Combining neuropsychological assessment and structural neuroimaging to identify early Alzheimer's disease in a memory clinic cohort.

INTRODUCTION: The current study examined the contributions of comprehensive neuropsychological assessment and volumetric assessment of selected mesial temporal subregions on structural magnetic resonance imaging (MRI) to identify patients with amnestic mild cognitive impairment (aMCI) and mild probable Alzheimer's disease (AD) dementia in a memory clinic cohort. METHODS: Comprehensive neuropsychological assessment and automated entorhinal, transentorhinal, and hippocampal volume measurements were conducted in 40 healthy controls, 38 patients with subjective memory symptoms, 16 patients with aMCI, 16 patients with mild probable AD dementia. Multinomial logistic regression was used to compare the neuropsychological and MRI measures. RESULTS: Combining the neuropsychological and MRI measures improved group membership prediction over the MRI measures alone but did not improve group membership prediction over the neuropsychological measures alone. CONCLUSION: Comprehensive neuropsychological assessment was an important tool to evaluate cognitive impairment. The mesial temporal volumetric MRI measures contributed no diagnostic value over and above the determinations made through neuropsychological assessment.

A growth chart of brain function from infancy to adolescence based on EEG.

BACKGROUND: In children, objective, quantitative tools that determine functional neurodevelopment are scarce and rarely scalable for clinical use. Direct recordings of cortical activity using routinely acquired electroencephalography (EEG) offer reliable measures of brain function. METHODS: We developed and validated a measure of functional brain age (FBA) using a residual neural network-based interpretation of the paediatric EEG. In this cross-sectional study, we included 1056 children with typical development ranging in age from 1 month to 18 years. We analysed a 10- to 15-min segment of 18-channel EEG recorded during light sleep (N1 and N2 states). FINDINGS: The FBA had a weighted mean absolute error (wMAE) of 0.85 years (95% CI: 0.69-1.02; n = 1056). A two-channel version of the FBA had a wMAE of 1.51 years (95% CI: 1.30-1.73; n = 1056) and was validated on an independent set of EEG recordings (wMAE = 2.27 years, 95% CI: 1.90-2.65; n = 723). Group-level maturational delays were also detected in a small cohort of children with Trisomy 21 (Cohen's d = 0.36, p = 0.028). INTERPRETATION: A FBA, based on EEG, is an accurate, practical and scalable automated tool to track brain function maturation throughout childhood with accuracy comparable to widely used physical growth charts. FUNDING: This research was supported by the National Health and Medical Research Council, Australia, Helsinki University Diagnostic Center Research Funds, Finnish Academy, Finnish Paediatric Foundation, and Sigrid Juselius Foundation.

Association between patent foramen ovale and migraine: evidence from a resting-state fMRI study.

A relationship between migraine without aura (MO) and patent foramen ovale (PFO) has been observed, but the neural basis underlying this relationship remains elusive. Utilizing independent component analysis via functional magnetic resonance imaging, we examined functional connectivity (FC) within and across networks in 146 patients with MO (75 patients with and 71 patients without PFO) and 70 healthy controls (35 patients each with and without PFO) to elucidate the individual effects of MO and PFO, as well as their interaction, on brain functional networks. The main effect of PFO manifested exclusively in the FC among the visual, auditory, default mode, dorsal attention and salience networks. Furthermore, the interaction effect between MO and PFO was discerned in brain clusters of the left frontoparietal network and lingual gyrus network, as well as the internetwork FC between the left frontoparietal network and the default mode network (DMN), the occipital pole and medial visual networks, and the dorsal attention and salience networks. Our findings suggest that the presence of a PFO shunt in patients with MO is accompanied by various FC changes within and across networks. These changes elucidate the intricate mechanisms linked to PFO-associated migraines and provide a basis for identifying novel noninvasive biomarkers.

EEG Source Imaging-Clinical Considerations for EEG Acquisition and Signal Processing for Improved Temporo-Spatial Resolution.

