Neuronal networks in west syndrome as revealed by source analysis and renormalized partial directed coherence

Identification and treatment of surgically-remediable causes of infantile epileptic spasms syndrome

INTRODUCTION

Infantile epileptic spasms syndrome (IESS) is a common developmental and epileptic encephalopathy with poor long-term outcomes. A substantial proportion of patients with IESS have a potentially surgically remediable etiology. Despite this, epilepsy surgery is underutilized in this patient group. Some surgically remediable etiologies, such as focal cortical dysplasia and malformation of cortical development with oligodendroglial hyperplasia in epilepsy (MOGHE), are under-diagnosed in infants and young children. Even when a surgically remediable etiology is recognised, for example, tuberous sclerosis or focal encephalomalacia, epilepsy surgery may be delayed or not considered due to diffuse EEG changes, unclear surgical boundaries, or concerns about operating in this age group.

AREAS COVERED

In this review, the authors discuss the common surgically remediable etiologies of IESS, their clinical and EEG features, and the imaging techniques that can aid in their diagnosis. They then describe the surgical approaches used in this patient group, and the beneficial impact that early epilepsy surgery can have on developing brain networks.

EXPERT OPINION

Epilepsy surgery remains underutilized even when a potentially surgically remediable cause is recognized. Overcoming the barriers that result in under-recognition of surgical candidates and underutilization of epilepsy surgery in IESS will improve long-term seizure and developmental outcomes.

Electroencephalogram synchronization measure as a predictive biomarker of Vagus nerve stimulation response in refractory epilepsy: A retrospective study

There are currently no established biomarkers for predicting the therapeutic effectiveness of Vagus Nerve Stimulation (VNS). Given that neural desynchronization is a pivotal mechanism underlying VNS action, EEG synchronization measures could potentially serve as predictive biomarkers of VNS response. Notably, an increased brain synchronization in delta band has been observed during sleep-potentially due to an activation of thalamocortical circuitry, and interictal epileptiform discharges are more frequently observed during sleep. Therefore, investigation of EEG synchronization metrics during sleep could provide a valuable insight into the excitatory-inhibitory balance in a pro-epileptogenic state, that could be pathological in patients exhibiting a poor response to VNS. A 19-channel-standard EEG system was used to collect data from 38 individuals with Drug-Resistant Epilepsy (DRE) who were candidates for VNS implantation. An EEG synchronization metric-the Weighted Phase Lag Index (wPLI)-was extracted before VNS implantation and compared between sleep and wakefulness, and between responders (R) and non-responders (NR). In the delta band, a higher wPLI was found during wakefulness compared to sleep in NR only. However, in this band, no synchronization difference in any state was found between R and NR. During sleep and within the alpha band, a negative correlation was found between wPLI and the percentage of seizure reduction after VNS implantation. Overall, our results suggest that patients exhibiting a poor VNS efficacy may present a more pathological thalamocortical circuitry before VNS implantation. EEG synchronization measures could provide interesting insights into the prerequisites for responding to VNS, in order to avoid unnecessary implantations in patients showing a poor therapeutic efficacy.

Interictal EEG features as computational biomarkers of West syndrome

Background

West syndrome (WS) is a devastating epileptic encephalopathy with onset in infancy and early childhood. It is characterized by clustered epileptic spasms, developmental arrest, and interictal hypsarrhythmia on electroencephalogram (EEG). Hypsarrhythmia is considered the hallmark of WS, but its visual assessment is challenging due to its wide variability and lack of a quantifiable definition. This study aims to analyze the EEG patterns in WS and identify computational diagnostic biomarkers of the disease.

Method

Linear and non-linear features derived from EEG recordings of 31 WS patients and 20 age-matched controls were compared. Subsequently, the correlation of the identified features with structural and genetic abnormalities was investigated.

Results

WS patients showed significantly elevated alpha-band activity (0.2516 vs. 0.1914, p < 0.001) and decreased delta-band activity (0.5117 vs. 0.5479, p < 0.001), particularly in the occipital region, as well as globally strengthened theta-band activity (0.2145 vs. 0.1655, p < 0.001) in power spectrum analysis. Moreover, wavelet-bicoherence analysis revealed significantly attenuated cross-frequency coupling in WS patients. Additionally, bi-channel coherence analysis indicated minor connectivity alterations in WS patients. Among the four non-linear characteristics of the EEG data (i.e., approximate entropy, sample entropy, permutation entropy, and wavelet entropy), permutation entropy showed the most prominent global reduction in the EEG of WS patients compared to controls (1.4411 vs. 1.5544, p < 0.001). Multivariate regression results suggested that genetic etiologies could influence the EEG profiles of WS, whereas structural factors could not.

Significance

A combined global strengthening of theta activity and global reduction of permutation entropy can serve as computational EEG biomarkers for WS. Implementing these biomarkers in clinical practice may expedite diagnosis and treatment in WS, thereby improving long-term outcomes.

