Impaired default mode network on resting-state FMRI in children with medically refractory epilepsy

Altered static and dynamic functional connectivity of the default mode network across epilepsy subtypes in children: A resting-state fMRI study

BACKGROUND

Epilepsy is a chronic neurologic disorder characterized by abnormal functioning of brain networks, making it a complex research topic. Recent advancements in neuroimaging technology offer an effective approach to unraveling the intricacies of the human brain. Within different types of epilepsy, there is growing recognition regarding ongoing changes in the default mode network (DMN). However, little is known about the shared and distinct alterations of static functional connectivity (sFC) and dynamic functional connectivity (dFC) in DMN among epileptic subtypes, especially in children with epilepsy.

METHODS

Here, 110 children with epilepsy at a single center, including idiopathic generalized epilepsy (IGE), frontal lobe epilepsy (FLE), temporal lobe epilepsy (TLE), and parietal lobe epilepsy (PLE), as well as 84 healthy controls (HC) underwent resting-state functional magnetic resonance imaging (fMRI) scan. We investigated both sFC and dFC between groups of the DMN.

RESULTS

Decreased static and dynamic connectivity within the DMN subsystem were shared by all subtypes. In each epilepsy subtype, children with epilepsy displayed significant and distinct patterns of DMN connectivity compared to the control group: the IGE group showed reduced interhemispheric connectivity, the FLE group consistently demonstrated disturbances in frontal region connectivity, the TLE group exhibited significant disruptions in hippocampal connectivity, and the PLE group displayed a notable decrease in parietal-temporal connectivity within the DMN. Some state-specific FC disruptions (decreased dFC) were observed in each epilepsy subtype that cannot detect by sFC. To determine their uniqueness within specific subtypes, bootstrapping methods were employed and found the significant results (IGE: between PCC and bilateral precuneus, FLE: between right middle frontal gyrus and bilateral middle temporal gyrus, TLE: between left Hippocampus and right fusiform, PLE: between left angular and cingulate cortex). Furthermore, only children with IGE exhibited dynamic features associated with clinical variables.

CONCLUSIONS

Our findings highlight both shared and distinct FC alterations within the DMN in children with different types of epilepsy. Furthermore, our work provides a novel perspective on the functional alterations in the DMN of pediatric patients, suggesting that combined sFC and dFC analysis can provide valuable insights for deepening our understanding of the neuronal mechanism underlying epilepsy in children.

Functional brain connectivity in young adults with post-stroke epilepsy

Approximately 1 in 10 young stroke patients (18-50 years) will develop post-stroke epilepsy, which is associated with cognitive impairment. While previous studies have shown altered brain connectivity in patients with epilepsy, little is however known about the changes in functional brain connectivity in young stroke patients with post-stroke epilepsy and their relationship with cognitive impairment. Therefore, we aimed to investigate whether young ischaemic stroke patients have altered functional networks and whether this alteration is related to cognitive impairment. We included 164 participants with a first-ever cerebral infarction at young age (18-50 years), along with 77 age- and sex-matched controls, from the Follow-Up of Transient Ischemic Attack and Stroke patients and Unelucidated Risk Factor Evaluation study. All participants underwent neuropsychological testing and resting-state functional MRI to generate functional connectivity networks. At follow-up (10.5 years after the index event), 23 participants developed post-stroke epilepsy. Graph theoretical analysis revealed functional network reorganization in participants with post-stroke epilepsy, in whom a weaker (i.e. network strength), less-integrated (i.e. global efficiency) and less-segregated (i.e. clustering coefficient and local efficiency) functional network was observed compared with the participants without post-stroke epilepsy group and the controls (P < 0.05). Regional analysis showed a trend towards decreased clustering coefficient, local efficiency and nodal efficiency in contralesional brain regions, including the caudal anterior cingulate cortex, posterior cingulate cortex, precuneus, superior frontal gyrus and insula in participants with post-stroke epilepsy compared with those without post-stroke epilepsy. Furthermore, participants with post-stroke epilepsy more often had impairment in the processing speed domain than the group without post-stroke epilepsy, in whom the network properties of the precuneus were positively associated with processing speed performance. Our findings suggest that post-stroke epilepsy is associated with functional reorganization of the brain network after stroke that is characterized by a weaker, less-integrated and less-segregated brain network in young ischaemic stroke patients compared with patients without post-stroke epilepsy. The contralesional brain regions, which are mostly considered as hub regions, might be particularly involved in the altered functional network and may contribute to cognitive impairment in post-stroke epilepsy patients. Overall, our findings provide additional evidence for a potential role of disrupted functional network as underlying pathophysiological mechanism for cognitive impairment in patients with post-stroke epilepsy.

