The default mode network and altered consciousness in epilepsy

Understanding of Consciousness in Absence Seizures: A Literature Review

Absence seizures are classically associated with behavioral arrest and transient deficits in consciousness, yet substantial variability exists in the severity of the impairment. Despite several decades of research on the topic, the pathophysiology of absence seizures and the mechanisms underlying behavioral impairment remain unclear. Several rationales have been proposed including widespread cortical deactivation, reduced perception of external stimuli, and transient suspension of the default mode network, among others. This review aims to summarize the current knowledge on the neural correlates of impaired consciousness in absence seizures. We review evidence from studies using animal models of absence epilepsy, electroencephalography, functional magnetic resonance imaging, magnetoencephalography, positron emission tomography, and single photon emission computed tomography.

Machine Learning Interpretability Methods to Characterize Brain Network Dynamics in Epilepsy

The rapid adoption of machine learning (ML) algorithms in a wide range of biomedical applications has highlighted issues of trust and the lack of understanding regarding the results generated by ML algorithms. Recent studies have focused on developing interpretable ML models and establish guidelines for transparency and ethical use, ensuring the responsible integration of machine learning in healthcare. In this study, we demonstrate the effectiveness of ML interpretability methods to provide important insights into the dynamics of brain network interactions in epilepsy, a serious neurological disorder affecting more than 60 million persons worldwide. Using high-resolution intracranial electroencephalogram (EEG) recordings from a cohort of 16 patients, we developed high accuracy ML models to categorize these brain activity recordings into either seizure or non-seizure classes followed by a more complex task of delineating the different stages of seizure progression to different parts of the brain as a multi-class classification task. We applied three distinct types of interpretability methods to the high-accuracy ML models to gain an understanding of the relative contributions of different categories of brain interaction patterns, including multi-focii interactions, which play an important role in distinguishing between different states of the brain. The results of this study demonstrate for the first time that post-hoc interpretability methods enable us to understand why ML algorithms generate a given set of results and how variations in value of input values affect the accuracy of the ML algorithms. In particular, we show in this study that interpretability methods can be used to identify brain regions and interaction patterns that have a significant impact on seizure events. The results of this study highlight the importance of the integrated implementation of ML algorithms together with interpretability methods in aberrant brain network studies and the wider domain of biomedical research.

Improved Seizure Onset-Zone Lateralization in Temporal Lobe Epilepsy using 7T Resting-State fMRI: A Direct Comparison with 3T

Objective

Resting-state functional magnetic resonance imaging (rs-fMRI) at ultra high-field strengths (≥7T) is known to provide superior signal-to-noise and statistical power than comparable acquisitions at lower field strengths. In this study, we aim to provide a direct comparison of the seizure onset-zone (SOZ) lateralizing ability of 7T rs-fMRI and 3T rs-fMRI.

Methods

We investigated a cohort of 70 temporal lobe epilepsy (TLE) patients. A paired cohort of 19 patients had 3T and 7T rs-fMRI acquisitions for direct comparison between the two field strengths. Forty-three patients had only 3T, and 8 patients had only 7T rs-fMRI acquisitions. We quantified the functional connectivity between the hippocampus and other nodes within the default mode network (DMN) using seed-to-voxel connectivity, and measured how hippocampo-DMN connectivity could inform SOZ lateralization at 7T and 3T field strengths.

Results

Differences between hippocampo-DMN connectivity ipsilateral and contralateral to the SOZ were significantly higher at 7T (pFDR=0.008) than at 3T (pFDR=0.80) when measured in the same subjects. We found that our ability to lateralize the SOZ, by distinguishing subjects with left TLE from subjects with right TLE, was superior at 7T (AUC = 0.97) than 3T (AUC = 0.68). Our findings were reproduced in extended cohorts of subjects scanned at either 3T or 7T. Our rs-fMRI findings at 7T, but not 3T, are consistent and highly correlated (Spearman Rho=0.65) with clinical FDG-PET lateralizing hypometabolism.

Significance

We show superior SOZ lateralization in TLE patients when using 7T relative to 3T rs-fMRI, supporting the adoption of high-field strength functional imaging in the epilepsy presurgical evaluation.

Altered neuromagnetic activity in default mode network in childhood absence epilepsy

Purpose

The electrophysiological characterization of resting state oscillatory functional connectivity within the default mode network (DMN) during interictal periods in childhood absence epilepsy (CAE) remains unclear. Using magnetoencephalographic (MEG) recordings, this study investigated how the connectivity within the DMN was altered in CAE.

Methods

Using a cross-sectional design, we analyzed MEG data from 33 children newly diagnosed with CAE and 26 controls matched for age and sex. The spectral power and functional connectivity of the DMN were estimated using minimum norm estimation combined with the Welch technique and corrected amplitude envelope correlation.

Results

Default mode network showed stronger activation in the delta band during the ictal period, however, the relative spectral power in other bands was significantly lower than that in the interictal period (pcorrected < 0.05 for DMN regions, except bilateral medial frontal cortex, left medial temporal lobe, left posterior cingulate cortex in the theta band, and the bilateral precuneus in the alpha band). It should be noted that the significant power peak in the alpha band was lost compared with the interictal data. Compared with controls, the interictal relative spectral power of DMN regions (except bilateral precuneus) in CAE patients was significantly increased in the delta band (pcorrected < 0.01), whereas the values of all DMN regions in the beta-gamma 2 band were significantly decreased (pcorrected < 0.01). In the higher frequency band (alpha-gamma1), especially in the beta and gamma1 band, the ictal node strength of DMN regions except the left precuneus was significantly higher than that in the interictal periods (pcorrected < 0.01), and the node strength of the right inferior parietal lobe increased most significantly in the beta band (Ictal: 3.8712 vs. Interictal: 0.7503, pcorrected < 0.01). Compared with the controls, the interictal node strength of DMN increased in all frequency bands, especially the right medial frontal cortex in the beta band (Controls: 0.1510 vs. Interictal: 3.527, pcorrected < 0.01). Comparing relative node strength between groups, the right precuneus in CAE children decreased significantly (β: Controls: 0.1009 vs. Interictal: 0.0475; γ 1: Controls:0.1149 vs. Interictal:0.0587, pcorrected < 0.01) such that it was no longer the central hub.

Conclusion

These findings indicated DMN abnormalities in CAE patients, even in interictal periods without interictal epileptic discharges. Abnormal functional connectivity in CAE may reflect abnormal anatomo-functional architectural integration in DMN, as a result of cognitive mental impairment and unconsciousness during absence seizure. Future studies are needed to examine if the altered functional connectivity can be used as a biomarker for treatment responses, cognitive dysfunction, and prognosis in CAE patients.

Neuronal networks underlying ictal and subclinical discharges in childhood absence epilepsy

Childhood absence epilepsy (CAE), involves 3 Hz generalized spikes and waves discharges (GSWDs) on the electroencephalogram (EEG), associated with ictal discharges (seizures) with clinical symptoms and impairment of consciousness and subclinical discharges without any objective clinical symptoms or impairment of consciousness. This study aims to comparatively characterize neuronal networks underlying absence seizures and subclinical discharges, using source localization and functional connectivity (FC), to better understand the pathophysiological mechanism of these discharges. Routine EEG data from 12 CAE patients, consisting of 45 ictal and 42 subclinical discharges were selected. Source localization was performed using the exact low-resolution electromagnetic tomography (eLORETA) algorithm, followed by FC based on the imaginary part of coherency. FC based on the thalamus as the seed of interest showed significant differences between ictal and subclinical GSWDs (p < 0.05). For delta (1-3 Hz) and alpha bands (8-12 Hz), the thalamus displayed stronger connectivity towards other brain regions for ictal GSWDs as compared to subclinical GSWDs. For delta band, the thalamus was strongly connected to the posterior cingulate cortex (PCC), precuneus, angular gyrus, supramarginal gyrus, parietal superior, and occipital mid-region for ictal GSWDs. The strong connections of the thalamus with other brain regions that are important for consciousness, and with components of the default mode network (DMN) suggest the severe impairment of consciousness in ictal GSWDs. However, for subclinical discharges, weaker connectivity between the thalamus and these brain regions may suggest the prevention of impairment of consciousness. This may benefit future therapeutic targets and improve the management of CAE patients.

Consciousness alteration in focal epilepsy is related to loss of signal complexity and information processing

Alteration of awareness is a main feature of focal epileptic seizures. In this work, we studied how the information contained in EEG signals was modified during temporal lobe seizures with altered awareness by using permutation entropy (PE) as a measure of the complexity of the signal. PE estimation was performed in thirty-six seizures of sixteen patients with temporal lobe epilepsy who underwent SEEG recordings. We tested whether altered awareness (based on the Consciousness Seizure Score) was correlated with a loss of signal complexity. We estimated global changes in PE as well as regional changes to gain insight into the mechanisms associated with awareness impairment. Our results reveal a positive correlation between the decrease of entropy and the consciousness score as well as the existence of a threshold on entropy that could discriminate seizures with no alteration of awareness from seizures with profound alteration of awareness. The loss of signal complexity was diffuse, extending bilaterally and to the associative cortices, in patients with profound alteration of awareness and limited to the temporal mesial structures in patients with no alteration of awareness. Thus PE is a promising tool to discriminate between the different subgroups of awareness alteration in TLE.

