Human local field potentials in motor and non-motor brain areas encode upcoming movement direction.

Limb movement direction can be inferred from local field potentials in motor cortex during movement execution. Yet, it remains unclear to what extent intended hand movements can be predicted from brain activity recorded during movement planning. Here, we set out to probe the directional-tuning of oscillatory features during motor planning and execution, using a machine learning framework on multi-site local field potentials (LFPs) in humans. We recorded intracranial EEG data from implanted epilepsy patients as they performed a four-direction delayed center-out motor task. Fronto-parietal LFP low-frequency power predicted hand-movement direction during planning while execution was largely mediated by higher frequency power and low-frequency phase in motor areas. By contrast, Phase-Amplitude Coupling showed uniform modulations across directions. Finally, multivariate classification led to an increase in overall decoding accuracy (>80%). The novel insights revealed here extend our understanding of the role of neural oscillations in encoding motor plans.

Comparative Study of Paraneoplastic and Nonparaneoplastic Autoimmune Encephalitis With GABABR Antibodies.

BACKGROUND AND OBJECTIVES: While patients with paraneoplastic autoimmune encephalitis (AE) with gamma-aminobutyric-acid B receptor antibodies (GABABR-AE) have poor functional outcomes and high mortality, the prognosis of nonparaneoplastic cases has not been well studied. METHODS: Patients with GABABR-AE from the French and the Dutch Paraneoplastic Neurologic Syndromes Reference Centers databases were retrospectively included and their data collected; the neurologic outcomes of paraneoplastic and nonparaneoplastic cases were compared. Immunoglobulin G (IgG) isotyping and human leukocyte antigen (HLA) genotyping were performed in patients with available samples. RESULTS: A total of 111 patients (44/111 [40%] women) were enrolled, including 84 of 111 (76%) paraneoplastic and 18 of 111 (16%) nonparaneoplastic cases (cancer status was undetermined for 9 patients). Patients presented with seizures (88/111 [79%]), cognitive impairment (54/111 [49%]), and/or behavioral disorders (34/111 [31%]), and 54 of 111 (50%) were admitted in intensive care unit (ICU). Nonparaneoplastic patients were significantly younger (median age 54 years [range 19-88] vs 67 years [range 50-85] for paraneoplastic cases, p < 0.001) and showed a different demographic distribution. Nonparaneoplastic patients more often had CSF pleocytosis (17/17 [100%] vs 58/78 [74%], p = 0.02), were almost never associated with KTCD16-abs (1/16 [6%] vs 61/70 [87%], p < 0.001), and were more frequently treated with second-line immunotherapy (11/18 [61%] vs 18/82 [22%], p = 0.003). However, no difference of IgG subclass or HLA association was observed, although sample size was small (10 and 26 patients, respectively). After treatment, neurologic outcome was favorable (mRS ≤2) for 13 of 16 (81%) nonparaneoplastic and 37 of 84 (48%) paraneoplastic cases (p = 0.03), while 3 of 18 (17%) and 42 of 83 (51%) patients had died at last follow-up (p = 0.008), respectively. Neurologic outcome no longer differed after adjustment for confounding factors but seemed to be negatively associated with increased age and ICU admission. A better survival was associated with nonparaneoplastic cases, a younger age, and the use of immunosuppressive drugs. DISCUSSION: Nonparaneoplastic GABABR-AE involved younger patients without associated KCTD16-abs and carried better neurologic and vital prognoses than paraneoplastic GABABR-AE, which might be due to a more intensive treatment strategy. A better understanding of immunologic mechanisms underlying both forms is needed.

Data-driven normative values based on generative manifold learning for quantitative MRI.

In medicine, abnormalities in quantitative metrics such as the volume reduction of one brain region of an individual versus a control group are often provided as deviations from so-called normal values. These normative reference values are traditionally calculated based on the quantitative values from a control group, which can be adjusted for relevant clinical co-variables, such as age or sex. However, these average normative values do not take into account the globality of the available quantitative information. For example, quantitative analysis of T1-weighted magnetic resonance images based on anatomical structure segmentation frequently includes over 100 cerebral structures in the quantitative reports, and these tend to be analyzed separately. In this study, we propose a global approach to personalized normative values for each brain structure using an unsupervised Artificial Intelligence technique known as generative manifold learning. We test the potential benefit of these personalized normative values in comparison with the more traditional average normative values on a population of patients with drug-resistant epilepsy operated for focal cortical dysplasia, as well as on a supplementary healthy group and on patients with Alzheimer's disease.

