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Human brain cellular assemblies generate emergent oscillations up to very high frequencies that can exceed the known firing rates of individual neurons. Using advanced intracranial microEEG recordings in a cohort of patients with epilepsy, we identified short-lasting local field oscillations with frequencies between 2 and 8 kHz. These ultra fast oscillations were consistently and locally detected in epileptic hippocampi but were extremely rare in normal brain tissue. The observed ultra high frequency oscillations may reflect local circuit hyperexcitability and we use a simple model to demonstrate the feasibility that these local fields are emergent oscillations representing the crest of collective high frequency neuronal unit activity.

Very high-frequency oscillations (VHFOs, > 500 Hz) are more specific in localizing the epileptogenic zone (EZ) than high-frequency oscillations (HFOs

Many methods applied to data acquired by various imaging modalities have been evaluated for their benefit in localizing lesions in magnetic resonance (MR) negative epilepsy patients. No approach has proven to be a stand‐alone method with sufficiently high sensitivity and specificity. The presented study addresses the potential benefit of the automated fusion of results of individual methods in presurgical evaluation. We collected electrophysiological, MR, and nuclear imaging data from 137 patients with pharmacoresistant MR‐negative/inconclusive focal epilepsy. A subgroup of 32 patients underwent surgical treatment with known postsurgical outcomes and histopathology. We employed a Gaussian mixture model to reveal several classes of gray matter tissue. Classes specific to epileptogenic tissue were identified and validated using the surgery subgroup divided into two disjoint sets. We evaluated the classification accuracy of the proposed method at a voxel‐wise level and assessed the effect of individual methods. The training of the classifier resulted in six classes of gray matter tissue. We found a subset of two classes specific to tissue located in resected areas. The average classification accuracy (i.e., the probability of correct classification) was significantly higher than the level of chance in the training group (0.73) and even better in the validation surgery subgroup (0.82). Nuclear imaging, diffusion‐weighted imaging, and source localization of interictal epileptic discharges were the strongest methods for classification accuracy. We showed that the automatic fusion of results can identify brain areas that show epileptogenic gray matter tissue features. The method might enhance the presurgical evaluations of MR‐negative epilepsy patients., There is no known stand‐alone imaging method for epileptogenic zone identification in nonlesional epilepsy. We examined the potential benefit of the automated fusion of results from individual methods. The proposed method can identify epileptogenic tissue with high accuracy at the voxel level, that is, at a millimeters scale.

Hippocampal high-frequency electrographic activity (HFOs) represents one of the major discoveries not only in epilepsy research but also in cognitive science over the past few decades. A fundamental challenge, however, has been the fact that physiological HFOs associated with normal brain function overlap in frequency with pathological HFOs. We investigated the impact of a cognitive task on HFOs with the aim of improving differentiation between epileptic and non-epileptic hippocampi in humans. Hippocampal activity was recorded with depth electrodes in 15 patients with focal epilepsy during a resting period and subsequently during a cognitive task. HFOs in ripple and fast ripple frequency ranges were evaluated in both conditions, and their rate, spectral entropy, relative amplitude and duration were compared in epileptic and non-epileptic hippocampi. The similarity of HFOs properties recorded at rest in epileptic and non-epileptic hippocampi suggests that they cannot be used alone to distinguish between hippocampi. However, both ripples and fast ripples were observed with higher rates, higher relative amplitudes and longer durations at rest as well as during a cognitive task in epileptic compared with non-epileptic hippocampi. Moreover, during a cognitive task, significant reductions of HFOs rates were found in epileptic hippocampi. These reductions were not observed in non-epileptic hippocampi. Our results indicate that although both hippocampi generate HFOs with similar features that probably reflect non-pathological phenomena, it is possible to differentiate between epileptic and non-epileptic hippocampi using a simple odd-ball task.

