Intrinsic brain activity as a diagnostic biomarker in children with benign epilepsy with centrotemporal spikes

Brain structural changes and molecular analyses in children with benign epilepsy with centrotemporal spikes

BACKGROUND

Benign epilepsy with centrotemporal spikes (BECTS) is a common childhood epilepsy syndrome, accompanied by behavioral problems and cognitive impairments. Previous studies of BECTS-related brain structures applied univariate analysis and showed inconsistent results. And neurotransmitter patterns associated with brain structural alterations were still unclear.

METHODS

Structural images of twenty-one drug-naïve children with BECTS and thirty-five healthy controls (HCs) were scanned. Segmented gray matter volume (GMV) images were decomposed into independent components (ICs) using the source-based morphometry method. Then spatial correlation analyses were applied to examine possible relationships between GMV changes and neurotransmitter systems.

RESULTS

Compared with HCs, drug-naïve children with BECTS showed increased volume in one GMV component (IC7), including bilateral precentral gyrus, bilateral supplementary motor area, left superior frontal cortex, bilateral middle/ inferior frontal cortex and bilateral anterior/ middle cingulate cortex. A positive correlation was observed between one GMV component (IC6) and seizure frequency. There were significantly positive correlations between abnormal GMV in IC7 and serotonergic, GABAergic and glutamatergic systems.

CONCLUSION

These findings provided further evidence of changed GMV in drug-naïve children with BECTS related to their behavioral problems and cognitive impairments, and associated neurotransmitters which could help to better understand neurobiological mechanisms and underlying molecular mechanisms of BECTS.

IMPACT

The article provides further evidence of changed gray matter volume in drug-naïve children with BECTS related to their behavioral problems and cognitive impairments as well as associated neurotransmitters. Most literature to date has applied univariate analysis and showed inconsistent results, and neurotransmitter patterns associated with brain structural alterations were still unclear. Therefore, this article uses multivariate method and JuSpace toolbox to fill the gap. Significantly increased gray matter volume was found in drug-naïve children with BECTS compared with healthy controls. Abnormal gray matter volume was significantly correlated with clinical data and specific neurotransmitters.

Structural and functional changes in drug-naïve benign childhood epilepsy with centrotemporal spikes and their associated gene expression profiles

Benign epilepsy with centrotemporal spikes (BECTS) is a common pediatric epilepsy syndrome that has been widely reported to show abnormal brain structure and function. However, the genetic mechanisms underlying structural and functional changes remain largely unknown. Based on the structural and resting-state functional magnetic resonance imaging data of 22 drug-naïve children with BECTS and 33 healthy controls, we conducted voxel-based morphology (VBM) and fractional amplitude of low-frequency fluctuation (fALFF) analyses to compare cortical morphology and spontaneous brain activity between the 2 groups. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial correlation analyses were applied to explore gene expression profiles associated with gray matter volume (GMV) and fALFF changes in BECTS. VBM analysis demonstrated significantly increased GMV in the right brainstem and right middle cingulate gyrus in BECTS. Moreover, children with BECTS exhibited significantly increased fALFF in left temporal pole, while decreased fALFF in right thalamus and left precuneus. These brain structural and functional alterations were closely related to behavioral and cognitive deficits, and the fALFF-linked gene expression profiles were enriched in voltage-gated ion channel and synaptic activity as well as neuron projection. Our findings suggest that brain morphological and functional abnormalities in children with BECTS involve complex polygenic genetic mechanisms.

Whole-Brain Dynamic Resting-State Functional Network Analysis in Benign Epilepsy with Centrotemporal Spikes

Benign epilepsy with centrotemporal spikes (BECTS), the most common type of epilepsy among children, is considered a network disorder. Both fMRI and EEG source imaging (ESI) studies have indicated that BECTS is associated with static resting-state functional network (SFN) alterations (e.g., decreased global efficiency) in source space. However, we find that the abovementioned alterations are not significant when the SFN calculations are performed in the scalp space using only clinical routine low-density (e.g., 19 channels) EEG recordings (shown in our results). In the context of EEG microstates, it is clear that networks in the scalp space with resting-state EEG recordings dynamically reconfigure in a well-organized way based on different functional states. We are therefore inspired to propose a whole-brain dynamic resting-state functional network (DFN) computation method based on resting-state low-density EEG recordings with four classical microstates in scalp space. Notably, on the one hand, this approach is suitable for clinical conditions, and, on the other hand, the dynamic alternations calculated with a DFN may promote our understanding of how the networks change in BECTS. We analysed the changes in a DFN in six frequency bands (, low, high, and) in patients with BECTS compared to those for healthy controls. Superior to traditional SFNs, the proposed DFN can reveal significant differences between individuals with BECTS and healthy controls (e.g., lower global efficiency), thus matching traditional fMRI and ESI methods in the source space. Our method directly performs DFN computations from low-density EEG recordings and avoids complex ESI computations, making it promising for clinical applications, especially in the outpatient diagnosis stage.

Involvement of brain structures in childhood epilepsy with centrotemporal spikes

BACKGROUND

We aimed to investigate electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) findings to elucidate the interictal epileptiform discharge (IED)-related functional alterations in deep brain structures and the neocortex in childhood epilepsy with centrotemporal spikes (CECTS).

METHODS

Ten children with CECTS (median age 8.2 years), referred to our hospital within a year of onset, were eligible for inclusion. They underwent EEG-fMRI recording during sleep. Llongitudinal evaluations, including medical examinations, intelligence tests, and questionnaires about developmental disabilities, were performed. The initial evaluation was performed at the same time as the EEG-fMRI, and the second evaluation was performed over 2 years after the initial evaluation.

RESULTS

Three children were unable to maintain sleep during the EEG-fMRI recording, and the remaining seven children were eligible for further assessment. All patients showed unilateral-dominant centrotemporal spikes during scans. One patient had only positive hemodynamic responses, while the others had both positive and negative hemodynamic responses. All patients showed IED-related hemodynamic responses in the bilateral neocortex. For deep brain structures, IED-related hemodynamic responses were observed in the cingulate gyrus (n = 4), basal ganglia (n = 3), thalamus (n = 2), and default mode network (n = 1). Seizure frequencies at the second evaluation were infrequent or absent, and the longitudinal results of intelligence tests and questionnaires were within normal ranges.

CONCLUSIONS

We demonstrated that IEDs affect broad brain areas, including deep brain structures such as the cingulate gyrus, basal ganglia, and thalamus. Deep brain structures may play an important role in the pathophysiology of CECTS.

