Study on the Relationships between Intrinsic Functional Connectivity of the Default Mode Network and Transient Epileptic Activity

Resting-state functional MRI study of conventional MRI-negative intractable epilepsy in children

Objective

The study aimed at investigating functional connectivity strength (FCS) changes in children with MRI-negative intractable epilepsy (ITE) and evaluating correlations between aberrant FCS and both disease duration and intelligence quotient (IQ).

Methods

Fifteen children with ITE, 24 children with non-intractable epilepsy (nITE) and 25 matched healthy controls (HCs) were subjected to rs-fMRI. IQ was evaluated by neuropsychological assessment. Voxelwise analysis of covariance was conducted in the whole brain, and then pairwise comparisons were made across three groups using Bonferroni corrections.

Results

FCS was significantly different among three groups. Relative to HCs, ITE patients exhibited decreased FCS in right temporal pole of the superior temporal gyrus, middle temporal gyrus, bilateral precuneus, etc and increased FCS values in left triangular part of the inferior frontal gyrus, parahippocampal gyrus, supplementary motor area, caudate and right calcarine fissure and surrounding cortex and midbrain. The nITE patients presented decreased FCS in right orbital superior frontal gyrus, precuneus etc and increased FCS in bilateral fusiform gyri, parahippocampal gyri, etc. In comparison to nITE patients, the ITE patients presented decreased FCS in right medial superior frontal gyrus and left inferior temporal gyrus and increased FCS in right middle temporal gyrus, inferior temporal gyrus and calcarine fissure and surrounding cortex. Correlation analysis indicated that FCS in left caudate demonstrated correlation with verbal IQ (VIQ) and disease duration.

Conclusion

ITE patients demonstrated changed FCS values in the temporal and prefrontal cortices relative to nITE patients, which may be related to drug resistance in epilepsy. FCS in the left caudate nucleus associated with VIQ, suggesting the caudate may become a key target for improving cognitive impairment and seizures in children with ITE.

Structural and functional abnormalities in first-episode drug-naïve pediatric idiopathic generalized epilepsy

The aim of this study was to investigate brain structure and corresponding static and dynamic functional connectivity (sFC & dFC) abnormalities in untreated, first-episode pediatric idiopathic generalized epilepsy (IGE), with the goal of better understanding the underlying pathological mechanisms of IGE. Thirty-one children with IGE and 31 age-matched healthy controls (HC) were recruited. Structural magnetic resonance imaging (sMRI) data were acquired, and voxel-based morphometry (VBM) analysis were performed to reveal abnormal gray matter volume (GMV). Moreover, sFC and dFC analyses were conducted using the brain areas exhibiting abnormal GMV as seed regions to explore abnormal functional couplings. Compared to HC, the IGE group exhibited increased GMV in left middle cingulate cortex (MCC) and right parahippocampus (ParaHipp). In addition, the analyses of dFC and sFC with MCC and ParaHipp as seeds revealed more extensive functional connectivity (FC) changes in dFC. Notably, the structurally and functionally abnormal brain areas were primarily localized in the default mode network (DMN). However, our study did not find any significant associations between these altered neuroimaging measurements and clinical outcomes. This study uncovered microstructural changes as well as corresponding sFC and dFC changes in patients with new-onset, untreated pediatric IGE. The affected brain regions were primarily located within the DMN, highlighting the DMN's crucial role in the development of pediatric IGE.

Functional connectivity discriminates epileptogenic states and predicts surgical outcome in children with drug resistant epilepsy

Normal brain functioning emerges from a complex interplay among regions forming networks. In epilepsy, these networks are disrupted causing seizures. Highly connected nodes in these networks are epilepsy surgery targets. Here, we assess whether functional connectivity (FC) using intracranial electroencephalography can quantify brain regions epileptogenicity and predict surgical outcome in children with drug resistant epilepsy (DRE). We computed FC between electrodes on different states (i.e. interictal without spikes, interictal with spikes, pre-ictal, ictal, and post-ictal) and frequency bands. We then estimated the electrodes' nodal strength. We compared nodal strength between states, inside and outside resection for good- (n = 22, Engel I) and poor-outcome (n = 9, Engel II-IV) patients, respectively, and tested their utility to predict the epileptogenic zone and outcome. We observed a hierarchical epileptogenic organization among states for nodal strength: lower FC during interictal and pre-ictal states followed by higher FC during ictal and post-ictal states (p < 0.05). We further observed higher FC inside resection (p < 0.05) for good-outcome patients on different states and bands, and no differences for poor-outcome patients. Resection of nodes with high FC was predictive of outcome (positive and negative predictive values: 47-100%). Our findings suggest that FC can discriminate epileptogenic states and predict outcome in patients with DRE.

Study of brain network alternations in non-lesional epilepsy patients by BOLD-fMRI

Objective

To investigate the changes of brain network in epilepsy patients without intracranial lesions under resting conditions.

Methods

Twenty-six non-lesional epileptic patients and 42 normal controls were enrolled for BOLD-fMRI examination. The differences in brain network topological characteristics and functional network connectivity between the epilepsy group and the healthy controls were compared using graph theory analysis and independent component analysis.

Results

The area under the curve for local efficiency was significantly lower in the epilepsy patients compared with healthy controls, while there were no differences in global indicators. Patients with epilepsy had higher functional connectivity in 4 connected components than healthy controls (orbital superior frontal gyrus and medial superior frontal gyrus, medial superior frontal gyrus and angular gyrus, superior parietal gyrus and paracentral lobule, lingual gyrus, and thalamus). In addition, functional connectivity was enhanced in the default mode network, frontoparietal network, dorsal attention network, sensorimotor network, and auditory network in the epilepsy group.

