Making Chiral Salen Complexes Work with Organocatalysts.

Bisimine derivatives of salicylaldehyde with chiral diamines (salens) are privileged ligands in asymmetric organometallic catalysis, which can be used in cooperation with organocatalysts as additives. The latter can be a modifier of the metal reactivity by liganding or a true co-catalyst working in tandem or in a dual system. All scenarios encountered in the literature are reviewed and classified according to the organocatalyst. In each case, mechanistic and physical-organic chemistry considerations are discussed to better understand the gears of these complex catalytic settings.

Evoked responses to single pulse electrical stimulation reveal impaired striatal excitability in a rat model of Parkinson's disease.

BACKGROUND: Sensorimotor beta oscillations are increased in Parkinson's disease (PD) due to the alteration of dopaminergic transmission. This electrophysiological read-out is reported both in patients and in animal models such as the 6-OHDA rat model obtained with unilateral nigral injection of 6-hydroxydopamine (6-OHDA). Current treatments, based on dopaminergic replacement, transiently normalize this pathological beta activity and improve patients' quality of life. OBJECTIVES: We wanted to assess in vivo whether the abnormal beta oscillations can be correlated with impaired striatal or cortical excitability of the sensorimotor system and modulated by the pharmacological manipulation of the dopaminergic system. METHODS: In the unilateral 6-OHDA rat model and control animals, we used intra-striatal and intra-cortical single-pulse electrical stimulation (SPES) and concurrent local field potentials (LFP) recordings. In the two groups, we quantified basal cortico-striatal excitability from time-resolved spectral analyses of LFP evoked responses induced remotely by intracerebral stimulations. The temporal dependance of cortico-striatal excitability to dopaminergic transmission was further tested using electrophysiological recordings combined with levodopa injection. RESULTS: LFP evoked responses after striatal stimulation showed a transient reduction of power in a large time-frequency domain in the 6-OHDA group compared to the sham group. This result was specific to the striatum, as no significant difference was observed in cortical LFP evoked responses between the two groups. This impaired striatal excitability in the 6-OHDA group was observed in the striatum at least during the first 3 months after the initial lesion. In addition, the striatum responses to SPES during a levodopa challenge showed a transient potentiation of the decrease of responsiveness in frequencies below 40 Hz. CONCLUSION: The spectral properties of striatal responses to SPES show high sensitivity to dopaminergic transmission in the unilateral 6-OHDA rat model. We thus propose that this approach could be used in preclinical models as a time-resolved biomarker of impaired dopaminergic transmission capable of monitoring progressive neurodegeneration and/or challenges to drug intake.

Neocortical and medial temporal seizures have distinct impacts on brain responsiveness.

Focal epileptic seizures are characterized by abnormal neuronal discharges that can spread to other cortical areas and interfere with brain activity, thereby altering the patient's experience and behavior. The origin of these pathological neuronal discharges encompasses various mechanisms that converge toward similar clinical manifestations. Recent studies have suggested that medial temporal lobe (MTL) and neocortical (NC) seizures are often underpinned by two characteristic onset patterns, which, respectively, affect and spare synaptic transmission in cortical slices. However, these synaptic alterations and their effects have never been confirmed or studied in intact human brains. To fill this gap, we here evaluate whether responsiveness of MTL and NC are differentially affected by focal seizures, using a unique data set of cortico-cortical evoked potentials (CCEPs) collected during seizures triggered by single-pulse electrical stimulation (SPES). We find that responsiveness is abruptly reduced by the onset of MTL seizures, despite increased spontaneous activity, whereas it is preserved in the case of NC seizures. The present results provide an extreme example of dissociation between responsiveness and activity and show that brain networks are diversely affected by the onset of MTL and NC seizures, thus extending at the whole brain level the evidence of synaptic alteration found in vitro.

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.

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.

Exploring the spatial resolution of TMS-EEG coupling on the sensorimotor region.

