatial distribution of amplitudes in the brain). We show that MEG has a considerable sensitivity of 0.80 and 0.84 and a specificity of 0.93 and 0.91 for reconstructing deep and superficial sources, respectively, when compared to the ground truth (SEEG). For each epileptic MEG-IC (n = 131), we found at least one significantly correlating SEEG contact close to zero lag after correcting for multiple comparisons. All the patients except one had at least one epileptic component that was highly correlated (Spearman rho>0.3) with that of SEEG traces. MEG-ICs correlated well with SEEG traces. The strength of correlation coefficients did not depend on the depth of the SEEG contacts or the clinical outcome of the patient. A significant proportion of the MEG-ICs (n = 83/131) were localized in proximity with their maximally correlating SEEG, within a mean distance of 20±12.18mm. Our research is the first to validate the MEG-retrieved beamformer IC sources against SEEG-derived ground truth in a simultaneous MEG-SEEG framework. Observations from the present study suggest that non-invasive MEG source components may potentially provide additional information, comparable to SEEG in a number of instances.

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.

Functional connectivity and epileptogenicity of nodular heterotopias: A single-pulse stimulation study.

OBJECTIVE: Nodular heterotopias (NHs) are malformations of cortical development associated with drug-resistant focal epilepsy with frequent poor surgical outcome. The epileptogenic network is complex and can involve the nodule, the overlying cortex, or both. Single-pulse electrical stimulation (SPES) during stereo-electroencephalography (SEEG) allows the investigation of functional connectivity between the stimulated and responsive cortices by eliciting cortico-cortical evoked potentials (CCEPs). We used SPES to analyze the NH connectome and its relation to the epileptogenic network organization. METHODS: We retrospectively studied 12 patients with NH who underwent 1 Hz or 0.2 Hz SPES of NH during SEEG. Outbound connectivity (regions where CCEPs were elicited by NH stimulation) and inbound connectivity (regions where stimulation elicited CCEPs in the NH) were searched. SEEG channels were then classified as "heterotopic" (located within the NH), "connected" (located in normotopic cortex and showing connectivity with the NH), and "unconnected." We used the epileptogenicity index (EI) to quantify implication of channels in the seizure-onset zone and to classify seizures as heterotopic, normotopic, and normo-heterotopic. RESULTS: One hundred thirty-five outbound and 72 inbound connections were found. Three patients showed connectivity between hippocampus and NH, and seven patients showed strong internodular connectivity. A total of 39 seizures were analyzed: 23 normo-heterotopic, 12 normotopic, and 4 heterotopic. Logistic regression found that "connected" channels were significantly (p = 8.4e-05) more likely to be epileptogenic than "unconnected" channels (odds ratio 4.71, 95% confidence interval (CI) [2.17, 10.21]) and heterotopic channels were also significantly (p = .024) more epileptogenic than "unconnected" channels (odds ratio 3.29, 95% CI [1.17, 9.23]). SIGNIFICANCE: SPES reveals widespread connectivity between NH and normotopic regions. Those connected regions show higher epileptogenicity. SPES might be useful to assess NH epileptogenic network.

MRI-based and robot-assisted stereotactic biopsy with intraoperative CT imaging.

BACKGROUND: As a pioneer center in the field of stereotaxy, Sainte-Anne school has always advocated the use of intraoperative imaging for stereotactic procedures to optimize both safety and accuracy. With the advent of intraoperative mobile CT unit, the robot-assisted stereotactic biopsy procedure has been recently updated. METHOD: Herein, we aim at describing our new surgical procedure that combines robotic assistance (NeuroMate, Renishaw) and intraoperative cone beam CT imaging (O-Arm, Medtronic). CONCLUSION: Intraoperative imaging with the O-Arm was efficiently incorporated into the workflow. This new equipment leads to optimizing operative time and an easier realization of intraoperative imaging.

Hippocampal Interictal Spikes during Sleep Impact Long-Term Memory Consolidation.

OBJECTIVE: Non-rapid eye movement (NREM) sleep is supposed to play a key role in long-term memory consolidation transferring information from hippocampus to neocortex. However, sleep also activates epileptic activities in medial temporal regions. This study investigated whether interictal hippocampal spikes during sleep would impair long-term memory consolidation. METHOD: We prospectively measured visual and verbal memory performance in 20 patients with epilepsy investigated with stereoelectroencephalography (SEEG) at immediate, 30-minute, and 1-week delays, and studied the correlations between interictal hippocampal spike frequency during waking and the first cycle of NREM sleep and memory performance, taking into account the number of seizures occurring during the consolidation period and other possible confounding factors, such as age and epilepsy duration. RESULTS: Retention of verbal memory over 1 week was negatively correlated with hippocampal spike frequency during sleep, whereas no significant correlation was found with hippocampal interictal spikes during waking. No significant result was found for visual memory. Regression tree analysis showed that the number of seizures was the first factor that impaired the verbal memory retention between 30 minutes and 1 week. When the number of seizures was below 5, spike frequency during sleep higher than 13 minutes was associated with impaired memory retention over 1 week. INTERPRETATION: Our results show that activation of interictal spikes in the hippocampus during sleep and seizures specifically impair long-term memory consolidation. We hypothesize that hippocampal interictal spikes during sleep interrupt hippocampal-neocortical transfer of information. ANN NEUROL 2020;87:976-987.

