Global nonlinear approach for mapping parameters of neural mass models.

Neural mass models (NMMs) are important for helping us interpret observations of brain dynamics. They provide a means to understand data in terms of mechanisms such as synaptic interactions between excitatory and inhibitory neuronal populations. To interpret data using NMMs we need to quantitatively compare the output of NMMs with data, and thereby find parameter values for which the model can produce the observed dynamics. Mapping dynamics to NMM parameter values in this way has the potential to improve our understanding of the brain in health and disease. Though abstract, NMMs still comprise of many parameters that are difficult to constrain a priori. This makes it challenging to explore the dynamics of NMMs and elucidate regions of parameter space in which their dynamics best approximate data. Existing approaches to overcome this challenge use a combination of linearising models, constraining the values they can take and exploring restricted subspaces by fixing the values of many parameters a priori. As such, we have little knowledge of the extent to which different regions of parameter space of NMMs can yield dynamics that approximate data, how nonlinearities in models can affect parameter mapping or how best to quantify similarities between model output and data. These issues need to be addressed in order to fully understand the potential and limitations of NMMs, and to aid the development of new models of brain dynamics in the future. To begin to overcome these issues, we present a global nonlinear approach to recovering parameters of NMMs from data. We use global optimisation to explore all parameters of nonlinear NMMs simultaneously, in a minimally constrained way. We do this using multi-objective optimisation (multi-objective evolutionary algorithm, MOEA) so that multiple data features can be quantified. In particular, we use the weighted horizontal visibility graph (wHVG), which is a flexible framework for quantifying different aspects of time series, by converting them into networks. We study EEG alpha activity recorded during the eyes closed resting state from 20 healthy individuals and demonstrate that the MOEA performs favourably compared to single objective approaches. The addition of the wHVG objective allows us to better constrain the model output, which leads to the recovered parameter values being restricted to smaller regions of parameter space, thus improving the practical identifiability of the model. We then use the MOEA to study differences in the alpha rhythm observed in EEG recorded from 20 people with epilepsy. We find that a small number of parameters can explain this difference and that, counterintuitively, the mean excitatory synaptic gain parameter is reduced in people with epilepsy compared to control. In addition, we propose that the MOEA could be used to mine for the presence of pathological rhythms, and demonstrate the application of this to epileptiform spike-wave discharges.

Interpretable surface-based detection of focal cortical dysplasias: a Multi-centre Epilepsy Lesion Detection study.

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.

Stationary EEG pattern relates to large-scale resting state networks - An EEG-fMRI study connecting brain networks across time-scales.

Relating brain dynamics acting on time scales that differ by at least an order of magnitude is a fundamental issue in brain research. The same is true for the observation of stable dynamical structures in otherwise highly non-stationary signals. The present study addresses both problems by the analysis of simultaneous resting state EEG-fMRI recordings of 53 patients with epilepsy. Confirming previous findings, we observe a generic and temporally stable average correlation pattern in EEG recordings. We design a predictor for the General Linear Model describing fluctuations around the stationary EEG correlation pattern and detect resting state networks in fMRI data. The acquired statistical maps are contrasted to several surrogate tests and compared with maps derived by spatial Independent Component Analysis of the fMRI data. By means of the proposed EEG-predictor we observe core nodes of known fMRI resting state networks with high specificity in the default mode, the executive control and the salience network. Our results suggest that both, the stationary EEG pattern as well as resting state fMRI networks are different expressions of the same brain activity. This activity is interpreted as the dynamics on (or close to) a stable attractor in phase space that is necessary to maintain the brain in an efficient operational mode. We discuss that this interpretation is congruent with the theoretical framework of complex systems as well as with the brain's energy balance.

Atlas of lesion locations and postsurgical seizure freedom in focal cortical dysplasia: A MELD study.