Introduction Takotsubo syndrome (TTS), also known as stress cardiomyopathy or “broken heart” syndrome, is a mysterious condition that often mimics an acute myocardial infarction. Both are characterized by left ventricular systolic dysfunction. However, this dysfunction is reversible in the majority of TTS patients. Purpose Recent studies surprisingly demonstrated that TTS, initially perceived as a benign condition, has a long-term prognosis akin to myocardial infarction. Therefore, the health consequences and societal impact of TTS are not trivial. The pathophysiological mechanisms of TTS are not yet completely understood. In the last decade, attention has been increasingly focused on the putative role of the central nervous system in the pathogenesis of TTS. Conclusion In this review, we aim to summarize the state of the art in the field of the brain–heart axis, regional structural and functional brain abnormalities, and connectivity aberrancies in TTS.

Objective The main aim of this study was to investigate the potential differences in terms of interictal high frequency oscillations (HFOs) between both hippocampi in unilateral (U-MTLE) and bilateral mesial temporal lobe epilepsy (B-MTLE). Methods Sixteen patients with MTLE underwent bilateral hippocampal depth electrode implantation as part of epilepsy surgery evaluation. Interictal HFOs were detected automatically. The analyses entail comparisons of the rates and spatial distributions of ripples and fast ripples (FR) in hippocampi and amygdalae, with respect to the eventual finding of hippocampal sclerosis (HS). Results In U-MTLE, higher ripple and FR rates were found in the hippocampi ipsilateral to the seizure onset than in the contralateral hippocampi. Non-epileptic hippocampi in U-MTLE were distinguished by significantly lower ripple rate than in the remaining analyzed hippocampi. There were not differences between the hippocampi in B-MTLE. In the hippocampi with proven HS, higher FR rates were observed in the ventral than in the dorsal parts. Conclusions Non-epileptic hippocampi in U-MTLE demonstrated significantly lower ripple rates than those epileptic in U-MTLE and B-MTLE. Significance Low interictal HFO occurrence might be considered as a marker of the non-epileptic hippocampi in MTLE.

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 (

For a correct assessment of stereo-electroencephalographic (SEEG) recordings, a proper signal electrical reference is necessary. Such a reference might be physical or virtual. Physical reference can be noisy and a proper virtual reference calculation is often time-consuming. This paper uses the variance of the SEEG signals to calculate the reference from relatively low noise signals to reduce the contamination by distant sources, while maintaining negligible computing time.Ten patients with SEEG recordings were used in this study. 20-second long recordings from each patient, sampled at 5000 Hz, were used to calculate variances of SEEG signals and a low-variance (LV) subset of signals was selected for each patient. Consequently, 4 different reference signals were calculated using: 1) an average signal from WM contacts only (AVG_WM); 2) an average signal from LV contacts only (AVG_LV); 3) independent component analysis (ICA) method from WM contacts only (ICA_WM); and 4) ICA method from LV signals only (ICA_LV). Also, the original testing reference, an average signal from all SEEG contacts (AVG) was utilized. Finally, bipolar signals and average signals from anatomical structures were calculated and used to evaluate reference signals.91.7% of the WM SEEG contacts were found below the average variance. ICA_LV showed the best and AVG_WM the worst overall results. AVG_LV had the most positive impact on minimizing the mutual correlations between separate brain structures and correcting the outliers. The average processing time for ICA methods was 66.72 seconds and 0.7870 seconds for AVG methods (100 000 samples, 125.7±20.4 SEEG signals).Utilizing the LV data subset improves the reference signal. WM references are difficult to obtain and seem to be more susceptible to errors caused by low number of WM contacts in the dataset. ICA_LV can be considered as one of the best reference estimations, however the calculation is very demanding and time consuming. AVG_LV shows good and stable results, while it is based on a straightforward methodology and outstandingly fast calculation.