Electrophysiological network predicts clinical response to vigabatrin in epileptic spasms

Purpose

This study aimed to discover electrophysiologic markers correlated with clinical responses to vigabatrin-based treatment in infants with epileptic spasms (ES).

Method

The study involved a descriptive analysis of ES patients from a single institution, as well as electroencephalogram (EEG) analyses of 40 samples and 20 age-matched healthy infants. EEG data were acquired during the interictal sleep state prior to the standard treatment. The weighted phase-lag index (wPLI) functional connectivity was explored across frequency and spatial domains, correlating these results with clinical features.

Results

Infants with ES exhibited diffuse increases in delta and theta power, differing from healthy controls. For the wPLI analysis, ES subjects exhibited higher global connectivity compared to control subjects. Subjects who responded favorably to treatment were characterized by higher beta connectivity in the parieto-occipital regions, while those with poorer outcomes exhibited lower alpha connectivity in the frontal regions. Individuals with structural neuroimaging abnormalities exhibited correspondingly low functional connectivity, implying that ES patients who maintain adequate structural and functional integrity are more likely to respond favorably to vigabatrin-based treatments.

Conclusion

This study highlights the potential utility of EEG functional connectivity analysis in predicting early response to treatments in infants with ES.

Comparing late-onset epileptic spasm outcomes after corpus callosotomy and subsequent disconnection surgery between post-encephalitis/encephalopathy and non-encephalitis/encephalopathy

OBJECTIVE

We aimed to analyze the efficiency of corpus callosotomy (CC) and subsequent disconnection surgeries in patients with late-onset epileptic spasms (LOES) by comparing post-encephalitis/encephalopathy (PE) and non-encephalitis/encephalopathy (NE). We hypothesized these surgeries can control potential focal onset epileptic spasms (ES) in the NE group but not in the PE group.

METHODS

We retrospectively included 23 patients (12 with PE and 11 with NE) who initially underwent CC and subsequent disconnection surgeries (five NE). We compared the clinical courses, seizure types, MRI, video-EEG, epilepsy surgery, and seizure outcomes between the two groups.

RESULTS

The median age of LOES onset in the PE group was 2.8 (range 1.0-10.1 years) and 2.9 years (range 1.1-12.6) in the NE group. Bilateral MRI abnormalities were observed in both groups (PE, n = 12; NE, n = 3; P < 0.05). The PE group presented ES alone (n = 2), ES + focal seizures (FS) (n = 3), ES + generalized seizures (GS) (n = 3), and ES + FS + GS (n = 4) in addition to stimulus-induced startle seizures (SS) (n = 8) (mean 3.1 seizure types/patient). The NE group presented ES alone (n = 1), ES + FS (n = 2), and ES + FS + GS (n = 8) (mean 2.7 seizure types/patient). In the PE group, CC stopped ES (n = 1) and SS (n = 1) and achieved <50% SS (n = 3). In the NE group, CC achieved immediate ES-free status (n = 2) and < 50% ES (n = 1), and additional disconnection surgeries subsided all seizure types (n = 3) based on lateralized interictal/ictal EEG findings. LOES was significantly remitted by surgery in the NE group (6/11 [55%]) compared with the PE group (1/12 [8%]) (P < 0.05).

SIGNIFICANCE

LOES is a drug-resistant, focal/generalized/unknown onset ES. Lateralization of ES in NE could be achieved after CC and eliminated by further disconnection surgeries because of potential focal onset ES. LOES in PE had little benefit from CC for generalized onset ES. However, CC might reduce SS in patients in the PE group with multiple seizure types.

The Electroencephalographic Characterization of Hypsarrhythmia in Older Pediatric Population With Epilepsy Using Computer-Added Quantitative Methods

Background Hypsarrhythmia is a classical multifocal electroencephalographic finding in patients of infantile spasm and related epileptic syndromes of early childhood including West syndrome and Otahara syndrome. It usually presents in early infancy and persists up to the age of two years, after which it usually resolves. The persistence of hypsarrhythmia beyond the age of two years has rarely been reported in the literature. The present study is an attempt to investigate and compare the origin and activation pattern of epileptic activity between the subjects aged 3-10 years with and without hypsarrythmia. Material and methods Forty-one patients in the age group of 3-10 years with features suggestive of seizure have been studied for quantitative electroencephalographic characteristics after dividing into hypsarrythmic and normal seizure patterns. Result The power spectral density (PSD) of 15 patients with hypsarrhythmia showed a significantly predominant delta frequency in quantitative electrography (qEEG) in comparison to the seizure subjects with normal electroencephalography (EEG) patterns. The amplitude progression analysis of both groups showed that the origin of focus of the hypsarrhythmic pattern is from the occipital region while no such pattern has been noticed in the control group. Discussion and conclusion Hypsarrythmia is known to show multifocal origin. Predominant occipital origin in older age group subjects distinguishes the condition from classical hypsarrythmia of early childhood. The occipital origin may be indicative of persistent immaturity of the thalamocortical synaptic pathway.

