Altered resting state functional network connectivity in children absence epilepsy

Reconstruction and application of multilayer brain network for juvenile myoclonic epilepsy based on link prediction

Juvenile myoclonic epilepsy (JME) exhibits abnormal functional connectivity of brain networks at multiple frequencies. We used the multilayer network model to address the heterogeneous features at different frequencies and assess the mechanisms of functional integration and segregation of brain networks in JME patients. To address the possibility of false edges or missing edges during network construction, we combined multilayer networks with link prediction techniques. Resting-state functional magnetic resonance imaging (rs-fMRI) data were procured from 40 JME patients and 40 healthy controls. The Multilayer Network framework is utilized to integrate information from different frequency bands and to fuse similarity metrics for link prediction. Finally, calculate the entropy of the multiplex degree and multilayer clustering coefficient of the reconfigured multilayer frequency network. The results showed that the multilayer brain network of JME patients had significantly reduced ability to integrate and separate information and significantly correlated with severity of JME symptoms. This difference was particularly evident in default mode network (DMN), motor and somatosensory network (SMN), and auditory network (AN). In addition, significant differences were found in the precuneus, suboccipital gyrus, middle temporal gyrus, thalamus, and insula. Results suggest that JME patients have abnormal brain function and reduced cross-frequency interactions. This may be due to changes in the distribution of connections within and between the DMN, SMN, and AN in multiple frequency bands, resulting in unstable connectivity patterns. The generation of these changes is related to the pathological mechanisms of JME and may exacerbate cognitive and behavioral problems in patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-024-10191-0.

EEG brain network variability is correlated with other pathophysiological indicators of critical patients in neurology intensive care unit

Continuous electroencephalogram (cEEG) plays a crucial role in monitoring and postoperative evaluation of critical patients with extensive EEG abnormalities. Recently, the temporal variability of dynamic resting-state functional connectivity has emerged as a novel approach to understanding the pathophysiological mechanisms underlying diseases. However, little is known about the underlying temporal variability of functional connections in critical patients admitted to neurology intensive care unit (NICU). Furthermore, considering the emerging field of network physiology that emphasizes the integrated nature of human organisms, we hypothesize that this temporal variability in brain activity may be potentially linked to other physiological functions. Therefore, this study aimed to investigate network variability using fuzzy entropy in 24-hour dynamic resting-state networks of critical patients in NICU, with an emphasis on exploring spatial topology changes over time. Our findings revealed both atypical flexible and robust architectures in critical patients. Specifically, the former exhibited denser functional connectivity across the left frontal and left parietal lobes, while the latter showed predominantly short-range connections within anterior regions. These patterns of network variability deviating from normality may underlie the altered network integrity leading to loss of consciousness and cognitive impairment observed in these patients. Additionally, we explored changes in 24-hour network properties and found simultaneous decreases in brain efficiency, heart rate, and blood pressure between approximately 1 pm and 5 pm. Moreover, we observed a close relationship between temporal variability of resting-state network properties and other physiological indicators including heart rate as well as liver and kidney function. These findings suggest that the application of a temporal variability-based cEEG analysis method offers valuable insights into underlying pathophysiological mechanisms of critical patients in NICU, and may present novel avenues for their condition monitoring, intervention, and treatment.

Abnormal dynamic functional network connectivity in patients with early-onset bipolar disorder

Objective

To explore the changes in dynamic functional brain network connectivity (dFNC) in patients with early-onset bipolar disorder (BD).

Methods

Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected from 39 patients with early-onset BD and 22 healthy controls (HCs). Four repeated and stable dFNC states were characterised by independent component analysis (ICA), sliding time windows and k-means clustering, and three dFNC temporal metrics (fraction of time, mean dwell time and number of transitions) were obtained. The dFNC temporal metrics and the differences in dFNC between the two groups in different states were evaluated, and the correlations between the differential dFNC metrics and neuropsychological scores were analysed.

Results

The dFNC analysis showed four connected patterns in all subjects. Compared with the HCs, the dFNC patterns of early-onset BD were significantly altered in all four states, mainly involving impaired cognitive and perceptual networks. In addition, early-onset BD patients had a decreased fraction of time and mean dwell time in state 2 and an increased mean dwell time in state 3 (p < 0.05). The mean dwell time in state 3 of BD showed a positive correlation trend with the HAMA score (r = 0.4049, p = 0.0237 × 3 > 0.05 after Bonferroni correction).

Conclusion

Patients with early-onset BD had abnormal dynamic properties of brain functional network connectivity, suggesting that their dFNC was unstable, mainly manifesting as impaired coordination between cognitive and perceptual networks. This study provided a new imaging basis for the neuropathological study of emotional and cognitive deficits in early-onset BD.

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 &lt; 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 &lt; 0.01), whereas the values of all DMN regions in the beta-gamma 2 band were significantly decreased (pcorrected &lt; 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 &lt; 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 &lt; 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 &lt; 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 &lt; 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.

Multilayer brain network modeling and dynamic analysis of juvenile myoclonic epilepsy

Objective: It is indisputable that the functional connectivity of the brain network in juvenile myoclonic epilepsy (JME) patients is abnormal. As a mathematical extension of the traditional network model, the multilayer network can fully capture the fluctuations of brain imaging data with time, and capture subtle abnormal dynamic changes. This study assumed that the dynamic structure of JME patients is abnormal and used the multilayer network framework to analyze the change brain community structure in JME patients from the perspective of dynamic analysis.

Methods: First, functional magnetic resonance imaging (fMRI) data were obtained from 35 JME patients and 34 healthy control subjects. In addition, the communities of the two groups were explored with the help of a multilayer network model and a multilayer community detection algorithm. Finally, differences were described by metrics that are specific to the multilayer network.

Results: Compared with healthy controls, JME patients had a significantly lower modularity degree of the brain network. Furthermore, from the level of the functional network, the integration of the default mode network (DMN) and visual network (VN) in JME patients showed a significantly higher trend, and the flexibility of the attention network (AN) also increased significantly. At the node level, the integration of seven nodes of the DMN was significantly increased, the integration of five nodes of the VN was significantly increased, and the flexibility of three nodes of the AN was significantly increased. Moreover, through division of the core-peripheral system, we found that the left insula and left cuneus were core regions specific to the JME group, while most of the peripheral systems specific to the JME group were distributed in the prefrontal cortex and hippocampus. Finally, we found that the flexibility of the opercular part of the inferior frontal gyrus was significantly correlated with the severity of JME symptoms.

Conclusion: Our findings indicate that the dynamic community structure of JME patients is indeed abnormal. These results provide a new perspective for the study of dynamic changes in communities in JME patients.

EEG Markers of Treatment Resistance in Idiopathic Generalized Epilepsy: From Standard EEG Findings to Advanced Signal Analysis

Idiopathic generalized epilepsy (IGE) represents a common form of epilepsy in both adult and pediatric epilepsy units. Although IGE has been long considered a relatively benign epilepsy syndrome, a remarkable proportion of patients could be refractory to treatment. While some clinical prognostic factors have been largely validated among IGE patients, the impact of routine electroencephalography (EEG) findings in predicting drug resistance is still controversial and a growing number of authors highlighted the potential importance of capturing the sleep state in this setting. In addition, the development of advanced computational techniques to analyze EEG data has opened new opportunities in the identification of reliable and reproducible biomarkers of drug resistance in IGE patients. In this manuscript, we summarize the EEG findings associated with treatment resistance in IGE by reviewing the results of studies considering standard EEGs, 24-h EEG recordings, and resting-state protocols. We discuss the role of 24-h EEG recordings in assessing seizure recurrence in light of the potential prognostic relevance of generalized fast discharges occurring during sleep. In addition, we highlight new and promising biomarkers as identified by advanced EEG analysis, including hypothesis-driven functional connectivity measures of background activity and data-driven quantitative findings revealed by machine learning approaches. Finally, we thoroughly discuss the methodological limitations observed in existing studies and briefly outline future directions to identify reliable and replicable EEG biomarkers in IGE patients.

