SUMMARYObjective: Frontal lobe seizures are difficult to characterize according to semiologic and electrical features. We wished to establish whether different semiologic subgroups can be identified and whether these relate to anatomic organization. Methods: We assessed all seizures from 54 patients with frontal lobe epilepsy that were explored with stereoelectroencephalography (SEEG) during presurgical evaluation. Semiologic features and concomitant intracerebral EEG changes were documented and quantified. These variables were examined using Principal Component Analysis and Cluster Analysis, and semiologic features correlated with anatomic localization. Results: Four main groups of patients were identified according to semiologic features, and correlated with specific patterns of anatomic seizure localization. Group 1 was characterized clinically by elementary motor signs and involved precentral and premotor regions. Group 2 was characterized by a combination of elementary motor signs and nonintegrated gestural motor behavior, and involved both premotor and prefrontal regions. Group 3 was characterized by integrated gestural motor behavior with distal stereotypies and involved anterior lateral and medial prefrontal regions. Group 4 was characterized by seizures with fearful behavior and involved the paralimbic system (ventromedial prefrontal cortex AE anterior temporal structures). The groups were organized along a rostrocaudal axis, representing bands within a spectrum rather than rigid categories. The more anterior the seizure organization, the more likely was the occurrence of integrated behavior during seizures. Distal stereotypies were associated with the most anterior prefrontal localizations, whereas proximal stereotypies occurred in more posterior prefrontal regions. Significance: Meaningful categorization of frontal seizures in terms of semiology is possible and correlates with anatomic organization along a rostrocaudal axis, in keeping with current hypotheses of frontal lobe hierarchical organization. The proposed electroclinical categorization offers pointers as to the likely zone of organization of networks underlying semiologic production, thus aiding presurgical localization. Furthermore, analysis of ictal motor behavior in prefrontal seizures, including stereotypies, leads to deciphering the cortico-subcortical networks that produce such behaviors.

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Objective: In this study, we seek to analyze the determinants of the intracranial electroencephalography seizure onset pattern (SOP) and the impact of the SOP in predicting postsurgical seizure outcome. Methods: To this end, we analyzed 820 seizures from 252 consecutive patients explored by stereo-electroencephalography (total of 2148 electrodes), including various forms of focal refractory epilepsies. We used a reproducible method combining visual and time-frequency analyses. Results: We described eight SOPs: low-voltage fast activity (LVFA), preictal spiking followed by LVFA, burst of polyspikes followed by LVFA, slow wave/ DC shift followed by LVFA, sharp theta/alpha waves, beta sharp waves, rhythmic spikes/spike-waves, and delta-brush. LVFA occurred in 79% of patients. The seizure onset pattern was significantly associated with (1) underlying etiology (burst of polyspikes followed by LVFA with the presence of a focal cortical dysplasia, LVFA with malformation of cortical development, postvascular and undetermined epilepsies), (2) spatial organization of the epileptogenic zone (EZ; burst of polyspikes followed by LVFA with focal organization, slow wave/DC shift followed by LVFA with network organization), and (3) postsurgical seizure outcome (better outcome when LVFA present). Significance: This study demonstrates that the main determinants of the SOP are the underlying etiology and the spatial organization of the EZ. Concerning the postsurgical seizure outcome, the main determinant factor is the spatial organization of the EZ, but the SOP plays also a role, conferring better prognosis when LVFA is present. K E Y W O R D S epilepsy, epilepsy surgery, epileptogenic zone, focal drug-resistant epilepsy, SEEG, seizure onset | 85 SUPPORTING INFORMATION Additional supporting information may be found online in the Supporting Information section at the end of the article. How to cite this article: Lagarde S, Buzori S, Trebuchon A, et al. The repertoire of seizure onset patterns in human focal epilepsies: Determinants and prognostic values. Epilepsia. 2019;60:85-95.