Quantitative pretreatment EEG predicts efficacy of ACTH therapy in infantile epileptic spasms syndrome

OBJECTIVE

This study aimed to determine the correlation between outcomes following adrenocorticotrophic hormone (ACTH) therapy and measurements of relative power spectrum (rPS), weighted phase lag index (wPLI), and graph theoretical analysis on pretreatment electroencephalography (EEG) in infants with non-lesional infantile epileptic spasms syndrome (IESS).

METHODS

Twenty-eight patients with non-lesional IESS were enrolled. Outcomes were classified based on seizure recurrence following ACTH therapy: seizure-free (F, n = 21) and seizure-recurrence (R, n = 7) groups. The rPS, wPLI, clustering coefficient, and betweenness centrality were calculated on pretreatment EEG and were statistically analyzed to determine the correlation with outcomes following ACTH therapy.

RESULTS

The rPS value was significantly higher in the delta frequency band in group R than in group F (p < 0.001). The wPLI values were significantly higher in the delta, theta, and alpha frequency bands in group R than in group F (p = 0.007, <0.001, and <0.001, respectively). The clustering coefficient in the delta frequency band was significantly lower in group R than in group F (p < 0.001).

CONCLUSIONS

Our findings demonstrate the significant differences in power and functional connectivity between outcome groups.

SIGNIFICANCE

This study may contribute to an early prediction of ACTH therapy outcomes and thus help in the development of appropriate treatment strategies.

Integration of multiscale entropy and BASED scale of electroencephalography after adrenocorticotropic hormone therapy predict relapse of infantile spasms

BACKGROUND

Even though adrenocorticotropic hormone (ACTH) demonstrated powerful efficacy in the initially successful treatment of infantile spasms (IS), nearly half of patients have experienced a relapse. We sought to investigate whether features of electroencephalogram (EEG) predict relapse in those IS patients without structural brain abnormalities.

METHODS

We retrospectively reviewed data from children with IS who achieved initial response after ACTH treatment, along with EEG recorded within the last two days of treatment. The recurrence of epileptic spasms following treatment was tracked for 12 months. Subjects were categorized as either non-relapse or relapse groups. General clinical and EEG recordings were collected, burden of amplitudes and epileptiform discharges (BASED) score and multiscale entropy (MSE) were carefully explored for cross-group comparisons.

RESULTS

Forty-one patients were enrolled in the study, of which 26 (63.4%) experienced a relapse. The BASED score was significantly higher in the relapse group. MSE in the non-relapse group was significantly lower than the relapse group in the γ band but higher in the lower frequency range (δ, θ, α). Sensitivity and specificity were 85.71% and 92.31%, respectively, when combining MSE in the δ/γ frequency of the occipital region, plus BASED score were used to distinguish relapse from non-relapse groups.

CONCLUSIONS

BASED score and MSE of EEG after ACTH treatment could be used to predict relapse for IS patients without brain structural abnormalities. Patients with BASED score ≥ 3, MSE increased in higher frequency, and decreased in lower frequency had a high risk of relapse.

Periodic electroencephalographic discharges and epileptic spasms involve cortico-striatal-thalamic loops on Arterial Spin Labeling Magnetic Resonance Imaging