Alterations of Cerebral Perfusion and Functional Connectivity in Children With Idiopathic Generalized Epilepsy

Background

Studies have demonstrated that adults with idiopathic generalized epilepsy (IGE) have functional abnormalities; however, the neuropathological pathogenesis differs between adults and children. This study aimed to explore alterations in the cerebral blood flow (CBF) and functional connectivity (FC) to comprehensively elucidate the neuropathological mechanisms of IGE in children.

Methods

We obtained arterial spin labeling (ASL) and resting state functional magnetic resonance imaging data of 28 children with IGE and 35 matched controls. We used ASL to determine differential CBF regions in children with IGE. A seed-based whole-brain FC analysis was performed for regions with significant CBF changes. The mean CBF and FC of brain areas with significant group differences was extracted, then its correlation with clinical variables in IGE group was analyzed by using Pearson correlation analysis.

Results

Compared to controls, children with IGE had CBF abnormalities that were mainly observed in the right middle temporal gyrus, right middle occipital gyrus (MOG), right superior frontal gyrus (SFG), left inferior frontal gyrus (IFG), and triangular part of the left IFG (IFGtriang). We observed that the FC between the left IFGtriang and calcarine fissure (CAL) and that between the right MOG and bilateral CAL were decreased in children with IGE. The CBF in the right SFG was correlated with the age at IGE onset. FC in the left IFGtriang and left CAL was correlated with the IGE duration.

Conclusion

This study found that CBF and FC were altered simultaneously in the left IFGtriang and right MOG of children with IGE. The combination of CBF and FC may provide additional information and insight regarding the pathophysiology of IGE from neuronal and vascular integration perspectives.

Shared Etiology in Autism Spectrum Disorder and Epilepsy with Functional Disability

Autism spectrum disorders and epilepsies are heterogeneous human disorders that have miscellaneous etiologies and pathophysiology. There is considerable risk of frequent epilepsy in autism that facilitates amplified morbidity and mortality. Several biological pathways appear to be involved in disease progression, including gene transcription regulation, cellular growth, synaptic channel function, and maintenance of synaptic structure. Here, abnormalities in excitatory/inhibitory (E/I) balance ratio are reviewed along with part of an epileptiform activity that may drive both overconnectivity and genetic disorders where autism spectrum disorders and epilepsy frequently co-occur. The most current ideas concerning common etiological and molecular mechanisms for co-occurrence of both autism spectrum disorders and epilepsy are discussed along with the powerful pharmacological therapies that protect the cognition and behavior of patients. Better understanding is necessary to identify a biological mechanism that might lead to possible treatments for these neurological disorders.

Altered Resting-State Electroencephalography Microstates in Idiopathic Generalized Epilepsy: A Prospective Case-Control Study

Objective: Idiopathic generalized epilepsy (IGE) involves aberrant organization and functioning of large-scale brain networks. This study aims to investigate whether the resting-state EEG microstate analysis could provide novel insights into the abnormal temporal and spatial properties of intrinsic brain activities in patients with IGE.

Methods: Three groups of participants were chosen for this study (namely IGE-Seizure, IGE-Seizure Free, and Healthy Controls). EEG microstate analysis on the resting-state EEG datasets was conducted for all participants. The average duration (“Duration”), the average number of microstates per second (“Frequency”), as well as the percentage of total analysis time occupied in that state (“Coverage”) of the EEG microstate were compared among the three groups.

Results: For microstate classes B and D, the differences in Duration, Frequency, and Coverage among the three groups were not statistically significant. Both Frequency and Coverage of microstate class A were statistically significantly larger in the IGE-Seizure group than in the other two groups. The Duration and Coverage of microstate class C were statistically significantly smaller in the IGE-Seizure group than those in the other two groups.

Conclusions: The Microstate class A was regarded as a sensorimotor network and Microstate class C was mainly related to the salience network, this study indicated an altered sensorimotor and salience network in patients with IGE, especially in those who had experienced seizures in the past 2 years, while the visual and attention networks seemed to be intact.

Significance: The temporal dynamics of resting-state networks were studied through EEG microstate analysis in patients with IGE, which is expected to generate indices that could be utilized in clinical researches of epilepsy.

Consciousness and complexity: a consilience of evidence

Over the last years, a surge of empirical studies converged on complexity-related measures as reliable markers of consciousness across many different conditions, such as sleep, anesthesia, hallucinatory states, coma, and related disorders. Most of these measures were independently proposed by researchers endorsing disparate frameworks and employing different methods and techniques. Since this body of evidence has not been systematically reviewed and coherently organized so far, this positive trend has remained somewhat below the radar. The aim of this paper is to make this consilience of evidence in the science of consciousness explicit. We start with a systematic assessment of the growing literature on complexity-related measures and identify their common denominator, tracing it back to core theoretical principles and predictions put forward more than 20 years ago. In doing this, we highlight a consistent trajectory spanning two decades of consciousness research and provide a provisional taxonomy of the present literature. Finally, we consider all of the above as a positive ground to approach new questions and devise future experiments that may help consolidate and further develop a promising field where empirical research on consciousness appears to have, so far, naturally converged.

Pretreatment Source Location and Functional Connectivity Network Correlated With Therapy Response in Childhood Absence Epilepsy: A Magnetoencephalography Study

Objective: This study aims to investigate the differences between antiepileptic drug (AED) responders and nonresponders among patients with childhood absence epilepsy (CAE) using magnetoencephalography (MEG) and to additionally evaluate whether the neuromagnetic signals of the brain neurons were correlated with the response to therapy.

Methods: Twenty-four drug-naïve patients were subjected to MEG under six frequency bandwidths during ictal periods. The source location and functional connectivity were analyzed using accumulated source imaging and correlation analysis, respectively. All patients were treated with appropriate AED, at least 1 year after their MEG recordings, their outcome was assessed, and they were consequently divided into responders and nonresponders.

Results: The source location of the nonresponders was mainly in the frontal cortex at a frequency range of 8–12 and 30–80 Hz, especially 8–12 Hz, while the source location of the nonresponders was mostly in the medial frontal cortex, which was chosen as the region of interest. The nonresponders showed strong positive local frontal connections and deficient anterior and posterior connections at 80–250 Hz.

Conclusion: The frontal cortex and especially the medial frontal cortex at α band might be relevant to AED-nonresponsive CAE patients. The local frontal positive epileptic network at 80–250 Hz in our study might further reveal underlying cerebral abnormalities even before treatment in CAE patients, which could cause them to be nonresponsive to AED. One single mechanism cannot explain AED resistance; the nonresponders may represent a subgroup of CAE who is refractory to several antiepileptic drugs.

Differentiating ictal/subclinical spikes and waves in childhood absence epilepsy by spectral and network analyses: A pilot study

OBJECTIVE

Childhood absence epilepsy (CAE) is a disease with distinct seizure semiology and electroencephalographic (EEG) features. Differentiating ictal and subclinical generalized spikes and waves discharges (GSWDs) in the EEG is challenging, since they appear to be identical upon visual inspection. Here, spectral and functional connectivity (FC) analyses were applied to routine EEG data of CAE patients, to differentiate ictal and subclinical GSWDs.

METHODS

Twelve CAE patients with both ictal and subclinical GSWDs were retrospectively selected for this study. The selected EEG epochs were subjected to frequency analysis in the range of 1-30 Hz. Further, FC analysis based on the imaginary part of coherency was used to determine sensor level networks.

RESULTS

Delta, alpha and beta band frequencies during ictal GSWDs showed significantly higher power compared to subclinical GSWDs. FC showed significant network differences for all frequency bands, demonstrating weaker connectivity between channels during ictal GSWDs.