Conclusion

The topological characteristics and functional connectivity of brain networks are changed in in non-lesional epilepsy patients. Abnormal functional connectivity may suggest reduced brain efficiency in epilepsy patients and also may be a compensatory response to brain function early at earlier stages of the disease.

Roles of fMRI and Wada tests in the presurgical evaluation of language functions in temporal lobe epilepsy

Surgical treatment of pharmacoresistant temporal lobe epilepsy (TLE) carries risks for language function that can significantly affect the quality of life. Predicting the risks of decline in language functions before surgery is, consequently, just as important as predicting the chances of becoming seizure-free. The intracarotid amobarbital test, generally known as the Wada test (WT), has been traditionally used to determine language lateralization and to estimate their potential decline after surgery. However, the test is invasive and it does not localize the language functions. Therefore, other noninvasive methods have been proposed, of which functional magnetic resonance (fMRI) has the greatest potential. Functional MRI allows localization of language areas. It has good concordance with the WT for language lateralization, and it is of predictive value for postsurgical naming outcomes. Consequently, fMRI has progressively replaced WT for presurgical language evaluation. The objective of this manuscript is to review the most relevant aspects of language functions in TLE and the current role of fMRI and WT in the presurgical evaluation of language. First, we will provide context by revising the language network distribution and the effects of TLE on them. Then, we will assess the functional outcomes following various forms of TLE surgery and measures to reduce postoperative language decline. Finally, we will discuss the current indications for WT and fMRI and the potential usefulness of the resting-state fMRI technique.

EEG-fMRI of epileptiform discharges: non-invasive investigation of the whole brain

Simultaneous EEG-fMRI is a unique and non-invasive method for investigating epileptic activity. Interictal epileptiform discharge-related EEG-fMRI provides cortical and subcortical blood oxygen level-dependent (BOLD) signal changes specific to epileptic discharges. As a result, EEG-fMRI has revealed insights into generators and networks involved in epileptic activity in different types of epilepsy, demonstrating-for instance-the implication of the thalamus in human generalized spike and wave discharges and the role of the Default Mode Network (DMN) in absences and focal epilepsy, and proposed a mechanism for the cortico-subcortical interactions in Lennox-Gastaut syndrome discharges. EEG-fMRI can find deep sources of epileptic activity not available to scalp EEG or MEG and provides critical new information to delineate the epileptic focus when considering surgical treatment or electrode implantation. In recent years, methodological advances, such as artifact removal and automatic detection of events have rendered this method easier to implement, and its clinical potential has since been established by evidence of the impact of BOLD response on clinical decision-making and of the relationship between concordance of BOLD responses with extent of resection and surgical outcome. This review presents the recent developments in EEG-fMRI methodology and EEG-fMRI studies in different types of epileptic disorders as follows: EEG-fMRI acquisition, gradient and pulse artifact removal, statistical analysis, clinical applications, pre-surgical evaluation, altered physiological state in generalized genetic epilepsy, and pediatric EEG-fMRI studies.

Localization of interictal discharge origin: A simultaneous intracranial electroencephalographic-functional magnetic resonance imaging study

OBJECTIVE

Scalp electroencephalographic (EEG)-functional magnetic resonance imaging (fMRI) studies suggest that the maximum blood oxygen level-dependent (BOLD) response to an interictal epileptiform discharge (IED) identifies the area of IED generation. However, the maximum BOLD response has also been reported in distant, seemingly irrelevant areas. Given the poor postoperative outcomes associated with extra-temporal lobe epilepsy, we hypothesized this finding is more common when analyzing extratemporal IEDs as compared to temporal IEDs. We further hypothesized that a subjective, holistic assessment of other significant BOLD clusters to identify the most clinically relevant cluster could be used to overcome this limitation and therefore better identify the likely origin of an IED. Specifically, we also considered the second maximum cluster and the cluster closest to the electrode contacts where the IED was observed.

METHODS

Maps of significant IED-related BOLD activation were generated for 48 different IEDs recorded from 33 patients who underwent intracranial EEG-fMRI. The locations of the maximum, second maximum, and closest clusters were identified for each IED. An epileptologist, blinded to these cluster assignments, selected the most clinically relevant BOLD cluster, taking into account all available clinical information. The distances between these BOLD clusters and their corresponding IEDs were then measured.

RESULTS

The most clinically relevant cluster was the maximum cluster for 56% (27/48) of IEDs, the second maximum cluster for 13% (6/48) of IEDs, and the closest cluster for 31% (15/48) of IEDs. The maximum clusters were closer to IED contacts for temporal than for extratemporal IEDs (p = .022), whereas the most clinically relevant clusters were not significantly different (p = .056).

SIGNIFICANCE

The maximum BOLD response to IEDs may not always be the most indicative of IED origin. We propose that available clinical information should be used in conjunction with EEG-fMRI data to identify a BOLD cluster representative of the IED origin.

Voxel-wise functional connectivity of the default mode network in epilepsies: a systematic review and meta-analysis

Background:

Default Mode Network (DMN) is recognized to be involved in the generation and propagation of epileptic activities in various epilepsies. Converging evidence has suggested disturbed Functional Connectivity (FC) in epilepsies, which was inferred to be related to underlying pathological mechanisms. However, abnormal changes of FC in DMN revealed by different studies are controversial, which obscures the role of DMN in distinct epilepsies.