OBJECTIVE: Drug-resistant focal epilepsy is often caused by focal cortical dysplasias (FCDs). The distribution of these lesions across the cerebral cortex and the impact of lesion location on clinical presentation and surgical outcome are largely unknown. We created a neuroimaging cohort of patients with individually mapped FCDs to determine factors associated with lesion location and predictors of postsurgical outcome. METHODS: The MELD (Multi-centre Epilepsy Lesion Detection) project collated a retrospective cohort of 580 patients with epilepsy attributed to FCD from 20 epilepsy centers worldwide. Magnetic resonance imaging-based maps of individual FCDs with accompanying demographic, clinical, and surgical information were collected. We mapped the distribution of FCDs, examined for associations between clinical factors and lesion location, and developed a predictive model of postsurgical seizure freedom. RESULTS: FCDs were nonuniformly distributed, concentrating in the superior frontal sulcus, frontal pole, and temporal pole. Epilepsy onset was typically before the age of 10 years. Earlier epilepsy onset was associated with lesions in primary sensory areas, whereas later epilepsy onset was associated with lesions in association cortices. Lesions in temporal and occipital lobes tended to be larger than frontal lobe lesions. Seizure freedom rates varied with FCD location, from around 30% in visual, motor, and premotor areas to 75% in superior temporal and frontal gyri. The predictive model of postsurgical seizure freedom had a positive predictive value of 70% and negative predictive value of 61%. SIGNIFICANCE: FCD location is an important determinant of its size, the age at epilepsy onset, and the likelihood of seizure freedom postsurgery. Our atlas of lesion locations can be used to guide the radiological search for subtle lesions in individual patients. Our atlas of regional seizure freedom rates and associated predictive model can be used to estimate individual likelihoods of postsurgical seizure freedom. Data-driven atlases and predictive models are essential for evidence-based, precision medicine and risk counseling in epilepsy.

White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA-Epilepsy study.

The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analysed from 1069 healthy controls and 1249 patients: temporal lobe epilepsy with hippocampal sclerosis (n = 599), temporal lobe epilepsy with normal MRI (n = 275), genetic generalized epilepsy (n = 182) and non-lesional extratemporal epilepsy (n = 193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fibre tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at P < 0.001). Across 'all epilepsies' lower fractional anisotropy was observed in most fibre tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. There were also less robust increases in mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Individuals with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced reductions in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and increased mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of diffusion abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibres in a large multicentre study of epilepsy. Overall, patients with epilepsy showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding more detailed insights into pathological substrates that may explain cognitive and psychiatric co-morbidities and be used to guide biomarker studies of treatment outcomes and/or genetic research.

Sensorimotor network hypersynchrony as an endophenotype in families with genetic generalized epilepsy: A resting-state functional magnetic resonance imaging study.

Recent evidence suggests that three specific brain networks show state-dependent levels of synchronization before, during, and after episodes of generalized spike-wave discharges (GSW) in patients with genetic generalized epilepsy (GGE). Here, we investigate whether synchronization in these networks differs between patients with GGE (n = 13), their unaffected first-degree relatives (n = 17), and healthy controls (n = 18). All subjects underwent two 10-minute simultaneous electroencephalographic-functional magnetic resonance imaging (fMRI) recordings without GSW. Whole-brain data were divided into 90 regions, and blood oxygen level-dependent (BOLD) phase synchrony in a 0.04-0.07-Hz band was estimated between all pairs of regions. Three networks were defined: (1) the network with highest synchrony during GSW events, (2) a sensorimotor network, and (3) an occipital network. Average synchrony (mean node degree) was inferred across each network over time. Notably, synchrony was significantly higher in the sensorimotor network in patients and in unaffected relatives, compared to controls. There was a trend toward higher synchrony in the GSW network in patients and in unaffected relatives. There was no difference between groups for the occipital network. Our findings provide evidence that elevated fMRI BOLD synchrony in a sensorimotor network is a state-independent endophenotype of GGE, present in patients in the absence of GSW, and present in unaffected relatives.

Abnormal temporal lobe morphology in asymptomatic relatives of patients with hippocampal sclerosis: A replication study.

We investigated gray and white matter morphology in patients with mesial temporal lobe epilepsy with hippocampal sclerosis (mTLE+HS) and first-degree asymptomatic relatives of patients with mTLE+HS. Using T1-weighted magnetic resonance imaging (MRI), we sought to replicate previously reported findings of structural surface abnormalities of the anterior temporal lobe in asymptomatic relatives of patients with mTLE+HS in an independent cohort. We performed whole-brain MRI in 19 patients with mTLE+HS, 14 first-degree asymptomatic relatives of mTLE+HS patients, and 32 healthy control participants. Structural alterations in patients and relatives compared to controls were assessed using automated hippocampal volumetry and cortical surface-based morphometry. We replicated previously reported cortical surface area contractions in the ipsilateral anterior temporal lobe in both patients and relatives compared to healthy controls, with asymptomatic relatives showing similar but less extensive changes than patients. These findings suggest morphologic abnormality in asymptomatic relatives of mTLE+HS patients, suggesting an inherited brain structure endophenotype.