CONCLUSION

Using spectral and FC analyses significant differences between ictal and subclinical GSWDs in CAE patients were detected, suggesting that these features could be used for machine learning classification purposes to improve EEG monitoring.

SIGNIFICANCE

Identifying differences between ictal and subclinical GSWDs using routine EEG, may improve understanding of this syndrome and the management of patients with CAE.

Graph-theory based degree centrality combined with machine learning algorithms can predict response to treatment with antiepileptic medications in children with epilepsy

BACKGROUND AND PURPOSE

The purpose of the current study is to detect changes of graph-theory-based degree centrality (DC) and their relationship with the clinical treatment effects of anti-epileptic drugs (AEDs) for patients with childhood absence epilepsy (CAE) using resting-state functional MRI (RS-fMRI).

METHODS

RS-fMRI data from 35 CAE patients were collected and compared with findings from 35 age and gender matched healthy controls (HCs). The patients were treated with AEDs for 46.03 weeks before undergoing a second RS-fMRI scan.

RESULTS

CAE children at baseline showed increased DC in thalamus, postcentral and precentral and reduced DC in medial frontal cortex, superior frontal cortex, middle temporal cortex, angular and precuneus. However, those abnormalities showed a clear renormalization after AEDs treatments. We then explored the viability of graph-theory-based degree centrality to accurately classify effectiveness to AEDs. Support Vector Machine analysis using leave-one-out cross-validation achieved a correct classification rate of 84.22% [sensitivity 78.76%, specificity 89.65%, and area under the receiver operating characteristic curve (AUC) 0.96] for differentiating effective subjects from ineffective subjects. Brain areas that contributed most to the classification model were mainly located within the right thalamus, bilateral middle temporal gyrus, right medial frontal gyrus, right inferior frontal gyrus, left precuneus, bilateral angular right precentral and left postcentral. Furthermore, the DC change within the bilateral angular are positively correlated with the symptom improvements after AEDs treatment.

CONCLUSION

These findings suggest that graph-theory-based measures, such as DC, combined with machine-learning algorithms, can provide crucial insights into pathophysiological mechanisms and the effectiveness of AEDs.

Altered spontaneous brain activity in patients with childhood absence epilepsy: associations with treatment effects

The study aims to detect resting-state functional MRI (RS-fMRI) changes and their relationships with the clinical treatment effects of anti-epileptic drugs (AEDs) for patients with childhood absence epilepsy (CAE) using the fractional amplitude of low-frequency fluctuation (fALFF). RS-fMRI data from 30 CAE patients were collected and compared with findings from 30 healthy controls (HCs) with matched sex and age. Patients were treated with first-line AEDs for 46.2 months before undergoing a second RS-fMRI scan. fALFF data were processed using DPABI and SPM12 software. Compared with the HCs, CAE patients at baseline showed increased fALFF in anterior cingulate cortex, inferior parietal lobule, inferior frontal lobule, supplementary motor area and reduced fALFF in putamen and thalamus. At follow-up, the fALFF showed a clear rebound which indicated a normalization of spontaneous brain activities in these regions. In addition, the fALFF changes within thalamus showed significant positive correlation with the seizure frequency improvements. Our results suggest that specific cortical and subcortical regions are involved in seizure generation and the neurological impairments found in CAE children and might shed new light about the AEDs effects on CAE patients.

Relationship between Tumor Necrosis Factor-Alpha and Neuropeptide Y Expression and Neurological Function Score in Epileptic Children

Background

To observe the relationship between Tumor Necrosis Factor-alpha (TNF-α) and Neuropeptide Y (NPY) expression and neurological function score in epileptic children.

Methods

Fifty-four epileptic children diagnosed and treated in Xuzhou Children's Hospital, China from Feb 2017 to Mar 2018 were collected and included in a research group (RG), while 30 healthy children who underwent physical examination at the same time were included in the control group (CG). ELISA was used to detect the expression of TNF-α and NPY in the serum of children in the two groups, and those before treatment were compared. The National Institute of Health stroke scale (NIHSS) and Hamilton Anxiety (HAMA) scores before and after treatment were observed, and Pearson correlation was used to analyze the relationship between the expression levels of TNF-α and NPY in the serum as well as NIHSS and HAMA scores.

Results

The expression levels of TNF-α and NPY in the serum of children in the RG were significantly higher than those in the CG (P<0.001). The expression level of TNF-α was positively correlated with the NIHSS and HAMA scores (r=0.748, P<0.001) (r=0.772, P<0.001). The expression level of NPY was positively correlated with the NIHSS and HAMA scores (r=0.768, P<0.001) (r=0.643, P<0.001).

Conclusion

TNF-α and NPY are highly expressed in epileptic children and are positively correlated with neurological function score.

Localization of Epileptic Foci Based on Simultaneous EEG-fMRI Data

Combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) enables a non-invasive investigation of the human brain function and evaluation of the correlation of these two important modalities of brain activity. This paper explores recent reports on using advanced simultaneous EEG-fMRI methods proposed to map the regions and networks involved in focal epileptic seizure generation. One of the applications of EEG and fMRI combination as a valuable clinical approach is the pre-surgical evaluation of patients with epilepsy to map and localize the precise brain regions associated with epileptiform activity. In the process of conventional analysis using EEG-fMRI data, the interictal epileptiform discharges (IEDs) are visually extracted from the EEG data to be convolved as binary events with a predefined hemodynamic response function (HRF) to provide a model of epileptiform BOLD activity and use as a regressor for general linear model (GLM) analysis of the fMRI data. This review examines the methodologies involved in performing such studies, including techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. It then discusses the results reported for patients with primary generalized epilepsy and patients with different types of focal epileptic disorders. An important matter that these results have brought to light is that the brain regions affected by interictal epileptic discharges might not be limited to the ones where they have been generated. The developed methods can help reveal the regions involved in or affected by a seizure onset zone (SOZ). As confirmed by the reviewed literature, EEG-fMRI provides information that comes particularly useful when evaluating patients with refractory epilepsy for surgery.

Predictive value of functional MRI and EEG in epilepsy diagnosis after a first seizure

It is often difficult to predict seizure recurrence in subjects who have suffered a first-ever epileptic seizure. In this study, the predictive value of physiological signals measured using Electroencephalography (EEG) and functional MRI (fMRI) is assessed. In particular those patients developing epilepsy (i.e. a second unprovoked seizure) that were initially evaluated as having a low risk of seizure recurrence are of interest. In total, 26 epilepsy patients, of which 8 were initially evaluated as having a low risk of seizure recurrence (i.e. converters), and 17 subjects with only a single seizure were included. All subjects underwent routine EEG as well as fMRI measurements. For diagnostic classification, features related to the temporal dynamics were determined for both the processed EEG and fMRI data. Subsequently, a logistic regression classifier was trained on epilepsy and first-seizure subjects. The trained model was tested using the clinically relevant converters group. The sensitivity, specificity, and AUC (mean ± SD) of the regression model including metrics from both modalities were 74 ± 19%, 82 ± 18%, and 0.75 ± 0.12, respectively. Positive and negative predictive values (mean ± SD) of the regression model with both EEG and fMRI features are 84 ± 14% and 78 ± 12%. Moreover, this EEG/fMRI model showed significant improvements compared to the clinical diagnosis, whereas the models using metrics from either EEG or fMRI do not reach significance (p > 0.05). Temporal metrics computationally derived from EEG and fMRI time signals may clinically aid and synergistically improve the predictive value in a first-seizure sample.