Functional and effective connectivity analysis of drug-resistant epilepsy: a resting-state fMRI analysis

Objective

Epilepsy is considered as a neural network disorder. Seizure activity in epilepsy may disturb brain networks and damage brain functions. We propose using resting-state functional magnetic resonance imaging (rs-fMRI) data to characterize connectivity patterns in drug-resistant epilepsy.

Methods

This study enrolled 47 participants, including 28 with drug-resistant epilepsy and 19 healthy controls. Functional and effective connectivity was employed to assess drug-resistant epilepsy patients within resting state networks. The resting state functional connectivity (FC) analysis was performed to assess connectivity between each patient and healthy controls within the default mode network (DMN) and the dorsal attention network (DAN). In addition, dynamic causal modeling was used to compute effective connectivity (EC). Finally, a statistical analysis was performed to evaluate our findings.

Results

The FC analysis revealed significant connectivity changes in patients giving 64.3% (18/28) and 78.6% (22/28) for DMN and DAN, respectively. Statistical analysis of FC was significant between the medial prefrontal cortex, posterior cingulate cortex, and bilateral inferior parietal cortex for DMN. For DAN, it was significant between the left and the right intraparietal sulcus and the frontal eye field. For the DMN, the patient group showed significant EC connectivity in the right inferior parietal cortex and the medial prefrontal cortex for the DMN. There was also bilateral connectivity between the medial prefrontal cortex and the posterior cingulate cortex, as well as between the left and right inferior parietal cortex. For DAN, patients showed significant connectivity in the right frontal eye field and the right intraparietal sulcus. Bilateral connectivity was also found between the left frontal eye field and the left intraparietal sulcus, as well as between the right frontal eye field and the right intraparietal sulcus. The statistical analysis of the EC revealed a significant result in the medial prefrontal cortex and the right intraparietal cortex for the DMN. The DAN was found significant in the left frontal eye field, as well as the left and right intraparietal sulcus.

Conclusion

Our results provide preliminary evidence to support that the combination of functional and effective connectivity analysis of rs-fMRI can aid in diagnosing epilepsy in the DMN and DAN networks.

Functional patterns of neural activation during vocal emotion recognition in youth with and without refractory epilepsy

Epilepsy has been associated with deficits in the social cognitive ability to decode others' nonverbal cues to infer their emotional intent (emotion recognition). Studies have begun to identify potential neural correlates of these deficits, but have focused primarily on one type of nonverbal cue (facial expressions) to the detriment of other crucial social signals that inform the tenor of social interactions (e.g., tone of voice). Less is known about how individuals with epilepsy process these forms of social stimuli, with a particular gap in knowledge about representation of vocal cues in the developing brain. The current study compared vocal emotion recognition skills and functional patterns of neural activation to emotional voices in youth with and without refractory focal epilepsy. We made novel use of inter-subject pattern analysis to determine brain areas in which activation to emotional voices was predictive of epilepsy status. Results indicated that youth with epilepsy were comparatively less able to infer emotional intent in vocal expressions than their typically developing peers. Activation to vocal emotional expressions in regions of the mentalizing and/or default mode network (e.g., right temporo-parietal junction, right hippocampus, right medial prefrontal cortex, among others) differentiated youth with and without epilepsy. These results are consistent with emerging evidence that pediatric epilepsy is associated with altered function in neural networks subserving social cognitive abilities. Our results contribute to ongoing efforts to understand the neural markers of social cognitive deficits in pediatric epilepsy, in order to better tailor and funnel interventions to this group of youth at risk for poor social outcomes.

Social brain networks: Resting-state and task-based connectivity in youth with and without epilepsy

Individuals with epilepsy often experience social difficulties and deficits in social cognition. It remains unknown how disruptions to neural networks underlying such skills may contribute to this clinical phenotype. The current study compared the organization of relevant brain circuits-the "mentalizing network" and a salience-related network centered on the amygdala-in youth with and without epilepsy. Functional connectivity between the nodes of these networks was assessed, both at rest and during engagement in a social cognitive task (facial emotion recognition), using functional magnetic resonance imaging. There were no group differences in resting-state connectivity within either neural network. In contrast, youth with epilepsy showed comparatively lower connectivity between the left posterior superior temporal sulcus and the medial prefrontal cortex-but greater connectivity within the left temporal lobe-when viewing faces in the task. These findings suggest that the organization of a mentalizing network underpinning social cognition may be disrupted in youth with epilepsy, though differences in connectivity within this circuit may shift depending on task demands. Our results highlight the importance of considering functional task-based engagement of neural systems in characterizations of network dysfunction in epilepsy.