Dynamic brain network states in human generalized spike-wave discharges.

Generalized spike-wave discharges in idiopathic generalized epilepsy are conventionally assumed to have abrupt onset and offset. However, in rodent models, discharges emerge during a dynamic evolution of brain network states, extending several seconds before and after the discharge. In human idiopathic generalized epilepsy, simultaneous EEG and functional MRI shows cortical regions may be active before discharges, and network connectivity around discharges may not be normal. Here, in human idiopathic generalized epilepsy, we investigated whether generalized spike-wave discharges emerge during a dynamic evolution of brain network states. Using EEG-functional MRI, we studied 43 patients and 34 healthy control subjects. We obtained 95 discharges from 20 patients. We compared data from patients with discharges with data from patients without discharges and healthy controls. Changes in MRI (blood oxygenation level-dependent) signal amplitude in discharge epochs were observed only at and after EEG onset, involving a sequence of parietal and frontal cortical regions then thalamus (P < 0.01, across all regions and measurement time points). Examining MRI signal phase synchrony as a measure of functional connectivity between each pair of 90 brain regions, we found significant connections (P < 0.01, across all connections and measurement time points) involving frontal, parietal and occipital cortex during discharges, and for 20 s after EEG offset. This network prominent during discharges showed significantly low synchrony (below 99% confidence interval for synchrony in this network in non-discharge epochs in patients) from 16 s to 10 s before discharges, then ramped up steeply to a significantly high level of synchrony 2 s before discharge onset. Significant connections were seen in a sensorimotor network in the minute before discharge onset. This network also showed elevated synchrony in patients without discharges compared to healthy controls (P = 0.004). During 6 s prior to discharges, additional significant connections to this sensorimotor network were observed, involving prefrontal and precuneus regions. In healthy subjects, significant connections involved a posterior cortical network. In patients with discharges, this posterior network showed significantly low synchrony during the minute prior to discharge onset. In patients without discharges, this network showed the same level of synchrony as in healthy controls. Our findings suggest persistently high sensorimotor network synchrony, coupled with transiently (at least 1 min) low posterior network synchrony, may be a state predisposing to generalized spike-wave discharge onset. Our findings also show that EEG onset and associated MRI signal amplitude change is embedded in a considerably longer period of evolving brain network states before and after discharge events.

An optimal strategy for epilepsy surgery: Disruption of the rich-club?

Surgery is a therapeutic option for people with epilepsy whose seizures are not controlled by anti-epilepsy drugs. In pre-surgical planning, an array of data modalities, often including intra-cranial EEG, is used in an attempt to map regions of the brain thought to be crucial for the generation of seizures. These regions are then resected with the hope that the individual is rendered seizure free as a consequence. However, post-operative seizure freedom is currently sub-optimal, suggesting that the pre-surgical assessment may be improved by taking advantage of a mechanistic understanding of seizure generation in large brain networks. Herein we use mathematical models to uncover the relative contribution of regions of the brain to seizure generation and consequently which brain regions should be considered for resection. A critical advantage of this modeling approach is that the effect of different surgical strategies can be predicted and quantitatively compared in advance of surgery. Herein we seek to understand seizure generation in networks with different topologies and study how the removal of different nodes in these networks reduces the occurrence of seizures. Since this a computationally demanding problem, a first step for this aim is to facilitate tractability of this approach for large networks. To do this, we demonstrate that predictions arising from a neural mass model are preserved in a lower dimensional, canonical model that is quicker to simulate. We then use this simpler model to study the emergence of seizures in artificial networks with different topologies, and calculate which nodes should be removed to render the network seizure free. We find that for scale-free and rich-club networks there exist specific nodes that are critical for seizure generation and should therefore be removed, whereas for small-world networks the strategy should instead focus on removing sufficient brain tissue. We demonstrate the validity of our approach by analysing intra-cranial EEG recordings from a database comprising 16 patients who have undergone epilepsy surgery, revealing rich-club structures within the obtained functional networks. We show that the postsurgical outcome for these patients was better when a greater proportion of the rich club was removed, in agreement with our theoretical predictions.

Focal Epilepsy: MR Imaging of Nonhemodynamic Field Effects by Using a Phase-cycled Stimulus-induced Rotary Saturation Approach with Spin-Lock Preparation.