Changes in epileptogenicity biomarkers after stereotactic thermocoagulation.

OBJECTIVE: Stereo-electroencephalography (SEEG)-guided radiofrequency thermocoagulation (RF-TC) aims at modifying epileptogenic networks to reduce seizure frequency. High-frequency oscillations (HFOs), spikes, and cross-rate are quantifiable epileptogenic biomarkers. In this study, we sought to evaluate, using SEEG signals recorded before and after thermocoagulation, whether a variation in these markers is related to the therapeutic effect of this procedure and to the outcome of surgery. METHODS: Interictal segments of SEEG signals were analyzed in 38 patients during presurgical evaluation. We used an automatized method to quantify the rate of spikes, rate of HFOs, and cross-rate (a measure combining spikes and HFOs) before and after thermocoagulation. We analyzed the differences both at an individual level with a surrogate approach and at a group level with analysis of variance. We then evaluated the correlation between these variations and the clinical response to RF-TC and to subsequent resective surgery. RESULTS: After thermocoagulation, 19 patients showed a clinical improvement. At the individual level, clinically improved patients more frequently had a reduction in spikes and cross-rate in the epileptogenic zone than patients without clinical improvement (p = .002, p = .02). At a group level, there was a greater decrease of HFOs in epileptogenic and thermocoagulated zones in patients with clinical improvement (p < .05) compared to those with no clinical benefit. Eventually, a significant decrease of all the markers after RF-TC was found in patients with a favorable outcome of resective surgery (spikes, p = .026; HFOs, p = .03; cross-rate, p = .03). SIGNIFICANCE: Quantified changes in the rate of spikes, rate of HFOs, and cross-rate can be observed after thermocoagulation, and the reduction of these markers correlates with a favorable clinical outcome after RF-TC and with successful resective surgery. This may suggest that interictal biomarker modifications after RF-TC can be clinically used to predict the effectiveness of the thermocoagulation procedure and the outcome of resective surgery.

Crossed brainstem syndrome revealing bleeding brainstem cavernous malformation: an illustrative case.

BACKGROUND: Since the nineteenth century, a great variety of crossed brainstem syndromes (CBS) have been described in the medical literature. A CBS typically combines ipsilateral cranial nerves deficits to contralateral long tracts involvement such as hemiparesis or hemianesthesia. Classical CBS seem in fact not to be so clear-cut entities with up to 20% of patients showing different or unnamed combinations of crossed symptoms. In terms of etiologies, acute brainstem infarction predominates but CBS secondary to hemorrhage, neoplasm, abscess, and demyelination have been described. The aim of this study was to assess the proportion of CBS caused by a bleeding episode arising from a brainstem cavernous malformation (BCM) reported in the literature. CASE PRESENTATION: We present the case of a typical Foville syndrome in a 65-year-old man that was caused by a pontine BCM with extralesional bleeding. Following the first bleeding episode, a conservative management was decided but the patient had eventually to be operated on soon after the second bleeding event. DISCUSSION: A literature review was conducted focusing on the five most common CBS (Benedikt, Weber, Foville, Millard-Gubler, Wallenberg) on Medline database from inception to 2020. According to the literature, hemorrhagic BCM account for approximately 7 % of CBS. Microsurgical excision may be indicated after the second bleeding episode but needs to be carefully weighted up against the risks of the surgical procedure and openly discussed with the patient. CONCLUSIONS: In the setting of a CBS, neuroimaging work-up may not infrequently reveal a BCM requiring complex multidisciplinary team management including neurosurgical advice.

Automated neurosurgical stereotactic planning for intraoperative use: a comprehensive review of the literature and perspectives.

The creation of intracranial stereotactic trajectories, from entry point to target point, is still mostly done manually by the neurosurgeon. The development of automated stereotactic planning tools has been described in the literature. This systematic review aims to assess the effectiveness of stereotactic planning procedure automation and develop tools for patients undergoing neurosurgical stereotactic procedures. PubMed/MEDLINE, EMBASE, Google Scholar, CINAHL, PsycINFO, and Cochrane Register of Controlled Trials databases were searched from inception to September 1, 2019, at the exception of Google Scholar (from 1 January 2010 to September 1, 2019) in French and English. Eligible studies included all studies proposing automated stereotactic planning. A total of 1543 studies were screened. Forty-two studies were included in the systematic review, including 18 (42.9%) conference papers. The surgical procedures planned automatically were mainly deep brain stimulation (n = 14, 33.3%), stereoelectroencephalography (n = 12, 28.6%), and not specified (n = 10, 23.8%). The most frequently used surgical constraints to plan the trajectory were blood vessels (n = 32, 76.2%), cerebral sulci (n = 27, 64.3%), and cerebral ventricles (n = 23, 54.8%). The distance from blood vessels ranged from 1.96 to 4.78 mm for manual trajectories and from 2.47 to 7.0 mm for automated trajectories. At least one neurosurgeon was involved in 36 studies (85.7%). The automated stereotactic trajectory was preferred in 75.4% of the studied cases (range 30-92.9). Only 3 (7.1%) studies were multicentric. No study reported prospective use of the planning software. Stereotactic planning automation is a promising tool to provide valuable stereotactic trajectories for clinical applications.