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

Background:

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

Objective:

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

Methods:

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

Results:

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

Neural functional connectivity in patients with periventricular nodular heterotopia-mediated epilepsy

Periventricular nodular heterotopia (PNH) is characterized by disabled neural migration and is usually associated with epilepsy. Despite awareness of PNH-related epilepsy, little is known about the brain-level underlying functional neural bases. Thus, we used functional magnetic resonance imaging (MRI) to examine the neurobiology of 42 subjects with PNH-related epilepsy and 42 sex- and age-matched healthy controls. Measurements of functional connectivity (FC) and whole-brain graph theory analysis of data in the resting state were performed to assess neurological organization and topology. PNH patients exhibited significantly higher FC in the parietal lobe, cingulum and thalamus, as well as significantly lower FC in frontoparietal, hippocampal, and precentral regions. Graph theory analysis identified no significant differences between patients and controls, while patients showed lower network global efficiency in the limbic and cerebellum network and occipital cortex. Seed-based FC analysis confirmed disruption of activities and interregional connectivity in remote epileptic networks of patients, which may point to underlying pathological mechanisms. The cerebellum and limbic system of patients showed altered topology, suggesting that these regions or hubs may contribute to whole-brain circuits in PNH and epilepsy.

Intrinsic brain activity changes in temporal lobe epilepsy patients revealed by regional homogeneity analysis

PURPOSE

Temporal lobe epilepsy is increasingly being recognized as a disorder associated with brain networks extending outside the seizure onset zone. In the current study, we aim to clarify regional functional changes using a regional homogeneity method.

METHODS

We retrospectively included resting-state fMRI data from 14 left and 18 right temporal lobe epilepsy patients. Data from the control group were acquired from an open dataset. Regional homogeneity was calculated, and a two-sample t-test was performed to compare the left and right temporal lobe epilepsy groups with the control group.

RESULTS

Compared with the healthy control group, the left temporal lobe epilepsy group showed increased regional homogeneity in the left anterior and middle cingulate cortex, and putamen; right inferior frontal gyrus; bilateral temporal lobe and precentral gyrus and decreased regional homogeneity in the left superior parietal gyrus, cuneus and inferior occipital gyrus; right inferior parietal lobule and bilateral rectus. The right temporal lobe epilepsy group showed increased regional homogeneity in the left middle cingulate cortex, precuneus, precentral and postcentral gyrus; right insula and bilateral temporal lobe and decreased regional homogeneity in the left cuneus and superior occipital gyrus; right supramarginal gyrus, fusiform gyrus, lingual gyrus, inferior occipital gyrus and putamen; and the bilateral rectus.

CONCLUSION

Regional homogeneity measurements provide evidence supporting that temporal lobe epilepsy is a complex network disease. Functional disruption of temporal lobe epilepsy at the brain region level was revealed, which may provide novel insights for any potential diagnostic and therapeutic approaches.

Investigation of functional variability and connectivity in temporal lobe epilepsy: A resting state fMRI study

It is crucial to reveal the variability between patients with epilepsy and healthy subjects to elucidate the underpinnings of the disease pathology. Herein, we assessed the inter-subject variability between patients with temporal lobe epilepsy (TLE) and healthy subjects in terms of estimating the functional connectivity using resting-state functional magnetic resonance (rs-fMRI) scans. According to inter-subject variability results between healthy and TLE population, the latter showed more variability mainly in frontoparietal control, default mode, dorsal/ventral attention, visual and somatomotor networks in line with the broad seizure onset and propagation pathway. As a result of 17-Network parcellation, a significant attenuation is observed in functional connectivity, mostly in bilateral frontoparietal control, somatomotor, default mode and ventral attention networks associated with the functional impairment in attention, long/short term memory, executive functioning. The results are in favor of the argument that the functional disruption in TLE spreads throughout the cortex beyond the temporal lobe with an implication of greater diversity in the TLE population.

Altered attention networks and DMN in refractory epilepsy: A resting-state functional and causal connectivity study

PURPOSE

Epilepsy is considered a disorder of neural networks. Patients diagnosed with refractory epilepsy frequently experience attention impairments. Seizure activity in epilepsy may disturb brain networks and damage the brain function of attention. The aims of this study were to assess functional and causal connectivities of the attention networks and default mode network using resting-state functional magnetic resonance imaging (fMRI).

METHOD

Resting-state fMRI data were gathered from 19 patients with refractory epilepsy (mixed localization and aetiologies) and 21 healthy people. The fMRI data were analyzed by group independent component analysis (ICA) fMRI toolbox to extract dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN). The components of the selected networks were compared between patients and healthy controls to explore the change in functional connectivity (FC). Granger causality analysis was performed by taking the aforementioned significant brain areas as regions of interest (ROIs) to calculate autoregression coefficients of each pair of ROIs. Comparisons were done to find the significantly different causal connectivity when FC was changed between patients and healthy controls.