Objective:

The present work aims to investigate the voxel-wise FC in DMN across epilepsies.

Methods:

A systematic review was conducted on 22 published articles before October 2020, indexed in PubMed and Web of Science. A meta-analysis with a random-effect model was performed using the effect-size signed differential mapping approach. Subgroup analyses were performed in three groups: Idiopathic Generalized Epilepsy (IGE), mixed Temporal Lobe Epilepsy (TLE), and mixed Focal Epilepsy (FE) with different foci.

Results:

The meta-analysis suggested commonly decreased FC in mesial prefrontal cortices across different epilepsies. Additionally decreased FC in posterior DMN was observed in IGE. The TLE showed decreased FC in temporal lobe regions and increased FC in the dorsal posterior cingulate cortex. Interestingly, an opposite finding in the ventral and dorsal middle frontal gyrus was observed in TLE. The FE demonstrated increased FC in the cuneus.

Spatiotemporal distribution and age of seizure onset in a pediatric epilepsy surgery cohort with cortical dysplasia

OBJECTIVE

Focal Cortical Dysplasias (CD) are a common etiology of refractory pediatric epilepsy and are amenable to epilepsy surgery. We investigated the association of lesion volume and location to age of seizure onset among children with CD who underwent epilepsy surgery.

METHODS

A retrospective study of epilepsy surgery patients with pathologically-confirmed CD. Regions of interest (ROI) determined preoperative lesion volumes on 1.5 T and 3 T T2 and SPGR MRIs, and location in 7 distributed neural networks. Descriptive and inferential statistics were used.

RESULTS

Fifty-five patients were identified: 35 girls (56.5 %). Median age of seizure onset: 19.0 months (range 0.02 months - 16.0 years). Median age of surgery: 7.8 years (range 2.89 months - 24.45 years). CD were frontal (n = 21, 38 %); temporal (n = 15, 27 %); parietal (n = 10, 18 %); occipital (n = 3, 5%); multilobar (n = 6, 11 %). Frontal FCD had seizure onset < 1-year-old (P = 0.10); temporal lobe CD seizure onset was more likely > 5-years-old (P= 0.06). Median lesion volume for CD was 23.23 cm³ (range: 1.87-591.73 cm³). Larger CD lesions were associated with earlier epilepsy (P = 0.01, r = -0.16). We did not find that lesions proximal to early maturing cortical regions were associated with earlier seizure onset. We found an association with CD location in the default mode network (DMN) and age onset < 5years old (P = 0.03). Age of seizure onset was negatively correlated with percent of CD overlapping motor cortex (P = 0.001, r =-0.794) but not with CD overlap of the visual cortex (P = 0.35). There was no effect of CD type on age of epilepsy onset.

SIGNIFICANCE

Larger CD lesions are associated with earlier onset epilepsy. CD most commonly occurs within the DMN and Limbic network, and DMN is associated with seizure onset before 5-years-old. Percent of CD overlapping motor cortex correlates with earlier seizure onset. These observations may reflect patterns of brain maturation or regional differences in clinical expression of seizures.

Abnormal blood oxygen level-dependent fluctuations and remote connectivity in sleep-related hypermotor epilepsy

OBJECTIVE

Sleep-related hypermotor epilepsy (SHE) is a form of the epileptic syndrome that involves stereotyped hypermotor seizures and presents as asymmetric tonic or dystonic posturing events. We aimed to investigate the brain activities of SHE patients using structural and functional magnetic resonance imaging (fMRI).

METHODS

A total of 41 patients with SHE and 41 age- and sex-matched healthy controls (HCs) were prospectively enrolled and assessed using fMRI. The two groups were compared in amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo), and potential correlations between these measures and clinical features were also examined. The involvement of functional network integration was explored by analyzing seed-based functional connectivity.

RESULTS

In SHE patients, ALFF in the right precentral gyrus was significantly higher than in HCs, and ReHo in the left postcentral and right precentral gyrus was higher. None of the brain regions had lower ALFF or ReHo compared to HCs. ReHo in the left postcentral gyrus and ALFF in the right precentral gyrus were both negatively correlated with epilepsy duration. Patients with SHE had higher functional connectivity mainly in the precuneus, postcentral gyrus, and supplementary motor area. However, none of the brain regions in SHE group presented lower functional connectivity than in HCs. SHE is associated with disrupted regional and interregional functional activities.

CONCLUSIONS

The patients showed abnormalities within the sensorimotor gyrus and supplementary motor area, suggesting spontaneous fluctuations correlated with remote functional brain network. These results at the whole-brain level argue for further investigation into connectivity disturbance in SHE.

Dynamic Temporospatial Patterns of Functional Connectivity and Alterations in Idiopathic Generalized Epilepsy

The dynamic profile of brain function has received much attention in recent years and is also a focus in the study of epilepsy. The present study aims to integrate the dynamics of temporal and spatial characteristics to provide comprehensive and novel understanding of epileptic dynamics. Resting state fMRI data were collected from eighty-three patients with idiopathic generalized epilepsy (IGE) and 87 healthy controls (HC). Specifically, we explored the temporal and spatial variation of functional connectivity density (tvFCD and svFCD) in the whole brain. Using a sliding-window approach, for a given region, the standard variation of the FCD series was calculated as the tvFCD and the variation of voxel-wise spatial distribution was calculated as the svFCD. We found primary, high-level, and sub-cortical networks demonstrated distinct tvFCD and svFCD patterns in HC. In general, the high-level networks showed the highest variation, the subcortical and primary networks showed moderate variation, and the limbic system showed the lowest variation. Relative to HC, the patients with IGE showed weaken temporal and enhanced spatial variation in the default mode network and weaken temporospatial variation in the subcortical network. Besides, enhanced temporospatial variation in sensorimotor and high-level networks was also observed in patients. The hyper-synchronization of specific brain networks was inferred to be associated with the phenomenon responsible for the intrinsic propensity of generation and propagation of epileptic activities. The disrupted dynamic characteristics of sensorimotor and high-level networks might potentially contribute to the driven motion and cognition phenotypes in patients. In all, presently provided evidence from the temporospatial variation of functional interaction shed light on the dynamics underlying neuropathological profiles of epilepsy.