The use of TMS-EEG coupling as a neuroimaging tool for the functional exploration of the human brain recently gained strong interest. If this tool directly inherits the fine temporal resolution from EEG, its spatial counterpart remains unknown. In this study, we explored the spatial resolution of TMS-EEG coupling by evaluating the minimal distance between two stimulated cortical sites that would significantly evoke different response dynamics. TMS evoked responses were mapped on the sensorimotor region in twenty participants. The stimulation grid was composed of nine targets separated between 10 and 15 mm on average. The dynamical signatures of TMS evoked activity were extracted and compared between sites using both local and remote linear regression scores and spatial generalized mixed models. We found a significant effect of the distance between stimulated sites on their dynamical signatures, neighboring sites showing differentiable response dynamics. Besides, common dynamical signatures were also found between sites up to 25-30 mm from each other. This overlap in dynamical properties decreased with distance and was stronger between sites within the same Brodmann area. Our results suggest that the spatial resolution of TMS-EEG coupling might be at least as high as 10 mm. Furthermore, our results reveal an anisotropic spatial resolution that was higher across than within the same Brodmann areas, in accordance with the TMS induced E-field modeling. Common cytoarchitectonic leading to shared dynamical properties within the same Brodmann area could also explain this anisotropy. Overall, these findings suggest that TMS-EEG benefits from the spatial resolution of TMS, which makes it an accurate technique for meso-scale brain mapping.

Optimization of sampling designs for pedigrees and association studies.

In many studies, related individuals are phenotyped in order to infer how their genotype contributes to their phenotype, through the estimation of parameters such as breeding values or locus effects. When it is not possible to phenotype all the individuals, it is important to properly sample the population to improve the precision of the statistical analysis. This article studies how to optimize such sampling designs for pedigrees and association studies. Two sampling methods are developed, stratified sampling and D optimality. It is found that it is important to take account of mutation when sampling pedigrees with many generations: as the size of mutation effects increases, optimized designs sample more individuals in late generations. Optimized designs for association studies tend to improve the joint estimation of breeding values and locus effects, all the more as sample size is low and the genetic architecture of the trait is simple. When the trait is determined by few loci, they are reminiscent of classical experimental designs for regression models and tend to select homozygous individuals. When the trait is determined by many loci, locus effects may be difficult to estimate, even if an optimized design is used.

Large-scale study validates that regional fungicide applications are major determinants of resistance evolution in the wheat pathogen Zymoseptoria tritici in France.

In modern cropping systems, the near-universal use of plant protection products selects for resistance in pest populations. The emergence and evolution of this adaptive trait threaten treatment efficacy. We identified determinants of fungicide resistance evolution and quantified their effects at a large spatiotemporal scale. We focused on Zymoseptoria tritici, which causes leaf blotch in wheat. Phenotypes of qualitative or quantitative resistance to various fungicides were monitored annually, from 2004 to 2017, at about 70 sites throughout 22 regions of France (territorial units of 25 000 km2 on average). We modelled changes in resistance frequency with regional anti-Septoria fungicide use, yield losses due to the disease and the regional area under organic wheat. The major driver of resistance dynamics was fungicide use at the regional scale. We estimated its effect on the increase in resistance and relative apparent fitness of each resistance phenotype. The predictions of the model replicated the spatiotemporal patterns of resistance observed in field populations (R2 from 0.56 to 0.82). The evolution of fungicide resistance is mainly determined at the regional scale. This study therefore showed that collective management at the regional scale could effectively complete local actions.

Mapping the Insula with Stereo-Electroencephalography: The Emergence of Semiology in Insula Lobe Seizures.