RESULTS

In DAN, the FC values of the bilateral frontal eye field (FEF) and left intraparietal sulcus (IPS) were decreased. In VAN, the FC values of the double-side ventral prefrontal cortex (vPFC) and the temporoparietal junction (TPJ) were reduced. As for DMN, the FC values of the bilateral medial prefrontal cortices (mPFC) were decreased whereas those for the bilateral precuneus (PCUN) were increased. Granger causal connectivity values were correlated: causal influence was decreased significantly from the left IPS (in DAN) to the double side of the vPFC but remained the same for the right FEF (in DAN) to the right TPJ. The value was decreased from the left PCUN (in DMN) to the right TPJ and FEF, and the causal flow from the right PCUN to the right TPJ and bilateral vPFC was also significantly inhibited (p < 0.05).

CONCLUSION

Frequent seizures in patients with refractory epilepsy may damage the cortex and disturb DAN, VAN, and DMN, leading to functional and causal connectivity alteration. In addition, epileptic activity may disrupt network interactions and further influence information communication.

Executive dysfunction is associated with an altered executive control network in pediatric temporal lobe epilepsy

OBJECTIVES

Children with temporal lobe epilepsy (TLE) exhibit executive dysfunction on traditional neuropsychological tests. However, there is limited evidence of neural network alterations associated with this clinical executive dysfunction. The objective of this study was to characterize working memory deficits in children with TLE via activation of the executive control network on functional magnetic resonance imaging (fMRI) and determine the relationships to fMRI behavioral findings and traditional neuropsychological tests.

EXPERIMENTAL DESIGN

Functional magnetic resonance imaging was conducted on 17 children with TLE and 18 healthy control participants (age 8-16 years) while they performed the N-back task in order to assess activation of the executive control network. N-back accuracy, N-back reaction time, and traditional neuropsychological tests (Delis-Kaplan Executive Function System [D-KEFS] color-word interference and card-sort test) were also assessed.

PRINCIPAL OBSERVATIONS

Children with TLE exhibited executive dysfunction on D-KEFS testing, reduced N-back accuracy, and increased N-back reaction time compared with healthy controls; D-KEFS and N-back behavioral findings were significantly correlated. Children with TLE also exhibited significant reduction in activation of the frontal lobe within the executive control network compared to healthy controls. These alterations were significantly correlated with N-back behavioral findings and D-KEFS testing.

CONCLUSIONS

Children with TLE exhibit executive dysfunction, which correlates with executive control network alterations. This lends validity to the theory that the executive control network contributes to working memory function. The findings also indicate that children with TLE have network alterations in nontemporal brain regions.

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.

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.

Presurgical thalamocortical connectivity is associated with response to vagus nerve stimulation in children with intractable epilepsy

Although chronic vagus nerve stimulation (VNS) is an established treatment for medically-intractable childhood epilepsy, there is considerable heterogeneity in seizure response and little data are available to pre-operatively identify patients who may benefit from treatment. Since the therapeutic effect of VNS may be mediated by afferent projections to the thalamus, we tested the hypothesis that intrinsic thalamocortical connectivity is associated with seizure response following chronic VNS in children with epilepsy. Twenty-one children (ages 5-21 years) with medically-intractable epilepsy underwent resting-state fMRI prior to implantation of VNS. Ten received sedation, while 11 did not. Whole brain connectivity to thalamic regions of interest was performed. Multivariate generalized linear models were used to correlate resting-state data with seizure outcomes, while adjusting for age and sedation status. A supervised support vector machine (SVM) algorithm was used to classify response to chronic VNS on the basis of intrinsic connectivity. Of the 21 subjects, 11 (52%) had 50% or greater improvement in seizure control after VNS. Enhanced connectivity of the thalami to the anterior cingulate cortex (ACC) and left insula was associated with greater VNS efficacy. Within our test cohort, SVM correctly classified response to chronic VNS with 86% accuracy. In an external cohort of 8 children, the predictive model correctly classified the seizure response with 88% accuracy. We find that enhanced intrinsic connectivity within thalamocortical circuitry is associated with seizure response following VNS. These results encourage the study of intrinsic connectivity to inform neural network-based, personalized treatment decisions for children with intractable epilepsy.