Modulation of epileptic networks by transient interictal epileptic activity: A dynamic approach to simultaneous EEG-fMRI

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EEG-fMRI has been instrumental in characterizing brain networks in epilepsy.

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Its value is documented in the pre-surgical assessment of drug-resistant epilepsy.

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The delineation of brain areas to resect is fundamental for the post-surgical outcome.

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Standard EEG-fMRI in epilepsy assesses static functional connectivity of the network.

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EEG-fMRI dynamic connectivity identifies transitory features of specific connections.

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We integrate dynamic fMRI connectivity and dynamic patterns of simultaneous scalp EEG.

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This allows to better characterize the spatiotemporal aspects of epileptic networks.

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This may help in more efficiently target the surgical intervention.

Epileptic networks, defined as brain regions involved in epileptic brain activity, have been mapped by functional connectivity in simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) recordings. This technique allows to define brain hemodynamic changes, measured by the Blood Oxygen Level Dependent (BOLD) signal, associated to the interictal epileptic discharges (IED), which together with ictal events constitute a signature of epileptic disease. Given the highly time-varying nature of epileptic activity, a dynamic functional connectivity (dFC) analysis of EEG-fMRI data appears particularly suitable, having the potential to identify transitory features of specific connections in epileptic networks. In the present study, we propose a novel method, defined dFC-EEG, that integrates dFC assessed by fMRI with the information recorded by simultaneous scalp EEG, in order to identify the connections characterised by a dynamic profile correlated with the occurrence of IED, forming the dynamic epileptic subnetwork. Ten patients with drug-resistant focal epilepsy were included, with different aetiology and showing a widespread (or multilobar) BOLD activation, defined as involving at least two distinct clusters, located in two different lobes and/or extended to the hemisphere contralateral to the epileptic focus. The epileptic focus was defined from the IED-related BOLD map. Regions involved in the occurrence of interictal epileptic activity; i.e., forming the epileptic network, were identified by a general linear model considering the timecourse of the fMRI-defined focus as main regressor. dFC between these regions was assessed with a sliding-window approach. dFC timecourses were then correlated with the sliding-window variance of the IED signal (VarIED), to identify connections whose dynamics related to the epileptic activity; i.e., the dynamic epileptic subnetwork. As expected, given the very different clinical picture of each individual, the extent of this subnetwork was highly variable across patients, but was but was reduced of at least 30% with respect to the initially identified epileptic network in 9/10 patients. The connections of the dynamic subnetwork were most commonly close to the epileptic focus, as reflected by the laterality index of the subnetwork connections, reported higher than the one within the original epileptic network. Moreover, the correlation between dFC timecourses and VarIED was predominantly positive, suggesting a strengthening of the dynamic subnetwork associated to the occurrence of IED. The integration of dFC and scalp IED offers a more specific description of the epileptic network, identifying connections strongly influenced by IED. These findings could be relevant in the pre-surgical evaluation for the resection or disconnection of the epileptogenic zone and help in reaching a better post-surgical outcome. This would be particularly important for patients characterised by a widespread pathological brain activity which challenges the surgical intervention.

Assessment of cognitive functions and related risk factors in Iranian patients with generalized epilepsy as compared to patients with non-epileptic neurological disorders

Background: The cognitive impairment in patients with generalized epilepsy may affect their social efficiency and quality of life (QOL). The aim of this study is to determine the cognitive dysfunction and related risk factors in patients with generalized epilepsy as compared to patients with non-epileptic neurological disorders. Methods: In the present descriptive cross-sectional study, the cognitive function was assessed by Montreal Cognitive Assessment (MoCA) test in 62 patients with generalized epilepsy and also 62 patients with non-epileptic neurological diseases who referred to the Neurology Clinic, Semnan University of Medical Sciences, Semnan, Iran. The relationship between cognitive impairment and related risk factors was also investigated. The data were analyzed by SPSS software. Results: The mean score of MoCA in the patients with generalized epilepsy and the control group was 22.80 ± 4.14 and 26.48 ± 2.85, respectively (P < 0.050). The results indicated significantly lower MoCA scores in the epileptic group rather than the non-epileptic one (P < 0.001). Moreover, there was a significant relationship between MoCA score and age, education level, living place, the dose and rate of medicines, and the number of seizures in patients with epilepsy (P < 0.001). Gender and the duration of disease had no significant effects on the cognitive impairment of patients with epilepsy (P > 0.05). Conclusion: Patients with epilepsy had a significant cognitive impairment as compared to the patients with non-epileptic neurological disorders. Age, education level, living place, the dose and rate of medicines, and the number of seizures were the risk factors of cognitive impairment in the patients with epilepsy, while duration of disease and gender had no effects on the intensity of cognitive deficits.