OBJECTIVE: Insula epilepsy is rare and can be evaluated effectively by Stereotactic intracerebral EEG (SEEG). Many previous studies of insulo-opercular seizures have been unable to separate insular and opercular onset. With adequate sampling of the insula, this study shows this is possible. METHODS: We analyzed intrainsular dynamics and extrainsular propagation in 12 patients with "pure" insula epilepsy (n = 9) or insular and only deepest opercular involvement (n = 3) at seizure onset. Review of semiology defined clinical groups, agglomerative cluster, and principal component analysis of semiological features were performed. Quantitative epileptogenicity, and intrainsular and extrainsular propagation were computed via time frequency analysis and epileptogenicity mapping. RESULTS: Seizure onset patterns were heterogeneous; the seizure onset zone was focal. Seizure onset and first ictal change within insula functional subdivision correlated with aura and reflex component. No paninsular spread occurred; contralateral insular spread was very early. While the discharge was intrainsular, clinical signs related to aura or vegetative signs. Extrainsular propagation was early and related to the emergence of the majority of clinical signs. Cluster analysis found an anterior, intermediate, and posterior insula seizure onset group. The largest principal component separated anterior insula manifestations, including early hypermotor signs, early recovery, and no aura from posterior insula features of early dystonia, early tonic motor features, and sensorimotor aura. INTERPRETATION: Aura is vital to identifying seizure onset and relates to insula functional subdivision. Seizures are heterogenous; extrainsular propagation occurs early, accounting for most of the semiology. With adequate sampling, "pure" insula epilepsy can be identified and focal curative resection is possible. ANN NEUROL 2020;88:477-488.

Probing regional cortical excitability via input-output properties using transcranial magnetic stimulation and electroencephalography coupling.

The modular organization of the cortex refers to subsets of highly interconnected nodes, sharing specific cytoarchitectural and dynamical properties. These properties condition the level of excitability of local pools of neurons. In this study, we described TMS evoked potentials (TEP) input-output properties to provide new insights into regional cortical excitability. We combined robotized TMS with EEG to disentangle region-specific TEP from threshold to saturation and describe their oscillatory contents. Twenty-two young healthy participants received robotized TMS pulses over the right primary motor cortex (M1), the right dorsolateral prefrontal cortex (DLPFC) and the right superior occipital lobe (SOL) at five stimulation intensities (40, 60, 80, 100, and 120% resting motor threshold) and one short-interval intracortical inhibition condition during EEG recordings. Ten additional subjects underwent the same experiment with a realistic sham TMS procedure. The results revealed interregional differences in the TEPs input-output functions as well as in the responses to paired-pulse conditioning protocols, when considering early local components (<80 ms). Each intensity in the three regions was associated with complex patterns of oscillatory activities. The quality of the regression of TEPs over stimulation intensity was used to derive a new readout for cortical excitability and dynamical properties, revealing lower excitability in the DLPFC, followed by SOL and M1. The realistic sham experiment confirmed that these early local components were not contaminated by multisensory stimulations. This study provides an entirely new analytic framework to characterize input-output relations throughout the cortex, paving the way to a more accurate definition of local cortical excitability.

Hubs disruption in mesial temporal lobe epilepsy. A resting-state fMRI study on a language-and-memory network.

Mesial temporal lobe epilepsy (mTLE) affects the brain networks at several levels and patients suffering from mTLE experience cognitive impairment for language and memory. Considering the importance of language and memory reorganization in this condition, the present study explores changes of the embedded language-and-memory network (LMN) in terms of functional connectivity (FC) at rest, as measured with functional MRI. We also evaluate the cognitive efficiency of the reorganization, that is, whether or not the reorganizations support or allow the maintenance of optimal cognitive functioning despite the seizure-related damage. Data from 37 patients presenting unifocal mTLE were analyzed and compared to 48 healthy volunteers in terms of LMN-FC using two methods: pairwise correlations (region of interest [ROI]-to-ROI) and graph theory. The cognitive efficiency of the LMN-FC reorganization was measured using correlations between FC parameters and language and memory scores. Our findings revealed a large perturbation of the LMN hubs in patients. We observed a hyperconnectivity of limbic areas near the dysfunctional hippocampus and mainly a hypoconnectivity for several cortical regions remote from the dysfunctional hippocampus. The loss of FC was more important in left mTLE (L-mTLE) than in right (R-mTLE) patients. The LMN-FC reorganization may not be always compensatory and not always useful for patients as it may be associated with lower cognitive performance. We discuss the different connectivity patterns obtained and conclude that interpretation of FC changes in relation to neuropsychological scores is important to determine cognitive efficiency, suggesting the concept of "connectome" would gain to be associated with a "cognitome" concept.