Periodic discharges are a rare peculiar electroencephalogram pattern, occasionally associated with motor or other clinical manifestations, usually observed in critically ill patients. Their underlying pathophysiology remains poorly understood. Epileptic spasms in clusters and periodic discharges with motor manifestations share similar electroencephalogram pattern and some aetiologies of unfavourable prognosis such as subacute sclerosing panencephalitis or herpes encephalitis. Arterial spin labelling magnetic resonance imaging identifies localizing ictal and inter-ictal changes in neurovascular coupling, therefore assumed able to reveal concerned cerebral structures. Here, we retrospectively analysed ictal and inter-ictal arterial spin labelling magnetic resonance imaging in patients aged 6 months to 15 years (median 3 years 4 months) with periodic discharges including epileptic spasms, and compared these findings with those of patients with drug-resistant focal epilepsy who never presented periodic discharges nor epileptic spasms as well as to those of age-matched healthy controls. Ictal electroencephalogram was recorded either simultaneously with arterial spin labelling magnetic resonance imaging or during the close time lapse of patients' periodic discharges, whereas inter-ictal examinations were performed during the patients' active epilepsy but without seizures during the arterial spin labelling magnetic resonance imaging. Ictal arterial spin labelling magnetic resonance imaging was acquired in five patients with periodic discharges [subacute sclerosing panencephalitis (1), stroke-like events (3), West syndrome with cortical malformation (1), two of them also had inter-ictal arterial spin labelling magnetic resonance imaging]. Inter-ictal group included patients with drug-resistant epileptic spasms of various aetiologies (14) and structural drug-resistant focal epilepsy (8). Cortex, striatum and thalamus were segmented and divided in six functional subregions: prefrontal, motor (rostral, caudal), parietal, occipital and temporal. Rest cerebral blood flow values, absolute and relative to whole brain, were compared with those of age-matched controls for each subregion. Main findings were diffuse striatal as well as cortical motor cerebral blood flow increase during ictal examinations in generalized periodic discharges with motor manifestations (subacute sclerosing panencephalitis) and focal cerebral blood flow increase in corresponding cortical-striatal-thalamic subdivisions in lateralized periodic discharges with or without motor manifestations (stroke-like events and asymmetrical epileptic spasms) with straight topographical correlation with the electroencephalogram focus. For inter-ictal examinations, patients with epileptic spasms disclosed cerebral blood flow changes in corresponding cortical-striatal-thalamic subdivisions (absolute-cerebral blood flow decrease and relative-cerebral blood flow increase), more frequently when compared with the group of drug-resistant focal epilepsies, and not related to Vigabatrin treatment. Our results suggest that corresponding cortical-striatal-thalamic circuits are involved in periodic discharges with and without motor manifestations, including epileptic spasms, opening new insights in their pathophysiology and new therapeutical perspectives. Based on these findings, we propose a model for the generation of periodic discharges and of epileptic spasms combining existing pathophysiological models of cortical-striatal-thalamic network dynamics.

Altered topological organization of resting-state functional networks in children with infantile spasms

Covering neuroimaging evidence has demonstrated that epileptic symptoms are associated with the disrupted topological architecture of the brain network. Infantile spasms (IS) as an age-specific epileptic encephalopathy also showed abnormal structural or functional connectivity in specific brain regions or specific networks. However, little is known about the topological alterations of whole-brain functional networks in patients with IS. To fill this gap, we used the graph theoretical analysis to investigate the topological properties (whole-brain small-world property and modular interaction) in 17 patients with IS and 34 age- and gender-matched healthy controls. The functional networks in both groups showed efficient small-world architecture over the sparsity range from 0.05 to 0.4. While patients with IS showed abnormal global properties characterized by significantly decreased normalized clustering coefficient, normalized path length, small-worldness, local efficiency, and significantly increased global efficiency, implying a shift toward a randomized network. Modular analysis revealed decreased intra-modular connectivity within the default mode network (DMN) and fronto-parietal network but increased inter-modular connectivity between the cingulo-opercular network and occipital network. Moreover, the decreased intra-modular connectivity in DMN was significantly negatively correlated with seizure frequency. The inter-modular connectivity between the cingulo-opercular and occipital network also showed a significant correlation with epilepsy frequency. Together, the current study revealed the disrupted topological organization of the whole-brain functional network, which greatly advances our understanding of neuronal architecture in IS and may contribute to predict the prognosis of IS as disease biomarkers.

EEG biomarkers for the diagnosis and treatment of infantile spasms

Early diagnosis and treatment are critical for young children with infantile spasms (IS), as this maximizes the possibility of the best possible child-specific outcome. However, there are major barriers to achieving this, including high rates of misdiagnosis or failure to recognize the seizures, medication failure, and relapse. There are currently no validated tools to aid clinicians in assessing objective diagnostic criteria, predicting or measuring medication response, or predicting the likelihood of relapse. However, the pivotal role of EEG in the clinical management of IS has prompted many recent studies of potential EEG biomarkers of the disease. These include both visual EEG biomarkers based on human visual interpretation of the EEG and computational EEG biomarkers in which computers calculate quantitative features of the EEG. Here, we review the literature on both types of biomarkers, organized based on the application (diagnosis, treatment response, prediction, etc.). Visual biomarkers include the assessment of hypsarrhythmia, epileptiform discharges, fast oscillations, and the Burden of AmplitudeS and Epileptiform Discharges (BASED) score. Computational markers include EEG amplitude and power spectrum, entropy, functional connectivity, high frequency oscillations (HFOs), long-range temporal correlations, and phase-amplitude coupling. We also introduce each of the computational measures and provide representative examples. Finally, we highlight remaining gaps in the literature, describe practical guidelines for future biomarker discovery and validation studies, and discuss remaining roadblocks to clinical implementation, with the goal of facilitating future work in this critical area.

Imaging Genetics in Epilepsy: Current Knowledge and New Perspectives

Epilepsy is a neurological network disease with genetics playing a much greater role than was previously appreciated. Unfortunately, the relationship between genetic basis and imaging phenotype is by no means simple. Imaging genetics integrates multidimensional datasets within a unified framework, providing a unique opportunity to pursue a global vision for epilepsy. This review delineates the current knowledge of underlying genetic mechanisms for brain networks in different epilepsy syndromes, particularly from a neural developmental perspective. Further, endophenotypes and their potential value are discussed. Finally, we highlight current challenges and provide perspectives for the future development of imaging genetics in epilepsy.