Seizure Freedom After Epilepsy Surgery and Higher Baseline Cognition May Be Associated With a Negatively Correlated Epilepsy Network in Temporal Lobe Epilepsy

Background: Brain regions positively correlated with the epileptogenic zone in patients with temporal lobe epilepsy vary in spread across the brain and in the degree of correlation to the temporal lobes, thalamus, and limbic structures, and these parameters have been associated with pre-operative cognitive impairment and seizure freedom after epilepsy surgery, but negatively correlated regions have not been as well studied. We hypothesize that connectivity within a negatively correlated epilepsy network may predict which patients with temporal lobe epilepsy will respond best to surgery. Methods: Scalp EEG and resting state functional MRI (rsfMRI) were collected from 19 patients with temporal lobe epilepsy and used to estimate the irritative zone. Using patients' rsfMRI, the negatively correlated epilepsy network was mapped by determining all the brain voxels that were negatively correlated with the voxels in the epileptogenic zone and the spread and average connectivity within the network was determined. Results: Pre-operatively, connectivity within the negatively correlated network was inversely related to the spread (diffuseness) of that network and positively associated with higher baseline verbal and logical memory. Pre-operative connectivity within the negatively correlated network was also significantly higher in patients who would go on to be seizure free. Conclusion: Patients with higher connectivity within brain regions negatively correlated with the epilepsy network had higher baseline memory function, narrower network spread, and were more likely to be seizure free after surgery.

Clinical and experimental insight into pathophysiology, comorbidity and therapy of absence seizures

Absence seizures in children and teenagers are generally considered relatively benign because of their non-convulsive nature and the large incidence of remittance in early adulthood. Recent studies, however, show that 30% of children with absence seizures are pharmaco-resistant and 60% are affected by severe neuropsychiatric comorbid conditions, including impairments in attention, cognition, memory and mood. In particular, attention deficits can be detected before the epilepsy diagnosis, may persist even when seizures are pharmacologically controlled and are aggravated by valproic acid monotherapy. New functional MRI-magnetoencephalography and functional MRI-EEG studies provide conclusive evidence that changes in blood oxygenation level-dependent signal amplitude and frequency in children with absence seizures can be detected in specific cortical networks at least 1 min before the start of a seizure, spike-wave discharges are not generalized at seizure onset and abnormal cortical network states remain during interictal periods. From a neurobiological perspective, recent electrical recordings and imaging of large neuronal ensembles with single-cell resolution in non-anaesthetized models show that, in contrast to the predominant opinion, cortical mechanisms, rather than an exclusively thalamic rhythmogenesis, are key in driving seizure ictogenesis and determining spike-wave frequency. Though synchronous ictal firing characterizes cortical and thalamic activity at the population level, individual cortico-thalamic and thalamocortical neurons are sparsely recruited to successive seizures and consecutive paroxysmal cycles within a seizure. New evidence strengthens previous findings on the essential role for basal ganglia networks in absence seizures, in particular the ictal increase in firing of substantia nigra GABAergic neurons. Thus, a key feature of thalamic ictogenesis is the powerful increase in the inhibition of thalamocortical neurons that originates at least from two sources, substantia nigra and thalamic reticular nucleus. This undoubtedly provides a major contribution to the ictal decrease in total firing and the ictal increase of T-type calcium channel-mediated burst firing of thalamocortical neurons, though the latter is not essential for seizure expression. Moreover, in some children and animal models with absence seizures, the ictal increase in thalamic inhibition is enhanced by the loss-of-function of the astrocytic GABA transporter GAT-1 that does not necessarily derive from a mutation in its gene. Together, these novel clinical and experimental findings bring about paradigm-shifting views of our understanding of absence seizures and demand careful choice of initial monotherapy and continuous neuropsychiatric evaluation of affected children. These issues are discussed here to focus future clinical and experimental research and help to identify novel therapeutic targets for treating both absence seizures and their comorbidities.

Interictal structural and functional connectivity in idiopathic generalized epilepsy: A systematic review of graph theoretical studies

The evaluation of the role of anomalous neuronal networks in epilepsy using a graph theoretical approach is of growing research interest. There is currently no consensus on optimal methods for performing network analysis, and it is possible that variations in study methodology account for diverging findings. This review focuses on global functional and structural interictal network characteristics in people with idiopathic generalized epilepsy (IGE) with the aim of appraising the methodological approaches used and assessing for meaningful consensus. Thirteen studies were included in the review. Data were heterogenous and not suitable for meta-analysis. Overall, there is a suggestion that the cerebral neuronal networks of people with IGE have different global structural and functional characteristics to people without epilepsy. However, the nature of the aberrations is inconsistent with some studies demonstrating a more regular network configuration in IGE, and some, a more random topology. There is greater consistency when different data modalities and connectivity subtypes are compared separately, with a tendency towards increased small-worldness of networks in functional electroencephalography/magnetoencephalography (EEG/MEG) studies and decreased small-worldness of networks in structural studies. Prominent variation in study design at all stages is likely to have contributed to differences in study outcomes. Despite increasing literature surrounding neuronal network analysis, systematic methodological studies are lacking. Absence of consensus in this area significantly limits comparison of results from different studies, and the ability to draw firm conclusions about network characteristics in IGE.

Functional brain network characteristics are associated with epilepsy severity in childhood absence epilepsy

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The functional network of children with childhood absence epilepsy is less efficiently organized in terms of clustering and small-worldness.

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Longer path lengths (i.e. less efficient organization) of the functional network relate to a longer duration of childhood absence epilepsy.

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Longer path lengths of the functional network relate to a higher seizure frequency in childhood absence epilepsy.

While cognitive impairments are not generally considered to be part of the childhood absence epilepsy (CAE) syndrome, some recent studies report cognitive, mainly attentional, deficits. Here we set out to investigate the whole brain functional network of children with CAE and controls. Furthermore, the possible relation of the functional network abnormalities with epilepsy and neurocognitive characteristics is studied.

Seventeen children with childhood CAE (aged 9.2 ± 2.1 years) and 15 controls (aged 9.8 ± 1.8 years) were included. Resting state functional MRI was acquired to study the functional network. Using graph theoretical analysis, three global metrics of the functional network were investigated: the characteristic path length, the clustering coefficient, and the small-worldness. A multivariable linear regression model including age, sex, and subject motion as covariates was used to investigate group differences in the graph metrics. Subsequently, relations of the graph metrics with epilepsy and neurocognitive characteristics were assessed.

Longer path lengths, weaker clustering and a lower small-world network topology were observed in children with CAE compared to controls. Moreover, longer path lengths were related to a longer duration of CAE and a higher number of absence seizure per hour. Clustering and small-worldness were not significantly related to epilepsy or neurocognitive characteristics.

The organization of the functional network of children with CAE is less efficient compared to controls, and is related to disease duration. These preliminary findings suggest that CAE is associated with alterations in the functional network.

Energy landscape of resting magnetoencephalography reveals fronto-parietal network impairments in epilepsy

Juvenile myoclonic epilepsy (JME) is a form of idiopathic generalized epilepsy. It is yet unclear to what extent JME leads to abnormal network activation patterns. Here, we characterized statistical regularities in magnetoencephalograph (MEG) resting-state networks and their differences between JME patients and controls by combining a pairwise maximum entropy model (pMEM) and novel energy landscape analyses for MEG. First, we fitted the pMEM to the MEG oscillatory power in the front-oparietal network (FPN) and other resting-state networks, which provided a good estimation of the occurrence probability of network states. Then, we used energy values derived from the pMEM to depict an energy landscape, with a higher energy state corresponding to a lower occurrence probability. JME patients showed fewer local energy minima than controls and had elevated energy values for the FPN within the theta, beta, and gamma bands. Furthermore, simulations of the fitted pMEM showed that the proportion of time the FPN was occupied within the basins of energy minima was shortened in JME patients. These network alterations were highlighted by significant classification of individual participants employing energy values as multivariate features. Our findings suggested that JME patients had altered multistability in selective functional networks and frequency bands in the fronto-parietal cortices.