SUMMARY: EEG source imaging (ESI) has gained traction in recent years as a useful clinical tool for the noninvasive surgical work-up of patients with drug-resistant focal epilepsy. Despite its proven benefits for the temporo-spatial modeling of spike and seizure sources, ESI remains widely underused in clinical practice. This partly relates to a lack of clarity around an optimal approach to the acquisition and processing of scalp EEG data for the purpose of ESI. Here, we describe some of the practical considerations for the clinical application of ESI. We focus on patient preparation, the impact of electrode number and distribution across the scalp, the benefit of averaging raw data for signal analysis, and the relevance of modeling different phases of the interictal discharge as it evolves from take-off to peak. We emphasize the importance of recording high signal-to-noise ratio data for reliable source analysis. We argue that the accuracy of modeling cortical sources can be improved using higher electrode counts that include an inferior temporal array, by averaging interictal waveforms rather than limiting ESI to single spike analysis, and by careful interrogation of earlier phase components of these waveforms. No amount of postacquisition signal processing or source modeling sophistication, however, can make up for suboptimally recorded scalp EEG data in a poorly prepared patient.

Validating ASHS-T1 automated entorhinal and transentorhinal cortical segmentation in Alzheimer's disease.

The current study aimed to validate entorhinal and transentorhinal cortical volumes measured by the automated segmentation tool Automatic Segmentation of Hippocampal Subfields (ASHS-T1). The study sample comprised 34 healthy controls (HCs), 37 individuals with amnestic mild cognitive impairment (aMCI), and 29 individuals with Alzheimer's disease (AD) dementia from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Entorhinal and transentorhinal cortical volumes were assessed using ASHS-T1, manual segmentation, as well as a widely used automated segmentation tool, FreeSurfer v6.0.1. Mean differences, intraclass correlation coefficients, and Bland-Altman plots were computed. ASHS-T1 tended to underestimate entorhinal and transentorhinal cortical volumes relative to manual segmentation and FreeSurfer. There was variable consistency and low agreement between ASHS-T1 and manual segmentation volumes. There was low-to-moderate consistency and low agreement between ASHS-T1 and FreeSurfer volumes. There was a trend toward higher consistency and agreement for the entorhinal cortex in the aMCI and AD groups compared to the HC group. Despite the differences in volume measurements, ASHS-T1 was sensitive to entorhinal and transentorhinal cortical atrophy in both early and late disease stages. Based on the current study, ASHS-T1 appears to be a promising tool for automated entorhinal and transentorhinal cortical volume measurement in individuals with likely underlying AD.

Dynamical Network Models From EEG and MEG for Epilepsy Surgery-A Quantitative Approach.

There is an urgent need for more informative quantitative techniques that non-invasively and objectively assess strategies for epilepsy surgery. Invasive intracranial electroencephalography (iEEG) remains the clinical gold standard to investigate the nature of the epileptogenic zone (EZ) before surgical resection. However, there are major limitations of iEEG, such as the limited spatial sampling and the degree of subjectivity inherent in the analysis and clinical interpretation of iEEG data. Recent advances in network analysis and dynamical network modeling provide a novel aspect toward a more objective assessment of the EZ. The advantage of such approaches is that they are data-driven and require less or no human input. Multiple studies have demonstrated success using these approaches when applied to iEEG data in characterizing the EZ and predicting surgical outcomes. However, the limitations of iEEG recordings equally apply to these studies-limited spatial sampling and the implicit assumption that iEEG electrodes, whether strip, grid, depth or stereo EEG (sEEG) arrays, are placed in the correct location. Therefore, it is of interest to clinicians and scientists to see whether the same analysis and modeling techniques can be applied to whole-brain, non-invasive neuroimaging data (from MRI-based techniques) and neurophysiological data (from MEG and scalp EEG recordings), thus removing the limitation of spatial sampling, while safely and objectively characterizing the EZ. This review aims to summarize current state of the art non-invasive methods that inform epilepsy surgery using network analysis and dynamical network models. We also present perspectives on future directions and clinical applications of these promising approaches.

Virtual intracranial EEG signals reconstructed from MEG with potential for epilepsy surgery.