Altered DMN functional connectivity and regional homogeneity in partial epilepsy patients: a seventy cases study

Purpose

Clinically diagnosed partial epilepsy is hard to be functionally diagnosed by regular electroencephalograph (EEG) and conventional magnetic resonance imaging (MRI). By collecting transient brain regional signals, blood oxygenation level-dependent (BOLD) function MRI (BOLD-fMRI) can provide brain function change information with high accuracy. By using resting state BOLD-fMRI technique, we aim to investigate the changes of brain function in partial epilepsy patients.

Methods

BOLD-fMRI scanning was performed in 70 partial epilepsy and 70 healthy people. BOLD-fMRI data was analyzed by using the Regional Homogeneity (ReHo) method and functional connectivity of Default Mode Network (DMN) methods. The abnormal brain functional connectivity in partial epilepsy patients was detected by Statistical Parametric Mapping 8 (SPM8) analysis.

Results

Compared to healthy group, epilepsy patients showed significant decreased ReHo in left inferior parietal lobule/pre- and post-central gyrus, right thalamus/paracentral lobule/Cerebellum anterior and posterior Lobe, bilateral insula. The DMN functional connectivity regions decreased significantly in right uncus, left Inferior parietal lobule, left supramarginal gyrus, left uncus, left parahippocampa gyrus, and left superior temporal gyrus, in epilepsy patients, compared to healthy controls.

Significance

This study clarified that both ReHo and functional connectivity of DMN decreased in partial epilepsy patients compared to healthy controls. While left inferior parietal lobule was detected in both ReHo and DMN, many other identified regions were different by using these two BOLD-fMRI techniques. We propose that both ReHo and DMN patterns in BOLD-fMRI may suggest networks responsible for partial epilepsy genesis or progression.

Altered Default Mode Network on Resting-State fMRI in Children with Infantile Spasms

Infantile spasms (IS) syndrome is an age-dependent epileptic encephalopathy, which occurs in children characterized by spasms, impaired consciousness, and hypsarrhythmia. Abnormalities in default mode network (DMN) might contribute to the loss of consciousness during seizures and cognitive deficits in children with IS. The purpose of the present study was to investigate the changes in DMN with functional connectivity (FC) and amplitude of low-frequency fluctuation (ALFF), the two methods to discover the potential neuronal underpinnings of IS. The consistency of the two calculate methods of DMN abnormalities in IS patients was also our main focus. To avoid the disturbance of interictal epileptic discharge, our testing was performed within the interictal durations without epileptic discharges. Resting-state fMRI data were collected from 13 patients with IS and 35 sex- and age-matched healthy controls. FC analysis with seed in posterior cingulate cortex (PCC) was used to compare the differences between two groups. We chose PCC as the seed region because PCC is the only node in the DMN that directly interacts with virtually all other nodes according to previous studies. Furthermore, the ALFF values within the DMN were also calculated and compared between the two groups. The FC results showed that IS patients exhibited markedly reduced connectivity between posterior seed region and other areas within DMN. In addition, part of the brain areas within the DMN showing significant difference of FC had significantly lower ALFF signal in the patient group than that in the healthy controls. The observed disruption in DMN through the two methods showed that the coherence of brain signal fluctuation in DMN during rest was broken in IS children. Neuronal functional impairment or altered integration in DMN would be one neuroimaging characteristic, which might help us to understand the underlying neural mechanism of IS. Further studies are needed to determine whether the disturbed FC and ALFF observed in the DMN are related to cognitive performance in IS patients.

Photosensitivity in generalized epilepsies

Photosensitivity, which is the hallmark of photosensitive epilepsy (PSE), is described as an abnormal EEG response to visual stimuli known as a photoparoxysmal response (PPR). The PPR is a well-recognized phenomenon, occurring in 2-14% of patients with epilepsy but its pathophysiology is not clearly understood. PPR is electrographically described as 2-5Hz spike, spike-wave, or slow wave complexes with frontal and paracentral prevalence. Diagnosis of PPR is confirmed using intermittent photic stimulation (IPS) as well as video monitoring. The PPR can be elicited by certain types of visual stimuli including flicker, high contrast gratings, moving patterns, and rapidly modulating luminance patterns which may be encountered during e.g., watching television, playing video games, or attending discotheques. Photosensitivity may present in different idiopathic (genetic) epilepsy syndromes e.g. juvenile myoclonic epilepsy (JME) as well as non-IGE syndromes e.g. severe myoclonic epilepsy of infancy. Consequently, PPR is present in patients with diverse seizure types including absence, myoclonic, and generalized tonic-clonic (GTC) seizures. Across syndromes, abnormalities in structural connectivity, functional connectivity, cortical excitability, cortical morphology, and behavioral and neuropsychological function have been reported. Treatment of photosensitivity includes antiepileptic drug administration, and the use of non-pharmacological agents, e.g. tinted or polarizing glasses, as well as occupational measures, e.g. avoidance of certain stimuli.