Increased migraine-free intervals with multifocal repetitive transcranial magnetic stimulation

INTRODUCTION

Episodic migraine is a debilitating condition associated with vast impairments of health, daily living, and life quality. Several prophylactic treatments exist, having a moderate ratio of action related to side effects and therapy costs. Repetitive transcranial magnetic stimulation (rTMS) is an evidence based therapy in several neuropsychiatric conditions, showing robust efficacy in alleviating specific symptoms. However, its efficacy in migraine disorders is unequivocal and might be tightly linked to the applied rTMS protocol. We hypothesized that multifocal rTMS paradigm could improve clinical outcomes in patients with episodic migraine by reducing the number of migraine days, frequency and intensity of migraine attacks, and improve the quality of life.

METHODS

We conducted an experimental, double-blind, randomized controlled study by applying a multifocal rTMS paradigm. Patients with episodic migraine with or without aura were enrolled in two centers from August 2018, to December 2019, and randomized to receive either real (n = 37) or sham (sham coil stimulation, n = 28) multifocal rTMS for six sessions over two weeks. Patients, physicians, and raters were blinded to the applied protocol. The experimental multifocal rTMS protocol included two components; first, swipe stimulation of 13 trains of 140 pulses/train, 67 Hz, 60% of RMT, and 2s intertrain interval and second, spot burst stimulation of 33 trains of 15 pulses/train, 67 Hz, 85% of RMT, and 8s intertrain interval. Reduction >50% from the baseline in migraine days (as primary outcome) and frequency and intensity of migraine attacks (as key secondary outcomes) over a 12-week period were assessed. To balance the baseline variables between the treatment arms, we applied the propensity score matching through the logistic regression.

RESULTS

Among 65 randomized patients, sixty (age 39.7 ± 11.6; 52 females; real rTMS n = 33 and sham rTMS n = 27) completed the trial and five patients dropped out. Over 12 weeks, the responder's rate in the number of migraine days was significantly higher in the real rTMS compared to the sham group (42% vs. 26%, p < 0.05). The mean migraine days per month decreased from 7.6 to 4.3 days in the real rTMS group and from 6.2 to 4.3 days in the sham rTMS group, resulting in a difference with real vs. sham rTMS of -3.2 days (p < 0.05). Similarly, over the 12-week period, the responder's rate in the reduction of migraine attacks frequency was higher in the real rTMS compared to the sham group (42% vs 33%, p < 0.05). No serious adverse events were observed.

CONCLUSION

Our pilot study shows compelling evidence in a double placebo-controlled trial that multifocal rTMS is an effective and well-tolerated preventive treatment in patients with episodic migraine.

Computational characteristics of interictal EEG as objective markers of epileptic spasms

OBJECTIVE

Favorable neurodevelopmental outcomes in epileptic spasms (ES) are tied to early diagnosis and prompt treatment, but uncertainty in the identification of the disease can delay this process. Therefore, we investigated five categories of computational electroencephalographic (EEG) measures as markers of ES.

METHODS

We measured 1) amplitude, 2) power spectra, 3) Shannon entropy and permutation entropy, 4) long-range temporal correlations, via detrended fluctuation analysis (DFA) and 5) functional connectivity using cross-correlation and phase lag index (PLI). EEG data were analyzed from ES patients (n = 40 patients) and healthy controls (n = 20 subjects), with multiple blinded measurements during wakefulness and sleep for each patient.

RESULTS

In ES patients, EEG amplitude was significantly higher in all electrodes when compared to controls. Shannon and permutation entropy were lower in ES patients than control subjects. The DFA intercept values in ES patients were significantly higher than control subjects, while DFA exponent values were not significantly different between the groups. EEG functional connectivity networks in ES patients were significantly stronger than controls when based on both cross-correlation and PLI. Significance for all statistical tests was p < 0.05, adjusted for multiple comparisons using the Benjamini-Hochberg procedure as appropriate. Finally, using logistic regression, a multi-attribute classifier was derived that accurately distinguished cases from controls (area under curve of 0.96).

CONCLUSIONS

Computational EEG features successfully distinguish ES patients from controls in a large, blinded study.

SIGNIFICANCE

These objective EEG markers, in combination with other clinical factors, may speed the diagnosis and treatment of the disease, thereby improving long-term outcomes.

Epileptogenic modulation index and synchronization in hypsarrhythmia of West syndrome secondary to perinatal arterial ischemic stroke

OBJECTIVE

Perinatal arterial ischemic stroke (PAIS) is associated with epileptic spasms of West syndrome (WS) and long term Focal epilepsy (FE). The mechanism of epileptogenic network generation causing hypsarrhythmia of WS is unknown. We hypothesized that Modulation index (MI) [strength of phase-amplitude coupling] and Synchronization likelihood (SL) [degree of connectivity] could interrogate the epileptogenic network in hypsarrhythmia of WS secondary to PAIS.