EEG Oscillatory Networks in Peri-Ictal Period of Absence Epilepsy

Objective

To investigate the dynamical brain network changes before and after an absence seizure episode in absence epilepsy (AE).

Methods

21 AE patients with a current high frequency of seizures and 21 sex- and age-matched health control (HC) who reported no history of neurological or psychiatric disorders and visited the hospital for routine physical examinations were included. Each included subject underwent a 2-h and 19-channel video EEG examination. For AE patients, five epochs of 10-s EEG data in inter-ictal, pre-ictal, and post-ictal states were collected. For the HC group, five 10-s resting-state EEG epochs were extracted. Functional independent components analysis (ICA) was carried out using the LORETA KEY tool.

Results

Compared with the resting-state EEG data of the HC group, the EEG data from AE patients during inter-ictal periods showed decreased alpha oscillations in regions involving the superior frontal gyrus (SFG) (BA11). From inter-ictal to pre-ictal, SFG (BA10) showed maximum decreased delta oscillations. Additionally, from pre-ictal to post-ictal, superior temporal gyrus (STG) (BA 22) presented maximum increased neural activity in the alpha band. Moreover, compared with inter-ictal EEG, post-ictal EEG showed significantly decreased theta activity in SFG (BA8).

Conclusion

The changes in SFG alpha oscillations are the key brain network differences between inter-ictal EEG of AE patients and resting-state EEG of HCs. The brain networks of EEG oscillatory during peri-ictal episodes are mainly involving SFG and STG. Our study suggests that altered EEG brain networks dynamics exist between inter-ictal EEG of AE patients and resting-state EEG of HCs and between pre- and post-ictal EEG in AE patients.

Distinct Functional Cortico-Striato-Thalamo-Cerebellar Networks in Genetic Generalized and Focal Epilepsies with Generalized Tonic-Clonic Seizures

This study aimed to delineate cortico-striato-thalamo-cerebellar network profiles based on static and dynamic connectivity analysis in genetic generalized and focal epilepsies with generalized tonic-clonic seizures, and to evaluate its potential for distinguishing these two epilepsy syndromes. A total of 342 individuals participated in the study (114 patients with genetic generalized epilepsy with generalized tonic-clonic seizures (GE-GTCS), and 114 age- and sex-matched patients with focal epilepsy with focal to bilateral tonic-clonic seizure (FE-FBTS), 114 healthy controls). Resting-state fMRI data were examined through static and dynamic functional connectivity (dFC) analyses, constructing cortico-striato-thalamo-cerebellar networks. Network patterns were compared between groups, and were correlated to epilepsy duration. A pattern-learning algorithm was applied to network features for classifying both epilepsy syndromes. FE-FBTS and GE-GTCS both presented with altered functional connectivity in subregions of the motor/premotor and somatosensory networks. Among these two groups, the connectivity within the cerebellum increased in the static, while the dFC variability decreased; conversely, the connectivity of the thalamus decreased in FE-FBTS and increased in GE-GTCS in the static state. Connectivity differences between patient groups were mainly located in the thalamus and cerebellum, and correlated with epilepsy duration. Support vector machine (SVM) classification had accuracies of 66.67%, 68.42%, and 77.19% when using static, dynamic, and combined approaches to categorize GE-GTCS and FE-GTCS. Network features with high discriminative ability predominated in the thalamic and cerebellar connectivities. The network embedding of the thalamus and cerebellum likely plays an important differential role in GE-GTCS and FE-FBTS, and could serve as an imaging biomarker for differential diagnosis.

Epilepsy-Connect: An Integrated Knowledgebase for Characterizing Alterations in Consciousness State of Pharmacoresistant Epilepsy Patients

Alterations in consciousness state are a defining characteristic of focal epileptic seizures. Consequently, understanding the complex changes in neurocognitive networks which underpin seizure-induced alterations in consciousness state is important for advancement in seizure classification. Comprehension of these changes are complicated by a lack of data standardization; however, the use of a common terminological system or ontology in a patient registry minimizes this issue. In this paper, we introduce an integrated knowledgebase called Epilepsy-Connect to improve the understanding of changes in consciousness states during focal seizures of pharmacoresistant epilepsy patients. This registry catalogues over 809 seizures from 70 patients at University Hospital's Epilepsy Center who were undergoing stereotactic electroencephalography (SEEG) monitoring as part of an evaluation for surgical intervention. Although Epilepsy-Connect focuses on consciousness states, it aims to enable users to leverage data from an informatics platform to analyze epilepsy data in a streamlined manner. Epilepsy-Connect is available at https://bmhinformatics.case.edu/Epilepsyconnect/login/.

A study of brain functional network and alertness changes in temporal lobe epilepsy with and without focal to bilateral tonic-clonic seizures

BACKGROUND

Temporal lobe epilepsy (TLE) is commonly refractory. Epilepsy surgery is an effective treatment strategy for refractory epilepsy, but patients with a history of focal to bilateral tonic-clonic seizures (FBTCS) have poor outcomes. Previous network studies on epilepsy have found that TLE and idiopathic generalized epilepsy with generalized tonic-clonic seizures (IGE-GTCS) showed altered global and nodal topological properties. Alertness deficits also were found in TLE. However, FBTCS is a common type of seizure in TLE, and the implications for alertness as well as the topological rearrangements associated with this seizure type are not well understood.

METHODS

We obtained rs-fMRI data and collected the neuropsychological assessment data from 21 TLE patients with FBTCS (TLE- FBTCS), 18 TLE patients without FBTCS (TLE-non- FBTCS) and 22 controls, and constructed their respective functional brain networks. The topological properties were analyzed using the graph theoretical approach and correlations between altered topological properties and alertness were analyzed.

RESULTS

We found that TLE-FBTCS patients showed more serious impairment in alertness effect, intrinsic alertness and phasic alertness than the patients with TLE-non-FBTCS. They also showed significantly higher small-worldness, normalized clustering coefficient (γ) and a trend of higher global network efficiency (gE) compared to TLE-non-FBTCS patients. The gE showed a significant negative correlation with intrinsic alertness for TLE-non-FBTCS patients.

CONCLUSION

Our findings show different impairments in brain network information integration, segregation and alertness between the patients with TLE-FBTCS and TLE-non-FBTCS, demonstrating that impairments of the brain network may underlie the disruptions in alertness functions.

Potential scalp stimulation targets for mental disorders: evidence from neuroimaging studies

Mental disorders widely contribute to the modern global disease burden, creating a significant need for improvement of treatments. Scalp stimulation methods (such as scalp acupuncture and transcranial electrical stimulation) have shown promising results in relieving psychiatric symptoms. However, neuroimaging findings haven’t been well-integrated into scalp stimulation treatments. Identifying surface brain regions associated with mental disorders would expand target selection and the potential for these interventions as treatments for mental disorders. In this study, we performed large-scale meta-analyses separately on eight common mental disorders: attention deficit hyperactivity disorder, anxiety disorder, autism spectrum disorder, bipolar disorder, compulsive disorder, major depression, post-traumatic stress disorder and schizophrenia; utilizing modern neuroimaging literature to summarize disorder-associated surface brain regions, and proposed neuroimaging-based target protocols. We found that the medial frontal gyrus, the supplementary motor area, and the dorsal lateral prefrontal cortex are commonly involved in the pathophysiology of mental disorders. The target protocols we proposed may provide new brain targets for scalp stimulation in the treatment of mental disorders, and facilitate its clinical application.

Disruption of functional connectivity among subcortical arousal system and cortical networks in temporal lobe epilepsy

Growing evidence has demonstrated widespread brain network alterations in temporal lobe epilepsy (TLE). However, the relatively accurate portrait of the subcortical-cortical relationship for impaired consciousness in TLE remains unclear. We proposed that consciousness-impairing seizures may invade subcortical arousal system and corresponding cortical regions, resulting in functional abnormalities and information flow disturbances between subcortical and cortical networks. We performed resting-state fMRI in 26 patients with TLE and 30 matched healthy controls. All included patients were diagnosed with impaired awareness during focal temporal lobe seizures. Functional connectivity density was adopted to determine whether local or distant network alterations occurred in TLE, and Granger causality analysis (GCA) was utilized to assess the direction and magnitude of causal influence among these altered brain networks further. Patients showed increased local functional connectivity in several arousal structures, such as the midbrain, thalamus, and cortical regions including bilateral prefrontal cortex (PFC), left superior temporal pole, left posterior insula, and cerebellum (P < 0.05, FDR corrected). GCA analysis revealed that the casual effects among these regions in patients were significantly sparser than those in controls (P < 0.05, uncorrected), including decreased excitatory and inhibitory effects among the midbrain, thalamus and PFC, and decreased inhibitory effect from the cerebellum to PFC. These findings suggested that consciousness-impairing seizures in TLE are associated with functional alterations and disruption of information process between the subcortical arousal system and cortical network. Understanding the functional networks and innervation pathway involved in TLE can provide insights into the mechanism underlying seizure-related loss of consciousness.