A systematic review of resting-state and task-based fmri in juvenile myoclonic epilepsy

Functional neuroimaging modalities have enhanced our understanding of juvenile myoclonic epilepsy (JME) underlying neural mechanisms. Due to its non-invasive, sensitive and analytical nature, functional magnetic resonance imaging (fMRI) provides valuable insights into relevant functional brain networks and their segregation and integration properties. We systematically reviewed the contribution of resting-state and task-based fMRI to the current understanding of the pathophysiology and the patterns of seizure propagation in JME Altogether, despite some discrepancies, functional findings suggest that corticothalamo-striato-cerebellar network along with default-mode network and salience network are the most affected networks in patients with JME. However, further studies are required to investigate the association between JME's main deficiencies, e.g., motor and cognitive deficiencies and fMRI findings. Moreover, simultaneous electroencephalography-fMRI (EEG-fMRI) studies indicate that alterations of these networks play a role in seizure modulation but fall short of identifying a causal relationship between altered functional properties and seizure propagation. This review highlights the complex pathophysiology of JME, which necessitates the design of more personalized diagnostic and therapeutic strategies in this group.

Auditory stimulation during sleep suppresses spike activity in benign epilepsy with centrotemporal spikes

Benign epilepsy with centrotemporal spikes (BECTS) is a common form of childhood epilepsy linked to diverse cognitive abnormalities. The electroencephalogram of patients shows focal interictal epileptic spikes, particularly during non-rapid eye movement (NonREM) sleep. Spike formation involves thalamocortical networks, which also contribute to the generation of sleep slow oscillations (SOs) and spindles. Motivated by evidence that SO-spindle activity can be controlled through closed-loop auditory stimulation, here, we show in seven patients that auditory stimulation also reduces spike rates in BECTS. Stimulation during NonREM sleep decreases spike rates, with most robust reductions when tones are presented 1.5 to 3.5 s after spikes. Stimulation further reduces the amplitude of spikes closely following tones. Sleep spindles are negatively correlated with spike rates, suggesting that tone-evoked spindle activity mediates the spike suppression. We hypothesize spindle-related refractoriness in thalamocortical circuits as a potential mechanism. Our results open an avenue for the non-pharmacological treatment of BECTS.

Spikes in BECTS epilepsy and sleep spindles may share thalamocortical generation

Auditory stimulation during sleep evokes sleep spindles and suppresses spikes

Stimulation may reduce spiking by inducing thalamocortical refractoriness

Interictal epileptiform discharges changed epilepsy-related brain network architecture in BECTS

To investigate directed information flow of epileptiform activity in benign epilepsy with centrotemporal spikes (BECTS) during ictal epileptiform discharges (IEDs) and non-IEDs periods. In this multi-center study, a total of 188 subjects, including 50 BECTS and 138 normal children's controls (NCs) from three different centers (Center 1: females/males, 38/55; mean age, 9.33 ± 2.6 years; Center 2: females/males,7/10; mean age, 8.59 ± 2.32 years; Center 3: females/males, 14/14; mean age, 13 ± 3.42 years) were recruited. The BECTS were classified into IEDs (females/males, 12/15; mean age, 8.15 ± 1.68 years) and non-IEDs (females/males, 10/13; mean age, 9.09 ± 1.98 years) subgroups depending on presence of central-temporal spikes from an EEG-fMRI examination. Three new methods, structural equation parametric modeling, dynamic causal modeling and granger causality density (GCD) were used to determine optimal network architectures for BECTS. Three multicentric NCs determined a reliable and consistent network architecture by structural equation parametric modeling method. Further analyses were used for IEDs and non-IEDs to determine the brain network architecture by structural equation parametric modeling, dynamic causal modeling and GCD, respectively. The brain network architecture of IEDs substate, non-IEDs substate and NCs are different. IEDs promoted the driving effect of the Rolandic areas with more output information flows, and increased the targeted effect of the top of pre-/post-central gyrus with more input information flows. The information flow arises from the Rolandic areas, and subsequently propagates to the top of pre-/post-central gyrus and thalamus. From non-IEDs status to IEDs status, the thalamus load may play an important role in the modulation and regulation of epileptiform activity. These findings shed new light on pathophysiological mechanism of directed localization of epileptiform activity in BECTS.

Brain function and network features in patients with chronic epilepsy before and after antiseizure medication withdrawal

OBJECTIVES

A considerable proportion of epilepsy patients who achieved long-term seizure freedom with standardized treatment of antiseizure medication will attempt to withdraw medications. Epilepsy is currently considered as a network disease, however, the characteristics of brain function and neural network before and after medication withdrawal remain to be discovered.

METHODS

Resting-state functional magnetic resonance imaging was obtained for 32 healthy controls, 32 seizure-free patients initiating medication tapering (PG1 group), and 16 seizure-free patients that had completely discontinued medications (PG2 group). Amplitude of low-frequency fluctuation and regional homogeneity were calculated to measure local functional activity. Global and nodal metrics of small-world network were calculated based on Graph theory. One-way analysis of variance was applied to analyze intergroup difference, withpost hoc analysis being conducted for each pair of groups.

RESULTS

Sex, age at scanning and other clinical variables showed no significant difference between groups. As compared to control, the amplitude of low-frequency fluctuation, regional homogeneity or nodal metrics of neural network in some brain areas were abnormal in the PG1 or PG2 group; when compared between patient groups, significant between-group differences were also found in the amplitude of low-frequency fluctuation, regional homogeneity or nodal metrics. But, the global metrics of neural network showed no differences among groups.

CONCLUSIONS

The global metrics of patients with long-term seizure freedom were normal either before or after antiseizure medication withdrawal, while the local functional activity and nodal metrics in some brain areas were abnormal and differed between before and after antiseizure medication withdrawal.

Influence of epileptogenic region on brain structural changes in Rolandic epilepsy

To investigate the influence of epileptogenic cortex (Rolandic areas) with executive functions in Rolandic epilepsy using structural covariance analysis of structural magnetic resonance imaging (MRI). Structural MRI data of drug-naive patients with Rolandic epilepsy (n = 70) and typically developing children as healthy controls (n = 83) were analyzed using voxel-based morphometry. Gray matter volumes in the patients were compared with those of healthy controls, and were further correlated with epilepsy duration and cognitive score of executive function, respectively. By applying Granger causal analysis to the sequenced morphometric data according to disease progression information, causal network of structural covariance was constructed to assess the causal influence of structural changes from Rolandic cortices to the regions engaging executive function in the patients. Compared with healthy controls, epilepsy patients showed increased gray matter volume in the Rolandic regions, and also the regions engaging in executive function. Covariance network analyses showed that along with disease progression, the Rolandic regions imposed positive causal influence on the regions engaging in executive function. In the patients with Rolandic epilepsy, epileptogenic regions have causal influence on the structural changes in the regions of executive function, implicating damaging effects of Rolandic epilepsy on human brain.