Advances in epileptic network findings of hypothalamic hamartomas.

Hypothalamic hamartomas (HHs) are congenital developmental malformations located in the hypothalamus. They are associated with a characteristic clinical manifestation known as gelastic seizures (GS). However, the traditional understanding of HHs has been limited, resulting in insufficient treatment options and high recurrence rates of seizures after surgery. This is consistent with the network hypothesis of focal epilepsy that the epileptogenic zone is not only limited to HH but may also involve the distant cerebral cortex external to the HH mass. The epilepsy network theory, on the other hand, provides a new perspective. In this study, we aim to explore HH-related epilepsy as a network disease, challenging the conventional notion of being a focal lesional disease. We analyze various aspects of HHs, including genes and signaling pathways, local circuits, the whole-brain level, phenotypical expression in terms of seizure semiology, and comorbidities. By examining HHs through the lens of network theory, we can enhance our understanding of the condition and potentially identify novel approaches for more effective management and treatment of epilepsy associated with HHs.

Hypothalamic hamartomas (HHs) are unusual brain malformations present from birth in the hypothalamus region. They often lead to a distinctive type of seizures known as GSs. However, our current understanding of HHs is limited, and this has made it challenging to treat them effectively. Many patients continue to experience seizures even after surgery. We've typically considered HH-related epilepsy as a localized problem, but a new theory suggests that it may involve a network of brain areas. In our study, we aim to change the way we view HH-related epilepsy. Instead of thinking of it as a single lesion in the brain, we explore the idea that it's a network disease. To do this, we'll investigate various aspects of HHs, such as the genes and pathways involved, how different parts of the brain interact, the impact on the whole brain, the types of seizures experienced, and any related health issues. By looking at HHs through this network theory, we hope to gain a deeper understanding of the condition and potentially discover new ways to manage and treat epilepsy associated with HHs. This shift in perspective could offer hope to those living with HH-related epilepsy and lead to more effective treatments, ultimately improving their quality of life.

Cross-frequency coupling in cortico-hippocampal networks supports the maintenance of sequential auditory information in short-term memory.

It has been suggested that cross-frequency coupling in cortico-hippocampal networks enables the maintenance of multiple visuo-spatial items in working memory. However, whether this mechanism acts as a global neural code for memory retention across sensory modalities remains to be demonstrated. Intracranial EEG data were recorded while drug-resistant patients with epilepsy performed a delayed matched-to-sample task with tone sequences. We manipulated task difficulty by varying the memory load and the duration of the silent retention period between the to-be-compared sequences. We show that the strength of theta-gamma phase amplitude coupling in the superior temporal sulcus, the inferior frontal gyrus, the inferior temporal gyrus, and the hippocampus (i) supports the short-term retention of auditory sequences; (ii) decodes correct and incorrect memory trials as revealed by machine learning analysis; and (iii) is positively correlated with individual short-term memory performance. Specifically, we show that successful task performance is associated with consistent phase coupling in these regions across participants, with gamma bursts restricted to specific theta phase ranges corresponding to higher levels of neural excitability. These findings highlight the role of cortico-hippocampal activity in auditory short-term memory and expand our knowledge about the role of cross-frequency coupling as a global biological mechanism for information processing, integration, and memory in the human brain.

SEEG electrode shaft affects amplitude and latency of potentials evoked with single pulse electrical stimulation.