Probabilistic mapping of language networks from high frequency activity induced by direct electrical stimulation.

Direct electrical stimulation (DES) at 50 Hz is used as a gold standard to map cognitive functions but little is known about its ability to map large-scale networks and specific subnetwork. In the present study, we aim to propose a new methodological approach to evaluate the specific hypothesis suggesting that language errors/dysfunction induced by DES are the result of large-scale network modification rather than of a single cortical region, which explains that similar language symptoms may be observed after stimulation of different cortical regions belonging to this network. We retrospectively examined 29 patients suffering from focal drug-resistant epilepsy who benefitted from stereo-electroencephalographic (SEEG) exploration and exhibited language symptoms during a naming task following 50 Hz DES. We assessed the large-scale language network correlated with behavioral DES-induced responses (naming errors) by quantifying DES-induced changes in high frequency activity (HFA, 70-150 Hz) outside the stimulated cortical region. We developed a probabilistic approach to report the spatial pattern of HFA modulations during DES-induced language errors. Similarly, we mapped the pattern of after-discharges (3-35 Hz) occurring after DES. HFA modulations concurrent to language symptoms revealed a brain network similar to our current knowledge of language gathered from standard brain mapping. In addition, specific subnetworks could be identified within the global language network, related to different language processes, generally described in relation to the classical language regions. Spatial patterns of after-discharges were similar to HFA induced during DES. Our results suggest that this new methodological DES-HFA mapping is a relevant approach to map functional networks during SEEG explorations, which would allow to shift from "local" to "network" perspectives.

Deep brain stimulation of the subthalamic nucleus in obsessive-compulsives disorders: long-term follow-up of an open, prospective, observational cohort.

BACKGROUND: Obsessive-compulsive disorder (OCD) is a major cause of disability in western country and responsible for severe impairment of quality of life. About 10% of patients present with severe OCD symptoms and require innovative treatment such as deep brain stimulation (DBS). Among possible targets, the non-motor subthalamic nucleus (STN) is a key node of the basal ganglia circuitry, strongly connected to limbic cortical areas known to be involved in OCD. METHOD: We analysed, in a prospective, observational, monocentric, open label cohort, the effect of chronic non-motor STN-DBS in 19 patients with treatment-resistant OCD consecutively operated in a single centre. Severity of OCD was evaluated using the Yale and Brown Obsessive-Compulsive Scale (YBOCS). YBOCS scores at 6, 12 and 24 months postoperatively were compared with baseline. Responders were defined by >35% improvement of YBOCS scores. Global Assessment Functioning (GAF) scale was used to evaluate the impact of improvement. RESULTS: At a 24-month follow-up, the mean YBOCS score improved by 53.4% from 33.3±3.5 to 15.8±9.1 (95% CI 11.2-20.4; p<0.0001). Fourteen out of 19 patients were considered as responders, 5 out of 19 being improved over 75% and 10 out of 19 over 50%. GAF scale improved by 92% from 34.1±3.9 to 66.4±18.8 (95% CI 56.7-76.1; p=0.0003). The most frequent adverse events consisted of transient DBS-induced hypomania and anxiety. CONCLUSION: Chronic DBS of the non-motor STN is an effective and relatively safe procedure to treat severe OCD resistant to conventional management.

A Chemical History of Polycyclic Musks.

Musk odorants are ubiquitous in fine perfumery as well as household products, and are divided into four main families, the nitromusks, the macrocyclic musks, the polycyclic aromatic musks, and the alicyclic musks, following their order of appearance on the perfumery market. This article presents the scientific and industrial adventures during the discovery of the seven commercial polycyclic musks, which invigorated the aroma chemistry corporations during the second half of the 20th century, resulting in relentless competition. Research and development strategies are exposed, and reactivity, analytical, mechanistic, and structure-activity relationships aspects are discussed as well as some biographical elements of the main scientific actors, and some fine perfumery examples are given as illustrations of their use.

Bayesian inference of natural selection from spatiotemporal phenotypic data.