Electrical stimulation for seizure induction during SEEG exploration: a useful predictor of postoperative seizure recurrence?

OBJECTIVE: Direct electrical stimulations of cerebral cortex are a traditional part of stereoelectroencephalography (SEEG) practice, but their value as a predictive factor for seizure outcome has never been carefully investigated. PATIENTS AND METHOD: We retrospectively analysed a cohort of 346 patients operated on for drug-resistant focal epilepsy after SEEG exploration. As potential predictors we included: aetiology, MRI data, age of onset, duration of epilepsy, age at surgery, topography of surgery and whether a seizure was induced by either low frequency electrical stimulation (LFS) or high frequency electrical stimulation. RESULTS: Of 346 patients, 63.6% had good outcome (no seizure recurrence, Engel I). Univariate analysis demonstrated significant correlation with favourable outcome (Engel I) for: aetiology, positive MRI and seizure induced by stimulation. At multivariate analysis, informative MRI, type II focal cortical dysplasia and tumour reduced the risk of seizure recurrence (SR) by 47%, 58% and 81%, respectively. Compared with the absence of induced seizures, the occurrence of ictal events after LFS significantly predicts a favourable outcome on seizures, with only 44% chance of disabling SR at last follow-up. CONCLUSION: Among the already known predictors outcome, seizure induction by LFS therefore represents a positive predictive factor for seizure outcome after surgery.

Relationship between PET metabolism and SEEG epileptogenicity in focal lesional epilepsy.

PURPOSE: This study aims to evaluate the performance of 18F-FDG PET for distinguishing the epileptogenic zone (EZ) from propagation and non-involved zones at brain area level, as defined using stereo-EEG (SEEG), in patients with pharmacoresistant epilepsy due to malformations of cortical development (MCD). Additionally, we seek to determine the relationship between 18F-FDG-PET data and post-surgical seizure outcome. METHODS: Thirty-eight patients with MCD were explored with 18F-FDG PET and SEEG. We compared PET metabolism of each patient to a control population of healthy subjects. Based on MRI and SEEG, we separated 4 distinct zones at individual level: lesional, epileptogenic non-lesional, propagation, and non-involved. Then, we analysed (1) difference of PET metabolism within these four distinct zones; (2) performance of PET in defining the EZ within the SEEG-sampled areas; and (3) relation between extension of PET hypometabolism and post-surgical seizure outcome. RESULTS: We found (1) a gradient of PET hypometabolism from non-involved to propagation, then to epileptogenic and lesional zones (p < 0.001); (2) good performance of PET in defining the EZ (AUC of ROC curve = 0.82); (3) poorer post-surgical prognosis associated with PET hypometabolism extension beyond SEEG sampling (p = 0.024). CONCLUSION: 18F-FDG-PET has good accuracy in determining EZ in patients with MCD even if the hypometabolism is not limited to the EZ. Furthermore, hypometabolic extension is unfavourably associated with post-surgical prognosis.

Quantitative analysis of hyperkinetic seizures and correlation with seizure onset zone.

OBJECTIVE: Hyperkinetic epileptic seizures (HKS) are difficult to characterize and localize according to semiologic features. We propose a multicriteria scale to help visual analysis and report results of cerebral localization. METHODS: We assessed seizures from 37 patients with HKS, explored with stereoelectroencephalography during presurgical evaluation. We used a multicriteria scale (hyperkinetic seizure scale [HSS]) with 10 semiologic features, scored independently by two neurologists. The item scores were used to group seizures using the k-means method. Semiologic features were correlated with the seizure onset zone (SOZ) localization (temporal, prefrontal dorsolateral, prefrontal ventromesial, parietal, insular). RESULTS: Fifty-five seizures were analyzed, and each item of the HSS was compared between the two examiners with good interrater agreement (85.3%). Dystonia, integrated behavior, and bilateral or unilateral hyperkinetic movements were statistically significant according to localization. Three clusters were identified according to the HSS and correlated with different patterns of anatomic localization of SOZ. Cluster 1 was characterized clinically by asymmetric hyperkinetic movements associated with marked dystonia and vocalization. It mainly included parietal seizures. Cluster 2 was characterized by bilateral and symmetrical stereotyped hyperkinetic movements without dystonia. It represented half of temporal seizures and one-third of prefrontal seizures (dorsolateral). Cluster 3 was characterized by seizures with strong emotionality and vocalization with bilateral and symmetrical hyperkinetic movements and integrated behavior. It involved half of temporal seizures and a majority of prefrontal (ventromesial) seizures. SIGNIFICANCE: We propose a first attempt to quantify clinical patterns of HKS. The HSS may help to predict SOZ localization according to three main groups of hyperkinetic seizures.