BACKGROUND: Long and thin shaft electrodes are implanted intracerebrally for stereoelectroencephalography (SEEG) in patients with pharmacoresistant focal epilepsies. Two adjacent contacts of one of such electrodes can deliver a train of single pulse electrical stimulations (SPES), and evoked potentials (EPs) are recorded on other contacts. In this study we assess if stimulating and recording on the same shaft, as opposed to different shafts, has an impact on common EP features. NEW METHOD: We leverage the large volume of SEEG data gathered in the F-TRACT database and analyze data from nearly one thousand SEEG implantations in order to verify whether stimulation and recording from the same shaft influence the EP pattern. RESULTS: We found that when the stimulated and the recording contacts were located on the same shaft, the mean and median amplitudes of an EP are greater, and its mean and median latencies are smaller than when the contacts were located on different shafts. This effect is small (Cohen's d ∼ 0.1), but robust (p-value < 10-3) across the SEEG database. COMPARISON WITH EXISTING METHOD(S): Our study is the first one to address this question. Due to the choice of commonly used EP features, our method is congruent with other studies. CONCLUSIONS: The magnitude of the reported effect does not obligate all standard analyses to correct for it, unless they aim at high precision. The source of the effect is not clear. Manufacturers of SEEG electrodes could examine it and potentially minimize the effect in their future products.

Human thalamic low-frequency oscillations correlate with expected value and outcomes during reinforcement learning.

Reinforcement-based adaptive decision-making is believed to recruit fronto-striatal circuits. A critical node of the fronto-striatal circuit is the thalamus. However, direct evidence of its involvement in human reinforcement learning is lacking. We address this gap by analyzing intra-thalamic electrophysiological recordings from eight participants while they performed a reinforcement learning task. We found that in both the anterior thalamus (ATN) and dorsomedial thalamus (DMTN), low frequency oscillations (LFO, 4-12 Hz) correlated positively with expected value estimated from computational modeling during reward-based learning (after outcome delivery) or punishment-based learning (during the choice process). Furthermore, LFO recorded from ATN/DMTN were also negatively correlated with outcomes so that both components of reward prediction errors were signaled in the human thalamus. The observed differences in the prediction signals between rewarding and punishing conditions shed light on the neural mechanisms underlying action inhibition in punishment avoidance learning. Our results provide insight into the role of thalamus in reinforcement-based decision-making in humans.

PIEZO1 expression at the glio-vascular unit adjusts to neuroinflammation in seizure conditions.

Mechanosensors are emerging players responding to hemodynamic and physical inputs. Their significance in the central nervous system remains relatively uncharted. Using human-derived brain specimens or cells and a pre-clinical model of mesio-temporal lobe epilepsy (MTLE), we examined how the mRNA levels of the mechanosensitive channel PIEZO1 adjust to disease-associated pro-inflammatory trajectories. In brain tissue micro-punches obtained from 18 drug-resistant MTLE patients, PIEZO1 expression positively correlated with pro-inflammatory biomarkers TNFα, IL-1ß, and NF-kB in the epileptogenic hippocampus compared to the adjacent amygdala and temporal cortex tissues. In an experimental MTLE model, hippocampal Piezo1 and cytokine expression levels were increased post-status epilepticus (SE) and during epileptogenesis. Piezo1 expression positively correlated with Tnfα, Il1ß, and Nf-kb in the hippocampal foci. Next, by combining RNAscope with immunohistochemistry, we identified Piezo1 in glio-vascular cells. Post-SE and during epileptogenesis, ameboid IBA1 microglia, hypertrophic GFAP astrocytes, and damaged NG2DsRed pericytes exhibited time-dependent patterns of increased Piezo1 expression. Digital droplet PCR analysis confirmed the Piezo1 trajectory in isolated hippocampal microvessels in the ipsi and contralateral hippocampi. The combined examinations performed in this model showed Piezo1 expression returning towards basal levels after the epileptogenesis-associated peak inflammation. From these associations, we next asked whether pro-inflammatory players directly regulate PIEZO1 expression. We used human-derived brain cells and confirmed that endothelium, astrocytes, and pericytes expressed PIEZO1. Exposure to human recombinant TNFα or IL1ß upregulated NF-kB in all cells. Furthermore, TNFα induced PIEZO1 expression in a dose and time-dependent manner, primarily in astrocytes. This exploratory study describes a spatiotemporal dialogue between PIEZO1 brain cell-mechanobiology and neuro-inflammatory cell remodeling. The precise functional mechanisms regulating this interplay in disease conditions warrant further investigation.