Enhanced gamma band mutual information is associated with impaired consciousness during temporal lobe seizures

Background

Epileptic seizures are characterized by aberrant synchronization. We hypothesized that higher synchronization across the seizure onset zone (SOZ) channels during a temporal lobe seizure contributes to impaired consciousness.

New method

All symmetric bivariate synchronization measures were extended to multivariate measure by a principal component analysis (PCA) based technique. A novel nonparametric method has been proposed to test the statistical significance between increased synchronization across the seizure onset zone (SOZ) channels and reduced consciousness.

Results

Increased synchronization in the gamma band towards seizure termination significantly contributes to impaired consciousness (p < 0.1). Synchronization reaches its peak in the extratemporal region (frontal lobe) ahead of the temporal region (p < 0.05). Synchronization is prominent in beta and gamma bands by most methods and it is more in the second half of seizure duration than in the first (p < 0.05).

Conclusions

Mutual information is the only synchronization measure out of the six that we studied, whose increase can be associated with the loss of consciousness in a statistically significant way.

Analysis of Interictal Epileptiform Discharges in Mesial Temporal Lobe Epilepsy Using Quantitative EEG and Neuroimaging

Objective: Investigate areas of correlation between gray matter volumes by MRI and interictal EEG source maps in subtypes of mesial temporal lobe epilepsy (MTLE). Method: 71 patients and 36 controls underwent 3T MRI and and routine EEG was performed. Voxel-based morphometry (VBM) was used for gray matter analysis and analysis of interictal discharge sources for quantitative EEG. Voxel-wise correlation analysis was conducted between the gray matter and EEG source maps in MTLE subtypes. Results: The claustrum was the main structure involved in the individual source analysis. Twelve patients had bilateral HA, VBM showed bilateral hippocampal. Twenty-one patients had right HA, VBM showed right hippocampal and thalamic atrophy and negatively correlated involving the right inferior frontal gyrus and insula. Twenty-two patients had left HA, VBM showed left hippocampal atrophy and negatively correlated involving the left temporal lobe and insula. Sixteen patients had MTLE without HA, VBM showed middle cingulate gyrus atrophy and were negatively correlated involving extra-temporal regions, the main one located in postcentral gyrus. Conclusions: Negative correlations between gray matter volumes and EEG source imaging. Neuroanatomical generators of interictal discharges are heterogeneous and vary according to MTLE subtype. Significance: These findings suggest different pathophysiological mechanisms among patients with different subtypes of MTLE.

Cortical and subcortical volume differences between Benign Epilepsy with Centrotemporal Spikes and Childhood Absence Epilepsy

OBJECTIVE

Benign Childhood Epilepsy with Centrotemporal Spikes (BECTS) and Childhood Absence Epilepsy (CAE) are the most common childhood epilepsy syndromes and they share a similar age-dependence. However, the two syndromes clearly differ in seizures and EEG patterns. The aim of this study is to investigate whether children of the same age with BECTS, CAE and typically-developing children have significant differences in grey matter volume that may underlie the different profiles of these syndromes.

METHODS

Twenty one patients with newly-diagnosed BECTS and 18 newly diagnosed and drug naïve CAE were included and compared to 31 typically-developing children. Voxel-based morphometry was utilized to investigate grey matter volume differences among BECTS, CAE, and controls. We also examined the effect of age on grey matter volume in all three groups. In addition to the whole brain analysis, we chose regions of interest analysis based on previous literature suggesting the involvement of these regions in BECTS or CAE. The group differences of grey matter volume was tested with 2-sample t-test for between two groups' comparisons and ANOVA for three group comparisons.

RESULTS

In the whole brain group comparisons, the grey matter volume in CAE was significantly decreased in the areas of right inferior frontal and anterior temporal compared to BECTS and controls (F_2,67  = 27.53, p < 0.001). In the control group, grey matter volume in bifrontal lobes showed a negative correlation with age (r=-0.54, p < 0.05), whereas no correlation was found in either CAE or BECTS. With ROI analyses, the grey matter volume of posterior thalami was increased in CAE compared to other 2 groups (p < 0.05).

SIGNIFICANCE

This study shows that there are grey matter volume differences between CAE and BECTS. Our findings of grey matter volume differences may suggest that there may be localized, specific differences in brain structure between these two types of epilepsy.

Arterial Spin Labeling Magnetic Resonance Imaging in the Assessment of Non-Convulsive Status Epilepticus in Alzheimer's Disease: A Report of Two Cases

Case series

Patients: Female, 69-year-old • Male, 70-year-old

Final Diagnosis: Nonconvulsive status epilepticus

Symptoms: Altered mental status • cognitive impairment

Medication: —

Clinical Procedure: ASL perfusion MRI

Specialty: Neurology

Distinct Topographical Patterns of Spike-Wave Discharge in Transgenic and Pharmacologically Induced Absence Seizure Models

Absence seizures (AS) are generalized non-convulsive seizures characterized by a brief loss of consciousness and spike-and-wave discharges (SWD) in an electroencephalogram (EEG). A number of animal models have been developed to explain the mechanisms of AS, and thalamo-cortical networks are considered to be involved. However, the cortical foci have not been well described in mouse models of AS. This study aims to use a high density EEG in pathophysiologically different AS models to compare the spatiotemporal patterns of SWDs. We used two AS models: a pharmacologically induced model (gamma-hydroxybutyric acid, GHB model) and a transgenic model (phospholipase beta4 knock-out, PLCβ4 model). The occurrences of SWDs were confirmed by thalamic recordings. The topographical analysis of SWDs showed that the onset and propagation patterns were markedly distinguishable between the two models. In the PLCβ4 model, the foci were located within the somatosensory cortex followed by propagation to the frontal cortex, whereas in the GHB model, a majority of SWDs was initiated in the prefrontal cortex followed by propagation to the posterior cortex. In addition, in the GHB model, foci were also observed in other cortical areas. This observation indicates that different cortical networks are involved in the generation of SWDs across the two models.

Precuneus-Dominant Degeneration of Parietal Lobe Is at Risk of Epilepsy in Mild Alzheimer's Disease

Introduction: Alzheimer's disease (AD) is the leading cause of cognitive decline. Epilepsy is a frequent comorbid condition of AD. While previous studies analyzed the risk factors of AD-related epileptic seizures, we still lack biomarkers of epilepsy in mild AD cases.

Purpose: The aim of our study was to analyze the correlations between neuropsychology, cortical thickness, and brain volumetric measurements in mild Alzheimer patients with concomitant epileptic seizures.

Materials and methods: We selected mild AD patients from our database to examine them with structural magnetic resonance imaging, 24 h electroencephalography, and detailed neuropsychology. We made the diagnosis of epilepsy based on epileptology data including neurophysiology. We retrospectively analyzed the neuropsychology pattern, clinical and epidemiologic features, cortical thickness, and volumetric values of mild AD patients with and without overt clinical seizures using covariance weighted general linear model.

Results: We found epileptic seizures in 26% of mild AD patients. Patients with seizures performed worse in visuo-spatial scores than patients without (p = 0.003). Patients with seizures had smaller parietal thickness (p = 0.018), being associated to reduced thickness of left (p = 0.007), and right precunei (p = 0.005). The visuo-spatial performance positively and strongly correlated with the thickness of the parietal lobe (r = 0.67; p = 0.002) and with the volume of the precuneus (r = 0.612; p = 0.005).

Conclusion: Epileptic seizures are common even in mild AD. We found that a prominent deficit in visuo-spatial skills is a red flag for epileptic seizures in the initial phase of AD, indicating the early involvement of parietal lobe in the neurodegenerative process. Because our findings suggest that the degeneration of precuneus is a sensitive marker of seizures associated to mild AD, clinicians need to pay special attention to the pattern of atrophy shown by structural MRI. Our results confirm previous data suggesting that epileptic seizures might be associated to a faster progressing type of AD with the early degeneration of posterior cortical areas.

Circadian phenotype impacts the brain's resting-state functional connectivity, attentional performance, and sleepiness

INTRODUCTION

Functional connectivity (FC) of the human brain's intrinsically connected networks underpins cognitive functioning and disruptions of FC are associated with sleep and neurological disorders. However, there is limited research on the impact of circadian phenotype and time of day on FC.