Modelling the interactions that arise from neural dynamics in seizure genesis is challenging but important in the effort to improve the success of epilepsy surgery. Dynamical network models developed from physiological evidence offer insights into rapidly evolving brain networks in the epileptic seizure. A limitation of previous studies in this field is the dependence on invasive cortical recordings with constrained spatial sampling of brain regions that might be involved in seizure dynamics. Here, we propose virtual intracranial electroencephalography (ViEEG), which combines non-invasive ictal magnetoencephalographic imaging (MEG), dynamical network models and a virtual resection technique. In this proof-of-concept study, we show that ViEEG signals reconstructed from MEG alone preserve critical temporospatial characteristics for dynamical approaches to identify brain areas involved in seizure generation. We show the non-invasive ViEEG approach may have some advantage over intracranial electroencephalography (iEEG). Future work may be designed to test the potential of the virtual iEEG approach for use in surgical management of epilepsy.

Agreement Between Automated and Manual MRI Volumetry in Alzheimer's Disease: A Systematic Review and Meta-Analysis.

BACKGROUND: Automated magnetic resonance imaging (MRI) volumetry is a promising tool to evaluate regional brain volumes in dementia and especially Alzheimer's disease (AD). PURPOSE: To compare automated methods and the gold standard manual segmentation in measuring regional brain volumes on MRI across healthy controls, patients with mild cognitive impairment, and patients with dementia due to AD. STUDY TYPE: Systematic review and meta-analysis. DATA SOURCES: MEDLINE, Embase, and PsycINFO were searched through October 2021. FIELD STRENGTH: 1.0 T, 1.5 T, or 3.0 T. ASSESSMENT: Two review authors independently identified studies for inclusion and extracted data. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). STATISTICAL TESTS: Standardized mean differences (SMD; Hedges' g) were pooled using random-effects meta-analysis with robust variance estimation. Subgroup analyses were undertaken to explore potential sources of heterogeneity. Sensitivity analyses were conducted to examine the impact of the within-study correlation between effect estimates on the meta-analysis results. RESULTS: Seventeen studies provided sufficient data to evaluate the hippocampus, lateral ventricles, and parahippocampal gyrus. The pooled SMD for the hippocampus, lateral ventricles, and parahippocampal gyrus were 0.22 (95% CI -0.50 to 0.93), 0.12 (95% CI -0.13 to 0.37), and -0.48 (95% CI -1.37 to 0.41), respectively. For the hippocampal data, subgroup analyses suggested that the pooled SMD was invariant across clinical diagnosis and field strength. Subgroup analyses could not be conducted on the lateral ventricles data and the parahippocampal gyrus data due to insufficient data. The results were robust to the selected within-study correlation value. DATA CONCLUSION: While automated methods are generally comparable to manual segmentation for measuring hippocampal, lateral ventricle, and parahippocampal gyrus volumes, wide 95% CIs and large heterogeneity suggest that there is substantial uncontrolled variance. Thus, automated methods may be used to measure these regions in patients with AD but should be used with caution. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

Interictal spike localization for epilepsy surgery using magnetoencephalography beamforming.

OBJECTIVE: Magnetoencephalography (MEG) kurtosis beamforming is an automated localization method for focal epilepsy. Visual examination of virtual sensors, which are source activities reconstructed by beamforming, can improve performance but can be time-consuming for neurophysiologists. We propose a framework to automate the method and evaluate its effectiveness against surgical resections and outcomes. METHODS: We retrospectively analyzed MEG recordings of 13 epilepsy surgery patients who had one-year minimum post-operative follow-up. Kurtosis beamforming was applied and manual inspection was confined to morphological clusters. The region with the Maximum Interictal Spike Frequency (MISF) was validated against prospectively modelled sLORETA solutions and surgical resections linked to outcome. RESULTS: Our approach localized spikes in 12 out of 13 patients. In eight patients with Engel I surgical outcomes, beamforming MISF regions were concordant with surgical resection at overlap level for five patients and at lobar level for three patients. The MISF regions localized to spike onset and propagation modelled by sLORETA in two and six patients, respectively. CONCLUSIONS: Automated beamforming using MEG can predict postoperative seizure freedom at the lobar level but tends to localize propagated MEG spikes. SIGNIFICANCE: MEG beamforming may contribute to non-invasive procedures to predict surgical outcome for patients with drug-refractory focal epilepsy.

Combined Isoflurane-Remifentanil Anaesthesia Permits Resting-State fMRI in Children with Severe Epilepsy and Intellectual Disability.