Brain network excitatory/inhibitory imbalance is a biomarker for drug-naive Rolandic epilepsy: A radiomics strategy

OBJECTIVE

Seizure occurs when the balance between excitatory and inhibitory (E/I) inputs to neurons is perturbed, resulting in abnormal electrical activity. This study investigated whether an existing E/I imbalance in neural networks is a useful diagnostic biomarker for Rolandic epilepsy by a resting-state dynamic causal modeling-based support vector machine (rs-DCM-SVM) algorithm.

METHODS

This multicenter study enrolled a discovery cohort (76 children with Rolandic epilepsy and 76 normal controls [NCs]) and a replication cohort (59 children with Rolandic epilepsy and 60 NCs). Spatial independent component analysis was used to seven canonical neural networks, and a total of 25 regions of interest were selected from these networks. The rs-DCM-SVM classifier was used for individual classification, consensus feature selection, and feature ranking.

RESULTS

The rs-DCM-SVM classifier showed that the E/I imbalance in brain networks is a useful neuroimaging biomarker for Rolandic epilepsy, with an accuracy of 88.2% and 81.5% and an area under curve of .92 and .83 in the discovery and the replication cohorts, respectively. Consensus brain regions with the highest contributions to the classification were located within the epilepsy-related networks, indicating that this classifier was suitable. Consensus functional connection pairs with the highest contributions to the classification were associated with an excitation network loop and an inhibition network loop. The excitation loop mediated the integration of advanced cognitive networks (subcortex, dorsal attention, default mode, executive control, and salience networks), whereas the inhibition loop was involved in the segregation of sensorimotor and language networks. The two loops showed functional segregation.

SIGNIFICANCE

Brain E/I imbalance has potential to serve as a biomarker for individual classification in children with Rolandic epilepsy, and might be an important mechanism for causing seizures and cognitive impairment in children with Rolandic epilepsy.

Reliability and availability of granger causality density in localization of Rolandic focus in BECTS

A new method, called granger causality density (GCD), could reflect the directed information flow of the epileptiform activity, which is much closely match with excitatory and inhibitory imbalance theory of epilepsy. Here, we investigated if GCD could effectively localize the Rolandic focus in 50 patients with benign childhood epilepsy with central-temporal spikes (BECTS) from 27 normal children. The BECTS were classified into ictal epileptiform discharges (IEDs; 12 females, 15 males;age, 8.15 ± 1.68 years) and non-IEDs (10 females, 13 males; age, 9.09 ± 1.98 years) subgroups depending on the presence of central-temporal spikes. Multiple correlation-modality analyses (Pearson, across-voxel and across-subject correlations) were used to calculate the couplings between the GCD maps and IEDs-related brain activation map. The individual lateralization coefficient of localize IEDs and multiple regression analysis were used to identify the reliability of the GCD method in localizing the Rolandic focus. In this study, multiple correlation-modality analyses showed that the IEDs-related brain activation map and the GCD maps had highly temporal (coefficient ׀r\= 0.56 ~ 0.65) and spatial (\r\=0.53~0.91) (r\=~ couplings. The proposed GCD method and multiple regression analyses showed consistent findings with the clinical EEG recordings in lateralization of Rolandic focus. Furthermore, the GCD method could reflect the epilepsy-related brain activity during non-IEDs substate. Therefore, the proposed GCD method has the potential to be served as an effective and reliable neuroimaging biomarker to localize the Rolandic focus of BECTS. These findings are critical for clinical early diagnosis, and may promote the progression of treatment and management of pediatric epilepsy.

Brain functional and structural characteristics of patients with seizure recurrence following drug withdrawal

PURPOSE

We aimed to analyze the characteristics of brain function and microstructure linked to epilepsy relapse after drug withdrawal in patients with focal epilepsy.

METHODS

Resting-state functional magnetic resonance imaging and high-resolution T1-weighted images were acquired within 1 month prior to drug withdrawal from 15 patients who did not have epilepsy relapse (PER - group) and 16 patients who subsequently had epilepsy relapse (PER + group). Additionally, 23 healthy participants undergoing the same scanning protocol were included as controls. Fractional amplitude of low-frequency fluctuation (fALFF) and gray matter density (GMD) were compared among groups. Subgroup and correlation analyses were also performed.

RESULTS

There were no significant differences in fALFF between patient groups, but the PER + group showed lower GMD in the bilateral calcarine, left precuneus, and right superior temporal gyrus than the PER - group (Gaussian random field correction, voxel-level P < 0.001 and cluster-level P < 0.05). Both increased seizure number and polytherapy were associated with lower GMD; also, patients using other antiseizure medications showed lower GMD than those using only levetiracetam (Gaussian random field correction, voxel-level P < 0.001, and cluster-level P < 0.05). The active period and disease duration showed both positive and negative correlations with GMD, while the seizure-free period mainly showed positive correlations with GMD (uncorrected, P < 0.001).

CONCLUSION

Gray matter microstructure, but not local functional activity, showed distinct characteristics between patients with and without epilepsy relapse and may serve as a potential biomarker for predicting seizure recurrence upon drug withdrawal.

Self-limited focal epilepsy decreased regional brain activity in sensorimotor areas

OBJECTIVE

The fractional amplitude of low-frequency fluctuation (fALFF) method was used to identify the regional brain activity deficits of self-limited focal epilepsy with centrotemporal spikes (SLFECS) relative to normal controls (NCs).

METHODS

A total of 21 SLFECS (10 females, 11 males; mean age, 8.57 ± 1.5 years) and 21 status-matched (age, sex, and education) NCs (10 females, 11 males; mean age, 8.76 ± 2.19 years) were recruited. The fALFF method was applied to identify SLFECS-related regional brain alterations. Receiver operating characteristic (ROC) curve was applied to identify the ability of these regional brain areas in distinguishing the SLFECS group from the NCs group. The relationships between the regional brain activity deficits and clinical features were evaluated by Pearson's correlation analysis.