Purpose To investigate whether nonhemodynamic resonant saturation effects can be detected in patients with focal epilepsy by using a phase-cycled stimulus-induced rotary saturation (PC-SIRS) approach with spin-lock (SL) preparation and whether they colocalize with the seizure onset zone and surface interictal epileptiform discharges (IED). Materials and Methods The study was approved by the local ethics committee, and all subjects gave written informed consent. Eight patients with focal epilepsy undergoing presurgical surface and intracranial electroencephalography (EEG) underwent magnetic resonance (MR) imaging at 3 T with a whole-brain PC-SIRS imaging sequence with alternating SL-on and SL-off and two-dimensional echo-planar readout. The power of the SL radiofrequency pulse was set to 120 Hz to sensitize the sequence to high gamma oscillations present in epileptogenic tissue. Phase cycling was applied to capture distributed current orientations. Voxel-wise subtraction of SL-off from SL-on images enabled the separation of T2* effects from rotary saturation effects. The topography of PC-SIRS effects was compared with the seizure onset zone at intracranial EEG and with surface IED-related potentials. Bayesian statistics were used to test whether prior PC-SIRS information could improve IED source reconstruction. Results Nonhemodynamic resonant saturation effects ipsilateral to the seizure onset zone were detected in six of eight patients (concordance rate, 0.75; 95% confidence interval: 0.40, 0.94) by means of the PC-SIRS technique. They were concordant with IED surface negativity in seven of eight patients (0.88; 95% confidence interval: 0.51, 1.00). Including PC-SIRS as prior information improved the evidence of the standard EEG source models compared with the use of uninformed reconstructions (exceedance probability, 0.77 vs 0.12; Wilcoxon test of model evidence, P < .05). Nonhemodynamic resonant saturation effects resolved in patients with favorable postsurgical outcomes, but persisted in patients with postsurgical seizure recurrence. Conclusion Nonhemodynamic resonant saturation effects are detectable during interictal periods with the PC-SIRS approach in patients with epilepsy. The method may be useful for MR imaging-based detection of neuronal currents in a clinical environment. (©) RSNA, 2016 Online supplemental material is available for this article.

Epileptic networks are strongly connected with and without the effects of interictal discharges.

OBJECTIVE: Epilepsy is increasingly considered as the dysfunction of a pathologic neuronal network (epileptic network) rather than a single focal source. We aimed to assess the interactions between the regions that comprise the epileptic network and to investigate their dependence on the occurrence of interictal epileptiform discharges (IEDs). METHODS: We analyzed resting state simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) recordings in 10 patients with drug-resistant focal epilepsy with multifocal IED-related blood oxygen level-dependent (BOLD) responses and a maximum t-value in the IED field. We computed functional connectivity (FC) maps of the epileptic network using two types of seed: (1) a 10-mm diameter sphere centered in the global maximum of IED-related BOLD map, and (2) the independent component with highest correlation to the IED-related BOLD map, named epileptic component. For both approaches, we compared FC maps before and after regressing out the effect of IEDs in terms of maximum and mean t-values and percentage of map overlap. RESULTS: Maximum and mean FC maps t-values were significantly lower after regressing out IEDs at the group level (p < 0.01). Overlap extent was 85% ± 12% and 87% ± 12% when the seed was the 10-mm diameter sphere and the epileptic component, respectively. SIGNIFICANCE: Regions involved in a specific epileptic network show coherent BOLD fluctuations independent of scalp EEG IEDs. FC topography and strength is largely preserved by removing the IED effect. This could represent a signature of a sustained pathologic network with contribution from epileptic activity invisible to the scalp EEG.

Theta burst stimulation over premotor cortex in Parkinson's disease: an explorative study on manual dexterity.

Dorsal pre-motor cortex (PMd) is thought to play a role in fine motor control. The aim of the present study was to investigate whether inhibitory or excitatory stimulation of PMd would have an impact on manual dexterity in Parkinson's disease (PD). Fifteen patients with PD participated in this study. High resolution structural MRI was used for neuro-navigated TBS. Participants were targeted with one train of TBS in three experimental sessions: sham stimulation over vertex, continuous TBS (cTBS) over PMd and intermittent TBS (iTBS) over PMd, respectively. Dexterity was measured by a coin rotation task (CRT), which is a valid measure to detect limb kinetic apraxia (LKA). Neither cTBS or iTBS significantly interfered with CRT. Post hoc sub-analysis in a group of PD patients (n = 5) with stronger baseline impairment, indicating LKA, revealed further deterioration of dexterous performance for the cTBS condition (p = 0.04). This sham controlled pilot study demonstrates that TBS over PMd does not significantly interfere with dexterity in PD. However, patients with dexterous impairment qualifying for LKA may be more susceptible to TBS.