Temporal lobe epilepsy (TLE) is a severe neurological disorder accompanied by recurrent spontaneous seizures. Although the knowledge of TLE onset is still incomplete, TLE pathogenesis most likely involves the aberrant expression of microRNAs (miRNAs). miRNAs play an essential role in organism homeostasis and are widely studied in TLE as potential therapeutics and biomarkers. However, many discrepancies in discovered miRNAs occur among TLE studies due to model-specific miRNA expression, different onset ages of epilepsy among patients, or technology-related bias. We employed a massive parallel sequencing approach to analyze brain tissues from 16 adult mesial TLE (mTLE)/hippocampal sclerosis (HS) patients, 8 controls and 20 rats with TLE-like syndrome, and 20 controls using the same workflow and categorized these subjects based on the age of epilepsy onset. All categories were compared to discover overlapping miRNAs with an aberrant expression, which could be involved in TLE. Our cross-comparative analyses showed distinct miRNA profiles across the age of epilepsy onset and found that the miRNA profile in rats with adult-onset TLE shows the closest resemblance to the profile in mTLE/HS patients. Additionally, this analysis revealed overlapping miRNAs between patients and the rat model, which should participate in epileptogenesis and ictogenesis. Among the overlapping miRNAs stand out miR-142-5p and miR-142-3p, which regulate immunomodulatory agents with pro-convulsive effects and suppress neuronal growth. Our cross-comparison study enhanced the insight into the effect of the age of epilepsy onset on miRNA expression and deepened the knowledge of epileptogenesis. We employed the same methodological workflow in both patients and the rat model, thus improving the reliability and accuracy of our results.

EEG signal processing is a fundamental method for neurophysiology research and clinical neurology practice. Historically the classification of EEG into physiological, pathological, or artifacts has been performed by expert visual review of the recordings. However, the size of EEG data recordings is rapidly increasing with a trend for higher channel counts, greater sampling frequency, and longer recording duration and complete reliance on visual data review is not sustainable. In this study, we publicly share annotated intracranial EEG data clips from two institutions: Mayo Clinic, MN, USA and St. Anne’s University Hospital Brno, Czech Republic. The dataset contains intracranial EEG that are labeled into three groups: physiological activity, pathological/epileptic activity, and artifactual signals. The dataset published here should support and facilitate training of generalized machine learning and digital signal processing methods for intracranial EEG and promote research reproducibility. Along with the data, we also propose a statistical method that is recommended for comparison of candidate classifier performance utilizing out-of-institution/out-of-patient testing., Measurement(s)brain measurement • physiological activity • epileptic seizure AE • Artifact • AnnotationTechnology Type(s)electroencephalography (EEG) • intracranial electroencephalography • data transformationFactor Type(s)institutionSample Characteristic - OrganismHomo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12326471

Manual and semi-automatic identification of artifacts and unwanted physiological signals in large intracerebral electroencephalographic (iEEG) recordings is time consuming and inaccurate. To date, unsupervised methods to accurately detect iEEG artifacts are not available. This study introduces a novel machine-learning approach for detection of artifacts in iEEG signals in clinically controlled conditions using convolutional neural networks (CNN) and benchmarks the method’s performance against expert annotations. The method was trained and tested on data obtained from St Anne’s University Hospital (Brno, Czech Republic) and validated on data from Mayo Clinic (Rochester, Minnesota, U.S.A). We show that the proposed technique can be used as a generalized model for iEEG artifact detection. Moreover, a transfer learning process might be used for retraining of the generalized version to form a data-specific model. The generalized model can be efficiently retrained for use with different EEG acquisition systems and noise environments. The generalized and specialized model F1 scores on the testing dataset were 0.81 and 0.96, respectively. The CNN model provides faster, more objective, and more reproducible iEEG artifact detection compared to manual approaches.