METHODS

We analyzed interictal scalp electroencephalography (EEG) in 10 WS and 11 FE patients with unilateral PAIS. MI between gamma (30-70 Hz) and slow waves (3-4 Hz) was calculated to measure phase-amplitude coupling. SL between electrode pairs was analyzed in 9-frequency bands (5-delta, theta, alpha, beta, gamma) to examine inter- and intra-hemispheric connectivity.

RESULTS

MI was higher in affected hemispheres in WS (p = 0.006); no differences observed in FE. Inter-hemispheric SL of 3-delta, theta, alpha, beta, gamma bands was significantly higher in WS (p < 0.001). In WS, modified Z-Score of intra-hemispheric SL values in 3-delta, theta, alpha, beta and gamma in the affected hemispheres were significantly higher than those in the unaffected hemispheres (p < 0.001) as well as 0.5-4 Hz (p = 0.004).

CONCLUSIONS

The significantly higher modulation in affected hemisphere and stronger inter- and intra-hemispheric connectivity generate hypsarrhythmia of WS secondary to PAIS.

SIGNIFICANCE

Epileptogenic cortical-subcortical transcallosal networks from affected hemisphere post-PAIS provokes infantile spasms.

Source imaging of deep-brain activity using the regional spatiotemporal Kalman filter

BACKGROUND AND OBJECTIVE

The human brain displays rich and complex patterns of interaction within and among brain networks that involve both cortical and subcortical brain regions. Due to the limited spatial resolution of surface electroencephalography (EEG), EEG source imaging is used to reconstruct brain sources and investigate their spatial and temporal dynamics. The majority of EEG source imaging methods fail to detect activity from subcortical brain structures. The reconstruction of subcortical sources is a challenging task because the signal from these sources is weakened and mixed with artifacts and other signals from cortical sources. In this proof-of-principle study we present a novel EEG source imaging method, the regional spatiotemporal Kalman filter (RSTKF), that can detect deep brain activity.

METHODS

The regional spatiotemporal Kalman filter (RSTKF) is a generalization of the spatiotemporal Kalman filter (STKF), which allows for the characterization of different regional dynamics in the brain. It is based on state-space modeling with spatially heterogeneous dynamical noise variances, since models with spatial and temporal homogeneity fail to describe the dynamical complexity of brain activity. First, RSTKF is tested using simulated EEG data from sources in the frontal lobe, putamen, and thalamus. After that, it is applied to non-averaged interictal epileptic spikes from a presurgical epilepsy patient with focal epileptic activity in the amygdalo-hippocampal complex. The results of RSTKF are compared to those of low-resolution brain electromagnetic tomography (LORETA) and of standard STKF.

RESULTS

Only RSTKF is successful in consistently and accurately localizing the sources in deep brain regions. Additionally, RSTKF shows improved spatial resolution compared to LORETA and STKF.

CONCLUSIONS

RSTKF is a generalization of STKF that allows for accurate, focal, and consistent localization of sources, especially in the deeper brain areas. In contrast to standard source imaging methods, RSTKF may find application in the localization of the epileptogenic zone in deeper brain structures, such as mesial frontal and temporal lobe epilepsies, especially in EEG recordings for which no reliable averaged spike shape can be obtained due to lack of the necessary number of spikes required to reach a certain signal-to-noise ratio level after averaging.

What are the epileptic encephalopathies?

PURPOSE OF REVIEW

To review the evolution of the concept of epileptic encephalopathy during the course of past years and analyze how the current definition might impact on both clinical practice and research.

RECENT FINDINGS

Developmental delay in children with epilepsy could be the expression of the cause, consequence of intense epileptiform activity (seizures and EEG abnormalities), or because of the combination of both factors. Therefore, the current International League Against Epilepsy classification identified three electroclinical entities that are those of developmental encephalopathy, epileptic encephalopathy, and developmental and epileptic encephalopathy (DEE). Many biological pathways could be involved in the pathogenesis of DEEs. DNA repair, transcriptional regulation, axon myelination, metabolite and ion transport, and peroxisomal function could all be involved in DEE. Also, epilepsy and epileptiform discharges might impact on cognition via several mechanisms, although they are not fully understood.

SUMMARY

The correct and early identification of cause in DEE might increase the chances of a targeted treatment regimen. Interfering with neurobiological processes of the disease will be the most successful way in order to improve both the cognitive disturbances and epilepsy that are the key features of DEE.

Engagement of cortico-cortical and cortico-subcortical networks in a patient with epileptic spasms: An integrated neurophysiological study

OBJECTIVE

We aimed to delineate the engagement of cortico-cortical and cortico-subcortical networks in the generation of epileptic spasms (ES) using integrated neurophysiological techniques.