RESULTS

Self-limited focal epilepsy with centrotemporal spikes was associated with widespread regional brain activity alterations, including left cuneus with higher fALFF values, and bilateral striatum, bilateral precentral gyrus, ventral and dorsal pathway of sensory area, left dorsolateral prefrontal cortex, and left Rolandic area with lower fALFF values. ROC curve revealed excellent AUC value (0.964) of these areas in distinguishing the SLFECS group from the NCs group with high degree of sensitivity (90.5%) and specificity (95.2%). Intelligence quotient score positively correlated with the fALFF value in the left striatum (r = 0.453, p = 0.039).

CONCLUSIONS

The fALFF parameter could be served as a potential biomarker to identify the SLFECS-related regional brain deficits in the sensorimotor cortex and their pathways, which may be the etiology of paresthesia in SLFECS.

Frequency-Dependent Interictal Neuromagnetic Activities in Children With Benign Epilepsy With Centrotemporal Spikes: A Magnetoencephalography (MEG) Study

Objective: This study aimed to investigate interictal neuromagnetic activities in the low- to high-frequency ranges in patients with benign epilepsy with centrotemporal spikes (BECTS), especially those without interictal epileptiform discharges (IEDs).

Methods: We studied 21 clinically-diagnosed BECTS patients and 11 age-matched healthy controls (HC) using high-sampling magnetoencephalography (MEG). Neuromagnetic sources were assessed with accumulated source imaging (ASI). The MEG data were analyzed in seven frequency bands. The MEG recordings distinguished BECTS without IEDs (n = 10) from those with IEDs (n = 11) and HC (n = 11).

Results: At 1–4 Hz, the neuromagnetic activities in healthy subjects tended to locate at the precuneus/posterior cingulate, while those of the BECTS patients without IEDs tended to locate at the medial frontal cortex (MFC) compared to BECTS patients with IEDs. The MEG source imaging at 30–80 Hz revealed that BECTS patients without IEDs had higher occurrences of interictal brain activity in the medial temporal lobe (MTL) compared to controls and the brain activity strength seemed to be weaker. There was a significant correlation between the source strength of the interictal gamma oscillations of BECTS patients without IEDs and the duration of epilepsy.

Conclusions: IEDs might disrupt the default mode network (DMN). Aberrant brain activities in BECTS patients without IEDs were associated with cognitive areas of the brain. The strength of gamma oscillations in the chronic epilepsy state reflected the duration of BECTS.

Significance: MEG could reveal the aberrant neural activities in BECTS patients during the interictal period, and such abnormality is frequency-dependent. Gamma oscillations could be used to identify BECTS patients without IEDs.

Electrical status epilepticus in sleep affects intrinsically connected networks in patients with benign childhood epilepsy with centrotemporal spikes

BACKGROUND

Although outcomes of benign childhood epilepsy with centrotemporal spikes (BECTS) are frequently excellent, some atypical forms of BECTS, especially electrical status epilepticus in sleep (ESES), are characterized by worse outcomes and negative impacts on cognitive development.

METHODS

To explore specific ESES-related brain networks in patients with BECTS, we used resting-state functional magnetic resonance imaging (fMRI) to scan patients with BECTS with ESES (n = 9), patients with BECTS without ESES (n = 17), and healthy controls (n = 36). Unbiased seed-based whole-brain functional connectivity (FC) was adopted to explore the connectivity mode of three resting-state cerebral networks: the default mode network (DMN), salience network (SN), and central executive network (CEN).

RESULTS

Compared with the other two groups, patients with BECTS with ESES showed FC in the SN or in the CEN decreased, but not in the DMN. Moreover, we found the FC in the CEN in patients with BECTS without ESES decreased when compared with controls. Our currently intrinsically defined anticorrelated networks strength was disrupted in BECTS and connote greater deactivation than the results from FC for a seed region in children with BECTS.

CONCLUSION

These results indicated that children with BECTS with ESES showed brain activity altered in the CEN and the SN. The difference of impairment in the SN and CEN may lead to improve the understanding of the underlying neuropathophysiology, and to assess the activity of patients with BECTS with ESES, which is crucial for measuring disease activity, improving patient care, and assessing the effect of antiepilepsy therapy.

Electromyography Biomarkers for Quantifying the Intraoperative Efficacy of Deep Brain Stimulation in Parkinson's Patients With Resting Tremor

Introduction: Deep brain stimulation (DBS) is an effective therapy for resting tremor in Parkinson's disease (PD). However, quick and objective biomarkers for quantifying the efficacy of DBS intraoperatively are lacking. Therefore, we aimed to study how DBS modulates the intraoperative neuromuscular pattern of resting tremor in PD patients and to find predictive surface electromyography (sEMG) biomarkers for quantifying the intraoperative efficacy of DBS. Methods: Intraoperative sEMG of 39 PD patients with resting tremor was measured with the DBS on and off, respectively, during the intraoperative DBS testing stage. Twelve signal features (time and frequency domains) were extracted from the intraoperative sEMG data. These sEMG features were associated with the clinical outcome to evaluate the efficacy of intraoperative DBS. Also, an sEMG-based prediction model was established to predict the clinical improvement rate (IR) of resting tremor with DBS therapy. Results: A typical resting tremor with a peak frequency of 4.93 ± 0.98 Hz (mean ± SD) was measured. Compared to the baseline, DBS modulated significant neuromuscular pattern changes in most features except for the peak frequency, by decreasing the motor unit firing rate, amplitude, or power and by changing the regularity pattern. Three sEMG features were detected with significant associations with the clinical improvement rate (IR) of the tremor scale: peak frequency power (R = 0.37, p = 0.03), weighted root mean square (R = 0.42, p = 0.01), and modified mean amplitude power (R = 0.48, p = 0.003). These were adopted to train a Gaussian process regression model with a leave-one-out cross-validation procedure. The prediction values from the trained sEMG prediction model (1,000 permutations, p = 0.003) showed a good correlation (r = 0.47, p = 0.0043) with the true IR of the tremor scale. Conclusion: DBS acutely modulated the intraoperative resting tremor, mainly by suppressing the amplitude and motor unit firing rate and by changing the regularity pattern, but not by modifying the frequency pattern. Three features showed strong robustness and could be used as quick intraoperative biomarkers to quantify and predict the efficacy of DBS in PD patients with resting tremor.