Resting-state functional MRI of the default mode network in epilepsy

The default mode network (DMN) is a major neuronal network that deactivates during goal-directed tasks. Recent advances in neuroimaging have shed light on its structure and function. Alterations in the DMN are increasingly recognized in a range of neurological and psychiatric conditions including epilepsy. This review first describes the current understanding of the DMN in health, normal aging, and disease as it is acquired via resting-state functional magnetic resonance imaging (MRI), before focusing on how it is affected in various types of focal and generalized epilepsy. These findings support the potential use of DMN parameters as future biomarkers in epilepsy research, diagnosis, and management.

Graph theory application with functional connectivity to distinguish left from right temporal lobe epilepsy

OBJECTIVE

To investigate the application of graph theory with functional connectivity to distinguish left from right temporal lobe epilepsy (TLE).

METHODS

Alterations in functional connectivity within several brain networks - default mode (DMN), attention (AN), limbic (LN), sensorimotor (SMN) and visual (VN) - were examined using resting-state functional MRI (rs-fMRI). The study accrued 21 left and 14 right TLE as well as 17 nonepileptic control subjects. The local nodal degree, a feature of graph theory, was calculated foreach of the brain networks. Multivariate logistic regression analysis was performed to determine the accuracy of identifying seizure laterality based on significant differences in local nodal degree in the selected networks.

RESULTS

Left and right TLE patients showed dissimilar patterns of alteration in functional connectivity when compared to control subjects. Compared with right TLE, patients with left TLE exhibited greater nodal degree' (i.e. hyperconnectivity) with right superomedial frontal gyrus (in DMN), inferior frontal gyrus pars triangularis (in AN), right caudate and left superior temporal gyrus (in LN) and left paracentral lobule (in SMN), while showing lesser nodal degree (i.e. hypoconnectivity) with left temporal pole (in DMN), right insula (in LN), left supplementary motor area (in SMN), and left fusiform gyrus (in VN). The LN showed the highest accuracy of 82.9% among all considered networks in determining laterality of the TLE. By combinations of local degree attributes in the DMN, AN, LN, and VN, logistic regression analysis demonstrated an accuracy of 94.3% by comparison.

CONCLUSION

Our study demonstrates the utility of graph theory application to brain network analysis as a potential biomarker to assist in the determination of TLE laterality and improve the confidence in presurgical decision-making in cases of TLE.

Pushing the Limits of EEG: Estimation of Large-Scale Functional Brain Networks and Their Dynamics Validated by Simultaneous fMRI

Functional magnetic resonance imaging (fMRI) is the technique of choice for detecting large-scale functional brain networks and to investigate their dynamics. Because fMRI measures brain activity indirectly, electroencephalography (EEG) has been recently considered a feasible tool for detecting such networks, particularly the resting-state networks (RSNs). However, a truly unbiased validation of such claims is still missing, which can only be accomplished by using simultaneously acquired EEG and fMRI data, due to the spontaneous nature of the activity underlying the RSNs. Additionally, EEG is still poorly explored for the purpose of mapping task-specific networks, and no studies so far have been focused on investigating networks' dynamic functional connectivity (dFC) with EEG. Here, we started by validating RSNs derived from the continuous reconstruction of EEG sources by directly comparing them with those derived from simultaneous fMRI data of 10 healthy participants, and obtaining an average overlap (quantified by the Dice coefficient) of 0.4. We also showed the ability of EEG to map the facial expressions processing network (FEPN), highlighting regions near the posterior superior temporal sulcus, where the FEPN is anchored. Then, we measured the dFC using EEG for the first time in this context, estimated dFC brain states using dictionary learning, and compared such states with those obtained from the fMRI. We found a statistically significant match between fMRI and EEG dFC states, and determined the existence of two matched dFC states which contribution over time was associated with the brain activity at the FEPN, showing that the dynamics of FEPN can be captured by both fMRI and EEG. Our results push the limits of EEG toward being used as a brain imaging tool, while supporting the growing literature on EEG correlates of (dynamic) functional connectivity measured with fMRI, and providing novel insights into the coupling mechanisms underlying the two imaging techniques.

ADHD with Comorbid Bipolar Disorders: A Systematic Review of Neurobiological, Clinical and Pharmacological Aspects Across the Lifespan

BACKGROUND

Attention deficit hyperactivity (ADHD) disorder is a neurodevelopmental disorder characterized by inattention, hyperactivity, disruptive behaviour, and impulsivity. Despite considered typical of children for a long time, the persistence of ADHD symptoms in adulthood gained increasing interest during the last decades. Indeed, its diagnosis, albeit controversial, is rarely carried out even because ADHD is often comorbid with several other psychiatric diosrders, in particular with bipolar disorders (BDs), a condition that complicates the clinical picture, assessment and treatment.

AIMS

The aim of this paper was to systematically review the scientific literature on the neurobiological, clinical features and current pharmacological management of ADHD comorbid with BDs across the entire lifespan, with a major focus on the adulthood.

DISCUSSION

The pharmacology of ADHD-BD in adults is still empirical and influenced by the individual experience of the clinicians. Stimulants are endowed of a prompt efficacy and safety, whilst non-stimulants are useful when a substance abuse history is detected, although they require some weeks in order to be fully effective. In any case, an in-depth diagnostic and clinical evaluation of the single individual is mandatory.