Spatiotemporal variations of natural selection may influence the evolution of various features of organisms such as local adaptation or specialisation. This article develops a method for inferring how selection varies between locations and between generations from phenotypic data. It is assumed that generations are non-overlapping and that individuals reproduce by selfing or asexually. A quantitative genetics model taking account of the effects of stabilising natural selection, the environment and mutation on phenotypic means and variances is developed. Explicit results on the evolution of populations are derived and used to develop a Bayesian inference method. The latter is applied to simulated data and to data from a wheat participatory plant breeding programme. It has some ability to infer evolutionary parameters, but estimates may be sensitive to prior distributions, for example when phenotypic time series are short and when environmental effects are large. In such cases, sensitivity to prior distributions may be reported or more data may be collected.

Sensory coding is impaired in rat absence epilepsy.

KEY POINTS: Absence epilepsy is characterized by the occurrence of spike-and-wave discharges concomitant with an alteration of consciousness and is associated with cognitive comorbidities. In a genetic model of absence epilepsy in the rat, the genetic absence epilepsy rat from Strasbourg (GAERS), spike-and-wave discharges are shown to be initiated in the barrel field primary somatosensory cortex that codes whisker-related information, therefore playing an essential role in the interactions of rodents with their environment. Sensory-information processing is impaired in the epileptic barrel field primary somatosensory cortex of GAERS, with a delayed sensory-evoked potential and a duplicated neuronal response to whisker stimulation in in vivo extracellular recordings. Yet, GAERS present no defaults of performance in a texture discrimination task, suggesting the existence of a compensatory mechanism within the epileptic neuronal network. The results of the present study indicate that physiological primary functions are processed differently in an epileptic cortical network. ABSTRACT: Several neurodevelopmental pathologies are associated with disorganized cortical circuits that may alter primary functions such as sensory processes. In the present study, we investigated whether the function of a cortical area is altered in the seizure onset zone of absence epilepsy, a prototypical form of childhood genetic epilepsy associated with cognitive impairments. We first combined in vivo multichannel electrophysiological recordings and histology to precisely localize the seizure onset zone in the genetic absence epilepsy rat from Strasbourg (GAERS). We then investigated the functionality of this epileptic zone using extracellular silicon probe recordings of sensory-evoked local field potentials and multi-unit activity, as well as a behavioural test of texture discrimination. We show that seizures in this model are initiated in the barrel field part of the primary somatosensory cortex and are associated with high-frequency oscillations. In this cortex, we found an increased density of parvalbumin-expressing interneurons in layer 5 in GAERS compared to non-epileptic Wistar rats. Its functional investigation revealed that sensory abilities of GAERS are not affected in a texture-discrimination task, whereas the intracortical processing of sensory-evoked information is delayed and duplicated. Altogether, these results suggest that absence seizures are associated with an increase of parvalbumin-inhibitory neurons, which may promote the functional relationship between epileptic oscillations and high-frequency activities. Our findings suggest that cortical circuits operate differently in the epileptic onset zone and may adapt to maintain their ability to process highly specialized information.

Spike discharge characteristic of the caudal mesencephalic reticular formation and pedunculopontine nucleus in MPTP-induced primate model of Parkinson disease.

The pedunculopontine nucleus (PPN) included in the caudal mesencephalic reticular formation (cMRF) plays a key role in the control of locomotion and wake state. Regarding its involvement in the neurodegenerative process observed in Parkinson disease (PD), deep brain stimulation of the PPN was proposed to treat levodopa-resistant gait disorders. However, the precise role of the cMRF in the pathophysiology of PD, particularly in freezing of gait and other non-motor symptoms is still not clear. Here, using micro electrode recording (MER) in 2 primates, we show that dopamine depletion did not alter the mean firing rate of the overall cMRF neurons, particularly the putative non-cholinergic ones, but only a decreased activity of the regular neurons sub-group (though to be the cholinergic PPN neurons). Interestingly, a significant increase in the relative proportion of cMRF neurons with a burst pattern discharge was observed after MPTP intoxication. The present results question the hypothesis of an over-inhibition of the CMRF by the basal ganglia output structures in PD. The decreased activity observed in the regular neurons could explain some non-motor symptoms in PD regarding the strong involvement of the cholinergic neurons on the modulation of the thalamo-cortical system. The increased burst activity under dopamine depletion confirms that this specific spike discharge pattern activity also observed in other basal ganglia nuclei and in different pathologies could play a mojor role in the pathophysiology of the disease and could explain several symptoms of PD including the freezing of gait. The present data will have to be replicated in a larger number of animals and will have to investigate more in details how the modification of the spike discharge of the cMRF neurons in the parkinsonian state could alter functions such as locomotion and attentional state. This will ultimely allow a better comprehension of the pathophysiology of freezing of gait.