Head motion is a significant barrier to functional MRI (fMRI) in patients who are unable to tolerate awake scanning, including young children or those with cognitive and behavioural impairments. General anaesthesia minimises motion and ensures patient comfort, however the optimal anaesthesia regimen for fMRI in the paediatric setting is unknown. In this study, we tested the feasibility of anaesthetised fMRI in 11 patients (mean age = 9.8 years) with Lennox-Gastaut syndrome, a severe form of childhood-onset epilepsy associated with intellectual disability. fMRI was acquired during clinically-indicated MRI sessions using a synergistic anaesthesia regimen we typically administer for epilepsy neurosurgery: combined low-dose isoflurane (≤ 0.8% end-tidal concentration) with remifentanil (≤ 0.1 mcg/kg/min). Using group-level independent component analysis, we assessed the presence of resting-state networks by spatially comparing results in the anaesthetised patients to resting-state network templates from the 'Generation R' study of 536 similarly-aged non-anaesthetised healthy children (Muetzel et al. in Hum Brain Mapp 37(12):4286-4300, 2016). Numerous resting-state networks commonly studied in non-anaesthetised healthy children were readily identifiable in the anaesthetised patients, including the default-mode, sensorimotor, and frontoparietal networks. Independent component time-courses associated with these networks showed spectral characteristics suggestive of a neuronal origin of fMRI signal fluctuations, including high dynamic range and temporal frequency power predominantly below 0.1 Hz. These results demonstrate the technical feasibility of anaesthetised fMRI in children, suggesting that combined isoflurane-remifentanil anaesthesia may be an effective strategy to extend the emerging clinical applications of resting-state fMRI (for example, neurosurgical planning) to the variety of patient groups who may otherwise be impractical to scan.

Performance gains with Compute Unified Device Architecture-enabled eddy current correction for diffusion MRI.

Correcting for eddy currents, movement-induced distortion and gradient inhomogeneities is imperative when processing diffusion MRI (dMRI) data, but is highly computing resource-intensive. Recently, Compute Unified Device Architecture (CUDA) was implemented for the widely-used eddy-correction software, 'eddy', which reduces processing time and allows more comprehensive correction. We investigated processing speed, performance and compatibility of CUDA-enabled eddy-current correction processing compared to commonly-used non-CUDA implementations. Four representative dMRI datasets from the Human Connectome Project, Alzheimer's Disease Neuroimaging Initiative and Chronic Diseases Connectome Project were processed on high-specification and regular workstations through three different configurations of 'eddy'. Processing times and graphics processing unit (GPU) resources used were monitored and compared. Using CUDA reduced the 'eddy' processing time by a factor of up to five. The CUDA slice-to-volume correction method was also faster than non-CUDA eddy except when datasets were large. We make a series of recommendations for eddy configuration and hardware. We suggest that users of eddy-correction software for dMRI processing utilise CUDA and take advantage of the slice-to-volume correction option. We recommend that users run eddy on computers with at least 32GB motherboard random access memory (RAM), and a graphics card with at least 4.5GB RAM and 3750 cores to optimise processing time.

Focal cortical hypermetabolism in atypical benign rolandic epilepsy.

OBJECTIVE: Atypical benign rolandic epilepsy (BRE) is an underrecognized and poorly understood manifestation of a common epileptic syndrome. Most consider it a focal epileptic encephalopathy in which frequent, interictal, centrotemporal spikes lead to negative motor seizures and interfere with motor and sometimes speech and cognitive abilities. We observed focal cortical hypermetabolism on PET in three children with atypical BRE and investigated the spatial and temporal relationship with their centrotemporal spikes. METHODS: EEG, MRI and PET were performed clinically in three children with atypical BRE. The frequency and source localization of centrotemporal spikes was determined and compared with the location of maximal metabolic activity on PET. RESULTS: Cortical hypermetabolism on thresholded PET t-maps and current density reconstructions of centrotemporal spikes overlapped in each child, in the central sulcus region, the distances between the "centers of maxima" being 2 cm or less. Hypermetabolism was not due to recent seizures or frequent centrotemporal spikes at the time of FDG uptake. SIGNIFICANCE: The findings suggest that localized, increased cortical activity, in the region of the EEG focus, underlies the negative clinical manifestations of atypical BRE. Similar findings are reported in the broader group of epileptic encephalopathies associated with electrical status epilepticus in sleep.