Dynamic directed interictal connectivity in left and right temporal lobe epilepsy.

OBJECTIVE: There is increasing evidence that epileptic activity involves widespread brain networks rather than single sources and that these networks contribute to interictal brain dysfunction. We investigated the fast-varying behavior of epileptic networks during interictal spikes in right and left temporal lobe epilepsy (RTLE and LTLE) at a whole-brain scale using directed connectivity. METHODS: In 16 patients, 8 with LTLE and 8 with RTLE, we estimated the electrical source activity in 82 cortical regions of interest (ROIs) using high-density electroencephalography (EEG), individual head models, and a distributed linear inverse solution. A multivariate, time-varying, and frequency-resolved Granger-causal modeling (weighted Partial Directed Coherence) was applied to the source signal of all ROIs. A nonparametric statistical test assessed differences between spike and baseline epochs. Connectivity results between RTLE and LTLE were compared between RTLE and LTLE and with neuropsychological impairments. RESULTS: Ipsilateral anterior temporal structures were identified as key drivers for both groups, concordant with the epileptogenic zone estimated invasively. We observed an increase in outflow from the key driver already before the spike. There were also important temporal and extratemporal ipsilateral drivers in both conditions, and contralateral only in RTLE. A different network pattern between LTLE and RTLE was found: in RTLE there was a much more prominent ipsilateral to contralateral pattern than in LTLE. Half of the RTLE patients but none of the LTLE patients had neuropsychological deficits consistent with contralateral temporal lobe dysfunction, suggesting a relationship between connectivity changes and cognitive deficits. SIGNIFICANCE: The different patterns of time-varying connectivity in LTLE and RTLE suggest that they are not symmetrical entities, in line with our neuropsychological results. The highest outflow region was concordant with invasive validation of the epileptogenic zone. This enhanced characterization of dynamic connectivity patterns could better explain cognitive deficits and help the management of epilepsy surgery candidates.

Detecting functional hubs of ictogenic networks.

Quantitative EEG (qEEG) has modified our understanding of epileptic seizures, shifting our view from the traditionally accepted hyper-synchrony paradigm toward more complex models based on re-organization of functional networks. However, qEEG measurements are so far rarely considered during the clinical decision-making process. To better understand the dynamics of intracranial EEG signals, we examine a functional network derived from the quantification of information flow between intracranial EEG signals. Using transfer entropy, we analyzed 198 seizures from 27 patients undergoing pre-surgical evaluation for pharmaco-resistant epilepsy. During each seizure we considered for each network the in-, out- and total "hubs", defined respectively as the time and the EEG channels with the maximal incoming, outgoing or total (bidirectional) information flow. In the majority of cases we found that the hubs occur around the middle of seizures, and interestingly not at the beginning or end, where the most dramatic EEG signal changes are found by visual inspection. For the patients who then underwent surgery, good postoperative clinical outcome was on average associated with a higher percentage of out- or total-hubs located in the resected area (for out-hubs p = 0.01, for total-hubs p = 0.04). The location of in-hubs showed no clear predictive value. We conclude that the study of functional networks based on qEEG measurements may help to identify brain areas that are critical for seizure generation and are thus potential targets for focused therapeutic interventions.

Focal hemodynamic patterns of status epilepticus detected by susceptibility weighted imaging (SWI).