Overt speech decoding from cortical activity: a comparison of different linear methods.

Introduction: Speech BCIs aim at reconstructing speech in real time from ongoing cortical activity. Ideal BCIs would need to reconstruct speech audio signal frame by frame on a millisecond-timescale. Such approaches require fast computation. In this respect, linear decoder are good candidates and have been widely used in motor BCIs. Yet, they have been very seldomly studied for speech reconstruction, and never for reconstruction of articulatory movements from intracranial activity. Here, we compared vanilla linear regression, ridge-regularized linear regressions, and partial least squares regressions for offline decoding of overt speech from cortical activity. Methods: Two decoding paradigms were investigated: (1) direct decoding of acoustic vocoder features of speech, and (2) indirect decoding of vocoder features through an intermediate articulatory representation chained with a real-time-compatible DNN-based articulatory-to-acoustic synthesizer. Participant's articulatory trajectories were estimated from an electromagnetic-articulography dataset using dynamic time warping. The accuracy of the decoders was evaluated by computing correlations between original and reconstructed features. Results: We found that similar performance was achieved by all linear methods well above chance levels, albeit without reaching intelligibility. Direct and indirect methods achieved comparable performance, with an advantage for direct decoding. Discussion: Future work will address the development of an improved neural speech decoder compatible with fast frame-by-frame speech reconstruction from ongoing activity at a millisecond timescale.

Complex visual discrimination is impaired after right, but not left, anterior temporal lobectomy.

The prevailing view in human cognitive neuroscience associates the medial temporal lobes (MTLs) with declarative memory. Compelling experimental evidence has, however, demonstrated that these regions are specialized according to the representations processed, irrespective of the cognitive domain assessed. This account was supported by the study of patients with bilateral medial temporal amnesia, who exhibit impairments in perceptual tasks involving complex visual stimuli. Yet, little is known regarding the impact of unilateral MTL damage on complex visual abilities. To address this issue, we administered a visual matching task to 20 patients who underwent left (N = 12) or right (N = 8) anterior temporal lobectomy for drug-resistant epilepsy and to 38 healthy controls. Presentation viewpoint was manipulated to increase feature ambiguity, as this is critical to reveal impairments in perceptual tasks. Similar to control participants, patients with left-sided damage succeeded in all task conditions. In contrast, patients with right-sided damage had decreased accuracy compared with that of the other two groups, as well as increased response time. Notably, the accuracy of those with right-sided damage did not exceed chance level when feature ambiguity was high (i.e., when stimuli were presented from different viewpoints) for the most complex classes of stimuli (i.e., scenes and buildings, compared with single objects). The pattern reported in bilateral patients in previous studies was therefore reproduced in patients with right, but not left, resection. These results suggest that the complex visual-representation functions supported by the MTL are right-lateralized, and raise the question as to how the representational account of these regions applies to representations supported by left MTL regions.

A Subpopulation of Spikes Predicts Successful Epilepsy Surgery Outcome.

OBJECTIVE: Epileptic spikes are the traditional interictal electroencephalographic (EEG) biomarker for epilepsy. Given their low specificity for identifying the epileptogenic zone (EZ), they are given only moderate attention in presurgical evaluation. This study aims to demonstrate that it is possible to identify specific spike features in intracranial EEG that optimally define the EZ and predict surgical outcome. METHODS: We analyzed spike features on stereo-EEG segments from 83 operated patients from 2 epilepsy centers (37 Engel IA) in wakefulness, non-rapid eye movement sleep, and rapid eye movement sleep. After automated spike detection, we investigated 135 spike features based on rate, morphology, propagation, and energy to determine the best feature or feature combination to discriminate the EZ in seizure-free and non-seizure-free patients by applying 4-fold cross-validation. RESULTS: The rate of spikes with preceding gamma activity in wakefulness performed better for surgical outcome classification (4-fold area under receiver operating characteristics curve [AUC] = 0.755 ± 0.07) than the seizure onset zone, the current gold standard (AUC = 0.563 ± 0.05, p = 0.015) and the ripple rate, an emerging seizure-independent biomarker (AUC = 0.537 ± 0.07, p = 0.006). Channels with a spike-gamma rate exceeding 1.9/min had an 80% probability of being in the EZ. Combining features did not improve the results. INTERPRETATION: Resection of brain regions with high spike-gamma rates in wakefulness is associated with a high probability of achieving seizure freedom. This rate could be applied to determine the minimal number of spiking channels requiring resection. In addition to quantitative analysis, this feature is easily accessible to visual analysis, which could aid clinicians during presurgical evaluation. ANN NEUROL 2023;93:522-535.