Distinctive epileptogenic networks for parietal operculum seizures.

OBJECTIVE: The present study investigated the electroclinical features and epileptogenic networks of parietal operculum seizures (POS) by using stereoelectroencephalography (SEEG) intracerebral recordings. METHODS: Comprehensive presurgical evaluation data of seven patients with drug-resistant epilepsy with POS were analyzed retrospectively. Stereoelectroencephalography-recorded seizures were processed visually and quantitatively by using epileptogenicity mapping (EM), which has been proposed to ergonomically quantify the epileptogenicity of brain structures with a neuroimaging approach. RESULTS: Six patients reported initial somatosensory or viscerosensitive symptoms. Ictal clinical signs comprised frequently nocturnal hypermotor seizures and contralateral focal motor seizures, including tonic, tonic-clonic, or dystonic seizures of the face and limbs. Interictal and ictal scalp EEG provided information regarding lateralization in the majority of patients, but the discharges were widely distributed over perisylvian or "rolandic-like" regions and the vertex. Furthermore, two subgroups of epileptogenic network organization were identified within POS by SEEG, visually and quantitatively, using an EM approach: group 1 (mesial frontal/cingulate networks) was observed in three patients who mainly exhibited hypermotor seizures; group 2 (perisylvian networks) was observed in four patients who mainly exhibited contralateral focal motor seizures. CONCLUSION: This study indicated that POS could be characterized by initial specific somatosensory sensations, followed by either frequently nocturnal hypermotor seizures or contralateral focal motor seizures. The distinctive seizure semiology depended on the organization of two primary epileptogenic networks. This article is part of the Special Issue "Individualized Epilepsy Management: Medicines, Surgery and Beyond.

Comparison of two integration methods for dynamic causal modeling of electrophysiological data.

Dynamic causal modeling (DCM) is a methodological approach to study effective connectivity among brain regions. Based on a set of observations and a biophysical model of brain interactions, DCM uses a Bayesian framework to estimate the posterior distribution of the free parameters of the model (e.g. modulation of connectivity) and infer architectural properties of the most plausible model (i.e. model selection). When modeling electrophysiological event-related responses, the estimation of the model relies on the integration of the system of delay differential equations (DDEs) that describe the dynamics of the system. In this technical note, we compared two numerical schemes for the integration of DDEs. The first, and standard, scheme approximates the DDEs (more precisely, the state of the system, with respect to conduction delays among brain regions) using ordinary differential equations (ODEs) and solves it with a fixed step size. The second scheme uses a dedicated DDEs solver with adaptive step sizes to control error, making it theoretically more accurate. To highlight the effects of the approximation used by the first integration scheme in regard to parameter estimation and Bayesian model selection, we performed simulations of local field potentials using first, a simple model comprising 2 regions and second, a more complex model comprising 6 regions. In these simulations, the second integration scheme served as the standard to which the first one was compared. Then, the performances of the two integration schemes were directly compared by fitting a public mismatch negativity EEG dataset with different models. The simulations revealed that the use of the standard DCM integration scheme was acceptable for Bayesian model selection but underestimated the connectivity parameters and did not allow an accurate estimation of conduction delays. Fitting to empirical data showed that the models systematically obtained an increased accuracy when using the second integration scheme. We conclude that inference on connectivity strength and delay based on DCM for EEG/MEG requires an accurate integration scheme.

Probabilistic functional tractography of the human cortex revisited.

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.