OBJECTIVE: To investigate pathological findings in the susceptibility weighted imaging (SWI) of patients experiencing convulsive (CSE) or non-convulsive status epilepticus (NCSE) with focal hyperperfusion in the acute setting. METHODS: Twelve patients (six with NCSE confirmed by electroencephalogram (EEG) and six patients with CSE with seizure event clinically diagnosed) underwent MRI in this acute setting (mean time between onset of symptoms and MRI was 3 h 8 min), including SWI, dynamic susceptibility contrast MR imaging (DSC) and diffusion-weighted imaging (DWI). MRI sequences were retrospectively evaluated and compared with EEG findings (10/12 patients), and clinical symptoms. RESULTS: Twelve out of 12 (100 %) patients showed a focal parenchymal area with pseudo-narrowed cortical veins on SWI, associated with focal hyperperfused areas (increased cerebral blood flow (CBF) and mean transit time (MTT) shortening), and cortical DWI restriction in 6/12 patients (50 %). Additionally, these areas were associated with ictal or postical EEG patterns in 8/10 patients (80 %). Most frequent acute clinical findings were aphasia and/or hemiparesis in eight patients, and all of them showed pseudo-narrowed veins in those parenchymal areas responsible for these symptoms. CONCLUSION: In this study series with CSE and NCSE patients, SWI showed focally pseudo-narrowed cortical veins in hyperperfused and ictal parenchymal areas. Therefore, SWI might have the potential to identify an ictal region in CSE/NCSE. KEY POINTS: • The focal ictal brain regions show hyperperfusion in DSC MR-perfusion imaging. • SWI shows focally diminished cortical veins in hyperperfused ictal regions. • SWI has the potential to identify a focal ictal region in CSE/NCSE.

Lesion location predicts transient and extended risk of aspiration after supratentorial ischemic stroke.

BACKGROUND AND PURPOSE: To assess the association of lesion location and risk of aspiration and to establish predictors of transient versus extended risk of aspiration after supratentorial ischemic stroke. METHODS: Atlas-based localization analysis was performed in consecutive patients with MRI-proven first-time acute supratentorial ischemic stroke. Standardized swallowing assessment was carried out within 8±18 hours and 7.8±1.2 days after admission. RESULTS: In a prospective, longitudinal analysis, 34 of 94 patients (36%) were classified as having acute risk of aspiration, which was extended (≥7 days) or transient (<7 days) in 17 cases. There were no between-group differences in age, sex, cause of stroke, risk factors, prestroke disability, lesion side, or the degree of age-related white-matter changes. Correcting for stroke volume and National Institutes of Health Stroke Scale with a multiple logistic regression model, significant adjusted odds ratios in favor of acute risk of aspiration were demonstrated for the internal capsule (adjusted odds ratio, 6.2; P<0.002) and the insular cortex (adjusted odds ratio, 4.8; P<0.003). In a multivariate model of extended versus transient risk of aspiration, combined lesions of the frontal operculum and insular cortex was the only significant independent predictor of poor recovery (adjusted odds ratio, 33.8; P<0.008). CONCLUSIONS: Lesions of the insular cortex and the internal capsule are significantly associated with acute risk of aspiration after stroke. Combined ischemic infarctions of the frontal operculum and the insular cortex are likely to cause extended risk of aspiration in stroke patients, whereas risk of aspiration tends to be transient in subcortical stroke.

Heterogeneity of resting-state EEG features in juvenile myoclonic epilepsy and controls.

Abnormal EEG features are a hallmark of epilepsy, and abnormal frequency and network features are apparent in EEGs from people with idiopathic generalized epilepsy in both ictal and interictal states. Here, we characterize differences in the resting-state EEG of individuals with juvenile myoclonic epilepsy and assess factors influencing the heterogeneity of EEG features. We collected EEG data from 147 participants with juvenile myoclonic epilepsy through the Biology of Juvenile Myoclonic Epilepsy study. Ninety-five control EEGs were acquired from two independent studies [Chowdhury et al. (2014) and EU-AIMS Longitudinal European Autism Project]. We extracted frequency and functional network-based features from 10 to 20 s epochs of resting-state EEG, including relative power spectral density, peak alpha frequency, network topology measures and brain network ictogenicity: a computational measure of the propensity of networks to generate seizure dynamics. We tested for differences between epilepsy and control EEGs using univariate, multivariable and receiver operating curve analysis. In addition, we explored the heterogeneity of EEG features within and between cohorts by testing for associations with potentially influential factors such as age, sex, epoch length and time, as well as testing for associations with clinical phenotypes including anti-seizure medication, and seizure characteristics in the epilepsy cohort. P-values were corrected for multiple comparisons. Univariate analysis showed significant differences in power spectral density in delta (2-5 Hz) (P = 0.0007, hedges' g = 0.55) and low-alpha (6-9 Hz) (P = 2.9 × 10-8, g = 0.80) frequency bands, peak alpha frequency (P = 0.000007, g = 0.66), functional network mean degree (P = 0.0006, g = 0.48) and brain network ictogenicity (P = 0.00006, g = 0.56) between epilepsy and controls. Since age (P = 0.009) and epoch length (P = 1.7 × 10-8) differed between the two groups and were potential confounders, we controlled for these covariates in multivariable analysis where disparities in EEG features between epilepsy and controls remained. Receiver operating curve analysis showed low-alpha power spectral density was optimal at distinguishing epilepsy from controls, with an area under the curve of 0.72. Lower average normalized clustering coefficient and shorter average normalized path length were associated with poorer seizure control in epilepsy patients. To conclude, individuals with juvenile myoclonic epilepsy have increased power of neural oscillatory activity at low-alpha frequencies, and increased brain network ictogenicity compared with controls, supporting evidence from studies in other epilepsies with considerable external validity. In addition, the impact of confounders on different frequency-based and network-based EEG features observed in this study highlights the need for careful consideration and control of these factors in future EEG research in idiopathic generalized epilepsy particularly for their use as biomarkers.