Variability of Single Pulse Electrical Stimulation Responses Recorded with Intracranial Electroencephalography in Epileptic Patients.

Cohort studies of brain stimulations performed with stereo-electroencephalographic (SEEG) electrodes in epileptic patients allow to derive large scale functional connectivity. It is known, however, that brain responses to electrical or magnetic stimulation techniques are not always reproducible. Here, we study variability of responses to single pulse SEEG electrical stimulation. We introduce a second-order probability analysis, i.e. we extend estimation of connection probabilities, defined as the proportion of responses trespassing a statistical threshold (determined in terms of Z-score with respect to spontaneous neuronal activity before stimulation) over all responses and derived from a number of individual measurements, to an analysis of pairs of measurements.Data from 445 patients were processed. We found that variability between two equivalent measurements is substantial in particular conditions. For long ( > ~ 90 mm) distances between stimulating and recording sites, and threshold value Z = 3, correlation between measurements drops almost to zero. In general, it remains below 0.5 when the threshold is smaller than Z = 4 or the stimulating current intensity is 1 mA. It grows with an increase of either of these factors. Variability is independent of interictal spiking rates in the stimulating and recording sites.We conclude that responses to SEEG stimulation in the human brain are variable, i.e. in a subject at rest, two stimulation trains performed at the same electrode contacts and with the same protocol can give discrepant results. Our findings highlight an advantage of probabilistic interpretation of such results even in the context of a single individual.

Brain mapping of auditory hallucinations and illusions induced by direct intracortical electrical stimulation.

BACKGROUND: The exact architecture of the human auditory cortex remains a subject of debate, with discrepancies between functional and microstructural studies. In a hierarchical framework for sensory perception, simple sound perception is expected to take place in the primary auditory cortex, while the processing of complex, or more integrated perceptions is proposed to rely on associative and higher-order cortices. OBJECTIVES: We hypothesize that auditory symptoms induced by direct electrical stimulation (DES) offer a window into the architecture of the brain networks involved in auditory hallucinations and illusions. The intracranial recordings of these evoked perceptions of varying levels of integration provide the evidence to discuss the theoretical model. METHODS: We analyzed SEEG recordings from 50 epileptic patients presenting auditory symptoms induced by DES. First, using the Juelich cytoarchitectonic parcellation, we quantified which regions induced auditory symptoms when stimulated (ROI approach). Then, for each evoked auditory symptom type (illusion or hallucination), we mapped the cortical networks showing concurrent high-frequency activity modulation (HFA approach). RESULTS: Although on average, illusions were found more laterally and hallucinations more posteromedially in the temporal lobe, both perceptions were elicited in all levels of the sensory hierarchy, with mixed responses found in the overlap. The spatial range was larger for illusions, both in the ROI and HFA approaches. The limbic system was specific to the hallucinations network, and the inferior parietal lobule was specific to the illusions network. DISCUSSION: Our results confirm a network-based organization underlying conscious sound perception, for both simple and complex components. While symptom localization is interesting from an epilepsy semiology perspective, the hallucination-specific modulation of the limbic system is particularly relevant to tinnitus and schizophrenia.

Epileptic spasms are associated with increased stereo-electroencephalography derived functional connectivity in tuberous sclerosis complex.