CONCLUSION

The comorbidity of ADHD with BD is still a controversial matter, as it is the notion of adult ADHD as a distinct nosological category. Indeed, some findings highlighted the presence of common neurobiological mechanisms and overlapping clinical features, although disagreement does exist. In any case, while expecting to disentangle this crucial question, a correct management of this comorbidity is essential, which requires the co-administration of mood stabilizers. Further controlled clinical studies in large samples of adult ADHD-BD patients appear extremely urgent in order to better define possible therapeutic guidelines, as well as alternative approaches for this potentially invalidating condition.

A connectome-based mechanistic model of focal cortical dysplasia

Neuroimaging studies have consistently shown distributed brain anomalies in epilepsy syndromes associated with a focal structural lesion, particularly mesiotemporal sclerosis. Conversely, a system-level approach to focal cortical dysplasia has been rarely considered, likely due to methodological difficulties in addressing variable location and topography. Given the known heterogeneity in focal cortical dysplasia histopathology, we hypothesized that lesional connectivity consists of subtypes with distinct structural signatures. Furthermore, in light of mounting evidence for focal anomalies impacting whole-brain systems, we postulated that patterns of focal cortical dysplasia connectivity may exert differential downstream effects on global network topology. We studied a cohort of patients with histologically verified focal cortical dysplasia type II (n = 27), and age- and sex-matched healthy controls (n = 34). We subdivided each lesion into similarly sized parcels and computed their connectivity to large-scale canonical functional networks (or communities). We then dichotomized connectivity profiles of lesional parcels into those belonging to the same functional community as the focal cortical dysplasia (intra-community) and those adhering to other communities (inter-community). Applying hierarchical clustering to community-reconfigured connectome profiles identified three lesional classes with distinct patterns of functional connectivity: decreased intra- and inter-community connectivity, a selective decrease in intra-community connectivity, and increased intra- as well as inter-community connectivity. Hypo-connectivity classes were mainly composed of focal cortical dysplasia type IIB, while the hyperconnected lesions were type IIA. With respect to whole-brain networks, patients with hypoconnected focal cortical dysplasia and marked structural damage showed only mild imbalances, while those with hyperconnected subtle lesions had more pronounced topological alterations. Correcting for interictal epileptic discharges did not impact connectivity patterns. Multivariate structural equation analysis provided a mechanistic model of such complex, diverging interactions, whereby the focal cortical dysplasia structural makeup shapes its functional connectivity, which in turn modulates whole-brain network topology.

Spatial and episodic memory tasks promote temporal lobe interictal spikes

Reflex epilepsies have been demonstrated to exploit specific networks that subserve normal physiological function. It is unclear whether more common forms of epilepsy share this particular feature. By measuring interictal spikes in patients with a range of epilepsies, we show that 2 tasks known to specifically engage the hippocampus and temporal neocortex promoted increased interictal spiking within these regions, whereas a nonhippocampal dependent task did not. This indicates that interictal spike frequency may reflect the processing demands being placed on specific functional-anatomical networks in epilepsy. ANN NEUROL 2019;86:304-309.

Relationship Between Seizure Frequency and Functional Abnormalities in Limbic Network of Medial Temporal Lobe Epilepsy

Background: We compared resting-state functional connectivity (RSFC) among limbic and temporal lobe regions between patients with medial temporal lobe epilepsy (mTLE) and healthy control subjects to identify imaging evidence of functional networks related to seizure frequency, age of seizure onset, and duration of epilepsy.

Methods: Twelve patients with drug-resistant, unilateral medial temporal lobe epilepsy and 12 healthy control subjects matched for age, sex, and handedness participated in the imaging experiments. We used network-based statistics to compare functional connectivity graphs in patients with mTLE and healthy controls to investigate the relationship between functional connectivity abnormalities and seizure frequency.

Results: Among mTLE patients, we found functional network abnormalities throughout the limbic system, but primarily in the hemisphere ipsilateral to the seizure focus. The RSFCs between ipsilateral hypothalamus and ventral anterior cingulate cortex and between ipsilateral subiculum and contralateral posterior cingulate cortex were highly correlated with seizure frequency.

Discussion: These findings suggest that in mTLE, changes in limbic networks ipsilateral to the epileptic focus are common. The pathological changes in connectivity between cingulate cortex, hypothalamus and subiculum ipsilateral to the seizure focus were correlated with increased seizure frequency.

Coping strategies and their relationship with emotional intelligence in patients with epilepsy referred to Isfahan Epilepsy Society in 2017

INTRODUCTION

Epilepsy is a common neurological disorder, and the patients with epilepsy are heavily influenced by the psychological and social aspects of the illness. Therefore, patients try to use coping strategies to control their stress and tension in this situation. Given the importance of the issue of adaptation and coping with stress in patients with epilepsy, as well as the different factors affecting coping strategies in these patients, the present study aimed to investigate the relationship between coping strategies and emotional intelligence in patients with epilepsy.

METHODS

This descriptive-analytic study conducted on 134 male and female patients with epilepsy referred to the Epilepsy Society of Isfahan, Iran. The consecutive sampling method was applied in this study. The data collection tool included a three-section questionnaire: the Demographic information, the Coping Inventory for Stressful Situations (CISS), and the Bar-On Emotional Quotient Inventory (EQ-i).

RESULTS

The emotion-focused coping strategy was mostly used by 53.7% of the samples. The mean and standard deviation of the total score of emotional intelligence was 285.6 ± 39.5. Moreover, Pearson correlation test showed a significant difference between emotional intelligence variables and coping strategies (p < 0.001).

CONCLUSION

According to the relationship between emotional intelligence and coping strategies, it is suggested to consider ways to improve the emotional intelligence of patients with epilepsy in order to use more adaptive coping strategies.