The epileptic network of Lennox-Gastaut syndrome: Cortically driven and reproducible across age.

OBJECTIVE: To identify brain regions underlying interictal generalized paroxysmal fast activity (GPFA), and their causal interactions, in children and adults with Lennox-Gastaut syndrome (LGS). METHODS: Concurrent scalp EEG-fMRI was performed in 2 separately analyzed patient groups with LGS: 10 children (mean age 8.9 years) scanned under isoflurane-remifentanil anesthesia and 15 older patients (mean age 31.7 years) scanned without anesthesia. Whole-brain event-related analysis determined GPFA-related activation in each group. Results were used as priors in a dynamic causal modeling (DCM) analysis comparing evidence for different neuronal hypotheses describing initiation and propagation of GPFA between cortex, thalamus, and brainstem. RESULTS: A total of 1,045 GPFA events were analyzed (cumulative duration 1,433 seconds). In both pediatric and older groups, activation occurred in distributed association cortical areas, as well as the thalamus and brainstem (p < 0.05, corrected for family-wise error). Activation was similar across individual patients with structural, genetic, and unknown etiologies of epilepsy, particularly in frontoparietal cortex. In both groups, DCM revealed that GPFA was most likely driven by prefrontal cortex, with propagation occurring first to the brainstem and then from brainstem to thalamus. CONCLUSIONS: We show reproducible evidence of a cortically driven process within the epileptic network of LGS. This network is present early (in children) and late (in older patients) in the course of the syndrome and across diverse etiologies of epilepsy, suggesting that LGS reflects shared "secondary network" involvement. A cortical-to-subcortical hierarchy is postulated whereby GPFA rapidly propagates from prefrontal cortex to the brainstem via extrapyramidal corticoreticular pathways, whereas the thalamus is engaged secondarily.

Comparative Utility of Manual versus Automated Segmentation of Hippocampus and Entorhinal Cortex Volumes in a Memory Clinic Sample.

Structural neuroimaging is a useful non-invasive biomarker commonly employed to evaluate the integrity of mesial temporal lobe structures that are typically compromised in Alzheimer's disease. Advances in quantitative neuroimaging have permitted the development of automated segmentation protocols (e.g., FreeSurfer) with significantly increased efficiency compared to earlier manual techniques. While these protocols have been found to be suitable for large-scale, multi-site research studies, we were interested in assessing the practical utility and reliability of automated FreeSurfer protocols compared to manual volumetry on routinely acquired clinical scans. Independent validation studies with newer automated segmentation protocols are scarce. Two FreeSurfer protocols for each of two regions of interest-the hippocampus and entorhinal cortex-were compared against manual volumetry. High reliability and agreement was found between FreeSurfer and manual hippocampal protocols, however, there was lower reliability and agreement between FreeSurfer and manual entorhinal protocols. Although based on a the relatively small sample of subjects drawn from a memory clinic (n = 27), our study findings suggest further refinements to improve measurement error and most accurately depict true regional brain volumes using automated segmentation protocols are required, especially for non-hippocampal mesial temporal structures, to achieve maximal utility for routine clinical evaluations.

Interictal and ictal source localization for epilepsy surgery using high-density EEG with MEG: a prospective long-term study.