OBJECTIVE: Epileptic spasms (ES) are common in tuberous sclerosis complex (TSC). However, the underlying network alterations and relationship with epileptogenic tubers are poorly understood. We examined interictal functional connectivity (FC) using stereo-electroencephalography (SEEG) in patients with TSC to investigate the relationship between tubers, epileptogenicity, and ES. METHODS: We analyzed 18 patients with TSC who underwent SEEG (mean age = 11.5 years). The dominant tuber (DT) was defined as the most epileptogenic tuber using the epileptogenicity index. Epileptogenic zone (EZ) organization was quantitatively separated into focal (isolated DT) and complex (all other patterns). Using a 20-min interictal recording, FC was estimated with nonlinear regression, h2 . We calculated (1) intrazone FC within all sampled tubers and normal-appearing cortical zones, respectively; and (2) interzone FC involving connections between DT, other tubers, and normal cortex. The relationship between FC and (1) presence of ES as a current seizure type at the time of SEEG, (2) EZ organization, and (3) epileptogenicity was analyzed using a mixed generalized linear model. Spike rate and distance between zones were considered in the model as covariates. RESULTS: Six patients had ES as a current seizure type at time of SEEG. ES patients had a greater number of tubers with a fluid-attenuated inversion recovery hypointense center (p < .001), and none had TSC1 mutations. The presence of ES was independently associated with increased FC within both intrazone (p = .033) and interzone (p = .011) networks. Post hoc analyses identified that increased FC was associated with ES across tuber and nontuber networks. EZ organization and epileptogenicity biomarkers were not associated with FC. SIGNIFICANCE: Increased cortical synchrony among both tuber and nontuber networks is characteristic of patients with ES and independent of both EZ organization and tuber epileptogenicity. This further supports the prospect of FC biomarkers aiding treatment paradigms in TSC.

Intracerebral mechanisms explaining the impact of incidental feedback on mood state and risky choice.

Identifying factors whose fluctuations are associated with choice inconsistency is a major issue for rational decision theory. Here, we investigated the neuro-computational mechanisms through which mood fluctuations may bias human choice behavior. Intracerebral EEG data were collected in a large group of subjects (n=30) while they were performing interleaved quiz and choice tasks that were designed to examine how a series of unrelated feedbacks affect decisions between safe and risky options. Neural baseline activity preceding choice onset was confronted first to mood level, estimated by a computational model integrating the feedbacks received in the quiz task, and then to the weighting of option attributes, in a computational model predicting risk attitude in the choice task. Results showed that (1) elevated broadband gamma activity (BGA) in the ventromedial prefrontal cortex (vmPFC) and dorsal anterior insula (daIns) was respectively signaling periods of high and low mood, (2) increased vmPFC and daIns BGA respectively promoted and tempered risk taking by overweighting gain vs. loss prospects. Thus, incidental feedbacks induce brain states that correspond to different moods and bias the evaluation of risky options. More generally, these findings might explain why people experiencing positive (or negative) outcome in some part of their life tend to expect success (or failure) in any other.

Seizure semiology: ILAE glossary of terms and their significance.

This educational topical review and Task Force report aims to address learning objectives of the International League Against Epilepsy (ILAE) curriculum. We sought to extract detailed features involving semiology from video recordings and interpret semiological signs and symptoms that reflect the likely localization for focal seizures in patients with epilepsy. This glossary was developed by a working group of the ILAE Commission on Diagnostic Methods incorporating the EEG Task Force. This paper identifies commonly used terms to describe seizure semiology, provides definitions, signs and symptoms, and summarizes their clinical value in localizing and lateralizing focal seizures based on consensus in the published literature. Video-EEG examples are included to illustrate important features of semiology in patients with epilepsy.

A brain atlas of axonal and synaptic delays based on modelling of cortico-cortical evoked potentials.