STUDY OBJECTIVES

The aim of this study was to investigate resting-state FC of the default mode network (DMN) in Early and Late circadian phenotypes over a socially constrained day.

METHODS

Thirty-eight healthy individuals (14 male, 22.7 ± 4.2 years) categorized as Early (n = 16) or Late (n = 22) using the Munich ChronoType Questionnaire took part. Following a 2-week baseline of actigraphy coupled with saliva samples for melatonin and cortisol rhythms, participants underwent testing at 14:00 hours, 20:00 hours, and 08:00 hours the following morning. Testing consisted of resting-state functional magnetic resonance imaging (fMRI), a structural T1 scan, attentional cognitive performance tasks, and self-reported daytime sleepiness. Seed-based FC analysis from the medial prefrontal and posterior cingulate cortices of the DMN was performed, compared between groups and linked with behavioral data.

RESULTS

Fundamental differences in the DMN were observed between Early and Late circadian phenotypes. Resting-state FC of the DMN predicted individual differences in attention and subjective ratings of sleepiness.

CONCLUSION

Differences in FC of the DMN may underlie the compromised attentional performance and increased sleepiness commonly associated with Late types when they conform to a societally constrained day that does not match their intrinsic circadian phenotype.

Galvanic Skin Response (GSR)/Electrodermal/Skin Conductance Biofeedback on Epilepsy: A Systematic Review and Meta-Analysis

Objectives: Dynamic changes in psychophysiological arousal are directly expressed in the sympathetic innervation of the skin. This activity can be measured as tonic and phasic fluctuations in electrodermal activity [Galvanic Skin Response (GSR)/skin conductance]. Biofeedback training can enable an individual to gain voluntary control over this autonomic response and its central correlates. Theoretically, control of psychophysiological arousal may be harnessed as a therapy for epilepsy, to mitigate pre-ictal states. Evidence is accumulating for the clinical efficacy of GSR biofeedback training in the management of drug resistant epilepsy. In this review, we analyse current evidence of efficacy with GSR biofeedback and evaluate the methodology of each study.

Method: We searched published literature pertaining to interventional studies of GSR biofeedback for epilepsy, through MEDLINE and Cochrane databases (1950–2018). Using percentage seizure reduction as an indicator of therapeutic efficacy induced by GSR biofeedback, we used meta-analytic methods to summarize extant findings. We also compare and contrast study design with relevance to the interpretation of outcomes.

Results: Out of 21 articles retrieved for GSR/EDA/Skin conductance biofeedback, four studies were identified as interventional trials, involving 99 patients with drug-resistant epilepsy in total. Three of these studies included a control group and a positive therapeutic effect of biofeedback was reported in each of these. The difference in seizure frequency percentage (Biofeedback—Control) was between −54.4 and −74.0% with an overall weighted mean difference of −64.3% (95% CI: −85.4 to −43.2%). The response rates (proportion of patients manifesting >50% reduction in seizure frequency) varied from 45 to 66% across studies.

Significance: This timely evaluation highlights the potential value of GSR biofeedback therapy, and informs the optimal study design of larger scale studies that are now required to more definitively establish the utility of this non-invasive, non-pharmacological interventional approach for drug-resistant epilepsy.

Spectral entropy indicates electrophysiological and hemodynamic changes in drug-resistant epilepsy - A multimodal MREG study

Objective

Epilepsy causes measurable irregularity over a range of brain signal frequencies, as well as autonomic nervous system functions that modulate heart and respiratory rate variability. Imaging dynamic neuronal signals utilizing simultaneously acquired ultra-fast 10 Hz magnetic resonance encephalography (MREG), direct current electroencephalography (DC-EEG), and near-infrared spectroscopy (NIRS) can provide a more comprehensive picture of human brain function. Spectral entropy (SE) is a nonlinear method to summarize signal power irregularity over measured frequencies. SE was used as a joint measure to study whether spectral signal irregularity over a range of brain signal frequencies based on synchronous multimodal brain signals could provide new insights in the neural underpinnings of epileptiform activity.

Methods

Ten patients with focal drug-resistant epilepsy (DRE) and ten healthy controls (HC) were scanned with 10 Hz MREG sequence in combination with EEG, NIRS (measuring oxygenated, deoxygenated, and total hemoglobin: HbO, Hb, and HbT, respectively), and cardiorespiratory signals. After pre-processing, voxelwise SE_MREG was estimated from MREG data. Different neurophysiological and physiological subfrequency band signals were further estimated from MREG, DC-EEG, and NIRS: fullband (0–5 Hz, FB), near FB (0.08–5 Hz, NFB), brain pulsations in very-low (0.009–0.08 Hz, VLFP), respiratory (0.12–0.4 Hz, RFP), and cardiac (0.7–1.6 Hz, CFP) frequency bands. Global dynamic fluctuations in MREG and NIRS were analyzed in windows of 2 min with 50% overlap.

Results

Right thalamus, cingulate gyrus, inferior frontal gyrus, and frontal pole showed significantly higher SE_MREG in DRE patients compared to HC. In DRE patients, SE of cortical Hb was significantly reduced in FB (p = .045), NFB (p = .017), and CFP (p = .038), while both HbO and HbT were significantly reduced in RFP (p = .038, p = .045, respectively). Dynamic SE of HbT was reduced in DRE patients in RFP during minutes 2 to 6. Fitting to the frontal MREG and NIRS results, DRE patients showed a significant increase in SE_EEG in FB in fronto-central and parieto-occipital regions, in VLFP in parieto-central region, accompanied with a significant decrease in RFP in frontal pole and parietal and occipital (O2, Oz) regions.

Conclusion

This is the first study to show altered spectral entropy from synchronous MREG, EEG, and NIRS in DRE patients. Higher SE_MREG in DRE patients in anterior cingulate gyrus together with SE_EEG and SE_NIRS results in 0.12–0.4 Hz can be linked to altered parasympathetic function and respiratory pulsations in the brain. Higher SE_MREG in thalamus in DRE patients is connected to disturbances in anatomical and functional connections in epilepsy. Findings suggest that spectral irregularity of both electrophysiological and hemodynamic signals are altered in specific way depending on the physiological frequency range.

•

Simultaneous imaging methods indicate spectral irregularity in neurovascular and electrophysiological brain pulsations in DRE.

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Altered spectral entropy in EEG, NIRS and BOLD indicate dysfunctional brain pulsations in respiratory frequency in epilepsy.

•

Spectral irregularity (0-5 Hz) of BOLD in right thalamus supports previous structural and functional findings in epilepsy.

Relationship Between Alpha Rhythm and the Default Mode Network: An EEG-fMRI Study

PURPOSE

Reports of the relationship between the default mode network (DMN) and alpha power are conflicting. Our goal was to assess this relationship by analyzing concurrently obtained EEG/functional MRI data using hypothesis-independent methods.

METHODS

We collected functional MRI and EEG data during eyes-closed rest in 20 participants aged 19 to 37 (10 females) and performed independent component analysis on the functional MRI data and a Hamming-windowed fast Fourier transform on the EEG data. We correlated functional MRI fluctuations in the DMN with alpha power.

RESULTS

Of the six independent components found to have significant relationships with alpha, four contained DMN-associated regions: One independent component was positively correlated with alpha power, whereas all others were negatively correlated. Furthermore, two independent components with opposite relationships with alpha had overlapping voxels in the medial prefrontal cortex and posterior cingulate cortex, suggesting that subpopulations of neurons within these classic nodes within the DMN may have different relationships to alpha power.

CONCLUSIONS

Different parts of the DMN exhibit divergent relationships to alpha power. Our results highlight the relationship between DMN activity and alpha power, indicating that networks, such as the DMN, may have subcomponents that exhibit different behaviors.

Anatomy Based Networks and Topology Alteration in Seizure-Related Cognitive Outcomes

Epilepsy is a paroxysmal neurological disorder characterized by recurrent and unprovoked seizures affecting approximately 50 million people worldwide. Cognitive dysfunction induced by seizures is a severe comorbidity of epilepsy and epilepsy syndromes and reduces patients’ quality of life. Seizures, along with accompanying histopathological and pathophysiological changes, are associated with cognitive comorbidities. Advances in imaging technology and computing allow anatomical and topological changes in neural networks to be visualized. Anatomical components including the hippocampus, amygdala, cortex, corpus callosum (CC), cerebellum and white matter (WM) are the fundamental components of seizure- and cognition-related topological networks. Damage to these structures and their substructures results in worsening of epilepsy symptoms and cognitive dysfunction. In this review article, we survey structural, network changes and topological alteration in different regions of the brain and in different epilepsy and epileptic syndromes, and discuss what these changes may mean for cognitive outcomes related to these disease states.