Altered Interactions Among Resting-State Networks in Individuals with Obesity

OBJECTIVE

The aim of this study was to investigate alterations in functional connectivity (FC) within and interactions between resting-state networks involved in salience, executive control, and interoception in participants with obesity (OB).

METHODS

Using resting-state functional magnetic resonance imaging with independent component analysis and FC, alterations within and interactions between resting-state networks in 35 OB and 35 normal-weight controls (NW) were investigated.

RESULTS

Compared with NW, OB showed reduced FC strength in the ventromedial prefrontal cortex and posterior cingulate cortex/precuneus within the default-mode network, dorsal anterior cingulate cortex within the salience network (SN), bilateral dorsolateral prefrontal cortex-angular gyrus within the frontoparietal network (FPN), and increased FC strength in the insula (INS) (Pfamilywise error  < 0.0125). The dorsal anterior cingulate cortex FC strength was negatively correlated with craving for food cues, left dorsolateral prefrontal cortex FC strength was negatively correlated with Yale Food Addiction Scale scores, and right INS FC strength was positively correlated with craving for high-calorie food cues. Compared with NW, OB also showed increased FC between the SN and FPN driven by altered FC of bilateral INS and anterior cingulate cortex-angular gyrus.

CONCLUSIONS

Alterations in FC within and interactions between the SN, default-mode network, and FPN might contribute to the high incentive value of food (craving), lack of control of overeating (compulsive overeating), and increased awareness of hunger (impaired interoception) in OB.

Towards a Better Understanding of Cognitive Deficits in Absence Epilepsy: a Systematic Review and Meta-Analysis

Cognition in absence epilepsy (AE) is generally considered undisturbed. However, reports on cognitive deficits in AE in recent years have suggested otherwise. This review systematically assesses current literature on cognitive performance in children with AE. A systematic literature search was performed in Pubmed, Embase, Cochrane and Web of Science. All studies reporting on cognitive performance in children with AE were considered. In total 33 studies were eligible for inclusion. Neuropsychological tests were classified into the following domains: intelligence; executive function; attention; language; motor & sensory-perceptual examinations; visuoperceptual/visuospatial/visuoconstructional function; memory and learning; achievement. Random-effect meta-analyses were conducted by estimating the pooled mean and/or pooling the mean difference in case-control studies. Full-scale IQ in children with AE was estimated at 96.78 (95%CI:94.46-99.10) across all available studies and in case-control studies IQ was on average 8.03 (95%CI:-10.45- -5.61) lower. Verbal IQ was estimated at 97.98 (95%CI:95.80-100.16) for all studies and 9.01 (95%CI:12.11- -5.90) points lower in case-control studies. Performance IQ was estimated at 97.23 (93.24-101.22) for all available studies and 5.32 (95%CI:-8.27-2.36) points lower in case-control studies. Lower performance was most often reported in executive function (cognitive flexibility, planning, and verbal fluency) and attention (sustained, selective and divided attention). Reports on school difficulties, neurodevelopmental problems, and attentional problems were high. In conclusion, in contrast to common beliefs, lower than average neurocognitive performance was noted in multiple cognitive domains, which may influence academic and psychosocial development.

Single-subject manual independent component analysis and resting state fMRI connectivity outcomes in patients with juvenile absence epilepsy

The quality of fMRI data impacts functional connectivity measures and consequently, the decisions that clinicians and researchers make regarding functional connectivity interpretation. The present study used resting state fMRI to investigate resting state network connectivity in a sample of patients with Juvenile Absence Epilepsy. Single-subject manual independent component analysis was used in two levels, whereby all noise components were removed, and cerebrospinal fluid pulsation components only were isolated and removed. Improved temporal signal to noise ratios and functional connectivity metrics were observed in each of the cleaning levels for both epilepsy and control cohorts. Results showed full, single-subject manual independent component analysis reduced the number of functional connectivity correlations and increased the strength of these correlations. Similar effects were also observed for the cerebrospinal fluid pulsation only cleaned data relative to the uncleaned, and fully cleaned data. Single-subject manual independent component analysis coupled with short TR multiband acquisition can significantly improve the validity of findings derived from fMRI data sets.

Reconfiguration of dynamic large-scale brain network functional connectivity in generalized tonic-clonic seizures

An increasing number of studies in patients with generalized tonic–clonic seizures (GTCS) have reported the alteration of functional connectivity (FC) in many brain networks. However, little is known about the underlying temporal variability of FC in large‐scale brain functional networks in patients. Recently, dynamic FC could provide novel insight into the physiological mechanisms in the brain. Here, we recruited 63 GTCS and 65 age‐ and sex‐matched healthy controls. Dynamic FC approaches were used to evaluate alterations in the temporal variability of FC in patients at the region‐ and network‐levels. In addition, two kinds of brain templates (>10² and > 10³ regions) and two kinds of temporal variability FC approaches were adopted to verify the stability of the results. Patients showed increased FC variability in regions of the default mode network (DMN), ventral attention network (VAN) and motor‐related areas. The DAN, VAN, and DMN illustrated enhanced FC variability at the within‐network level. In addition, increased FC variabilities between networks were found between the DMN and cognition‐related networks, including the VAN, dorsal attention network and frontal–parietal network in GTCS. Meanwhile, the alterations in FC variability were relatively consistent across different methods and templates. Therefore, the consistent alteration of FC variability would reflect a dynamic restructuring of the large‐scale brain networks in patients with GTCS. Overly frequent information communication among cognition‐related networks, especially in the DMN, might play a role in the epileptic activity and/or cognitive dysfunction in patients.

Common psychiatric comorbidities in epilepsy: How big of a problem is it?

Psychiatric illness and epilepsy commonly co-occur in adults and in children and adolescents. Theories of comorbidity are complex, but recurring associations between the conditions suggest overlap that is more than simple co-occurrence. Common underlying pathophysiology may imply that epilepsy itself may constituently include psychiatric symptoms. Conditions such as depression or cognitive difficulties commonly occur and in some cases, are considered to be associated with specific epilepsy characteristics such as localization or seizure type. Regardless of etiologic attributions to psychiatric comorbidity, it is clear today that treatment for epilepsy needs to target psychiatric illness. In many cases, quality-of-life improvements depend more upon addressing psychiatric symptoms than seizures themselves. This article is part of the Special Issue "Obstacles of Treatment of Psychiatric Comorbidities in Epilepsy".

The epileptic network and cognition: What functional connectivity is teaching us about the childhood epilepsies

Our objective was to summarize and evaluate the rapidly expanding body of literature studying functional connectivity in childhood epilepsy. In the self-limited childhood epilepsies, awareness of cognitive comorbidities has been steadily increasing, and recent advances in our understanding of the network effects of these disorders promise insights into the underlying neurobiology. We reviewed publications addressing functional connectivity in children with epilepsy with an emphasis on studies of children with self-limited childhood epilepsies. The majority of studies have been published in the past 10 years and predominantly examine childhood epilepsy with centrotemporal spikes and childhood absence epilepsy. Cognitive network alterations are commonly observed across the childhood epilepsies. Some of these effects appear to be nonspecific to epilepsy syndrome or even to category of neurological disorder. Other patterns, such as changes in the connectivity of cortical language areas in childhood epilepsy with centrotemporal spikes, provide clues to the underlying cognitive deficits seen in affected children. The literature to date is dominated by general observations of connectivity patterns without a priori hypotheses. These data-driven studies build an important foundation for hypothesis generation and are already providing useful insights into the neuropathology of the childhood epilepsies. Future work should emphasize hypothesis-driven approaches and rigorous clinical correlations to better understand how the knowledge of network alterations can be applied to guidance and treatment for the children in our clinics.

Altered structural and causal connectivity in frontal lobe epilepsy

Background

Albeit the few resting-state fMRI neuroimaging studies in frontal lobe epilepsy (FLE) patients, these studies focused on functional connectivity. The aim of this current study was to examine the effective connectivity based on voxel-based morphometry in FLE patients.