Cil: Cilem studie bylo zjistit, jakým způsobem ovlivňuje epileptochirurgicka lecba kvalitu života u pacientů operovaných pro farmakorezistentni epilepsii. Metodika: Pacienti operovani pro farmakorezistentni epilepsii vyplnili dotaznik se zaměřenim na kvalitu života (Quality of Life in Epilepsy Inventory-89, QOLIE-89) před a po operaci. QOLIE-89 hodnoti 17 podoblasti kvality života, je možne rovněž hodnotit celkovou kvalitu života pomoci celkoveho skore. Statisticky jsme vyhodnotili, zda doslo po operaci ke změně kvality života. Nasledně jsme výsledky QOLIE-89 korelovali s demografickými daty pacientů, vcetně hodnoty IQ a psychiatrických/ somatických komorbidit. Výsledky: Do studie jsme zařadili celkem 95 pacientů po resekcnim epileptochirurgickem výkonu, kteři spravně a kompletně vyplnili dotaznik před a minimalně jeden rok po operaci. Ke statisticky významnemu zlepseni dochazi v nasledujicich podoblastech: vnimani zdravi (p < 0,001), změna zdravi (p < 0,001), celkove zdravi (p < 0,001), prace/řizeni motoroveho vozidla/socialni fungovani (p < 0,001), obava ze zachvatu (p < 0,001), ztrata odvahy v souvislosti se zdravotnim stavem (p = 0,049), ucinky leků (p = 0,002) a celkova kvalita života (p = 0,001). Po operaci bylo zjistěno i statisticky významne zlepseni celkoveho skore (p = 0,008). Nebyla zjistěna statisticky významna korelace celkoveho skore s demografickými udaji. Zavěr: Na zakladě nasi dotaznikove studie můžeme konstatovat, že epileptochirurgicka lecba vede u větsiny pacientů nejen k eliminaci zachvatů, ale výrazně rovněž přispiva ke zlepseni kvality života.

SummaryObjective Mesial temporal lobe epilepsy (mTLE) is a severe neurological disorder characterized by recurrent seizures. mTLE is frequently accompanied by neurodegeneration in the hippocampus resulting in hippocampal sclerosis (HS), the most common morphological correlate of drug resistance in mTLE patients. Incomplete knowledge of pathological changes in mTLE+HS complicates its therapy. The pathological mechanism underlying mTLE+HS may involve abnormal gene expression regulation, including posttranscriptional networks involving microRNAs (miRNAs). miRNA expression deregulation has been reported in various disorders, including epilepsy. However, the miRNA profile of mTLE+HS is not completely known and needs to be addressed. Methods Here, we have focused on hippocampal miRNA profiling in 33 mTLE+HS patients and nine postmortem controls to reveal abnormally expressed miRNAs. In this study, we significantly reduced technology-related bias (the most common source of false positivity in miRNA profiling data) by combining two different miRNA profiling methods, namely next generation sequencing and miRNA-specific quantitative real-time polymerase chain reaction. Results These methods combined have identified and validated 20 miRNAs with altered expression in the human epileptic hippocampus; 19 miRNAs were up-regulated and one down-regulated in mTLE+HS patients. Nine of these miRNAs have not been previously associated with epilepsy, and 19 aberrantly expressed miRNAs potentially regulate the targets and pathways linked with epilepsy (such as potassium channels, γ-aminobutyric acid, neurotrophin signaling, and axon guidance). Significance This study extends current knowledge of miRNA-mediated gene expression regulation in mTLE+HS by identifying miRNAs with altered expression in mTLE+HS, including nine novel abnormally expressed miRNAs and their putative targets. These observations further encourage the potential of microRNA-based biomarkers or therapies.

Objective: In the present study, we aimed to investigate depth electroencephalographic (EEG) recordings in a large cohort of patients with drug-resistant epilepsy and to focus on interictal very high-frequency oscillations (VHFOs) between 500Hz and 2kHz. We hypothesized that interictal VHFOs are more specific biomarkers for epileptogenic zone compared to traditional HFOs. Methods: Forty patients with focal epilepsy who underwent presurgical stereo-EEG (SEEG) were included in the study. SEEG data were recorded with a sampling rate of 25kHz, and a 30-minute resting period was analyzed for each patient. Ten patients met selected criteria for analyses of correlations with surgical outcome: detection of interictal ripples (Rs), fast ripples (FRs), and VHFOs; resective surgery; and at least 1 year of postoperative follow-up. Using power envelope computation and visual inspection of power distribution matrixes, electrode contacts with HFOs and VHFOs were detected and analyzed. Results: Interictal very fast ripples (VFRs; 500-1,000Hz) were detected in 23 of 40 patients and ultrafast ripples (UFRs; 1,000-2,000Hz) in almost half of investigated subjects (n=19). VFRs and UFRs were observed only in patients with temporal lobe epilepsy and were recorded exclusively from mesiotemporal structures. The UFRs were more spatially restricted in the brain than lower-frequency HFOs. When compared to R oscillations, significantly better outcomes were observed in patients with a higher percentage of removed contacts containing FRs, VFRs, and UFRs. Interpretation: Interictal VHFOs are relatively frequent abnormal phenomena in patients with epilepsy, and appear to be more specific biomarkers for epileptogenic zone when compared to traditional HFOs.