Epileptic Seizures are Reduced by Autonomic Biofeedback Therapy Through Enhancement of Fronto-limbic Connectivity: A Controlled Trial and Neuroimaging Study

BACKGROUND

Thirty-percent of patients with epilepsy are drug-resistant, and might benefit from effective noninvasive therapeutic interventions. Evidence is accumulating on the efficacy of autonomic biofeedback therapy using galvanic skin response (GSR; an index of sympathetic arousal) in treating epileptic seizures. This study aimed to extend previous controlled clinical trials of autonomic biofeedback therapy with a larger homogeneous sample of patients with temporal lobe epilepsy. In addition, we used neuroimaging to characterize neural mechanisms of change in seizure frequency following the therapy.

METHODS

Forty patients with drug-resistant temporal lobe epilepsy (TLE) (age: 18 to 70years old), on stable doses of anti-epileptic medication, were recruited into a controlled and parallel-group trial from three screening centers in the UK. Patients were allocated to either an active intervention group, who received therapy with GSR biofeedback, or a control group, who received treatment as usual. Allocation to the group was informed, in part, by whether patients could travel to attend repeated therapy sessions (non-randomized). Measurement of outcomes was undertaken by an assessor blinded to the patients' group membership. Resting-state functional and structural MRI data were acquired before and after one month of therapy in the therapy group, and before and after a one-month interval in the control group. The percentage change of seizure frequency was the primary outcome measure. The analysis employed an intention-to-treat principle. The secondary outcome was the change in default mode network (DMN) and limbic network functional connectivity tested for effects of therapy. The trial was registered with the National Institute for Health Research (NIHR) portfolio (ID 15967).

FINDINGS

Data were acquired between May 2014 and October 2016. Twenty participants were assigned to each group. Two patients in the control group dropped out before the second scan, leaving 18 control participants. There was a significant difference in reduction of seizure frequency between the therapy and control groups (p<0.001: Mann Whitney U Test). The seizure frequency in the therapy group was significantly reduced (p<0.001: Wilcoxon Signed Rank Test) following GSR biofeedback, with a mean seizure reduction of 43% (SD=± 32.12, median=-37.26, 95% CI -58.02% to -27.96%). No significant seizure reduction was observed in the control group, with a mean increase in seizure frequency of 31% (SD=±88.27, median=0, 95% CI -12.83% to 74.96%). The effect size of group comparison was 1.14 (95% CI 0.44 to 1.82). 45% of patients in the therapy group showed a seizure reduction of >50%. Neuroimaging analysis revealed that post-therapy seizure reduction was linearly correlated with enhanced functional connectivity between right amygdala and both the orbitofrontal cortex (OFC) and frontal pole (FP).

INTERPRETATION

Our clinical study provides evidence for autonomic biofeedback therapy as an effective and potent behavioral intervention for patients with drug-resistant epilepsy. This approach is non-pharmacological, non-invasive and seemingly side-effect free.

Differential patterns of dynamic functional connectivity variability of striato-cortical circuitry in children with benign epilepsy with centrotemporal spikes

Benign epilepsy with centrotemporal spikes (BECTS) is characterized by abnormal (static) functional interactions among cortical and subcortical regions, regardless of the active or chronic epileptic state. However, human brain connectivity is dynamic and associated with ongoing rhythmic activity. The dynamic functional connectivity (dFC) of the distinct striato-cortical circuitry associated with or without interictal epileptiform discharges (IEDs) are poorly understood in BECTS. Herein, we captured the pattern of dFC using sliding window correlation of putamen subregions in the BECTS (without IEDs, n = 23; with IEDs, n = 20) and sex- and age-matched healthy controls (HCs, n = 28) during rest. Furthermore, we quantified dFC variability using their standard deviation. Compared with HCs and patients without IEDs, patients with IEDs exhibited excessive variability in the dorsal striatal-sensorimotor circuitry related to typical seizure semiology. By contrast, excessive stability (decreased dFC variability) was found in the ventral striatal-cognitive circuitry (p < .05, GRF corrected). In addition, correlation analysis revealed that the excessive variability in the dorsal striatal-sensorimotor circuitry was related to highly frequent IEDs (p < .05, uncorrected). Our finding of excessive variability in the dorsal striatal-sensorimotor circuitry could be an indication of increased sensitivity to regional fluctuations in the epileptogenic zone, while excessive stability in the ventral striatal-cognitive circuitry could represent compensatory mechanisms that prevent or postpone cognitive impairments in BECTS. Overall, the differentiated dynamics of the striato-cortical circuitry extend our understanding of interactions among epileptic activity, striato-cortical functional architecture, and neurocognitive processes in BECTS.

Altered Local Spatiotemporal Consistency of Resting-State BOLD Signals in Patients with Generalized Tonic-Clonic Seizures

The purpose of this study was to evaluate the spatiotemporal Consistency of spontaneous activities in local brain regions in patients with generalized tonic-clonic seizures (GTCS). The resting-state fMRI data were acquired from nineteen patients with GTCS and twenty-two matched healthy subjects. FOur-dimensional (spatiotemporal) Consistency of local neural Activities (FOCA) metric was used to analyze the spontaneous activity in whole brain. The FOCA difference between two groups were detected using a two sample t-test analysis. Correlations between the FOCA values and features of seizures were analyzed. The findings of this study showed that patients had significantly increased FOCA in motor-related cortex regions, including bilateral supplementary motor area, paracentral lobule, precentral gyrus and left basal ganglia, as well as a substantial reduction of FOCA in regions of default mode network (DMN) and parietal lobe. In addition, several brain regions in DMN demonstrated more reduction with longer duration of epilepsy and later onset age, and the motor-related regions showed higher FOCA value in accompany with later onset age. These findings implicated the abnormality of motor-related cortical network in GTCS which were associated with the genesis and propagation of epileptiform activity. And the decreased FOCA in DMN might reflect the intrinsic disturbance of brain activity. Moreover, our study supported that the FOCA might be potential tool to investigate local brain spontaneous activity related with the epileptic activity, and to provide important insights into understanding the underlying pathophysiological mechanisms of GTCS.

The Mechanisms of Psychedelic Visionary Experiences: Hypotheses from Evolutionary Psychology

Neuropharmacological effects of psychedelics have profound cognitive, emotional, and social effects that inspired the development of cultures and religions worldwide. Findings that psychedelics objectively and reliably produce mystical experiences press the question of the neuropharmacological mechanisms by which these highly significant experiences are produced by exogenous neurotransmitter analogs. Humans have a long evolutionary relationship with psychedelics, a consequence of psychedelics' selective effects for human cognitive abilities, exemplified in the information rich visionary experiences. Objective evidence that psychedelics produce classic mystical experiences, coupled with the finding that hallucinatory experiences can be induced by many non-drug mechanisms, illustrates the need for a common model of visionary effects. Several models implicate disturbances of normal regulatory processes in the brain as the underlying mechanisms responsible for the similarities of visionary experiences produced by psychedelic and other methods for altering consciousness. Similarities in psychedelic-induced visionary experiences and those produced by practices such as meditation and hypnosis and pathological conditions such as epilepsy indicate the need for a general model explaining visionary experiences. Common mechanisms underlying diverse alterations of consciousness involve the disruption of normal functions of the prefrontal cortex and default mode network (DMN). This interruption of ordinary control mechanisms allows for the release of thalamic and other lower brain discharges that stimulate a visual information representation system and release the effects of innate cognitive functions and operators. Converging forms of evidence support the hypothesis that the source of psychedelic experiences involves the emergence of these innate cognitive processes of lower brain systems, with visionary experiences resulting from the activation of innate processes based in the mirror neuron system (MNS).

A unique pattern of cortical connectivity characterizes patients with attention deficit disorders: a large electroencephalographic coherence study

BACKGROUND

Attentional disorders (ADD) feature decreased attention span, impulsivity, and over-activity interfering with successful lives. Childhood onset ADD frequently persists to adulthood. Etiology may be hereditary or disease associated. Prevalence is 5% but recognition may be 'overshadowed' by comorbidities (brain injury, mood disorder) thereby escaping formal recognition. Blinded diagnosis by MRI has failed. ADD may not itself manifest a single anatomical pattern of brain abnormality but may reflect multiple, unique responses to numerous and diverse etiologies. Alternatively, a stable ADD-specific brain pattern may be better detected by brain physiology. EEG coherence, measuring cortical connectivity, is used to explore this possibility.