Drug-resistant focal epilepsy is a major clinical problem and surgery is under-used. Better non-invasive techniques for epileptogenic zone localization are needed when MRI shows no lesion or an extensive lesion. The problem is interictal and ictal localization before propagation from the epileptogenic zone. High-density EEG (HDEEG) and magnetoencephalography (MEG) offer millisecond-order temporal resolution to address this but co-acquisition is challenging, ictal MEG studies are rare, long-term prospective studies are lacking, and fundamental questions remain. Should HDEEG-MEG discharges be assessed independently [electroencephalographic source localization (ESL), magnetoencephalographic source localization (MSL)] or combined (EMSL) for source localization? Which phase of the discharge best characterizes the epileptogenic zone (defined by intracranial EEG and surgical resection relative to outcome)? Does this differ for interictal and ictal discharges? Does MEG detect mesial temporal lobe discharges? Thirteen patients (10 non-lesional, three extensive-lesional) underwent synchronized HDEEG-MEG (72-94 channel EEG, 306-sensor MEG). Source localization (standardized low-resolution tomographic analysis with MRI patient-individualized boundary-element method) was applied to averaged interictal epileptiform discharges (IED) and ictal discharges at three phases: 'early-phase' (first latency 90% explained variance), 'mid-phase' (first of 50% rising-phase, 50% mean global field power), 'late-phase' (negative peak). 'Earliest-solution' was the first of the three early-phase solutions (ESL, MSL, EMSL). Prospective follow-up was 3-21 (median 12) months before surgery, 14-39 (median 21) months after surgery. IEDs (n = 1474) were recorded, seen in: HDEEG only, 626 (42%); MEG only, 232 (16%); and both 616 (42%). Thirty-three seizures were captured, seen in: HDEEG only, seven (21%); MEG only, one (3%); and both 25 (76%). Intracranial EEG was done in nine patients. Engel scores were I (9/13, 69%), II (2/13,15%), and III (2/13). MEG detected baso-mesial temporal lobe epileptogenic zone sources. Epileptogenic zone OR [odds ratio(s)] were significantly higher for earliest-solution versus early-phase IED-surgical resection and earliest-solution versus all mid-phase and late-phase solutions. ESL outperformed EMSL for ictal-surgical resection [OR 3.54, 95% confidence interval (CI) 1.09-11.55, P = 0.036]. MSL outperformed EMSL for IED-intracranial EEG (OR 4.67, 95% CI 1.19-18.34, P = 0.027). ESL outperformed MSL for ictal-surgical resection (OR 3.73, 95% CI 1.16-12.03, P = 0.028) but was outperformed by MSL for IED-intracranial EEG (OR 0.18, 95% CI 0.05-0.73, P = 0.017). Thus, (i) HDEEG and MEG source solutions more accurately localize the epileptogenic zone at the earliest resolvable phase of interictal and ictal discharges, not mid-phase (as is common practice) or late peak-phase (when signal-to-noise ratios are maximal); (ii) from empirical observation of the differential timing of HDEEG and MEG discharges and based on the superiority of ESL plus MSL over either modality alone and over EMSL, concurrent HDEEG-MEG signals should be assessed independently, not combined; (iii) baso-mesial temporal lobe sources are detectable by MEG; and (iv) MEG is not 'more accurate' than HDEEG-emphasis is best placed on the earliest signal (whether HDEEG or MEG) amenable to source localization. Our findings challenge current practice and our reliance on invasive monitoring in these patients. 10.1093/brain/awz015_video1 awz015media1 6018582479001.

Structural brain abnormalities in genetic generalized epilepsies: A systematic review and meta-analysis.

According to the International League Against Epilepsy (ILAE) definition, no structural abnormalities are present on a standard brain magnetic resonance image in genetic generalized epilepsy (GGE) patients. However, recent studies raise contradictory evidence with increasing use of quantitative magnetic resonance imaging techniques. Following PRISMA guidelines, a systematic, quantitative review was conducted using 28 peer-reviewed, case-control studies published after 1989. Furthermore, a meta-analysis with a random-effect model revealed differences in structural brain abnormalities between GGE patients and controls. Significant structural differences between GGE and healthy controls were observed with volume reductions in whole brain, thalamus, putamen, caudate, pallidum, and supplementary motor area. Furthermore, gray matter volume reduction in the right and left hemispheres, thalamus, and insula, and surface area reduction in the caudal anterior cingulate cortex were revealed, along with gray matter increase in the medial frontal gyrus. Due to methodological differences, findings should be interpreted with caution. Nevertheless, contrary to the ILAE definition, it would appear that structural brain abnormalities may be present in GGE patients. Findings are consistent with a hypothesis regarding the underlying involvement of the thalamocortical networks in the generation of generalized spike-wave discharges, but structural abnormalities appear to extend outside these regions to potentially involve attention and other cognitive domains.

Cognitive network reorganization following surgical control of seizures in Lennox-Gastaut syndrome.