Abnormal dynamics of functional connectivity density in children with benign epilepsy with centrotemporal spikes

Converging evidence has shown the link between benign epilepsy with centrotemporal spikes (BECTS) and abnormal functional connectivity among distant brain regions. However, prior research in BECTS has not examined the dynamic changes in functional connectivity as networks form. We combined functional connectivity density (FCD) mapping and sliding windows correlation analyses, to fully capture the functional dynamics in patients with respect to the presence of interictal epileptic discharges (IEDs). Resting-state fMRI was performed in 43 BECTS patients and 28 healthy controls (HC). Patients were further classified into two subgroups, namely, IED (n = 20) and non-IED (n = 23) depending on the simultaneous EEG-fMRI recordings. The global dynamic FCD (dFCD) was measured using sliding window correlation. Then we quantified dFCD variability using their standard deviation. Compared with HC, patients with and without IEDs both showed invariable dFCD (decreased) among the orbital fontal cortex, anterior cingulate cortex and striatum, as well as variable dFCD (increased) in the posterior default mode network (P < 0.05, AlphaSim corrected). Correlation analysis indicated that the variable dFCD in precuneus was related to seizure onset age (P < 0.05, uncorrected). BECTS with IEDs showed variable dFCD in regions related to the typical seizure semiology. The abnormal patterns of fluctuating FCD in BECTS suggest that both active and chronic epileptic state may contribute to altered dynamics of functional connectivity associated with cognitive disturbances and developmental alterations. These findings highlight the importance of considering fluctuating dynamic neural communication among brain systems to deepen our understanding of epilepsy diseases.

BECTS Substate Classification by Granger Causality Density Based Support Vector Machine Model

Objectives: To investigate the performance of substate classification of children with benign epilepsy with centrotemporal spikes (BECTS) by granger causality density (GCD) based support vector machine (SVM) model.

Methods: Forty-two children with BECTS (21 females, 21 males; mean age, 8.6 ± 1.96 years) were classified into interictal epileptic discharges (IEDs; 11 females, 10 males) and non-IEDs (10 females, 11 males) substates depending on presence of central-temporal spikes or not. GCD was calculated on four metrics, including inflow, outflow, total-flow (inflow + outflow) and int-flow (inflow – outflow) connectivity. SVM classifier was applied to discriminate the two substates.

Results: The Rolandic area, caudate, dorsal attention network, visual cortex, language networks, and cerebellum had discriminative effect on distinguishing the two substates. Relative to each of the four GCD metrics, using combined metrics could reach up the classification performance (best value; AUC, 0.928; accuracy rate, 90.83%; sensitivity, 90%; specificity, 95%), especially for the combinations with more than three GCD metrics. Specially, combined the inflow, outflow and int-flow metric received the best classification performance with the highest AUC value, classification accuracy and specificity. Furthermore, the GCD-SVM model received good and stable classification performance across 14 dimension reduced data sets.

Conclusions: The GCD-SVM model could be used for BECTS substate classification, which might have the potential to provide a promising model for IEDs detection. This may help assist clinicians for administer drugs and prognosis evaluation.

Alteration of cerebello-thalamocortical spontaneous low-frequency oscillations in juvenile myoclonic epilepsy

OBJECTIVE

Altered thalamocortical network has been proposed to play a pivotal role in the principal pathophysiology underlying juvenile myoclonic epilepsy (JME). Recently, resting-state fMRI studies have provided converging evidence for thalamocortical dysconnectivity in patients with JME. Herein, we investigated the amplitude and spatial distribution of spontaneous low-frequency oscillations using analysis of fractional amplitude of low-frequency fluctuation (fALFF) in a large group of JME patients in comparison with controls.

METHODS

Volumetric MRI and resting-state fMRI were acquired in 75 patients with JME and 62 matched controls. After preprocessing of MRI data, fALFF was computed and then Z-transformed for standardization. fALFF was compared between controls and patients, and correlation analysis between regional fALFF and clinical parameters were performed in patients.

RESULTS

Compared with controls, JME patients revealed significant fALFF increases in the bilateral medial thalamus, insular cortex/inferior frontal gyrus, and cerebellum vermis (false discovery rate-corrected P < 0.05). There was no region of fALFF reduction in JME patients relative to controls. No significant correlation was observed between regional fALFF and disease duration or cumulative number of generalized tonic-clonic seizures.

CONCLUSIONS

We have shown alterations of low-frequency oscillations in the thalamus, insular cortex/inferior frontal gyrus, and cerebellum in patients with JME, implicating cerebello-thalamocortical network abnormality in the pathophysiology underlying JME. Our results could further support the recent concept that JME is a network epilepsy involving specific cortical and subcortical structures, especially the cerebello-thalamocortical network.

The Role of EEG-fMRI in Studying Cognitive Network Alterations in Epilepsy

Brain functions do not arise from isolated brain regions, but from interactions in widespread networks necessary for both normal and pathological conditions. These Intrinsic Connectivity Networks (ICNs) support cognitive processes such as language, memory, or executive functions, but can be disrupted by epileptic activity. Simultaneous EEG-fMRI can help explore the hemodynamic changes associated with focal or generalized epileptic discharges, thus providing information about both transient and non-transient impairment of cognitive networks related to spatio-temporal overlap with epileptic activity. In the following review, we discuss the importance of interictal discharges and their impact on cognition in different epilepsy syndromes. We explore the cognitive impact of interictal activity in both animal models and human connectivity networks in order to confirm that this effect could have a possible clinical impact for prescribing medication and characterizing post-surgical outcome. Future work is needed to further investigate electrophysiological changes, such as amplitude/latency of single evoked responses or spontaneous epileptic activity in either scalp or intracranial EEG and determine its relative change in hemodynamic response with subsequent network modifications.

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 temporal dynamics of brain activity in patients with generalized tonic-clonic seizures

Generalized seizures engage bilateral networks from their onset at a low temporal scale. Previous studies findings have demonstrated focal/local brain activity abnormalities in the patients with generalized tonic-clonic seizures (GTCS). Resting state functional magnetic resonance imaging (fMRI) allows the detection of aberrant spontaneous brain activity in GTCS. Little is known, however, about alterations of dynamics (temporal variability) of spontaneous brain activity. It also remains unclear whether temporal variability of spontaneous brain activity is associated with disease severity. To address these questions, the current study assessed patients with GTCS (n = 35), and age- and sex-matched healthy controls (HCs, n = 33) who underwent resting state fMRI. We first assessed the dynamics of spontaneous brain activity using dynamic amplitude of low-frequency fluctuation (dALFF). Furthermore, the temporal variability of brain activity was quantified as the variance of dALFF across sliding window. Compared to HCs, patients with GTCS showed hyper-temporal variability of dALFF in parts of the default mode network, whereas they showed hypo-temporal variability in the somatomotor cortex. Furthermore, dynamic ALFF in the subgenual anterior cingulate cortex was positively correlated with duration of disease, indicating that disease severity is associated with excessive variability. These results suggest both an excessive variability and excessive stability in patients with GTCS. Overall, the current findings from brain activity dynamics contribute to our understanding of the pathophysiological mechanisms of generalized seizure.