METHODS

Participants: Ages 2 to 22 years; 347 ADD and 619 neurotypical controls (CON). Following artifact reduction, principal components analysis (PCA) identifies coherence factors with unique loading patterns. Discriminant function analysis (DFA) determines discrimination success differentiating ADD from CON. Split-half and jackknife analyses estimate prospective diagnostic success. Coherence factor loading constitutes an ADD-specific pattern or 'connectome'.  RESULTS: PCA identified 40 factors explaining 50% of total variance. DFA on CON versus ADD groups utilizing all factors was highly significant (p≤0.0001). ADD subjects were separated into medication and comorbidity subgroups. DFA (stepping allowed) based on CON versus ADD without comorbidities or medication treatment successfully classified the correspondingly held out ADD subjects in every instance. Ten randomly generated split-half replications of the entire population demonstrated high-average classification success for each of the left out test-sets (overall: CON, 83.65%; ADD, 90.07%). Higher success was obtained with more restricted age sub-samples using jackknifing: 2-8 year olds (CON, 90.0%; ADD, 90.6%); 8-14 year olds (CON, 96.8%; ADD 95.9%); and 14-20 year-olds (CON, 100.0%; ADD, 97.1%). The connectome manifested decreased and increased coherence. Patterns were complex and bi-hemispheric; typically reported front-back and left-right loading patterns were not observed. Subtemporal electrodes (seldom utilized) were prominently involved.  CONCLUSIONS: Results demonstrate a stable coherence connectome differentiating ADD from CON subjects including subgroups with and without comorbidities and/or medications. This functional 'connectome', constitutes a diagnostic ADD phenotype. Split-half replications support potential for EEG-based ADD diagnosis, with increased accuracy using limited age ranges. Repeated studies could assist recognition of physiological change from interventions (pharmacological, behavioral).

An unaware agenda: interictal consciousness impairments in epileptic patients

Consciousness impairments have been described as a cornerstone of epilepsy. Generalized seizures are usually characterized by a complete loss of consciousness, whereas focal seizures have more variable degrees of responsiveness. In addition to these impairments that occur during ictal episodes, alterations of consciousness have also been repeatedly observed between seizures (i.e. during interictal periods). In this opinion article, we review evidence supporting the novel hypothesis that epilepsy produces consciousness impairments which remain present interictally. Then, we discuss therapies aimed to reduce seizure frequency, which may modulate consciousness between epileptic seizures. We conclude with a consideration of relevant pathophysiological mechanisms. In particular, the thalamocortical network seems to be involved in both seizure generation and interictal consciousness impairments, which could inaugurate a promising translational agenda for epilepsy studies.

Heterogeneity of trans-callosal structural connectivity and effects on resting state subnetwork integrity may underlie both wanted and unwanted effects of therapeutic corpus callostomy

BACKGROUND

The corpus callosum (CC) is the primary structure supporting interhemispheric connectivity in the brain. Partial or complete surgical callosotomy may be performed for the palliation of intractable epilepsy. A variety of disconnection syndromes are recognised after injury to or division of the CC however their mechanisms are poorly understood and their occurrence difficult to predict. We use novel high resolution structural connectivity analyses to demonstrate reasons for this poor predictability.

METHODS

Diffusion weighted MRI data from five healthy adult controls was subjected to novel high-resolution structural connectivity analysis. We simulated the effects of CC lesions of varying extents on the integrity of resting state subnetworks (RSNs).

RESULTS

There is substantial between-individual variation in patterns of CC connectivity. However in all individuals termination points of callosal connections mostly involve medial and superior sensory-motor areas. Superior temporal and lateral sensory-motor areas were not involved. Resting state networks showed selective vulnerability to simulated callosotomy of progressively greater anterior to posterior extent. The default mode network was most vulnerable followed by, in decreasing order: frontoparietal, limbic, somatomotor, ventral attention, dorsal attention and visual subnetworks.

CONCLUSION

Consideration of the selective vulnerability of resting state sub-networks, and of between-individual variability in connectivity patterns, sheds new light on the occurrence of both wanted and unwanted effects of callosotomy. We propose that beneficial effects (seizure reduction) relate to disruption of the default mode network, with unwanted "disconnection syndrome" effects due to disruption particularly of the somatomotor and frontoparietal RSNs. Our results may also explain why disconnection syndromes primary reflect lateralised sensory-motor problems (e.g. of limb movement) rather than midline function (e.g. tongue movement). Marked between-subject variation in callosal connectivity may underlie the poor predictability of effects of callosotomy. High resolution structural connectivity studies of this nature may be useful in pre-surgical planning of therapeutic callosotomy for intractable epilepsy.

Cortical and subcortical brain alterations in Juvenile Absence Epilepsy

Despite the common assumption that genetic generalized epilepsies are characterized by a macroscopically normal brain on magnetic resonance imaging, subtle structural brain alterations have been detected by advanced neuroimaging techniques in Childhood Absence Epilepsy syndrome. We applied quantitative structural MRI analysis to a group of adolescents and adults with Juvenile Absence Epilepsy (JAE) in order to investigate micro-structural brain changes using different brain measures. We examined grey matter volumes, cortical thickness, surface areas, and subcortical volumes in 24 patients with JAE compared to 24 healthy controls; whole-brain voxel-based morphometry (VBM) and Freesurfer analyses were used. When compared to healthy controls, patients revealed both grey matter volume and surface area reduction in bilateral frontal regions, anterior cingulate, and right mesial-temporal lobe. Correlation analysis with disease duration showed that longer disease was correlated with reduced surface area in right pre- and post-central gyrus. A possible effect of valproate treatment on brain structures was excluded. Our results indicate that subtle structural brain changes are detectable in JAE and are mainly located in anterior nodes of regions known to be crucial for awareness, attention and memory.

Aberrant long-range functional connectivity density in generalized tonic-clonic seizures

Studies in generalized tonic-clonic seizures (GTCS) have reported both structural and functional alterations in the brain. However, changes in spontaneous neuronal functional organization in GTCS remain largely unknown.In this study, 70 patients with idiopathic generalized epilepsy characterized by tonic-clonic seizures and 70 age- and sex-matched healthy controls were recruited. Here, functional connectivity density (FCD) mapping, an ultrafast data-driven method based on functional magnetic resonance imaging (fMRI), was applied for the first time to investigate the changes of spontaneous functional brain activity caused by epilepsy.The results showed significantly decreased long-range FCD in the middle and inferior temporal, prefrontal, and inferior parietal cortices as well as increased long-range FCD in the cerebellum anterior lobe and sensorimotor areas. Negative correlation between duration of disease and reduced long-range FCD was found. In addition, most regions with reduced long-range FCD showed decreased resting-state functional connectivity (rsFC) within default mode network.Negative correlation between duration of disease and long-range FCD may reflect an adverse consequence eventually from original. Furthermore, the observed FCD and rsFC alterations have been speculated to be associated with the social-cognitive impairments as well as motor control. Our study provided novel evidences to look into neuro-pathophysiological mechanisms underlying GTCS.

The sensitivity and significance of lateralized interictal slow activity on magnetoencephalography in focal epilepsy

OBJECTIVE

Asymmetric large-amplitude slow activity is sometimes observed on interictal electroencephalography (EEG) in epilepsy. However, few studies have examined slowing during magnetoencephalography (MEG) recordings, which are performed primarily to localize interictal spikes. Also, no prior investigations have compared the sensitivity of MEG to scalp EEG in detecting slow rhythms.

METHODS

We performed a retrospective cohort study of focal epilepsy patients who received MEG followed by surgical resection at our institution. We examined MEG, simultaneous EEG, and long-term EEG recordings for prominent asymmetric slow activity (delta-range, 1-4 Hz), and evaluated post-operative seizure outcomes.

RESULTS

We studied 132 patients with ≥ 1 year post-operative follow-up (mean, 3.6 years). Mean age was 27 (range, 3-68) years, and 55% of patients were male. Asymmetric large-amplitude slow wave activity was observed on interictal MEG in 21 of 132 (16%) patients. Interictal slowing lateralized to the hemisphere of resection in all but one (95%) patient. Among the 21 patients with interictal MEG slowing, 11 (52%) individuals had similarly lateralized EEG slowing, 7 patients had no EEG slowing, and 3 had bilateral symmetric EEG slowing. Meanwhile, none of the 111 patients without lateralized MEG slowing had asymmetric EEG slowing, suggesting significantly higher sensitivity of MEG versus EEG in detecting asymmetric slowing (χ(2)=63.4, p<0.001). MEG slowing was associated with shorter epilepsy duration with an odds ratio of 5.4 (1.7-17.0, 95% confidence interval). At last follow-up, 92 (70%) patients were seizure free (Engel I outcome), with no difference in seizure freedom rates between patients with (71%) or without (69%) asymmetric MEG slowing (χ(2)=0.4, p=0.99).

SIGNIFICANCE

MEG has higher sensitivity than scalp EEG in detecting asymmetric slow activity in focal epilepsy, which reliably lateralizes to the epileptogenic hemisphere. Other uses of MEG beyond spike localization may further improve presurgical evaluations in epilepsy.