Seizure Frequency Can Alter Brain Connectivity: Evidence from Resting-State fMRI

BACKGROUND AND PURPOSE

The frequency of seizures is an important factor that can alter functional brain connectivity. Analysis of this factor in patients with epilepsy is complex because of disease- and medication-induced confounders. Because patients with hot-water epilepsy generally are not on long-term drug therapy, we used seed-based connectivity analysis in these patients to assess connectivity changes associated with seizure frequency without confounding from antiepileptic drugs.

MATERIALS AND METHODS

Resting-state fMRI data from 36 patients with hot-water epilepsy (18 with frequent seizures [>2 per month] and 18 with infrequent seizures [≤2 per month]) and 18 healthy age- and sex-matched controls were analyzed for seed-to-voxel connectivity by using 106 seeds. Voxel wise paired t-test analysis (P < .005, corrected for false-discovery rate) was used to identify significant intergroup differences between these groups.

RESULTS

Connectivity analysis revealed significant differences between the 2 groups (P < .001). Patients in the frequent-seizure group had increased connectivity within the medial temporal structures and widespread areas of poor connectivity, even involving the default mode network, in comparison with those in the infrequent-seizure group. Patients in the infrequent-seizure group had focal abnormalities with increased default mode network connectivity and decreased left entorhinal cortex connectivity.

CONCLUSIONS

The results of this study suggest that seizure frequency can alter functional brain connectivity, which can be visualized by using resting-state fMRI. Imaging features such as diffuse network abnormalities, involvement of the default mode network, and recruitment of medial temporal lobe structures were seen only in patients with frequent seizures. Future studies in more common epilepsy groups, however, will be required to further establish this finding.

Disrupted Global and Regional Structural Networks and Subnetworks in Children with Localization-Related Epilepsy

BACKGROUND AND PURPOSE

Structural connectivity has been thought to be a less sensitive measure of network changes relative to functional connectivity in children with localization-related epilepsy. The aims of this study were to investigate the structural networks in children with localization-related epilepsy and to assess the relation among structural connectivity, intelligence quotient, and clinical parameters.

MATERIALS AND METHODS

Forty-five children with nonlesional localization-related epilepsy and 28 healthy controls underwent DTI. Global network (network strength, clustering coefficient, characteristic path length, global efficiency, and small-world parameters), regional network (nodal efficiency), and the network-based statistic were compared between patients and controls and correlated with intelligence quotient and clinical parameters.

RESULTS

Patients showed disrupted global network connectivity relative to controls, including reduced network strength, increased characteristic path length and reduced global efficiency, and reduced nodal efficiency in the frontal, temporal, and occipital lobes. Connectivity in multiple subnetworks was reduced in patients, including the frontal-temporal, insula-temporal, temporal-temporal, frontal-occipital, and temporal-occipital lobes. The frontal lobe epilepsy subgroup demonstrated more areas with reduced nodal efficiency and more impaired subnetworks than the temporal lobe epilepsy subgroup. Network parameters were not significantly associated with intelligence quotient, age at seizure onset, or duration of epilepsy.

CONCLUSIONS

We found disruption in global and regional networks and subnetworks in children with localization-related epilepsy. Regional efficiency and subnetworks were more impaired in frontal lobe epilepsy than in temporal lobe epilepsy. Future studies are needed to evaluate the implications of disrupted networks for surgical resection and outcomes for specific epileptogenic zones and the relation of disrupted networks to more complex cognitive function.

Pathological uncoupling between amplitude and connectivity of brain fluctuations in epilepsy

Amplitude and functional connectivity are two fundamental parameters for describing the spontaneous brain fluctuations. These two parameters present close coupling in physiological state, and present different alteration patterns in epilepsy revealed by functional MRI (fMRI). We hypothesized that the alteration of coupling between these two imaging parameters may be underpinned by specific pathological factors of epilepsy, and can be employed to improve the capability for epileptic focus detection. Forty-seven patients (26 left- and 21 right-sided) with mesial temporal lobe epilepsy (mTLE) and 32 healthy controls underwent resting-state fMRI scans. All patients were detected to have interictal epileptic discharges on simultaneous electroencephalograph (EEG) recordings. Amplitude-connectivity coupling was calculated by correlating amplitude and functional connectivity density of low-frequency brain fluctuations. We observed reduced amplitude-connectivity coupling associated with epileptic discharges in the mesial temporal regions in both groups of patients, and increased coupling associated with epilepsy durations in the posterior regions of the default-mode network in the right-sided patients. Moreover, we proposed a new index of amplitude subtracting connectivity, which elevated imaging contrast for differentiating the patients from the controls. The findings indicated that epileptic discharges and chronic damaging effect of epilepsy might both contribute to alterations of amplitude-connectivity coupling in different pivotal regions in mTLE. Investigation on imaging coupling provides synergistic approach for describing brain functional changing features in epilepsy.