Identification of epileptic brain states by dynamic functional connectivity analysis of simultaneous EEG-fMRI: a dictionary learning approach

Most fMRI studies of the brain's intrinsic functional connectivity (FC) have assumed that this is static; however, it is now clear that it changes over time. This is particularly relevant in epilepsy, which is characterized by a continuous interchange between epileptic and normal brain states associated with the occurrence of epileptic activity. Interestingly, recurrent states of dynamic FC (dFC) have been found in fMRI data using unsupervised learning techniques, assuming either their sparse or non-sparse combination. Here, we propose an l₁-norm regularized dictionary learning (l₁-DL) approach for dFC state estimation, which allows an intermediate and flexible degree of sparsity in time, and demonstrate its application in the identification of epilepsy-related dFC states using simultaneous EEG-fMRI data. With this l₁-DL approach, we aim to accommodate a potentially varying degree of sparsity upon the interchange between epileptic and non-epileptic dFC states. The simultaneous recording of the EEG is used to extract time courses representative of epileptic activity, which are incorporated into the fMRI dFC state analysis to inform the selection of epilepsy-related dFC states. We found that the proposed l₁-DL method performed best at identifying epilepsy-related dFC states, when compared with two alternative methods of extreme sparsity (k-means clustering, maximum; and principal component analysis, minimum), as well as an l₀-norm regularization framework (l₀-DL), with a fixed amount of temporal sparsity. We further showed that epilepsy-related dFC states provide novel insights into the dynamics of epileptic networks, which go beyond the information provided by more conventional EEG-correlated fMRI analysis, and which were concordant with the clinical profile of each patient. In addition to its application in epilepsy, our study provides a new dFC state identification method of potential relevance for studying brain functional connectivity dynamics in general.

Brain network dynamics in the human articulatory loop

OBJECTIVE

The articulatory loop is a fundamental component of language function, involved in the short-term buffer of auditory information followed by its vocal reproduction. We characterized the network dynamics of the human articulatory loop, using invasive recording and stimulation.

METHODS

We measured high-gamma activity_{70-110 Hz} recorded intracranially when patients with epilepsy either only listened to, or listened to and then reproduced two successive tones by humming. We also conducted network analyses, and analyzed behavioral responses to cortical stimulation.

RESULTS

Presentation of the initial tone elicited high-gamma augmentation bilaterally in the superior-temporal gyrus (STG) within 40ms, and in the precentral and inferior-frontal gyri (PCG and IFG) within 160ms after sound onset. During presentation of the second tone, high-gamma augmentation was reduced in STG but enhanced in IFG. The task requiring tone reproduction further enhanced high-gamma augmentation in PCG during and after sound presentation. Event-related causality (ERC) analysis revealed dominant flows within STG immediately after sound onset, followed by reciprocal interactions involving PCG and IFG. Measurement of cortico-cortical evoked-potentials (CCEPs) confirmed connectivity between distant high-gamma sites in the articulatory loop. High-frequency stimulation of precentral high-gamma sites in either hemisphere induced speech arrest, inability to control vocalization, or forced vocalization. Vocalization of tones was accompanied by high-gamma augmentation over larger extents of PCG.

CONCLUSIONS

Bilateral PCG rapidly and directly receives feed-forward signals from STG, and may promptly initiate motor planning including sub-vocal rehearsal for short-term buffering of auditory stimuli. Enhanced high-gamma augmentation in IFG during presentation of the second tone may reflect high-order processing of the tone sequence.

SIGNIFICANCE

The articulatory loop employs sustained reciprocal propagation of neural activity across a network of cortical sites with strong neurophysiological connectivity.

Electrophysiological resting-state biomarker for diagnosing mesial temporal lobe epilepsy with hippocampal sclerosis

The main aim of the present study was to evaluate whether resting-state functional connectivity of magnetoencephalography (MEG) signals can differentiate patients with mesial temporal lobe epilepsy (MTLE) from healthy controls (HC) and can differentiate between right and left MTLE as a diagnostic biomarker. To this end, a support vector machine (SVM) method among various machine learning algorithms was employed. We compared resting-state functional networks between 46 MTLE (right MTLE=23; left MTLE=23) patients with histologically proven HS who were free of seizure after surgery, and 46 HC. The optimal SVM group classifier distinguished MTLE patients with a mean accuracy of 95.1% (sensitivity=95.8%; specificity=94.3%). Increased connectivity including the right posterior cingulate gyrus and decreased connectivity including at least one sensory-related resting-state network were key features reflecting the differences between MTLE patients and HC. The optimal SVM model distinguished between right and left MTLE patients with a mean accuracy of 76.2% (sensitivity=76.0%; specificity=76.5%). We showed the potential of electrophysiological resting-state functional connectivity, which reflects brain network reorganization in MTLE patients, as a possible diagnostic biomarker to differentiate MTLE patients from HC and differentiate between right and left MTLE patients.