Modulation of intrinsic brain activity by electroconvulsive therapy in major depression

INTRODUCTION

One of the most effective interventions for intractable major depressive episodes is electroconvulsive therapy (ECT). Because ECT is also relatively fast-acting, longitudinal study of its neurobiological effects offers critical insight into the mechanisms underlying depression and antidepressant response. Here we assessed modulation of intrinsic brain activity in corticolimbic networks associated with ECT and clinical response.

METHODS

We measured resting-state functional connectivity (RSFC) in patients with treatment-resistant depression (n=30), using functional magnetic resonance imaging (fMRI) acquired before and after completing a treatment series with right-unilateral ECT. Using independent component analysis, we assessed changes in RSFC with 1) symptom improvement and 2) ECT regardless of treatment outcome in patients, with reference to healthy controls (n=33, also scanned twice).

RESULTS

After ECT, consistent changes in RSFC within targeted depression-relevant functional networks were observed in the dorsal anterior cingulate (ACC), mediodorsal thalamus (mdTh), hippocampus, and right anterior temporal, medial parietal, and posterior cingulate cortex in all patients. In a separate analysis, changes in depressive symptoms were associated with RSFC changes in the dorsal ACC, mdTh, putamen, medial prefrontal, and lateral parietal cortex. RSFC of these regions did not change in healthy controls.

CONCLUSIONS

Neuroplasticity underlying clinical change was in part separable from changes associated with the effects of ECT observed in all patients. However, both ECT and clinical change were associated with RSFC modulation in dorsal ACC, mdTh and hippocampus, which may indicate that these regions underlie the mechanisms of clinical outcome in ECT and may be effective targets for future neurostimulation therapies.

A unified 3D default space consciousness model combining neurological and physiological processes that underlie conscious experience

The Global Workspace Theory and Information Integration Theory are two of the most currently accepted consciousness models; however, these models do not address many aspects of conscious experience. We compare these models to our previously proposed consciousness model in which the thalamus fills-in processed sensory information from corticothalamic feedback loops within a proposed 3D default space, resulting in the recreation of the internal and external worlds within the mind. This 3D default space is composed of all cells of the body, which communicate via gap junctions and electrical potentials to create this unified space. We use 3D illustrations to explain how both visual and non-visual sensory information may be filled-in within this dynamic space, creating a unified seamless conscious experience. This neural sensory memory space is likely generated by baseline neural oscillatory activity from the default mode network, other salient networks, brainstem, and reticular activating system.

Global and regional functional connectivity maps of neural oscillations in focal epilepsy

Intractable focal epilepsy is a devastating disorder with profound effects on cognition and quality of life. Epilepsy surgery can lead to seizure freedom in patients with focal epilepsy; however, sometimes it fails due to an incomplete delineation of the epileptogenic zone. Brain networks in epilepsy can be studied with resting-state functional connectivity analysis, yet previous investigations using functional magnetic resonance imaging or electrocorticography have produced inconsistent results. Magnetoencephalography allows non-invasive whole-brain recordings, and can be used to study both long-range network disturbances in focal epilepsy and regional connectivity at the epileptogenic zone. In magnetoencephalography recordings from presurgical epilepsy patients, we examined: (i) global functional connectivity maps in patients versus controls; and (ii) regional functional connectivity maps at the region of resection, compared to the homotopic non-epileptogenic region in the contralateral hemisphere. Sixty-one patients were studied, including 30 with mesial temporal lobe epilepsy and 31 with focal neocortical epilepsy. Compared with a group of 31 controls, patients with epilepsy had decreased resting-state functional connectivity in widespread regions, including perisylvian, posterior temporo-parietal, and orbitofrontal cortices (P < 0.01, t-test). Decreased mean global connectivity was related to longer duration of epilepsy and higher frequency of consciousness-impairing seizures (P < 0.01, linear regression). Furthermore, patients with increased regional connectivity within the resection site (n = 24) were more likely to achieve seizure postoperative seizure freedom (87.5% with Engel I outcome) than those with neutral (n = 15, 64.3% seizure free) or decreased (n = 23, 47.8% seizure free) regional connectivity (P < 0.02, chi-square). Widespread global decreases in functional connectivity are observed in patients with focal epilepsy, and may reflect deleterious long-term effects of recurrent seizures. Furthermore, enhanced regional functional connectivity at the area of resection may help predict seizure outcome and aid surgical planning.

Temporal lobe epilepsy and affective disorders: the role of the subgenual anterior cingulate cortex

OBJECTIVE

Reduced deactivation within the default mode network (DMN) is common in individuals with primary affective disorders relative to healthy volunteers (HVs). It is unknown whether similar network abnormalities are present in temporal lobe epilepsy (TLE) patients with a history of affective psychopathology.

METHODS

17 TLE patients with a lifetime affective diagnosis, 31 TLE patients with no formal psychiatric history and 30 HVs were included. We used a visuo-spatial 'n-back' paradigm to compare working memory (WM) network activation between these groups. Post hoc analyses included voxel-based morphometry and diffusion tensor imaging. The Beck Depression Inventory-Fast Screen and Beck Anxiety Inventory were completed on the day of scanning.

FINDINGS

Each group activated the fronto-parietal WM networks and deactivated the typical DMN in response to increasing task demands. Group comparison revealed that TLE patients with lifetime affective morbidity showed significantly greater deactivation in subgenual anterior cingulate cortex (sACC) than either the TLE-only or the HVs (p<0.001). This effect persisted after covarying for current psychotropic medication and severity of current depressive/anxiety symptoms (all p<0.001). Correlational analysis revealed that this finding was not driven by differences in task performance. There were no significant differences in grey matter volume or structural connectivity between the TLE groups.

CONCLUSIONS

Our results provide novel evidence suggesting that affective psychopathology in TLE has a neurobiological correlate, and in this context the sACC performs differently compared with network activity in primary affective disorders.

Altered intrinsic connectivity networks in frontal lobe epilepsy: a resting-state fMRI study

Examining the resting-state networks (RSNs) may help us to understand the neural mechanism of the frontal lobe epilepsy (FLE). Resting-state functional MRI (fMRI) data were acquired from 46 patients with FLE (study group) and 46 age- and gender-matched healthy subjects (control group). The independent component analysis (ICA) method was used to identify RSNs from each group. Compared with the healthy subjects, decreased functional connectivity was observed in all the networks; however, in some areas of RSNs, functional connectivity was increased in patients with FLE. The duration of epilepsy and the seizure frequency were used to analyze correlation with the regions of interest (ROIs) in the nine RSNs to determine their influence on FLE. The functional network connectivity (FNC) was used to study the impact on the disturbance and reorganization of FLE. The results of this study may offer new insight into the neuropathophysiological mechanisms of FLE.

Cortical network switching: possible role of the lateral septum and cholinergic arousal

BACKGROUND

Cortical networks undergo large-scale switching between states of increased or decreased activity in normal sleep and cognition as well as in pathological conditions such as epilepsy. We previously found that focal hippocampal seizures in rats induce increased neuronal firing and cerebral blood flow in subcortical structures including the lateral septal area, along with frontal cortical slow oscillations resembling slow wave sleep. In addition, stimulation of the lateral septum in the absence of a seizure resulted in cortical deactivation with slow oscillations.

HYPOTHESIS

We hypothesized that lateral septal activation might cause neocortical deactivation indirectly, possibly through impaired subcortical arousal. But how does subcortical stimulation cause slow wave activity in frontal cortex? How do arousal neurotransmitter levels (e.g. acetylcholine) change in cortex during the excitation of inhibitory projection nuclei?

METHODS AND RESULTS

In the current study, we used simultaneous electrophysiology and enzyme-based amperometry in a rat model, and found a decrease in choline, along with slow wave activity in orbital frontal cortex during lateral septal stimulation in the absence of seizures. In contrast, the choline signal and local field potential in frontal cortex had no significant changes when stimulating the hippocampus, but showed increased choline and decreased slow wave activity with an arousal stimulus produced by toe pinch.

CONCLUSIONS

These findings indicate that the activation of subcortical inhibitory structures (such as lateral septum) can depress subcortical cholinergic arousal. This mechanism may play an important role in large-scale transitions of cortical activity in focal seizures, as well as in normal cortical function.

Differences in paracingulate connectivity associated with epileptiform discharges and uncontrolled seizures in genetic generalized epilepsy

OBJECTIVE

Patients with genetic generalized epilepsy (GGE) frequently continue to have seizures despite appropriate clinical management. GGE is associated with changes in the resting-state networks modulated by clinical factors such as duration of disease and response to treatment. However, the effect of generalized spike and wave discharges (GSWDs) and/or seizures on resting-state functional connectivity (RSFC) is not well understood.

METHODS

We investigated the effects of GSWD frequency (in GGE patients), GGE (patients vs. healthy controls), and seizures (uncontrolled vs. controlled) on RSFC using seed-based voxel correlation in simultaneous electroencephalography (EEG) and resting-state functional magnetic resonance imaging (fMRI) (EEG/fMRI) data from 72 GGE patients (23 with uncontrolled seizures) and 38 healthy controls. We used seeds in paracingulate cortex, thalamus, cerebellum, and posterior cingulate cortex to examine changes in cortical-subcortical resting-state networks and the default mode network (DMN). We excluded from analyses time points surrounding GSWDs to avoid possible contamination of the resting state.