Altered connectivity patterns among resting state networks in patients with ischemic white matter lesions

White matter lesions (WMLs) have been associated with cognitive and motor decline. Resting state networks (RSNs) are spatially coherent patterns in the human brain and their interactions sustain our daily function. Therefore, investigating the altered intra- and inter-network connectivity among the RSNs may help to understand the association of WMLs with impaired cognitive and motor function. Here, we assessed alterations in functional connectivity patterns based on six well-defined RSNs-the default mode network (DMN), dorsal attention network (DAN), frontal-parietal control network (FPCN), auditory network (AN), sensory motor network (SMN) and visual network (VN)-in 15 patients with ischemic WMLs and 15 controls. In the patients, Spearman's correlation analysis was further performed between these alterations and cognitive test scores, including Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Our results showed wide alterations of inter-network connectivity mainly involving the SMN, DMN, FPCN and DAN, and some alterations correlated with cognitive test scores in the patients. The reduced functional connectivities in the SMN-AN, SMN-VN, FPCN-AN, DAN-VN pairs may account for the cognitive and motor decline in patients with ischemic WMLs, while the increased functional connectivities in the DMN-AN, DMN-FPCN and DAN-FPCN pairs may reflect a functional network reorganization after damage to white matter. It is unexpected that altered intra-network connectivities were found within the AN and VN, which may explain the impairments in verbal fluency and information retrieval associated with WMLs. This study highlights the importance of functional connectivity in understanding how WMLs influence cognitive and behavior dysfunction.

Frequency-specific alterations in the amplitude and synchronization of resting-state spontaneous low-frequency oscillations in benign childhood epilepsy with centrotemporal spikes

OBJECTIVES

Spontaneous low-frequency oscillations in different frequency bands have diverse physiological meanings. The amplitude of low-frequency fluctuation (ALFF) and functional connectivity (FC) in different frequency bands in Benign Childhood Epilepsy with Centrotemporal Spikes (BECTS) are unknown and worth exploring.

METHOD

Resting-state functional magnetic resonance imaging data were collected in 51 drug-naïve BECTS patients and 76 healthy controls. The ALFF was calculated for the typical (0.01 - 0.08 Hz), slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), and slow-3 (0.073-0.198 Hz) frequency bands. The bilateral precuneus/posterior cingulate cortex (PCU/PCC) showed a common alteration of ALFF in different frequency bands, and was selected as the seed for calculating FC per voxel.

RESULTS

In the typical band, BECTS patients showed increased ALFF in the left rolandic operculum and the right pre/postcentral gyrus, and decreased ALFF in the bilateral PCU/PCC, some of which were shared by the slow-5, slow-4, and slow-3 bands. Decreased ALFF in the left angular gyrus was also found in the slow-3 band. Only the bilateral PCU/PCC showed a frequency-dependent correlation with the total seizure frequency and full-scale intelligence quotient. Regions having degenerated FC with the bilateral PCU/PCC in BECTS patients were mainly in the left prefrontal cortex and bilateral anterior cingulate cortex for the typical and slow-5 bands, and in the bilateral temporal limbic system and striatum for the slow-4 and slow-3 bands.

CONCLUSION

Alteration of the ALFF and FC differed with distinct frequency bands. Therefore, employing different frequency bands would provide more meaningful findings for BECTS patients.

Stimulated left DLPFC-nucleus accumbens functional connectivity predicts the anti-depression and anti-anxiety effects of rTMS for depression

Not all depression patients effectively respond to repeated transcranial magnetic stimulation (rTMS). We tested whether the intrinsic functional connectivity (FC) strength between the stimulated left dorsolateral prefrontal cortex (DLPFC) and left nucleus accumbens (NAcc) might predict effects of rTMS. Twenty-two medication-naïve depression patients received rTMS on left DLPFC for 2 weeks and underwent baseline functional magnetic resonance imaging (fMRI). We compared the amplitude of the low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) in the stimulated target (the cortex region directly stimulated by rTMS) located in the left DLPFC, and the left NAcc, as well as the intrinsic FC of the DLPFC-NAcc between early improvers and non-improvers. We evaluated the association between the baseline brain imaging features (ALFF, ReHo, and FC) and improvements in depression and anxiety symptoms. We found that the pretreatment ALFF and ReHo in the stimulated DLPFC and left NAcc did not significantly differ between the subgroups. The early improvers displayed increased negative FC strength between the stimulated DLPFC and left NAcc with respect to non-improvers. The stimulated DLPFC-NAcc FC strength negatively correlated with improved depressive and anxious symptoms. This study is the first to demonstrate that the resting-state FC of the stimulated DLPFC-NAcc, rather than regional brain activity or local synchronization in the stimulated target, might predict the anti-depression and anti-anxiety effects of rTMS for depression.

Structural Covariance Network of Cortical Gyrification in Benign Childhood Epilepsy with Centrotemporal Spikes

Benign childhood epilepsy with centrotemporal spikes (BECTS) is associated with cognitive and language problems. According to recent studies, disruptions in brain structure and function in children with BECTS are beyond a Rolandic focus, suggesting atypical cortical development. However, previous studies utilizing surface-based metrics (e.g., cortical gyrification) and their structural covariance networks at high resolution in children with BECTS are limited. Twenty-six children with BECTS (15 males/11 females; 10.35 ± 2.91 years) and 26 demographically matched controls (15 males/11 females; 11.35 ± 2.51 years) were included in this study and subjected to high-resolution structural brain MRI scans. The gyrification index was calculated, and structural brain networks were reconstructed based on the covariance of the cortical folding. In the BECTS group, significantly increased gyrification was observed in the bilateral Sylvain fissures and the left pars triangularis, temporal, rostral middle frontal, lateral orbitofrontal, and supramarginal areas (cluster-corrected p < 0.05). Global brain network measures were not significantly different between the groups; however, the nodal alterations were most pronounced in the insular, frontal, temporal, and occipital lobes (FDR corrected, p < 0.05). In children with BECTS, brain hubs increased in number and tended to shift to sensorimotor and temporal areas. Furthermore, we observed significantly positive relationships between the gyrification index and age (vertex p < 0.001, cluster-level correction) as well as duration of epilepsy (vertex p < 0.001, cluster-level correction). Our results suggest that BECTS may be a condition that features abnormal over-folding of the Sylvian fissures and uncoordinated development of structural wiring, disrupted nodal profiles of centrality, and shifted hub distribution, which potentially represents a neuroanatomical hallmark of BECTS in the developing brain.