Distinguishing transient from persistent tactile agnosia after partial anterior circulation infarcts - Behavioral and neuroimaging evidence for white matter disconnection.

From a cohort of 36 patients presenting apperceptive tactile agnosia after first cortical ischemic stroke, 14 showed temporary impairment at admission. A previous multi-voxel analysis of the cortical lesions, using as explanatory variable the course of tactile object recognition performance over the recovery period of 9 months, partitioned the cohort into three subgroups. Of the 14 patients constituting two of the subgroups, 7 recovered from their impairment whereas 7 did not. These two subgroups could not be distinguished at admission. The primary aim of the present study is to present two assessments that can do so. The first assessment comprises a pattern of behavioral measures, determined via principal component analysis, encoded in three tests: picking small objects, macrogeometrical discrimination and tactile object recognition. The receiver operating characteristic curve derived from permutation of the behavioral test scores yielded an 80% probability of correct identification of the patient subgroup and an 8% probability for false identification. As done with the permuted scores, the pattern could predict the persistence of affliction of new stroke patients with tactile agnosia. The second predictive assessment extends our previous evaluation of cortical MRI lesion maps to include subcortical regions. Confirming our previous study, the lesions of the persistently impaired subgroup disrupted significantly the anterior arcuatus fasciculus and associated superior longitudinal fasciculus III in the ipsilesional hemisphere, impeding reciprocal information transfer between supramarginal gyrus and both the ventral premotor cortex and Brodmann area 44. Due to the importance of interhemispheric information transfer in tactile agnosia, we performed a supplementary analysis of tactile object recognition scores. It showed that haptic information transfer from the non-affected to the affected hands in the persistent cases partly restored function during the nine months, possibly following restoration of functional interhemispheric haptic information transfer at the border of posterior corpus callosum and splenium. In conclusion, the combined findings of the cortical lesion at subarea PFt of the inferior parietal lobule and the associated subcortical tract lesions permit almost perfect prediction of persistent impairment of tactile object recognition. The study substantiates the need for combined analysis of both cortical lesions and white matter tract disconnections.

First Human In Vivo Neuroelectrophysiology Recordings of Uncrossed Dentatothalamocortical White-Matter Connections: On the Fast Tract.

OBJECTIVES: We aim to demonstrate intraoperative recording of cerebellar to cortical pathways that have not been previously recorded in humans, though imaged. METHODS: We report 2 cases with intraoperative neurophysiologic mapping of cerebellocortical tracts. Direct electrical stimulation of subcortical cerebellum along with recordings of cortical evoked potential and motor muscle recordings was performed during surgery. MR tractography data from healthy participants were used to further illustrate the pathways. RESULTS: Neurophysiologic recordings showed large waveforms of evoked potentials in bilateral electrodes over premotor/motor cortices on stimulation of the dentate nucleus. EMG recordings showed responses in face and neck muscles on stimulation of the dentate nucleus at the motor threshold. We thus demonstrated first-in-human in vivo neurophysiologic evidence of cerebellum to cortex responses through an uncrossed dentatothalamocortical tract to the motor/premotor cortices. DISCUSSION: This technique provides a methodology for the direct mapping of the cerebellum and cerebello-cerebral connections. We hypothesize a direct structural connection from the dentate nucleus to the premotor and motor cortices, as well as to ipsilateral hemibody muscles, acting as a fast route of cerebellar output and back up for immediate motor responses. This will further help explain the modulatory effects of the cerebellum on motor, language, and cognitive functions.