Regional and global connectivity disturbances in focal epilepsy, related neurocognitive sequelae, and potential mechanistic underpinnings

Epilepsy is among the most common brain network disorders, and it is associated with substantial morbidity and increased mortality. Although focal epilepsy was traditionally considered a regional brain disorder, growing evidence has demonstrated widespread network alterations in this disorder that extend beyond the epileptogenic zone from which seizures originate. The goal of this review is to summarize recent investigations examining functional and structural connectivity alterations in focal epilepsy, including neuroimaging and electrophysiologic studies utilizing model-based or data-driven analytic methods. A significant subset of studies in both mesial temporal lobe epilepsy and focal neocortical epilepsy have demonstrated patterns of increased connectivity related to the epileptogenic zone, coupled with decreased connectivity in widespread distal networks. Connectivity patterns appear to be related to the duration and severity of disease, suggesting progressive connectivity reorganization in the setting of recurrent seizures over time. Global resting-state connectivity disturbances in focal epilepsy have been linked to neurocognitive problems, including memory and language disturbances. Although it is possible that increased connectivity in a particular brain region may enhance the propensity for seizure generation, it is not clear if global reductions in connectivity represent the damaging consequences of recurrent seizures, or an adaptive mechanism to prevent seizure propagation away from the epileptogenic zone. Overall, studying the connectome in focal epilepsy is a critical endeavor that may lead to improved strategies for epileptogenic-zone localization, surgical outcome prediction, and a better understanding of the neuropsychological implications of recurrent seizures.

Interictal activity is an important contributor to abnormal intrinsic network connectivity in paediatric focal epilepsy

Patients with focal epilepsy have been shown to have reduced functional connectivity in intrinsic connectivity networks (ICNs), which has been related to neurocognitive development and outcome. However, the relationship between interictal epileptiform discharges (IEDs) and changes in ICNs remains unclear, with evidence both for and against their influence. EEG-fMRI data was obtained in 27 children with focal epilepsy (mixed localisation and aetiologies) and 17 controls. A natural stimulus task (cartoon blocks verses blocks where the subject was told "please wait") was used to enhance the connectivity within networks corresponding to ICNs while reducing potential confounds of vigilance and motion. Our primary hypothesis was that the functional connectivity within visual and attention networks would be reduced in patients with epilepsy. We further hypothesized that controlling for the effects of IEDs would increase the connectivity in the patient group. The key findings were: (1) Patients with mixed epileptic foci showed a common connectivity reduction in lateral visual and attentional networks compared with controls. (2) Having controlled for the effects of IEDs there were no connectivity differences between patients and controls. (3) A comparison within patients revealed reduced connectivity between the attentional network and basal ganglia associated with interictal epileptiform discharges. We also found that the task activations were reduced in epilepsy patients but that this was unrelated to IED occurrence. Unexpectedly, connectivity changes in ICNs were strongly associated with the transient effects of interictal epileptiform discharges. Interictal epileptiform discharges were shown to have a pervasive transient influence on the brain's functional organisation. Hum Brain Mapp 38:221-236, 2017. © 2016 Wiley Periodicals, Inc.

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

OBJECTIVE

Epilepsy is increasingly considered as the dysfunction of a pathologic neuronal network (epileptic network) rather than a single focal source. We aimed to assess the interactions between the regions that comprise the epileptic network and to investigate their dependence on the occurrence of interictal epileptiform discharges (IEDs).

METHODS

We analyzed resting state simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) recordings in 10 patients with drug-resistant focal epilepsy with multifocal IED-related blood oxygen level-dependent (BOLD) responses and a maximum t-value in the IED field. We computed functional connectivity (FC) maps of the epileptic network using two types of seed: (1) a 10-mm diameter sphere centered in the global maximum of IED-related BOLD map, and (2) the independent component with highest correlation to the IED-related BOLD map, named epileptic component. For both approaches, we compared FC maps before and after regressing out the effect of IEDs in terms of maximum and mean t-values and percentage of map overlap.

RESULTS

Maximum and mean FC maps t-values were significantly lower after regressing out IEDs at the group level (p < 0.01). Overlap extent was 85% ± 12% and 87% ± 12% when the seed was the 10-mm diameter sphere and the epileptic component, respectively.

SIGNIFICANCE

Regions involved in a specific epileptic network show coherent BOLD fluctuations independent of scalp EEG IEDs. FC topography and strength is largely preserved by removing the IED effect. This could represent a signature of a sustained pathologic network with contribution from epileptic activity invisible to the scalp EEG.

The Significance of the Default Mode Network (DMN) in Neurological and Neuropsychiatric Disorders: A Review

The relationship of cortical structure and specific neuronal circuitry to global brain function, particularly its perturbations related to the development and progression of neuropathology, is an area of great interest in neurobehavioral science. Disruption of these neural networks can be associated with a wide range of neurological and neuropsychiatric disorders. Herein we review activity of the Default Mode Network (DMN) in neurological and neuropsychiatric disorders, including Alzheimer's disease, Parkinson's disease, Epilepsy (Temporal Lobe Epilepsy - TLE), attention deficit hyperactivity disorder (ADHD), and mood disorders. We discuss the implications of DMN disruptions and their relationship to the neurocognitive model of each disease entity, the utility of DMN assessment in clinical evaluation, and the changes of the DMN following treatment.

Multimodal imaging of dynamic functional connectivity

The study of large-scale functional interactions in the human brain with functional magnetic resonance imaging (fMRI) extends almost to the first applications of this technology. Due to historical reasons and preconceptions about the limitations of this brain imaging method, most studies have focused on assessing connectivity over extended periods of time. It is now clear that fMRI can resolve the temporal dynamics of functional connectivity, like other faster imaging techniques such as electroencephalography and magnetoencephalography (albeit on a different temporal scale). However, the indirect nature of fMRI measurements can hinder the interpretability of the results. After briefly summarizing recent advances in the field, we discuss how the simultaneous combination of fMRI with electrophysiological activity measurements can contribute to a better understanding of dynamic functional connectivity in humans both during rest and task, wakefulness, and other brain states.