We previously observed that adults with Lennox-Gastaut syndrome (LGS) show abnormal functional connectivity among cognitive networks, suggesting that this may contribute to impaired cognition. Herein we report network reorganization following seizure remission in a child with LGS who underwent functional magnetic resonance imaging (fMRI) before and after resection of a cortical dysplasia. Concurrent electroencephalography (EEG) was acquired during presurgical fMRI. Presurgical and postsurgical functional connectivity were compared using (1) graph theoretical analyses of small-world network organization and node-wise strength; and (2) seed-based analyses of connectivity within and between five functional networks. To explore the specificity of these postsurgical network changes, connectivity was further compared to nine children with LGS who did not undergo surgery. The presurgical EEG-fMRI revealed diffuse activation of association cortex during interictal discharges. Following surgery and seizure control, functional connectivity showed increased small-world organization, stronger connectivity in subcortical structures, and greater within-network integration/between-network segregation. These changes suggest network improvement, and diverged sharply from the comparison group of nonoperated children. Following surgery, this child with LGS achieved seizure control and showed extensive reorganization of networks that underpin cognition. This case illustrates that the epileptic process of LGS can directly contribute to abnormal network organization, and that this network disruption may be reversible.

Effects of a common transcranial direct current stimulation (tDCS) protocol on motor evoked potentials found to be highly variable within individuals over 9 testing sessions.

Transcranial direct current stimulation (tDCS) uses a weak electric current to modulate neuronal activity. A neurophysiologic outcome measure to demonstrate reliable tDCS modulation at the group level is transcranial magnetic stimulation engendered motor evoked potentials (MEPs). Here, we conduct a study testing the reliability of individual MEP response patterns following a common tDCS protocol. Fourteen participants (7m/7f) each underwent nine randomized sessions of 1 mA, 10 min tDCS (3 anode; 3 cathode; 3 sham) delivered using an M1/orbito-frontal electrode montage (sessions separated by an average of ~5.5 days). Fifteen MEPs were obtained prior to, immediately following and in 5 min intervals for 30 min following tDCS. TMS was delivered at 130 % resting motor threshold using neuronavigation to ensure consistent coil localization. A number of non-experimental variables were collected during each session. At the individual level, considerable variability was seen among different testing sessions. No participant demonstrated an excitatory response ≥20 % to all three anodal sessions, and no participant demonstrated an inhibitory response ≥20 % to all three cathodal sessions. Intra-class correlation revealed poor anodal and cathodal test-retest reliability [anode: ICC(2,1) = 0.062; cathode: ICC(2,1) = 0.055] and moderate sham test-retest reliability [ICC(2,1) = 0.433]. Results also revealed no significant effect of tDCS at the group level. Using this common protocol, we found the effects of tDCS on MEP amplitudes to be highly variable at the individual level. In addition, no significant effects of tDCS on MEP amplitude were found at the group level. Future studies should consider utilizing a more strict experimental protocol to potentially account for intra-individual response variations.

Does the region of epileptogenicity influence the pattern of change in cortical excitability?

OBJECTIVE: To investigate whether cortical excitability measures on transcranial magnetic stimulation (TMS) differed between groups of patients with different focal epilepsy syndromes. METHODS: 85 Patients with focal epilepsy syndromes divided into temporal and extra-temporal lobe epilepsy were studied. The cohorts were further divided into drug naïve-new onset, refractory and seizure free groups. Motor threshold (MT) and paired pulse TMS at short (2, 5, 10, 15 ms) and long (100-300 ms) interstimulus intervals (ISIs) were measured. Results were compared to those of 20 controls. RESULTS: Cortical excitability was higher at 2 & 5 ms and 250, 300 ms ISIs (p<0.01) in focal epilepsy syndromes compared to controls however significant inter-hemispheric differences in MT and the same ISIs were only seen in the drug naïve state early at onset and were much more prominent in temporal lobe epilepsy. CONCLUSION: Disturbances in cortical excitability are more confined to the affected hemisphere in temporal lobe epilepsy but only early at onset in the drug naïve state. SIGNIFICANCE: Group TMS studies show that cortical excitability measures are different in temporal lobe epilepsy and can be distinguished from other focal epilepsies early at onset in the drug naïve state. Further studies are needed to determine whether these results can be applied clinically as the utility of TMS in distinguishing between epilepsy syndromes at an individual level remains to be determined.