Disrupted intrinsic and remote functional connectivity in heterotopia-related epilepsy

OBJECTIVES

Several neuroimaging studies have examined neural interactions in patients with periventricular nodular heterotopia (PNH). However, features of the underlying functional network remain poorly understood. In this study, we examined alterations in the local (regional) and remote (interregional) cerebral networks in this disorder.

METHODS

Twenty-eight subjects all having suffered from PNH with epilepsy, as well as 28 age- and sex- matched healthy controls, were enrolled in this study. Amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity (FC) were calculated to detect regional neural function and functional network integration, respectively.

RESULTS

Compared with healthy controls, patients with PNH-related epilepsy showed decreased ALFF in the ventromedial prefrontal cortex (vmPFC) and precuneus areas. ALFF values in both areas were negative correlated with epilepsy duration (P < .05, Bonferroni-corrected). Furthermore, patients with PNH-related epilepsy had increased remote interregional FC mainly in bilateral prefrontal and parietal cortices, supramarginal gyrus, dorsal cingulate gyrus, and right insula; lower FC was found in posterior brain regions including bilateral parahippocampal gyrus and inferior temporal gyrus.

CONCLUSIONS

Focal spontaneous hypofunction, as assessed by ALFF, correlates with epilepsy duration in patients with PNH-related epilepsy. Abnormalities existed both within the default-mode network and then across the whole brain, demonstrating that intrinsic brain dysfunction may be related to specific network interactions. Our findings provide novel understanding of the connectivity-based pathophysiological mechanisms of PNH.

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

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

Epileptic Discharge Related Functional Connectivity Within and Between Networks in Benign Epilepsy with Centrotemporal Spikes

Benign epilepsy with centrotemporal spikes (BECTS) is a common childhood epilepsy syndrome associated with abnormalities in neurocognitive domains, particularly during interictal epileptiform discharges (IEDs). Here, we investigated the effects of IEDs on brain’s intrinsic connectivity networks in 43 BECTS patients and 28 matched healthy controls (HCs). Patients were further divided into IED and non-IED subgroups based on simultaneous EEG-fMRI recordings. Functional connectivity within and between five networks, corresponding to seizure origination and cognitive processes, were analyzed to measure IED effects. We found that patients exhibited increased connectivity within the auditory network (AN) and the somato-motor network (SMN), and decreased connectivity within the basal ganglia network and the dorsal attention network, suggesting that both transient and chronic seizure activity may disturb normal network organization. The IED group showed decreased functional connectivity within the default mode network (DMN) compared with the non-IED group and HCs, implying that the DMN was selectively impaired during epileptiform discharges associated with altered self-referential cognitive functions. Moreover, the IED group exhibited increased positive correlations between the AN and the SMN, which suggests a possible excessive influence of centrotemporal spiking on information processing in the auditory system. The association between epileptic activity and network dysfunctions highlights their importance in investigating the pathological mechanism underlying BECTS.

Alterations in Spontaneous Brain Activity and Functional Network Reorganization following Surgery in Children with Medically Refractory Epilepsy: A Resting-State Functional Magnetic Resonance Imaging Study

For some patients with medically refractory epilepsy (MRE), surgery is a safe and effective treatment for controlling epilepsy. However, the functional consequences of such surgery on brain activity and connectivity in children remain unknown. In the present study, we carried out a longitudinal study using resting-state functional magnetic resonance imaging in 10 children with MRE before and again at a mean of 79 days after surgery, as well as in a group of 28 healthy controls. Compared with the controls, children with epilepsy exhibited abnormalities in intrinsic activity in the thalamus, putamen, pallidum, insula, hippocampus, cerebellum, and cingulate gyrus both before and after surgery. Longitudinal analyses showed that the amplitude of low frequency fluctuations (ALFF) increased in the parietal–frontal cortex and decreased in the deep nuclei from pre- to post-surgery. The percentage changes in ALFF values in the deep nuclei were positively correlated with the age of epilepsy onset. Functional connectivity (FC) analyses demonstrated a reorganization of FC architecture after surgery. These changes in brain activity and FC after surgery might indicate that the previously disrupted functional interactions were reorganized after surgery. All these results provide preliminary evidence that the age of epilepsy onset may have some potential to predict the outcome of brain functional reorganization after surgery in children with MRE.

Altered language network in benign childhood epilepsy patients with spikes from non-dominant side: A resting-state fMRI study

Benign childhood epilepsy with centrotemporal spikes (BECTS) is one of the most common childhood epilepsy syndromes, and language deficits associated with BECTS have become a hot topic. This study investigated alterations of the language network in BECTS children with spikes from the non-dominant side in comparison with healthy controls. Twenty-three children with BECTS and 20 age-matched healthy controls were enrolled. Region of interest -based whole brain functional connectivity analysis was used to identify the potential differences in the functional connectivity of the Broca's area between the two groups. Increased positive functional connectivity within the Broca's region was detected mainly at the left superior frontal gyrus (Brodmann area 8), bilateral insula, and anterior and posterior cingulate in the BECTS group. No regions showed significantly decreased connection in the BECTS patients compared to the controls. This study suggested alterations in the language network that was related with the Broca's area in children with BECTS from the non-dominant side. Further studies with longitudinal assessments from the perceptive of functional neuroimaging are needed to illustrate the dynamic course of language development and corresponding neuroimaging evidence.