METHODS

Seventeen-year-old male patient with intractable ES underwent chronic subdural electrode implantation for presurgical evaluation. Networks were evaluated in ictal periods using high-frequency oscillation (HFO) analysis and in interictal periods using magnetoencephalography (MEG) and simultaneous electroencephalography, and functional magnetic resonance imaging (EEG-fMRI). Cortico-cortical evoked potentials (CCEPs) were recorded to trace connections among the networks.

RESULTS

Ictal HFO revealed a network comprising multilobar cortical regions (frontal, parietal, and temporal), but sparing the positive motor area. Interictally, MEG and EEG-fMRI revealed spike-and-wave-related activation in these cortical regions. Analysis of CCEPs provided evidence of connectivity within the cortico-cortical network. Additionally, EEG-fMRI results indicate the involvement of subcortical structures, such as bilateral thalamus (predominantly right) and midbrain.

CONCLUSIONS

In this case study, integrated neurophysiological techniques provided converging evidence for the involvement of a cortico-cortical network (sparing the positive motor area) and a cortico-subcortical network in the generation of ES in the patient.

SIGNIFICANCE

Cortico-cortical and cortico-subcortical pathways, with the exception of the direct descending corticospinal pathway from the positive motor area, may play important roles in the generation of ES.

Treatment of infantile spasms: why do we know so little?

INTRODUCTION

Infantile spasm (IS) is an epileptic syndrome with typical onset within the first 2 years of life. This condition might be caused by several etiologies. IS is associated with pathological neuronal networks; however, definite hypotheses on neurobiological processes are awaited.

AREAS COVERED

Changes in NMDA and GABA_B receptors and increase of Ca²⁺ conductance are some of the possible pathophysiological mechanisms. Animal models can help, but most have only some features of IS. Outcome is strongly affected by etiology and the timing of treatment, which relies still on ACTH, oral steroids, and vigabatrin. No significant differences in terms of efficacy have been documented, though a combination of ACTH and vigabatrin seems to be associated with better long-term outcomes. Despite the increasing knowledge about the etiology and pathophysiology of IS, in the last years, no new treatment approaches have been recognized to be able to modify the neurobiological process underlying IS. Precision medicine has far to come in IS.

EXPERT OPINION

Recently, no new therapeutic options for IS have emerged, probably due to the lack of reliable animal models and to the extreme variability in etiologies. Consequently, the outlook for patients and families is poor and early recognition and intervention remain research priorities.

Interictal scalp fast ripple occurrence and high frequency oscillation slow wave coupling in epileptic spasms

OBJECTIVE

Intracranial high frequency oscillation (HFO) occurrence rate (OR) and slow wave activity (SWA) coupling are potential markers of epileptogenicity in epileptic spasms (ES). Scalp ripple (R) detection and SWA coupling have been described in ES; however, the feasibility of scalp fast ripple (FR) detection and measurement of scalp FR coupling to SWA is not known. We evaluated interictal scalp R and FR OR and SWA coupling in pre-treatment EEG in children with short-term treatment-refractory ES compared to short-term treatment non-refractory ES.

METHODS

We retrospectively identified children with ES and identified HFOs using a semi-automated HFO detector on pre-treatment scalp EEG during sleep. We evaluated HFO OR and event-triggered modulation index (MI) to quantify R (100-250 Hz) and FR (250-600 Hz) coupling strength with different SWA passbands (0.5-1, 1-2, 2-3, 3-4, and 4-8 Hz). We used HFO phasor transform and circular statistics to evaluate phase coupling angle distributions.

RESULTS

We identified 15 children with ES with pre-treatment EEG recorded at 2000 Hz. Thirteen out of 15 patients had HFOs and were included for analysis. There were six treatment responders and seven nonresponders three months after treatment initiation. Responders and nonresponders were similar in age (6.1 vs 7.2 mo), ES diagnosis duration (0.7 vs 2.6 mo), and HFO OR (R: 1.07 vs 2.30/min, FR: 0.43 vs 1.96/min). No differences between responders and nonresponders were seen in HFO MI at different SWA. Coupling of R and FR to 2-3 Hz SWA demonstrated increased incidence rate ratio in nonresponders relative to responders at distinct phase coupling angle distributions.

CONCLUSIONS

This study demonstrates the feasibility of interictal scalp R and FR detection and quantification of scalp R and FR coupling to SWA in ES.

SIGNIFICANCE

HFO phase coupling with SWA may be useful as a marker of potential treatment refractoriness in patients with ES.

Emerging roles of network analysis for epilepsy

In recent years there has been increasing interest in applying network science tools to EEG data. At the 2018 American Epilepsy Society conference in New Orleans, LA, the yearly session of the Engineering and Neurostimulation Special Interest Group focused on emerging, translational technologies to analyze seizure networks. Each speaker demonstrated practical examples of how network tools can be utilized in clinical care and provide additional data to help care for patients with intractable epilepsy. The groups presented advances using tools from functional connectivity, control theory, and graph theory to analyze human EEG data. These tools have great potential to augment clinical interpretation of EEG signals.