Epilepsy presurgical investigation may include focal intracortical single-pulse electrical stimulations with depth electrodes, which induce cortico-cortical evoked potentials at distant sites because of white matter connectivity. Cortico-cortical evoked potentials provide a unique window on functional brain networks because they contain sufficient information to infer dynamical properties of large-scale brain connectivity, such as preferred directionality and propagation latencies. Here, we developed a biologically informed modelling approach to estimate the neural physiological parameters of brain functional networks from the cortico-cortical evoked potentials recorded in a large multicentric database. Specifically, we considered each cortico-cortical evoked potential as the output of a transient stimulus entering the stimulated region, which directly propagated to the recording region. Both regions were modelled as coupled neural mass models, the parameters of which were estimated from the first cortico-cortical evoked potential component, occurring before 80 ms, using dynamic causal modelling and Bayesian model inversion. This methodology was applied to the data of 780 patients with epilepsy from the F-TRACT database, providing a total of 34 354 bipolar stimulations and 774 445 cortico-cortical evoked potentials. The cortical mapping of the local excitatory and inhibitory synaptic time constants and of the axonal conduction delays between cortical regions was obtained at the population level using anatomy-based averaging procedures, based on the Lausanne2008 and the HCP-MMP1 parcellation schemes, containing 130 and 360 parcels, respectively. To rule out brain maturation effects, a separate analysis was performed for older (>15 years) and younger patients (<15 years). In the group of older subjects, we found that the cortico-cortical axonal conduction delays between parcels were globally short (median = 10.2 ms) and only 16% were larger than 20 ms. This was associated to a median velocity of 3.9 m/s. Although a general lengthening of these delays with the distance between the stimulating and recording contacts was observed across the cortex, some regions were less affected by this rule, such as the insula for which almost all efferent and afferent connections were faster than 10 ms. Synaptic time constants were found to be shorter in the sensorimotor, medial occipital and latero-temporal regions, than in other cortical areas. Finally, we found that axonal conduction delays were significantly larger in the group of subjects younger than 15 years, which corroborates that brain maturation increases the speed of brain dynamics. To our knowledge, this study is the first to provide a local estimation of axonal conduction delays and synaptic time constants across the whole human cortex in vivo, based on intracerebral electrophysiological recordings.

Surgical outcome of temporal plus epilepsy is improved by multilobar resection.

OBJECTIVE: Temporal plus epilepsy (TPE) represents a rare type of epilepsy characterized by a complex epileptogenic zone including the temporal lobe and the close neighboring structures. We investigated whether the complete resection of temporal plus epileptogenic zone as defined through stereoelectroencephalography (SEEG) might improve seizure outcome in 38 patients with TPE. METHODS: Inclusion criteria were as follows: epilepsy surgery performed between January 1990 and December 2001, SEEG defining a temporal plus epileptogenic zone, unilobar temporal operations ("temporal lobe epilepsy [TLE] surgery") or multilobar interventions including the temporal lobe ("TPE surgery"), magnetic resonance imaging either normal or showing signs of hippocampal sclerosis, and postoperative follow-up of at least 12 months. For each assessment of postoperative seizure outcome, at 1, 2, 5, and 10 years, we carried out descriptive analysis and classical tests of hypothesis, namely, Pearson χ2 test or Fisher exact test of independence on tables of frequency for each categorical variable of interest and Student t-test for each continuous variable of interest, when appropriate. RESULTS: Twenty-one patients underwent TPE surgery and 17 underwent TLE surgery with a follow-up of 12.4 ± 8.16 years. In the multivariate models, there was a significant effect of the time from surgery on Engel Class IA versus IB-IV outcome, with a steadily worsening trend from 5-year follow-up onward. TPE surgery was associated with better results than TLE surgery. SIGNIFICANCE: This study suggests that surgical outcome in patients with TPE can be improved by a tailored, multilobar resection and confirms that SEEG is mandatory when a TPE is suspected.

Development and Validation of the 5-SENSE Score to Predict Focality of the Seizure-Onset Zone as Assessed by Stereoelectroencephalography.