Methods

Resting-state structural and functional magnetic resonance imaging (fMRI) data were acquired from 19 FLE patients and 19 age and gender-matched healthy controls using the 3.0 Tesla magnetic resonance imaging (3.0 T MRI). The investigations were done by acquiring the structural information through voxel-based morphometry, then based on the seed obtained, Granger causality analysis was used to evaluate the causal flow of the designated seed to and from other significant voxels.

Results

Our results showed altered structural and effective connectivity. Compared with healthy controls, FLE patients showed reduced grey matter volume in bilateral putamen and right caudate as well as altered causality with increased, and decreased causal outflow from the right caudate (seed region) to inferior frontal gyrus-triangular, from bilateral putamen (seed regions) to right middle frontal gyrus and frontal gyrus medial-orbital representing the frontal executive areas, respectively. Also, significantly increased and decreased inflow from left calcarine to right caudate and from cerebellum_6 and vermis_6 to bilateral putamen, respectively. Moreover, we found that the causal alterations to and from the seed regions (from vermis_6 to right putamen and from left putamen to right middle frontal gyrus) negatively correlated with clinical scores (duration of epilepsy).

Conclusions

The findings point to the impairment within the executive and motor-controlled system including the cerebellum, frontal, caudate and putamen regions in FLE patients. These results would therefore enhance our understanding of structural and effective mechanisms in FLE.

Disrupted Coupling Between the Spontaneous Fluctuation and Functional Connectivity in Idiopathic Generalized Epilepsy

Purpose: The purpose of this study was to comprehensively evaluate alterations of resting-state spontaneous brain activity in patients with idiopathic generalized epilepsy (IGE) and its subgroups [juvenile myoclonic epilepsy (JME) and generalized tonic-clonic seizures (GTCS)]. Methods: Resting state functional magnetic resonance imaging (fMRI) data were acquired from 60 patients with IGE and 60 healthy controls (HCs). Amplitude of low frequency fluctuation (ALFF), global functional connectivity density (gFCD), local FCD (lFCD), and long range FCD (lrFCD) were used to evaluate spontaneous brain activity in the whole brain. Moreover, the coupling between ALFF and FCDs (gFCD, lFCD, and lrFCD) was analyzed on both voxel-wise and subject-wise levels. Two-sample t-tests were used to analyze the difference in ALFF, FCDs and coupling on a subject-wise level between the two groups. Nonparametric permutation tests were used to evaluate differences in coupling on a voxel-wise level. Key findings: Patients with IGE and its subgroups showed reduced ALFF, gFCD and lrFCD in posterior regions of the default mode network (DMN). In addition, decreased ALFF and increased coupling with FCD were found in the cerebellum, while decreased coupling was observed in the bilateral pre- and postcentral gyrus in IGE compared with the coupling in HCs. Similar findings were found in the analysis between each of the two subgroups of IGE (JME and GTCS) and HCs, and JME patients had increased coupling in the cerebellum and bilateral middle occipital gyrus compared with coupling in the GTCS patients. Significance: This study demonstrated a multifactor abnormality of the DMN in IGE and emphasized that the abnormality in the cerebellum was associated with dysfunctional motor symptoms during seizures and might participate in the regulation of GSWDs in IGE.

Unravelling the brain networks driving spike-wave discharges in genetic generalized epilepsy-common patterns and individual differences

Objective

Genetic generalized epilepsies (GGEs) are characterized by generalized spike-wave discharges (GSWDs) in electroencephalography (EEG) recordings without underlying structural brain lesions. The origin of the epileptic activity remains unclear, although several studies have reported involvement of thalamus and default mode network (DMN). The aim of the current study was to investigate the networks involved in the generation and temporal evolution of GSWDs to elucidate the origin and propagation of the underlying generalized epileptic activity.

Methods

We examined 12 patients with GGE and GSWDs using EEG-functional magnetic resonance imaging (fMRI) and identified involved brain areas on the basis of a classical general linear model (GLM) analysis. The activation time courses of these areas were further investigated to reveal their temporal sequence of activations and deactivations. Dynamic causal modeling (DCM) was used to determine the generator of GSWDs in GGE.

Results

We observed activity changes in the thalamus, DMN, dorsal attention network (DAN), salience network (SN), basal ganglia, dorsolateral prefrontal cortex, and motor cortex with supplementary motor area, however, with a certain heterogeneity between patients. Investigation of the temporal sequence of activity changes showed deactivations in the DMN and DAN and activations in the SN and thalamus preceding the onset of GSWDs on EEG by several seconds. DCM analysis indicated that the DMN gates GSWDs in GGE.

Significance

The observed interplay between DMN, DAN, SN, and thalamus may indicate a downregulation of consciousness. The DMN seems to play a leading role as a driving force behind these changes. Overall, however, there were also clear differences in activation patterns between patients, reflecting a certain heterogeneity in this cohort of GGE patients.

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.

Aberrant Thalamocortical Connectivity in Juvenile Myoclonic Epilepsy

The purpose of this study was to investigate the functional connectivity (FC) of thalamic subdivisions in patients with juvenile myoclonic epilepsy (JME). Resting state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) data were acquired from 22 JME and 25 healthy controls. We first divided the thalamus into eight subdivisions by performing independent component analysis on tracking fibers and clustering thalamus-related FC maps. We then analyzed abnormal FC in each subdivision in JME compared with healthy controls, and we investigated their associations with clinical features. Eight thalamic sub-regions identified in the current study showed unbalanced thalamic FC in JME: decreased FC with the superior frontal gyrus and enhanced FC with the supplementary motor area in the posterior thalamus increased thalamic FC with the salience network (SN) and reduced FC with the default mode network (DMN). Abnormalities in thalamo-prefrontocortical networks might be related to the propagation of generalized spikes with frontocentral predominance in JME, and the network connectivity differences with the SN and DMN might be implicated in emotional and cognitive defects in JME. JME was also associated with enhanced FC among thalamic sub-regions and with the basal ganglia and cerebellum, suggesting the regulatory role of subcortical nuclei and the cerebellum on the thalamo-cortical circuit. Additionally, increased FC with the pallidum was positive related with the duration of disease. The present study provides emerging evidence of FC to understand that specific thalamic subdivisions contribute to the abnormalities of thalamic-cortical networks in JME. Moreover, the posterior thalamus could play a crucial role in generalized epileptic activity in JME.

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.

Altered Spontaneous Brain Activity in Children with Early Tourette Syndrome: a Resting-state fMRI Study

Tourette syndrome (TS) is a childhood-onset chronic disorder characterized by the presence of multiple motor and vocal tics. This study investigated the alterations of spontaneous brain activities in children with TS by resting-state functional magnetic resonance imaging (rs-fMRI). We obtained rs-fMRI scans from 21 drug-naïve and pure TS children and 29 demographically matched healthy children. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF) and regional homogeneity (ReHo) of rs-fMRI data were calculated to measure spontaneous brain activity. We found significant alterations of ALFF or fALFF in vision-related structures including the calcarine sulcus, the cuneus, the fusiform gyrus, and the left insula in TS children. Decreased ReHo was found in the right cerebellum. Further analysis showed that the ReHo value of the right cerebellum was positively correlated with TS duration. Our study provides empirical evidence for abnormal spontaneous neuronal activity in TS patients, which may implicate the neurophysiological mechanism in TS children. Moreover, the right cerebellum can be potentially used as a biomarker for the pathophysiology of early TS in children.