RESULTS

(1) Higher frequency of GSWDs was associated with an increase in seed-based voxel correlation with cortical and subcortical brain regions associated with executive function, attention, and the DMN; (2) RSFC in patients with GGE, when compared to healthy controls, was increased between paracingulate cortex and anterior, but not posterior, thalamus; and (3) GGE patients with uncontrolled seizures exhibited decreased cerebellar RSFC.

SIGNIFICANCE

Our findings in this large sample of patients with GGE (1) demonstrate an effect of interictal GSWDs on resting-state networks, (2) provide evidence that different thalamic nuclei may be affected differently by GGE, and (3) suggest that cerebellum is a modulator of ictogenic circuits.

Disruption of brain connectivity in acute stroke patients with early impairment in consciousness

Impairment in consciousness is common in acute stroke patients and is correlated with the clinical outcome after stroke. The underlying mechanism is not completely understood, with little known about brain activity and connectivity changes in acute stroke patients having impaired consciousness. In this study, we investigated changes in regional brain activity and brain networks of consciousness impaired stroke patients, as well as the amplitude of spontaneous low frequency fluctuation (ALFF) of each time series. Regional homogeneity (ReHo) of each voxel was measured, and resting state network analysis was consequently conducted. Results from this study demonstrate that, compared to normal subjects, the intensities of ALFF and ReHo, as well as the strength of the default mode network (DMN) connectivity, were significantly decreased in the precuneus and posterior cingulate cortex regions among stroke patients with impaired consciousness. Furthermore, the strength of the DMN was highly correlated with differences in the Glasgow Coma Scale (GCS) scores between the onset time and the scanning time. Results from this study suggest that the resting state fMRI is a feasible tool for the evaluation of acute stroke patients with an early impairment of consciousness. The detailed mechanisms, implications of these brain activities and networks exhibiting changes will require further investigation.

A review of attention-deficit/hyperactivity disorder from the perspective of brain networks

Attention-deficit/hyperactivity disorder (ADHD) is the most commonly diagnosed neurodevelopmental disorder in childhood, which affects more than 5% of the population worldwide. ADHD is characterized by developmentally inappropriate behaviors of inattention, and/or impulsivity and hyperactivity. These behavioral manifestations contribute to diminished academic, occupational and social functioning, and have neurobiological bases. Neuronal deficits, especially in the attention and executive function processing networks, have been implicated in both children and adults with ADHD by using sophisticated structural and functional neuroimaging approaches. These structural and functional abnormalities in the brain networks have been associated with the impaired cognitive, affective, and motor behaviors seen in the disorder. The goal of this review is to summarize and integrate emerging themes from the existing neuroimaging connectivity studies based on advanced imaging techniques, applied in data of structural magnetic resonance imaging (MRI), functional MRI (fMRI), diffusion tensor imaging, electroencephalography and event related potential; and to discuss the results of these studies when considering future directions for understanding pathophysiological mechanisms and developmental trajectories of the behavioral manifestations in ADHD. We conclude this review by suggesting that future research should put more effort on understanding the roles of the subcortical structures and their structural/functional pathways in ADHD.

Reduced default mode network connectivity in treatment-resistant idiopathic generalized epilepsy

PURPOSE

Idiopathic generalized epilepsy (IGE) resistant to treatment is common, but its neuronal correlates are not entirely understood. Therefore, the aim of this study was to examine resting-state default mode network (DMN) functional connectivity in patients with treatment-resistant IGE.

METHODS

Treatment resistance was defined as continuing seizures despite an adequate dose of valproic acid (valproate, VPA). Data from 60 epilepsy patients and 38 healthy controls who underwent simultaneous electroencephalography (EEG) and resting-state functional magnetic resonance imaging (fMRI) were included (EEG/fMRI). Independent component analysis (ICA) and dual regression were used to quantify DMN connectivity. Confirmatory analysis using seed-based voxel correlation was performed.

KEY FINDINGS

There was a significant reduction of DMN connectivity in patients with treatment-resistant epilepsy when compared to patients who were treatment responsive and healthy controls. Connectivity was negatively correlated with duration of epilepsy.

SIGNIFICANCE

Our findings in this large sample of patients with IGE indicate the presence of reduced DMN connectivity in IGE and show that connectivity is further reduced in treatment-resistant epilepsy. DMN connectivity may be useful as a biomarker for treatment resistance.

Her versus his migraine: multiple sex differences in brain function and structure

Migraine is twice as common in females as in males, but the mechanisms behind this difference are still poorly understood. We used high-field magnetic resonance imaging in male and female age-matched interictal (migraine free) migraineurs and matched healthy controls to determine alterations in brain structure. Female migraineurs had thicker posterior insula and precuneus cortices compared with male migraineurs and healthy controls of both sexes. Furthermore, evaluation of functional responses to heat within the migraine groups indicated concurrent functional differences in male and female migraineurs and a sex-specific pattern of functional connectivity of these two regions with the rest of the brain. The results support the notion of a 'sex phenotype' in migraine and indicate that brains are differentially affected by migraine in females compared with males. Furthermore, the results also support the notion that sex differences involve both brain structure as well as functional circuits, in that emotional circuitry compared with sensory processing appears involved to a greater degree in female than male migraineurs.

Spontaneous EEG-Functional MRI in Mesial Temporal Lobe Epilepsy: Implications for the Neural Correlates of Consciousness

The combination of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) has been shown to have great potential for providing a greater understanding of normal and diseased states in both human and animal studies. Simultaneous EEG-fMRI is particularly well suited for the study of epilepsy in that it may reveal the neurobiology of ictal and interictal epileptiform discharges and noninvasively localize epileptogenic foci. Spontaneous, coherent fluctuations of neuronal activity and the coupled hemodynamic responses have also been shown to provide diagnostic markers of disease, extending our understanding of intrinsically structured ongoing brain activity. Following a short summary of the hardware and software development of simultaneous EEG-fMRI, this paper reviews a unified framework of integrating neuronal and hemodynamic processes during epileptic seizures and discusses the role and impact of spontaneous activity in the mesial temporal lobe epilepsies with particular emphasis on the neural and physiological correlates of consciousness.

The adolescent or adult with generalized tonic-clonic seizures

Primary and secondary generalized tonic-clonic seizures (GTCs) together constitute up to 50% of adolescent and adult patients with epilepsy as diagnosed by history and EEG. Syncope and psychogenic nonepileptic seizures are major differential diagnoses and must be carefully excluded in therapy-resistant cases. Individual episodes can have up to seven phases in secondarily generalized GTCs. The distinction between primary and secondary GTCs depends mainly on history and EEG, and yield can be improved with sleep deprivation or overnight recording. Epilepsies with primary or unclassified GTCs can respond to any one of the five broad-spectrum antiepileptic drugs (AEDs): valproate, lamotrigine, levetiracetam, topiramate and zonisamide. Unless a focal onset is clearly confirmed, a sodium-channel blocking AED should not be used in the initial treatment of these conditions.

Temporal lobe epilepsy semiology

Epilepsy represents a multifaceted group of disorders divided into two broad categories, partial and generalized, based on the seizure onset zone. The identification of the neuroanatomic site of seizure onset depends on delineation of seizure semiology by a careful history together with video-EEG, and a variety of neuroimaging technologies such as MRI, fMRI, FDG-PET, MEG, or invasive intracranial EEG recording. Temporal lobe epilepsy (TLE) is the commonest form of focal epilepsy and represents almost 2/3 of cases of intractable epilepsy managed surgically. A history of febrile seizures (especially complex febrile seizures) is common in TLE and is frequently associated with mesial temporal sclerosis (the commonest form of TLE). Seizure auras occur in many TLE patients and often exhibit features that are relatively specific for TLE but few are of lateralizing value. Automatisms, however, often have lateralizing significance. Careful study of seizure semiology remains invaluable in addressing the search for the seizure onset zone.

Epilepsy and the consciousness system: transient vegetative state?

Recent advances have shown much in common between epilepsy and other disorders of consciousness. Behavior in epileptic seizures often resembles a transient vegetative or minimally conscious state. These disorders all converge on the "consciousness system" -the bilateral medial and lateral fronto-parietal association cortex and subcortical arousal systems. Epileptic unconsciousness has enormous clinical significance leading to accidental injuries, decreased work and school productivity, and social stigmatization. Ongoing research to better understand the mechanisms of impaired consciousness in epilepsy, including neuroimaging studies and fundamental animal models, will hopefully soon enable treatment trails to reduce epileptic unconsciousness and improve patient quality of life.