Objective The purpose of the presented study is to determine whether there are frequency-independent high-frequency oscillation (HFO) parameters which may differ in epileptic and non-epileptic regions. Methods We studied 31 consecutive patients with medically intractable focal (temporal and extratemporal) epilepsies who were examined by either intracerebral or subdural electrodes. Automated detection was used to detect HFO. The characteristics (rate, amplitude, and duration) of HFO were statistically compared within three groups: the seizure onset zone (SOZ), the irritative zone (IZ), and areas outside the IZ and SOZ (nonSOZ/nonIZ). Results In all patients, fast ripples (FR) and ripples (R) were significantly more frequent and shorter in the SOZ than in the nonSOZ/nonIZ region. In the group of patients with favorable surgical outcomes, the relative amplitude of FR was higher in the SOZ than in the IZ and nonIZ/nonSOZ regions; in patients with poor outcomes, the results were reversed. The relative amplitude of R was significantly higher in the SOZ, with no difference between patients with poor and favorable surgical outcomes. Conclusions FR are more frequent, shorter, and have higher relative amplitudes in the SOZ area than in other regions. The study suggests a worse prognosis in patients with higher amplitudes of FR outside the SOZ. Significance Various HFO parameters, especially of FR, differ in epileptic and non-epileptic regions. The amplitude and duration may be as important as the frequency band and rate of HFO in marking the seizure onset region or the epileptogenic area and may provide additional information on epileptogenicity.

Objective When considering all patients with focal drug-resistant epilepsy, as high as 40–50% of patients suffer seizure recurrence after surgery. To achieve seizure freedom without side effects, accurate localization of the epileptogenic tissue is crucial before its resection. We investigate an automated, fast, objective mapping process that uses only interictal data. Methods We propose a novel approach based on multiple iEEG features, which are used to train a support vector machine (SVM) model for classification of iEEG electrodes as normal or pathologic using 30 min of inter-ictal recording. Results The tissue under the iEEG electrodes, classified as epileptogenic, was removed in 17/18 excellent outcome patients and was not entirely resected in 8/10 poor outcome patients. The overall best result was achieved in a subset of 9 excellent outcome patients with the area under the receiver operating curve = 0.95. Conclusion SVM models combining multiple iEEG features show better performance than algorithms using a single iEEG marker. Multiple iEEG and connectivity features in presurgical evaluation could improve epileptogenic tissue localization, which may improve surgical outcome and minimize risk of side effects. Significance In this study, promising results were achieved in localization of epileptogenic regions by SVM models that combine multiple features from 30 min of inter-ictal iEEG recordings.

Abstract. The aim of the current research was to study functional connectivity (FC) of the right superior temporal sulcus (rSTS) during visual target stimulus processing. This structure is presumed to be crucial in social cognition, but evidently participates in target detection as well. Twenty subjects participated in functional magnetic resonance examination for studying FC. We used psychophysiological interaction (PPI) analysis of data acquired during the visual oddball task. During the visual oddball task rSTS had increased connectivity bilaterally with structures involved in memory operations (mesiotemporal cortices and basal ganglia) and evaluative processing related to decision making (left anterior cingulate cortex). Moreover, we revealed decreased connectivity of rSTS with structures involved in attentional processes (right dorsolateral prefrontal cortex (DLPFC) and the posterior area with bilateral parietal cortex). Based on our results we hypothesize that in the detection of rare events, during visual information processing, rSTS is involved within neuronal networks related to attention, but also at later stages of stimuli processing.