Altered Effective Connectivity Network in Childhood Absence Epilepsy: A Multi-frequency MEG Study

Using multi-frequency magnetoencephalography (MEG) data, we investigated whether the effective connectivity (EC) network of patients with childhood absence epilepsy (CAE) is altered during the inter-ictal period in comparison with healthy controls. MEG data from 13 untreated CAE patients and 10 healthy controls were recorded. Correlation analysis and Granger causality analysis were used to construct an EC network at the source level in eight frequency bands. Alterations in the spatial pattern and topology of the network in CAE were investigated by comparing the patients with the controls. The network pattern was altered mainly in 1-4 Hz, showing strong connections within the frontal cortex and weak connections in the anterior-posterior pathways. The EC involving the precuneus/posterior cingulate cortex (PC/PCC) significantly decreased in low-frequency bands. In addition, the parameters of graph theory were significantly altered in several low- and high-frequency bands. CAE patients display frequency-specific abnormalities in the network pattern even during the inter-ictal period, and the frontal cortex and PC/PCC might play crucial roles in the pathophysiology of CAE. The EC network of CAE patients was over-connective and random during the inter-ictal period. This study is the first to reveal the frequency-specific alteration in the EC network during the inter-ictal period in CAE patients. Multiple-frequency MEG data are useful in investigating the pathophysiology of CAE, which can serve as new biomarkers of this disorder.

The Functional Integration in the Sensory-Motor System Predicts Aging in Healthy Older Adults

Healthy aging is typically accompanied by a decrease in the motor capacity. Although the disrupted neural representations and performance of movement have been observed in older age in previous studies, the relationship between the functional integration of sensory-motor (SM) system and aging could be further investigated. In this study, we examine the impact of healthy aging on the resting-state functional connectivity (rsFC) of the SM system, and investigate as to how aging is affecting the rsFC in SM network. The SM network was identified and evaluated in 52 healthy older adults and 51 younger adults using two common data analytic approaches: independent component analysis and seed-based functional connectivity (seed at bilateral M1 and S1). We then evaluated whether the altered rsFC of the SM network could delineate trajectories of the age of older adults using a machine learning methodology. Compared with the younger adults, the older demonstrated reduced functional integration with increasing age in the mid-posterior insula of SM network and increased rsFC among the sensorimotor cortex. Moreover, the reduction in the rsFC of mid-posterior insula is associated with the age of older adults. Critically, the analysis based on two-aspect connectivity-based prediction frameworks revealed that the age of older adults could be reliably predicted by this reduced rsFC. These findings further indicated that healthy aging has a marked influence on the SM system that would be associated with a reorganization of SM system with aging. Our findings provide further insight into changes in sensorimotor function in the aging brain.

Altered degree centrality in childhood absence epilepsy: A resting-state fMRI study

Modern network studies have suggested that the pathology of many neurological diseases is in fact not equally distributed over the brain but preferentially affects the hub regions. This study aims to investigate how hub regions were affected in Children with Childhood absence epilepsy (CAE) using resting-state fMRI (rs-fMRI). As one important measures obtained from rs-fMRI, degree centrality (DC) calculates the number of direct connections between a given node and the rest of the brain within the entire connectivity matrix of the brain. In this study, twenty-five CAE children and 25 healthy controls were recruited to investigate the DC changes in CAE patients. Compared with healthy controls, children with CAE showed significantly decreased DC in default mode network (DMN, medial prefrontal cortex, posterior cingulate cortex, precuneus and middle temporal cortex) and increased DC in thalamus. Importantly, significant negative correlation between the epilepsy duration and DC was found in precuneus. Our results suggested selective and specific disruption of hub nodes, especially thalamus and the highly connected brain regions within DMN, might underlie the pathophysiological mechanism of CAE.

Altered basal ganglia-cortical functional connections in frontal lobe epilepsy: A resting-state fMRI study

OBJECTIVES

The purpose of this study was to investigate alterations of basal ganglia-cortical functional connections in patients with frontal lobe epilepsy (FLE).

METHOD

Resting-state functional magnetic resonance imaging (fMRI) data were gathered from 19 FLE patients and 19 age- and gender-matched healthy controls. Functional connectivity (FC) analysis was used to assess the functional connections between basal ganglia and cerebral cortex. Regions of interest, including the left/right caudate, putamen, pallidum and thalamus, were selected as the seeds. Two sample t-test was used to determine the difference between patients and controls, while controlling the age, gender and head motions.

RESULTS

Compared with controls, FLE patients demonstrated increased FCs between basal ganglia and regions including the right fusiform gyrus, the bilateral cingulate gyrus, the precuneus and anterior cingulate gyrus. Reduced FCs were mainly located in a range of brain regions including the bilateral middle occipital gyrus, the ventral frontal lobe, the right putamen, the left fusiform gyrus and right rolandic operculum. In addition, the relationships between basal ganglia-cingulate connections and durations of epilepsy were also found.

CONCLUSION

The alterations of functional integrity within the basal ganglia, as well as its connections to limbic and ventral frontal areas, indicate the important roles of the basal ganglia-cortical functional connections in FLE, and provide new insights in the pathophysiological mechanism of FLE.

Dynamic functional network connectivity in idiopathic generalized epilepsy with generalized tonic-clonic seizure

Idiopathic generalized epilepsy (IGE) has been linked with disrupted intra-network connectivity of multiple resting-state networks (RSNs); however, whether impairment is present in inter-network interactions between RSNs, remains largely unclear. Here, 50 patients with IGE characterized by generalized tonic-clonic seizures (GTCS) and 50 demographically matched healthy controls underwent resting-state fMRI scans. A dynamic method was implemented to investigate functional network connectivity (FNC) in patients with IGE-GTCS. Specifically, independent component analysis was first carried out to extract RSNs, and then sliding window correlation approach was employed to obtain dynamic FNC patterns. Finally, k-mean clustering was performed to characterize six discrete functional connectivity states, and state analysis was conducted to explore the potential alterations in FNC and other dynamic metrics. Our results revealed that state-specific FNC disruptions were observed in IGE-GTCS and the majority of aberrant functional connectivity manifested itself in default mode network. In addition, temporal metrics derived from state transition vectors were altered in patients including the total number of transitions across states and the mean dwell time, the fraction of time spent and the number of subjects in specific FNC state. Furthermore, the alterations were significantly correlated with disease duration and seizure frequency. It was also found that dynamic FNC could distinguish patients with IGE-GTCS from controls with an accuracy of 77.91% (P < 0.001). Taken together, this study not only provided novel insights into the pathophysiological mechanisms of IGE-GTCS but also suggested that the dynamic FNC analysis was a promising avenue to deepen our understanding of this disease. Hum Brain Mapp 38:957-973, 2017. © 2016 Wiley Periodicals, Inc.

Structural Abnormalities in Childhood Absence Epilepsy: Voxel-Based Analysis Using Diffusion Tensor Imaging

Purpose: Childhood absence epilepsy (CAE) is a common syndrome of idiopathic generalized epilepsy. However, little is known about the brain structural changes in this type of epilepsy, especially in the default mode network (DMN) regions. This study aims at using the diffusion tensor imaging (DTI) technique to quantify structural abnormalities of DMN nodes in CAE patients.

Method: DTI data were acquired in 14 CAE patients (aged 8.64 ± 2.59 years, seven females and seven males) and 16 age- and sex-matched healthy controls. The data were analyzed using voxel-based analysis (VBA) and statistically compared between patients and controls. Pearson correlation was explored between altered DTI metrics and clinical parameters. The difference of brain volumes between patients and controls were also tested using unpaired t-test.

Results: Patients showed significant increase of mean diffusivity (MD) and radial diffusivity (RD) in left medial prefrontal cortex (MPFC), and decrease of fractional anisotropy (FA) in left precuneus and axial diffusivity (AD) in both left MPFC and precuneus. In correlation analysis, MD value from left MPFC was positively associated with duration of epilepsy. Neither the disease duration nor the seizure frequency showed significant correlation with FA values. Between-group comparison of brain volumes got no significant difference.

Conclusion: The findings indicate that structural impairments exist in DMN regions in children suffering from absence epilepsy and MD values positively correlate with epilepsy duration. This may contribute to understanding the pathological mechanisms of chronic neurological deficits and promote the development of new therapies for this disorder.