Drug-refractory focal epilepsies are network diseases associated with functional connectivity alterations both during ictal and interictal periods. A large majority of studies on the interictal/resting state have focused on functional MRI-based functional connectivity. Few studies have used electrophysiology, despite its high temporal capacities. In particular, stereotactic-EEG is highly suitable to study functional connectivity because it permits direct intracranial electrophysiological recordings with relative large-scale sampling. Most previous studies in stereotactic-EEG have been directed towards temporal lobe epilepsy, which does not represent the whole spectrum of drug-refractory epilepsies. The present study aims at filling this gap, investigating interictal functional connectivity alterations behind cortical epileptic organization and its association with post-surgical prognosis. To this purpose, we studied a large cohort of 59 patients with malformation of cortical development explored by stereotactic-EEG with a wide spatial sampling (76 distinct brain areas were recorded, median of 13.2 per patient). We computed functional connectivity using non-linear correlation. We focused on three zones defined by stereotactic-EEG ictal activity: the epileptogenic zone, the propagation zone and the non-involved zone. First, we compared within-zone and between-zones functional connectivity. Second, we analysed the directionality of functional connectivity between these zones. Third, we measured the associations between functional connectivity measures and clinical variables, especially post-surgical prognosis. Our study confirms that functional connectivity differs according to the zone under investigation. We found: (i) a gradual decrease of the within-zone functional connectivity with higher values for epileptogenic zone and propagation zone, and lower for non-involved zones; (ii) preferential coupling between structures of the epileptogenic zone; (iii) preferential coupling between epileptogenic zone and propagation zone; and (iv) poorer post-surgical outcome in patients with higher functional connectivity of non-involved zone (within- non-involved zone, between non-involved zone and propagation zone functional connectivity). Our work suggests that, even during the interictal state, functional connectivity is reinforced within epileptic cortices (epileptogenic zone and propagation zone) with a gradual organization. Moreover, larger functional connectivity alterations, suggesting more diffuse disease, are associated with poorer post-surgical prognosis. This is consistent with computational studies suggesting that connectivity is crucial in order to model the spatiotemporal dynamics of seizures.10.1093/brain/awy214_video1awy214media15833456182001.

The hippocampus and amygdala are key brain structures of the medial temporal lobe, involved in cognitive and emotional processes as well as pathological states such as epilepsy. Despite their importance, it is still unclear whether their  neural activity can be recorded non-invasively. Here, using simultaneous intracerebral and magnetoencephalography (MEG) recordings in patients with focal drug-resistant epilepsy, we demonstrate a direct contribution of amygdala and hippocampal activity to surface MEG recordings. In particular, a method of blind source separation, independent component analysis, enabled activity arising from large neocortical networks to be disentangled from that of deeper structures, whose amplitude at the surface was small but significant. This finding is highly relevant for our understanding of hippocampal and amygdala brain activity as it implies that their activity could potentially be measured non-invasively.

In patients with pharmaco-resistant focal epilepsies investigated with intracranial electroencephalography (iEEG), direct electrical stimulations of a cortical region induce cortico-cortical evoked potentials (CCEP) in distant cerebral cortex, which properties can be used to infer large scale brain connectivity. In 2013, we proposed a new probabilistic functional tractography methodology to study human brain connectivity. We have now been revisiting this method in the F-TRACT project (f-tract.eu) by developing a large multicenter CCEP database of several thousand stimulation runs performed in several hundred patients, and associated processing tools to create a probabilistic atlas of human cortico-cortical connections. Here, we wish to present a snapshot of the methods and data of F-TRACT using a pool of 213 epilepsy patients, all studied by stereo-encephalography with intracerebral depth electrodes. The CCEPs were processed using an automated pipeline with the following consecutive steps: detection of each stimulation run from stimulation artifacts in raw intracranial EEG (iEEG) files, bad channels detection with a machine learning approach, model-based stimulation artifact correction, robust averaging over stimulation pulses. Effective connectivity between the stimulated and recording areas is then inferred from the properties of the first CCEP component, i.e. onset and peak latency, amplitude, duration and integral of the significant part. Finally, group statistics of CCEP features are implemented for each brain parcel explored by iEEG electrodes. The localization (coordinates, white/gray matter relative positioning) of electrode contacts were obtained from imaging data (anatomical MRI or CT scans before and after electrodes implantation). The iEEG contacts were repositioned in different brain parcellations from the segmentation of patients' anatomical MRI or from templates in the MNI coordinate system. The F-TRACT database using the first pool of 213 patients provided connectivity probability values for 95% of possible intrahemispheric and 56% of interhemispheric connections and CCEP features for 78% of intrahemisheric and 14% of interhemispheric connections. In this report, we show some examples of anatomo-functional connectivity matrices, and associated directional maps. We also indicate how CCEP features, especially latencies, are related to spatial distances, and allow estimating the velocity distribution of neuronal signals at a large scale. Finally, we describe the impact on the estimated connectivity of the stimulation charge and of the contact localization according to the white or gray matter. The most relevant maps for the scientific community are available for download on f-tract. eu (David et al., 2017) and will be regularly updated during the following months with the addition of more data in the F-TRACT database. This will provide an unprecedented knowledge on the dynamical properties of large fiber tracts in human.