The paper presents a long-term follow-up study of VNS patients, analyzing seizure outcome, medication changes, and surgical problems.74 adults with VNS for 10 to 17 years were evaluated yearly as: non-responder - NR (seizure frequency reduction50%), responder - R (reduction ≥ 50% and90%), and 90% responder - 90R (reduction ≥ 90%). Delayed R or 90R (≥ 4 years after surgery), patients with antiepileptic medication changes and battery or complete system replacement were identified. Statistical analysis of potential outcome predictors (age, seizure duration, MRI, seizure type) was performed.The rates of R and 90R related to the patients with outcome data available for the study years 1, 2, 10, and 17 were for R 38.4%, 51.4%, 63.6%, and 77.8%, and for 90R 1.4%, 5.6%, 15.1%, and 11.1%. The absolute numbers of R and 90R increased until years 2 and 6. Antiepileptic therapy was changed in 62 patients (87.9%). There were 11 delayed R and four delayed 90R, with medication changes in the majority. At least one battery replacement was performed in 51 patients (68.9%), 49 of whom R or 90R. VNS system was completely replaced in 7 patients (9.5%) and explanted in 7 NR (9.5%). No significant predictor of VNS outcome was found.After an initial increase, the rate of R and 90R remains stable in long-term follow-up. The changes of antiepileptic treatment in most patients potentially influence the outcome. Battery replacements or malfunctioning system exchange reflect the patient's satisfaction and correlate with good outcomes.

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. he research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 616268 “F-TRACT”. All the computations presented in this paper were performed using the CIMENT infrastructure (https://ciment.ujf-grenoble.fr), which is supported by the Rhône-Alpes region (GRANT CPER07_13 CIRA: http://www.ci-ra.org). We thank Bruno Bzenik and Romain Cavagna for their help on the CIMENT facility, and Jean-François Mangin and Cyril Poupon from Neurospin, CEA Saclay, for providing us with the ARCHI DTI database.

Visual information is transferred via the optic pathway and processed by an interaction of the striate cortex with visual associative areas. These areas evaluate different properties of the signal and contribute to an overall perception of the visual environment. Lesions of associative cortices in humans cause the so-called central visual disorders that may accompany homonymous visual field defects. An understanding of the functions of these areas is important, as many of these patients will first contact an ophthalmologist, usually with vague complaints that may be difficult to specifically define. This chapter gives an overview of central visual disorders that can be found in patients with homonymous visual field defects and of the principles of neurological and neuropsychological examination in these patients.

Introduction Morphological correlates of nonpathological déjà vu (DV) have been identified recently within the human brain. Significantly reduced gray matter volume (GMV) within a set of cortical and subcortical regions reported in subjects experiencing DV seems to mirror the distribution of GMV reduction in mesial temporal lobe epilepsy (MTLE) patients but vary in terms of the hippocampus. Another condition associated with hippocampal GMV reduction and DV alike disturbance in memory processing is schizophrenia (SCH). Here, we tested the hypothesis that hippocampal involvement in nonpathological DV resembles more closely the pattern of GMV decrease observed in MTLE compared with that occurring in SCH. Methods Using automated segmentation of the MRI data we compared the medians of GMV within 12 specific hippocampal subfields in healthy individuals that do (DV+; N = 87) and do not report déjà vu experience (DV−; N = 26), and patients with MTLE (N = 47) and SCH (N = 29). By Pearson correlation, we then evaluated the similarity of MTLE and SCH groups to DV+ group with respect to spatial distribution of GMV deviation from DV− group. Results Significant GMV decrease was found in MTLE group in most of the subfields. There were just trends in the hippocampal GMV decrease found in DV+ or SCH groups. Concerning the spatial distribution of GMV decrease, we revealed statistically significant correlation for the left hippocampus for SCH vs DV+. Otherwise there was no statistically significant correlation. Conclusions Our findings reveal structural features of hippocampal involvement in nonpathological DV, MTLE, and SCH. Despite our expectations, the pattern of GMV reduction in the DV+ relative to the DV− group does not resemble the pattern observed in MTLE any more than that observed in SCH. The highly similar patterns of the three clinical groups rather suggest an increased vulnerability of certain hippocampal subfields; namely, Cornu Ammonis (CA)4, CA3, dentate gyrus granular cell layer (GC‐DG), hippocampal–amygdaloid transition area (HATA) and subiculum.