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

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

Resilience of developing brain networks to interictal epileptiform discharges is associated with cognitive outcome

The effects of interictal epileptiform discharges on neurocognitive development in children with medically-intractable epilepsy are poorly understood. Such discharges may have a deleterious effect on the brain's intrinsic connectivity networks, which reflect the organization of functional networks at rest, and in turn on neurocognitive development. Using a combined functional magnetic resonance imaging-magnetoencephalography approach, we examine the effects of interictal epileptiform discharges on intrinsic connectivity networks and neurocognitive outcome. Functional magnetic resonance imaging was used to determine the location of regions comprising various intrinsic connectivity networks in 26 children (7-17 years), and magnetoencephalography data were reconstructed from these locations. Inter-regional phase synchronization was then calculated across interictal epileptiform discharges and graph theoretical analysis was applied to measure event-related changes in network topology in the peri-discharge period. The magnitude of change in network topology (network resilience/vulnerability) to interictal epileptiform discharges was associated with neurocognitive outcomes and functional magnetic resonance imaging networks using dual regression. Three main findings are reported: (i) large-scale network changes precede and follow interictal epileptiform discharges; (ii) the resilience of network topologies to interictal discharges is associated with stronger resting-state network connectivity; and (iii) vulnerability to interictal discharges is associated with worse neurocognitive outcomes. By combining the spatial resolution of functional magnetic resonance imaging with the temporal resolution of magnetoencephalography, we describe the effects of interictal epileptiform discharges on neurophysiological synchrony in intrinsic connectivity networks and establish the impact of interictal disruption of functional networks on cognitive outcome in children with epilepsy. The association between interictal discharges, network changes and neurocognitive outcomes suggests that it is of clinical importance to suppress discharges to foster more typical brain network development in children with focal epilepsy.

Network Connectivity in Epilepsy: Resting State fMRI and EEG-fMRI Contributions

There is a growing body of evidence pointing toward large-scale networks underlying the core phenomena in epilepsy, from seizure generation to cognitive dysfunction or response to treatment. The investigation of networks in epilepsy has become a key concept to unlock a deeper understanding of the disease. Functional imaging can provide valuable information to characterize network dysfunction; in particular resting state fMRI (RS-fMRI), which is increasingly being applied to study brain networks in a number of diseases. In patients with epilepsy, network connectivity derived from RS-fMRI has found connectivity abnormalities in a number of networks; these include the epileptogenic, cognitive and sensory processing networks. However, in majority of these studies, the effect of epileptic transients in the connectivity of networks has been neglected. EEG–fMRI has frequently shown networks related to epileptic transients that in many cases are concordant with the abnormalities shown in RS studies. This points toward a relevant role of epileptic transients in the network abnormalities detected in RS-fMRI studies. In this review, we summarize the network abnormalities reported by these two techniques side by side, provide evidence of their overlapping findings, and discuss their significance in the context of the methodology of each technique. A number of clinically relevant factors that have been associated with connectivity changes are in turn associated with changes in the frequency of epileptic transients. These factors include different aspects of epilepsy ranging from treatment effects, cognitive processes, or transition between different alertness states (i.e., awake–sleep transition). For RS-fMRI to become a more effective tool to investigate clinically relevant aspects of epilepsy it is necessary to understand connectivity changes associated with epileptic transients, those associated with other clinically relevant factors and the interaction between them, which represents a gap in the current literature. We propose a framework for the investigation of network connectivity in patients with epilepsy that can integrate epileptic processes that occur across different time scales such as epileptic transients and disease duration and the implications of this approach are discussed.

Neuroimaging of epilepsy: a review of MRI findings in uncommon etiologies and atypical presentations of seizures

ABSTRACT: 

Imaging patients with seizures presents a challenge to both clinician and radiologist, especially when symptoms or EEG features are atypical, not conforming to established epilepsy syndromes or EEG patterns. Appropriate, directed use of MRI enhances the detection of underlying epileptogenic foci and can evaluate both common and unusual etiologies. This review examines imaging evaluation of epilepsies due to uncommon presentations of common conditions, unusual conditions and atypical seizure presentations. Understanding these uncommon presentations of seizures ensures optimal clinical management and can guide appropriate intervention. Advances in newer imaging methods including diffusion tensor imaging, functional connectivity MRI, magnetic source imaging and magnetic resonance spectroscopic imaging can further increase sensitivity to detect subtle structural abnormalities causing epilepsy and can also be used to plan more successful epilepsy surgery.