The goal of this study was to determine the temporal response properties of different auditory cortical areas in humans. This is achieved by recording the phase-locked neural activity to white noises modulated sinusoidally in amplitude (AM) at frequencies between 4 and 128 Hz, in the left and right cortices of 20 subjects. Phase-locked neural responses are recorded in four auditory cortical areas with intracerebral electrodes, and modulation transfer functions (MTFs) are computed from these responses. A number of MTFs are bandpass in shape, demonstrating a selective encoding of AM frequencies below 64 Hz in the auditory cortex. This result provides strong physiological support to the idea that the human auditory system decomposes the temporal envelope of sounds (such as speech) into its constituting AM components. Moreover, the results show a predominant response of cortical auditory areas to the lowest AM frequencies (4-16 Hz). This range matches the range of AM frequencies crucial for speech intelligibility, emphasizing therefore the role played by these initial stations of cortical processing in the analysis of speech. Finally, the results show differences in AM sensitivity across cortical areas and hemispheres, and provide a physiological foundation for claims of functional specialization of auditory areas based on previous population measures.

SUMMARYObjectives: The study of intracerebral electroencephalography (EEG) seizure-onset patterns is crucial to accurately define the epileptogenic zone and guide successful surgical resection. It also raises important pathophysiologic issues concerning mechanisms of seizure generation. Until now, several seizure-onset patterns have been described using distinct recording methods (subdural, depth electrode), mostly in temporal lobe epilepsies or with heterogeneous neocortical lesions. Methods: We analyzed data from a cohort of 53 consecutive patients explored by stereoelectroencephalography (SEEG) and with pathologically confirmed malformation of cortical development (MCD; including focal cortical dysplasia [FCD] and neurodevelopmental tumors [NDTs]). Results: We identified six seizure-onset patterns using visual and time-frequency analysis: low-voltage fast activity (LVFA); preictal spiking followed by LVFA; burst of polyspikes followed by LVFA; slow wave/DC shift followed by LVFA; theta/alpha sharp waves; and rhythmic spikes/spike-waves. We found a high prevalence of patterns that included LVFA (83%), indicating nevertheless that LVFA is not a constant characteristic of seizure onset. An association between seizure-onset patterns and histologic types was found (p = 001). The more prevalent patterns were as follows: (1) in FCD type I LVFA (23.1%) and slow wave/baseline shift followed by LVFA (15.4%); (2) in FCD type II burst of polyspikes followed by LVFA (31%), LVFA (27.6%), and preictal spiking followed by LVFA (27.6%); (3) in NDT, LVFA (54.5%). We found that a seizure-onset pattern that included LVFA was associated with favorable postsurgical outcome, but the completeness of the EZ resection was the sole independent predictive variable. Significance: Six different seizure-onset patterns can be described in FCD and NDT. Better postsurgical outcome is associated with patterns that incorporate LVFA.