Alien Hand, Restless Brain: Salience Network and Interhemispheric Connectivity Disruption Parallel Emergence and Extinction of Diagonistic Dyspraxia

Diagonistic dyspraxia (DD) is by far the most spectacular manifestation reported by sufferers of acute corpus callosum (CC) injury (so-called “split-brain”). In this form of alien hand syndrome, one hand acts at cross purposes with the other “against the patient’s will”. Although recent models view DD as a disorder of motor control, there is still little information regarding its neural underpinnings, due to widespread connectivity changes produced by CC insult, and the obstacle that non-volitional movements represent for task-based functional neuroimaging studies. Here, we studied patient AM, the first report of DD in patient with complete developmental CC agenesis. This unique case also offers the opportunity to study the resting-state connectomics of DD in the absence of diffuse changes subsequent to CC injury or surgery. AM developed DD following status epilepticus (SE) which resolved over a 2-year period. Whole brain functional connectivity (FC) was compared (Crawford-Howell [CH]) to 16 controls during the period of acute DD symptoms (Time 1) and after remission (Time 2). Whole brain graph theoretical models were also constructed and topological efficiency examined. At Time 1, disrupted FC was observed in inter-hemispheric and intra-hemispheric right edges, involving frontal superior and midline structures. Graph analysis indicated disruption of the efficiency of salience and right frontoparietal (FP) networks. At Time 2, after remission of diagnostic dyspraxia symptoms, FC and salience network changes had resolved. In sum, longitudinal analysis of connectivity in AM indicates that DD behaviors could result from disruption of systems that support the experience and control of volitional movements and the ability to generate appropriate behavioral responses to salient stimuli. This also raises the possibility that changes to large-scale functional architecture revealed by resting-state functional magnetic resonance imaging (fMRI) (rs-fMRI) may provide relevant information on the evolution of behavioral syndromes in addition to that provided by structural and task-based functional imaging.

Complex discharge-affecting networks in juvenile myoclonic epilepsy: A simultaneous EEG-fMRI study

Juvenile myoclonic epilepsy (JME) is a common subtype of idiopathic generalized epilepsies (IGEs) and is characterized by myoclonic jerks, tonic-clonic seizures and infrequent absence seizures. The network notion has been proposed to better characterize epilepsy. However, many issues remain not fully understood in JME, such as the associations between discharge-affecting networks and the relationships among resting-state networks. In this project, eigenspace maximal information canonical correlation analysis (emiCCA) and functional network connectivity (FNC) analysis were applied to simultaneous EEG-fMRI data from JME patients. The main findings of our study are as follows: discharge-affecting networks comprising the default model (DMN), self-reference (SRN), basal ganglia (BGN) and frontal networks have linear and nonlinear relationships with epileptic discharge information in JME patients; the DMN, SRN and BGN have dense/specific associations with discharge-affecting networks as well as resting-state networks; and compared with controls, significantly increased FNCs between the salience network (SN) and resting-state networks are found in JME patients. These findings suggest that the BGN, DMN and SRN may play intermediary roles in the modulation and propagation of epileptic discharges. These roles further tend to disturb the switching function of the SN in JME patients. We also postulate that emiCCA and FNC analysis may provide a potential analysis platform to provide insights into our understanding of the pathophysiological mechanism of epilepsy subtypes such as JME. Hum Brain Mapp 37:3515-3529, 2016. © 2016 Wiley Periodicals, Inc.

The Lateralization of Intrinsic Networks in the Aging Brain Implicates the Effects of Cognitive Training

Lateralization of function is an important organization of the human brain. The distribution of intrinsic networks in the resting brain is strongly related to cognitive function, gender and age. In this study, a longitudinal design with 1 year’s duration was used to evaluate the cognitive training effects on the lateralization of intrinsic networks among healthy older adults. The subjects were divided into two groups randomly: one with multi-domain cognitive training over 3 months and the other as a wait-list control group. Resting state fMRI data were acquired before training and 1 year after training. We analyzed the functional lateralization in 10 common resting state fMRI networks. We observed statically significant training effects on the lateralization of two important RSNs related to high-level cognition: right- and left- frontoparietal networks (FPNs). The lateralization of the left-FPN was retained especially well in the training group but decreased in the control group. The increased lateralization with aging was observed in the cerebellum network (CereN), in which the lateralization was significantly increased in the control group, although the same change tendency was observed in the training group. These findings indicate that the lateralization of the high-level cognitive intrinsic networks is sensitive to multi-domain cognitive training. This study provides neuroimaging evidence to support the hypothesis that cognitive training should have an advantage in preventing cognitive decline in healthy older adults.

Resting State fMRI Demonstrates a Disturbance of the Cerebello-Cortical Circuit in Essential Tremor

Individuals with essential tremor (ET) have postural and active movement abnormalities. Disturbances in the cerebello-thalamo-cortical circuit may contribute to the several motor symptoms of ET. Resting state fMRI provides a valuable, noninvasive tool to study intrinsic activation in the human brain, particularly in the brains of individuals with neuropsychiatric diseases. To investigate the low frequency oscillation features of intrinsic activation in ET in this study, we performed a resting state fMRI analysis in 24 patients with ET and 23 healthy controls. The amplitudes of low frequency fluctuation (ALFF) were analyzed. When compared with healthy controls, patients showed significantly enhanced ALFF in the bilateral cerebral cortex, which is related to motor function, including the pre- and post-central gyrus, supplementary motor area and paracentral lobule. The larger ALFF value in the right precentral gyrus is related to a longer duration of tremor. The decreased ALFF in the bilateral cerebellum was also observed in patients. In addition, aberrant ALFF in the right cerebellar tonsil was negatively associated with the duration of tremor. Our findings suggest that abnormalities exist in the intrinsic activation of brain regions in patients with ET. These findings provide noninvasive evidence that supports the hypothesis that the abnormality of intrinsic activity in the cerebello-cerebral cortex pathway could be associated with the motor-related symptoms of ET. Furthermore, the duration of a tremor might relate to the severity of the alterations to the motor system of ET.

Altered Local Spontaneous Brain Activity in Juvenile Myoclonic Epilepsy: A Preliminary Resting-State fMRI Study

Purpose. The purpose of this study was to evaluate the regional synchronization of brain in patients with juvenile myoclonic epilepsy (JME). Methods. Resting-state fMRI data were acquired from twenty-one patients with JME and twenty-two healthy subjects. Regional homogeneity (ReHo) was used to analyze the spontaneous activity in whole brain. Two-sample t-test was performed to detect the ReHo difference between two groups. Correlations between the ReHo values and features of seizures were calculated further. Key Findings. Compared with healthy controls, patients showed significantly increased ReHo in bilateral thalami and motor-related cortex regions and a substantial reduction of ReHo in cerebellum and occipitoparietal lobe. In addition, greater ReHo value in the left paracentral lobule was linked to the older age of onset in patients. Significance. These findings implicated the abnormality of thalamomotor cortical network in JME which were associated with the genesis and propagation of epileptiform activity. Moreover, our study supported that the local brain spontaneous activity is a potential tool to investigate the epileptic activity and provided important insights into understanding the pathophysiological mechanisms of JME.

Altered Basal Ganglia Network Integration in Schizophrenia

The basal ganglia involve in a range of functions that are disturbed in schizophrenia patients. This study decomposed the resting-state data of 28 schizophrenia patients and 31 healthy controls with spatial independent component analysis and identified increased functional integration in the bilateral caudate nucleus in schizophrenia patients. Further, the caudate nucleus in patients showed altered functional connection with the prefrontal area and cerebellum. These results identified the importance of basal ganglia in schizophrenia patients. Clinical Trial Registration: Chinese Clinical Trial Registry. Registration number ChiCTR-RCS-14004878.