Objective: We compared the possible contribution (in the detection of seizure onset zone – SOZ) of simple visual assessment of intracerebrally recorded high-frequency oscillations (HFO) with standard automated detection. Methods: We analyzed stereo-EEG (SEEG) recordings from 20 patients with medically intractable partial seizures (10 temporal/10 extratemporal). Independently using simple visual assessment and automated detection of HFO, we identified the depth electrode contacts with maximum occurrences of ripples (R) and fast ripples (FR). The SOZ was determined by independent visual identification in standard SEEG recordings, and the congruence of results from visual versus automated HFO detection was compared. Results: Automated detection of HFO correctly identified the SOZ in 14 (R)/10 (FR) out of 20 subjects; a simple visual assessment of SEEG recordings in the appropriate frequency ranges correctly identified the SOZ in 13 (R)/9 (FR) subjects. Conclusions: Simple visual assessment of SEEG traces and standard automated detection of HFO seem to contribute comparably to the identification of the SOZ in patients with focal epilepsies. When using macroelectrodes in neocortical extratemporal epilepsies, the SOZ might be better determined by the ripple range. Significance: Standard automated detection of HFO enables the evaluation of HFO characteristics in whole data. This detection allows general purpose and objective evaluation, without any bias from the neurophysiologist’s experiences and practice

Purpose: To determine whether voxel-based morphometry (VBM) might contribute to the detection of cortical dysplasia within the temporal pole in patients with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE/ HS). Key Findings: Histopathologic examination revealed cortical dysplasia within the temporal pole in 11 patients. Significance: We found that VBM made a superior contribution to the detection of temporopolar structural malformations (cortical dysplasia) compared to visual inspection. The agreement with postoperative histopathologic proof was clearly significant for VBM results and nonsignificant for visual inspection.

Objective Falls are not supposed to be common signs of temporal lobe epilepsy (TLE). The main aim of this study was to identify a group of patients with known history of unexpected falls which could not be explained by presence of ictal asystole or concomitant heart disesase. Methods We retrospectively evaluated the data of all patient who underwent pre-surgical evaluation in Brno Epilepsy Center since 2002. We identified 49 patients with TLE who reported unexpected falls. Thirteen (33%) out of 49 patients (TLE-falls group) underwent surgery which led to disappearance of both seizures and falls. In the next step, the control group of age- and gender- matched patients with TLE (TLE-control group) was formed. We identified RR intervals and following parameters were analyzed duration of RR intervals and heart rate variability (HRV). Results There were no statistically significant differences between TLE-falls group and TLE-surgery group regarding age of epilepsy onset, duration of epilepsy, age at surgery. Both the duration of RR intervals and HRV were statistically significantly different between TLE-falls group and TLE-control group (p = 0.025, respectively p = 0.025). Conclusion It seems that unexpected falls could be a novel rare signs in TLE epilepsy. Their presence could be conditioned by heart rhythms.

To determine whether changes in gray matter volume (GMV) differ according to the affected side in mesial temporal lobe epilepsy/hippocampal sclerosis (MTLE/HS) syndrome, and moreover to test the hypothesis of more pronounced structural changes in right-sided MTLE/HS. This hypothesis (especially that the contralateral thalamus is more affected in right-sided MTLE/HS) arose from the results of our recent study, wherein more expressed structural and functional changes were observed in a small sample of patients with right-sided MTLE/HS (Brázdil et al., 2009).Twenty patients with left-sided and 20 with right-sided MTLE/HS and 40 sex- and age-matched healthy controls were included in the study. Voxel-based morphometry (VBM) with a modulation step was applied to magnetic resonance imaging (MRI) brain images. Statistical parametric maps were used to compare structural changes between patients and controls separately for the left- and right-sided MTLE/HS subgroups. We also compared the local GMV of the brain structures (insula and thalamus) between the subgroups of patients.In the subgroup with right-sided MTLE/HS, a reduction of GMV was detected in the mesiotemporal structures and the ipsilateral thalamus (as in left-sided MTLE/HS), but also notably in the ipsilateral insula and contralateral thalamus. A statistical analysis revealed a significantly more extensive reduction of GMV in the ipsilateral/contralateral insula and the contralateral thalamus in the subgroup with right-sided compared to left-sided MTLE/HS.We found asymmetrical morphologic changes in patients with left- and right-sided MTLE/HS syndrome (more pronounced in right-sided MTLE/HS). These differences could be theoretically explained by different neuronal networks and pathophysiologic changes in temporolimbic structures.