Impaired development of intrinsic connectivity networks in children with medically intractable localization-related epilepsy

Typical childhood development is characterized by the emergence of intrinsic connectivity networks (ICNs) by way of internetwork segregation and intranetwork integration. The impact of childhood epilepsy on the maturation of ICNs is, however, poorly understood. The developmental trajectory of ICNs in 26 children (8-17 years) with localization-related epilepsy and 28 propensity-score matched controls was evaluated using graph theoretical analysis of whole brain connectomes from resting-state functional magnetic resonance imaging (fMRI) data. Children with epilepsy demonstrated impaired development of regional hubs in nodes of the salience and default mode networks (DMN). Seed-based connectivity and hierarchical clustering analysis revealed significantly decreased intranetwork connections, and greater internetwork connectivity in children with epilepsy compared to controls. Significant interactions were identified between epilepsy duration and the expected developmental trajectory of ICNs, indicating that prolonged epilepsy may cause progressive alternations in large-scale networks throughout childhood. DMN integration was also associated with better working memory, whereas internetwork segregation was associated with higher full-scale intelligence quotient scores. Furthermore, subgroup analyses revealed the thalamus, hippocampus, and caudate were weaker hubs in children with secondarily generalized seizures, relative to other patient subgroups. Our findings underscore that epilepsy interferes with the developmental trajectory of brain networks underlying cognition, providing evidence supporting the early treatment of affected children.

Generation of the probabilistic template of default mode network derived from resting-state fMRI

Default-mode network (DMN) has become a prominent network among all large-scale brain networks which can be derived from the resting-state fMRI (rs-fMRI) data. Statistical template labeling the common location of hubs in DMN is favorable in the identification of DMN from tens of components resulted from the independent component analysis (ICA). This paper proposed a novel iterative framework to generate a probabilistic DMN template from a coherent group of 40 healthy subjects. An initial template was visually selected from the independent components derived from group ICA analysis of the concatenated rs-fMRI data of all subjects. An effective similarity measure was designed to choose the best-fit component from all independent components of each subject computed given different component numbers. The selected DMN components for all subjects were averaged to generate an updated DMN template and then used to select the DMN for each subject in the next iteration. This process iterated until the convergence was reached, i.e., the overlapping region between the DMN areas of the current template and the one generated from the previous stage is more than 95%. By validating the constructed DMN template on the rs-fMRI data from another 40 subjects, the generated probabilistic DMN template and the proposed similarity matching mechanism were demonstrated to be effective in automatic selection of independent components from the ICA analysis results.

Potential use and challenges of functional connectivity mapping in intractable epilepsy

This review focuses on the use of resting-state functional magnetic resonance imaging data to assess functional connectivity in the human brain and its application in intractable epilepsy. This approach has the potential to predict outcomes for a given surgical procedure based on the pre-surgical functional organization of the brain. Functional connectivity can also identify cortical regions that are organized differently in epilepsy patients either as a direct function of the disease or through indirect compensatory responses. Functional connectivity mapping may help identify epileptogenic tissue, whether this is a single focal location or a network of seizure-generating tissues. This review covers the basics of connectivity analysis and discusses particular issues associated with analyzing such data. These issues include how to define nodes, as well as differences between connectivity analyses of individual nodes, groups of nodes, and whole-brain assessment at the voxel level. The need for arbitrary thresholds in some connectivity analyses is discussed and a solution to this problem is reviewed. Overall, functional connectivity analysis is becoming an important tool for assessing functional brain organization in epilepsy.

Resting-state functional MRI in pediatric epilepsy surgery

Resting-state functional MRI (rs-fMRI) identifies resting-state networks (RSN) in the human brain by analyzing the connectivity of anatomically remote neuronal populations with synchronous low-frequency fluctuation in blood oxygen level-dependent (BOLD) signal. Network analysis has informed the understanding of functional brain organization and is beginning to reveal the impact that neurological disorders such as epilepsy may have on the developing cerebral cortex. Among children undergoing epilepsy surgery, mapping the brain networks supporting language, sensorimotor and visual function is a critical part of the preoperative evaluation. However, task-based functional mapping techniques are particularly difficult in immature patients and those with severe impairment. Functional mapping of RSN is a promising tool that may help circumvent the challenges of adequate cooperation and limited abilities of developmentally disabled children to perform age-appropriate functions. We discuss the current methodology of rs-fMRI in the pediatric population, review the literature of rs-fMRI in pediatric epilepsy and present our experience of using rs-fMRI for functional network mapping in children undergoing epilepsy surgery.