Abnormal asymmetry in benign epilepsy with unilateral and bilateral centrotemporal spikes: A combined fMRI and DTI study

Benign epilepsy with centrotemporal spikes (BECTS) is the most common idiopathic focal childhood epilepsy associated with either unilateral or bilateral epileptic discharge. Asymmetry as an important characteristic of the human brain is beneficial for brain functions. However, little is known about on asymmetry of BECTS patients with different epileptic spikes pattern. In the present study, we investigated functional and structural asymmetries in unilateral spikes BECTS (U_BECTS) patients and bilateral spikes BECTS (B_BECTS) patients using resting state functional magnetic resonance images and diffusion tensor imaging. Compared with the controls, we observed a decreased voxel-mirrored interhemispheric functional connectivity (FC) in primary sensorimotor cortex (SM1) in U_BECTS and B_BECTS groups, and reduced fractional anisotropy (FA) values of the corpus callosum (CC) connecting bilateral SM1 were also observed in B_BECTS group. Further region-based FC map analysis of SM1 demonstrated increased functional asymmetry with ipsilateral hemisphere, contralateral hemisphere and the whole brain in U_BECTS and increased functional asymmetry with the contralateral hemisphere and the whole brain in B_BECTS groups. The correlation between functional asymmetry of SM1 and intelligence quotient scores was found in the U_BECTS group. The altered asymmetries of the SM1 further indicated the important role of SM1 in the pathophysiology of the BECTS. Furthermore, the B_BECTS group also showed abnormal voxel-mirrored interhemispheric FC in the temporal pole, the lobule IX of the cerebellum, the caudate and the occipital cortex relative to the controls. Altogether, our findings provide additional insight into the neuronal mechanism of BECTS with different epileptic spikes pattern and cognitive impairments with BECTS patients.

Decreased Network Efficiency in Benign Epilepsy with Centrotemporal Spikes

Purpose To investigate the functional connectome alterations in benign epilepsy with centrotemporal spikes with respect to the occurrence of interictal epileptic discharges (IEDs) during functional magnetic resonance (MR) imaging. Materials and Methods This prospective study was approved by the local institutional review board and was HIPAA compliant. All participants were consecutively enrolled with written informed consent. Forty-three right-handed patients were classified into IED (n = 20, 13 girls and seven boys; mean age ± standard deviation, 9.00 years ± 1.95) and non-IED (n = 23, 11 girls and 12 boys; mean age, 10.22 years ± 2.13) groups on the basis of electroencephalographic data simultaneously recorded during resting-state functional MR imaging at 3.0 T. The functional connectome features (estimated with graph theoretical analysis) in patient groups and control subjects who were matched for sex, age, and education level (n = 28, all right-handed, 13 girls and 15 boys; mean age, 10.00 years ± 2.31) were compared by using one-way analysis of variance. Results Patients with IEDs and those without IEDs showed consistently abnormal global topology in their functional networks (ie, decreased global efficiency; P < .05) relative to that of control subjects, with no differences between the two patient groups (P > .05). Decreased regional efficiency and connectivity strength were observed in the patients with IEDs and those without (mainly in the perirolandic and frontal areas) relative to control subjects (P < .05). Moreover, the altered functional features significantly correlated with clinical characteristics (ie, disease duration and age at symptom onset, P < .05). Conclusion These findings suggest that decreased global and regional efficiency are prominent functional deficits in children with benign epilepsy with centrotemporal spikes and can be readily identified with resting-state functional MR imaging, irrespective of IEDs. ^© RSNA, 2016 Online supplemental material is available for this article.

Inter-hemispheric Intrinsic Connectivity as a Neuromarker for the Diagnosis of Boys with Tourette Syndrome

Tourette syndrome (TS) is associated with gross morphological changes in the corpus callosum, suggesting deficits in inter-hemispheric coordination. The present study sought to identify changes in inter-hemispheric functional and anatomical connectivity in boys with "pure" TS as well as their potential value for clinical diagnosis. TS boys without comorbidity (pure TS, n = 24) were selected from a large dataset and compared to age- and education-matched controls (n = 32). Intrinsic functional connectivity (iFC) between bilateral homotopic voxels was computed and compared between groups. Abnormal iFC was found in the bilateral prefronto-striatum-midbrain networks as well as bilateral sensorimotor and temporal cortices. The iFC between the bilateral anterior cingulate cortex (ACC) was negatively correlated with symptom severity. Anatomical connectivity strengths between functionally abnormal regions were estimated by diffusion probabilistic tractography, but no significant between-group difference was found. To test the clinical applicability of these neuroimaging findings, multivariate pattern analysis was used to develop a classification model in half of the total sample. The classification model exhibited excellent classification power for discriminating TS patients from controls in the other half samples. In summary, our findings emphasize the role of inter-hemispheric communication deficits in the pathophysiology of TS and suggest that iFC is a potential quantitative neuromarker for clinical diagnosis.

Frequency-Specific Local Synchronization Changes in Paroxysmal Kinesigenic Dyskinesia

The neurobiological basis of paroxysmal kinesigenic dyskinesia (PKD) is poorly defined due to the lack of reliable neuroimaging differences that can distinguish PKD with dystonia (PKD-D) from PKD with chorea (PKD-C). Consequently, diagnosis of PKD remains largely based on the clinical phenotype. Understanding the pathophysiology of PKD may facilitate discrimination between PKD-D and PKD-C, potentially contributing to more accurate diagnosis. We conducted resting-state functional magnetic resonance imaging on patients with PKD-D (n = 22), PKD-C (n = 10), and healthy controls (n = 32). Local synchronization was measured in all 3 groups via regional homogeneity (ReHo) and evaluated using receiver operator characteristic analysis to distinguish between PKD-C and PKD-D. Cortical-basal ganglia circuitry differed significantly between the 2 groups at a specific frequency. Furthermore, the PKD-D and PKD-C patients were observed to show different spontaneous brain activity in the right precuneus, right putamen, and right angular gyrus at the slow-5 frequency band (0.01-0.027 Hz). The frequency-specific abnormal local synchronization between the 2 types of PKD offers new insights into the pathophysiology of this disorder to some extent.

Altered regional homogeneity in epileptic patients with infantile spasm: A resting-state fMRI study

Infantile spasm (IS) syndrome is an age-related epileptic encephalopathy that occurs in children. The purpose of this study was to investigate regional homogeneity (ReHo) changes in IS patients. Resting-state fMRI was performed on 11 patients with IS, along with 35 age- and sex-matched healthy subjects. Group comparisons between the two groups demonstrate that the pattern of regional synchronization synchronization in IS patients is changed. Decreased ReHo values were found in default mode network, bilateral motor-related areas and left occipital gyrus of the patient group. Increased ReHo was found in regions of cingulum, cerebellum, supplementary motor area and brain deep nucleus, such as hippocampus, caudate, thalamus and insula. The significant differences might indicate that epileptic action have some injurious effects on the motor, executive and cognitive related regions. In addition, ReHo values of left precuneus and right superior frontal gyrus were associated with the epilepsy duration in the IS group. The correlation results indicate that the involvement of these regions may be related to the seizure generation. Our results suggest that IS may have an injurious effect on the brain activation. The findings may shed new light on the understanding the neural mechanism of IS epilepsy.