We report on a patient who developed generalized asymmetric myoclonus associated with frontotemporal lobar degeneration with TDP-43 positive inclusions (FTLD-TDP).

To determine whether voxel-based morphometry (VBM) might contribute to the detection of cortical dysplasia within the temporal pole in patients with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE/HS).Eighteen patients with intractable MTLE/HS and 30 sex- and age-matched healthy controls were included in the study. All of the patients fulfilled the diagnostic criteria for MTLE/HS and underwent anteromedial temporal resection. VBM without a modulation step was applied to the magnetic resonance (MR) images of the brain. Statistical parametric maps were used to compare structural characteristics such as gray matter concentration (GMC) within the temporal pole among patients and controls separately. The acquired data were then statistically analyzed to determine the congruency between visually inspected MR imaging (MRI) scans and VBM results in the detection of morphologic abnormalities in the temporal pole compared to postoperative histopathologic findings of cortical dysplasia.Histopathologic examination revealed cortical dysplasia within the temporal pole in 11 patients. In detail, according to Palmini's classification, mild malformations of cortical development (mMCDs) were disclosed in three patients, focal cortical dysplasia (FCD) type Ia in three patients, and FCD type Ib in five patients. Some type of structural temporal pole abnormality was suggested by VBM in 14 patients and by visually inspected MRI scans in 11 patients. The results of VBM were in agreement with the presence/absence of cortical dysplasia in 13 patients (72.2%); this correspondence was significant (p = 0.047). In one case, VBM was false negative and in four cases it was false positive. There was congruence between the results of visual analysis and histologic proof in 55.6% of examined patients, which was not significant.We found that VBM made a superior contribution to the detection of temporopolar structural malformations (cortical dysplasia) compared to visual inspection. The agreement with postoperative histopathologic proof was clearly significant for VBM results and nonsignificant for visual inspection.

Methods. We evaluated prospectively 596 patients with pharmacoresistant seizures. All these patients underwent continuous video-EEG monitoring. In consenting patients, we used suggestive seizure provocation. The seizure semiology, inter-ictal EEG, brain MRI, psychiatric co-morbidities, and the impact of the provocative testing and other parameters on the seizure outcome were assesed. Results. In the sample of 596 monitored patients, we detected 111 (19.3%) patients with PNES. Of the 111 patients with PNES, 86.5% had spontaneous and 76.5% had provoked seizures. The five most typical symptoms – initially closed eyelids (67.6%), rapid tremor (47.7%), asynchronous limb movement (37.8%), preictal pseudosleep (33.3%), and side-to-side head movement (32.4%) – were presented on video. Inter-ictal EEG was rated as abnormal in 46.2% and with epileptiform abnormality in 9%. Brain MRI was abnormal in 32 (28.8%) patients. Personality disorders (46.8%), anxiety (39.6%), and depression (12.6%) were the most frequent additional psychiatric co-morbidities. Psychogenic non-epileptic seizures outcome after at least 2 years is reported; 22.5% of the patients were seizure-free; one third had markedly reduced seizure frequency. The provocative testing had no negative impact on the seizure outcome. We determined eight variables which could affect the seizure outcome. The trend to be the predictor of worse results was PNES duration before appropriate diagnosis (pb0.013). Conclusions. Video-EEG monitoring with suggestive seizure provocation supported by clinical psychiatric and psychological evaluations sig