Importance: Stereoelectroencephalography (SEEG) has become the criterion standard in case of inconclusive noninvasive presurgical epilepsy workup. However, up to 40% of patients are subsequently not offered surgery because the seizure-onset zone is less focal than expected or cannot be identified. Objective: To predict focality of the seizure-onset zone in SEEG, the 5-point 5-SENSE score was developed and validated. Design, Setting, and Participants: This was a monocentric cohort study for score development followed by multicenter validation with patient selection intervals between February 2002 to October 2018 and May 2002 to December 2019. The minimum follow-up period was 1 year. Patients with drug-resistant epilepsy undergoing SEEG at the Montreal Neurological Institute were analyzed to identify a focal seizure-onset zone. Selection criteria were 2 or more seizures in electroencephalography and availability of complete neuropsychological and neuroimaging data sets. For validation, patients from 9 epilepsy centers meeting these criteria were included. Analysis took place between May and July 2021. Main Outcomes and Measures: Based on SEEG, patients were grouped as focal and nonfocal seizure-onset zone. Demographic, clinical, electroencephalography, neuroimaging, and neuropsychology data were analyzed, and a multiple logistic regression model for developing a score to predict SEEG focality was created and validated in an independent sample. Results: A total of 128 patients (57 women [44.5%]; median [range] age, 31 [13-58] years) were analyzed for score development and 207 patients (97 women [46.9%]; median [range] age, 32 [16-70] years) were analyzed for validation. The score comprised the following 5 predictive variables: focal lesion on structural magnetic resonance imaging, absence of bilateral independent spikes in scalp electroencephalography, localizing neuropsychological deficit, strongly localizing semiology, and regional ictal scalp electroencephalography onset. The 5-SENSE score had an optimal mean (SD) probability cutoff for identifying a focal seizure-onset zone of 37.6 (3.5). Area under the curve, specificity, and sensitivity were 0.83, 76.3% (95% CI, 66.7-85.8), and 83.3% (95% CI, 72.30-94.1), respectively. Validation showed 76.0% (95% CI, 67.5-84.0) specificity and 52.3% (95% CI, 43.0-61.5) sensitivity. Conclusions and Relevance: High specificity in score development and validation confirms that the 5-SENSE score predicts patients where SEEG is unlikely to identify a focal seizure-onset zone. It is a simple and useful tool for assisting clinicians to reduce unnecessary invasive diagnostic burden on patients and overutilization of limited health care resources.

Correcting for physiological ripples improves epileptic focus identification and outcome prediction.

OBJECTIVE: The integration of high-frequency oscillations (HFOs; ripples [80-250 Hz], fast ripples [250-500 Hz]) in epilepsy evaluation is hampered by physiological HFOs, which cannot be reliably differentiated from pathological HFOs. We evaluated whether defining abnormal HFO rates by statistical comparison to region-specific physiological HFO rates observed in the healthy brain improves identification of the epileptic focus and surgical outcome prediction. METHODS: We detected HFOs in 151 consecutive patients who underwent stereo-electroencephalography and subsequent resective epilepsy surgery at two tertiary epilepsy centers. We compared how HFOs identified the resection cavity and predicted seizure-free outcome using two thresholds from the literature (HFO rate > 1/min; 50% of the total number of a patient's HFOs) and three thresholds based on normative rates from the Montreal Neurological Institute Open iEEG Atlas (https://mni-open-ieegatlas. RESEARCH: mcgill.ca/): global Atlas threshold, regional Atlas threshold, and regional + 10% threshold after regional Atlas correction. RESULTS: Using ripples, the regional + 10% threshold performed best for focus identification (77.3% accuracy, 27% sensitivity, 97.1% specificity, 80.6% positive predictive value [PPV], 78.2% negative predictive value [NPV]) and outcome prediction (69.5% accuracy, 58.6% sensitivity, 76.3% specificity, 60.7% PPV, 74.7% NPV). This was an improvement for focus identification (+1.1% accuracy, +17.0% PPV; p < .001) and outcome prediction (+12.0% sensitivity, +1.0% PPV; p = .05) compared to the 50% threshold. The improvement was particularly marked for foci in cortex, where physiological ripples are frequent (outcome: +35.3% sensitivity, +5.3% PPV; p = .014). In these cases, the regional + 10% threshold outperformed fast ripple rate > 1/min (+3.6% accuracy, +26.5% sensitivity, +21.6% PPV; p < .001) and seizure onset zone (+13.5% accuracy, +29.4% sensitivity, +17.0% PPV; p < .05-.01) for outcome prediction. Normalization did not improve the performance of fast ripples. SIGNIFICANCE: Defining abnormal HFO rates by statistical comparison to rates in healthy tissue overcomes an important weakness in the clinical use of ripples. It improves focus identification and outcome prediction compared to standard HFO measures, increasing their clinical applicability.