Quantitative Characteristics of Hypsarrhythmia in Infantile Spasms

Infantile spasms is a type of epilepsy characterized by clinical seizures termed "spasms" and often an electroencephalographic (EEG) pattern known as hypsarrhythmia. Multiple studies have shown that the interrater reliability for human visual recognition of hypsarrhythmia is poor. Quantitative measurements of this EEG pattern would provide objective basis for identification; however, the basic temporal and spectral characteristics of hypsarrhythmia have never been assessed. Thus, we measured EEG amplitude and power spectra in 21 infantile spasms patients before and after treatment, as well as 21 control subjects. The hypsarrhythmia EEG pattern was associated with (1) high broadband amplitude, especially in frontal and central brain regions, (2) high median power in the delta and alpha frequency bands, and (3) low spectral edge frequency. Our results indicate that hypsarrhythmia can be quantitatively distinguished from data without hypsarrhythmia. Introduction of these quantitative measures into clinical practice may increase diagnostic accuracy, expediting proper treatment and improving outcomes.

EEG before and after total corpus callosotomy for pharmacoresistant infantile spasms: Fast oscillations and slow-wave connectivity in hypsarrhythmia

OBJECTIVE

We analyzed the features of fast oscillations (FOs) and connectivity in hypsarrhythmia to identify biomarkers for predicting seizure outcomes after total corpus callosotomy (TCC) in children with pharmacoresistant infantile spasms (IS). We hypothesize that the power of FOs and connectivity of slow waves in hypsarrhythmia would indicate the prognosis of IS.

METHOD

We retrospectively identified 42 children with pharmacoresistant IS who underwent TCC from 2009 to 2014 at Nagasaki Medical Center. We collected preoperative hypsarrhythmia for 200 seconds from each child. Children were categorized into three groups with interictal epileptic discharges on EEG at 6 months after TCC: group A, no epileptic discharge; group B, lateralized epileptic discharges; and group C; bilateral epileptic discharges. We analyzed spectral power and phase synchronization in preoperative hypsarrhythmia among the three groups.

RESULTS

We found 10 children in group A, 10 children in group B, and 22 children in group C. All group A and 1 in group B achieved seizure freedom after TCC. Six (67%) of 9 group B children who underwent further surgeries achieved seizure freedom. Ten (45%) of group C children had seizure reduction >50% after TCC, and 13 (87%) of 15 children who underwent further surgeries had residual seizures. The clinical profiles of the three groups did not differ significantly. The power of FOs (≥45 Hz) in hypsarrhythmia was significantly stronger in group C at the midline and temporal regions than in groups B and A (P = .014). The connectivity of theta (4-9 Hz) and FOs (29-70 Hz) tended to increase in group C, compared with the increased connectivity of 1-2 Hz in group A (P = .08).

SIGNIFICANCE

The increased power and connectivity of FOs in hypsarrhythmia may correlate with pharmacoresistant and surgically resistant seizures in IS. The existence and connectivity of FOs are associated with unilateral/bilateral cortical epileptogenicity in hypsarrhythmia. Prominent slow waves and connectivity without FOs might correlate with seizure freedom after TCC. Modulation of the callosal system with subcortical/cortical epileptic discharges might play a role in generating hypsarrhythmia and IS.

Strength and stability of EEG functional connectivity predict treatment response in infants with epileptic spasms

OBJECTIVE

Epileptic spasms (ES) are associated with pathological neuronal networks, which may underlie characteristic EEG patterns such as hypsarrhythmia. Here we evaluate EEG functional connectivity as a quantitative marker of treatment response, in comparison to classic visual EEG features.

METHODS

We retrospectively identified 21 ES patients and 21 healthy controls. EEG data recorded before treatment and after ≥10 days of treatment underwent blinded visual assessment, and functional connectivity was measured using cross-correlation techniques. Short-term treatment response and long-term outcome data were collected.

RESULTS

Subjects with ES had stronger, more stable functional networks than controls. After treatment initiation, all responders (defined by cessation of spasms) exhibited decreases in functional connectivity strength, while an increase in connectivity strength occurred only in non-responders. There were six subjects with unusually strong pre-treatment functional connectivity, and all were responders. Visually assessed EEG features were not predictive of treatment response.

CONCLUSIONS

Changes in network connectivity and stability correlate to treatment response for ES, and high pre-treatment connectivity may predict favorable short-term treatment response. Quantitative measures outperform visual analysis of the EEG.

SIGNIFICANCE

Functional networks may have value as objective markers of treatment response in ES, with potential to facilitate rapid identification of personalized, effective treatments.

Network dynamics in the healthy and epileptic developing brain

Electroencephalography (EEG) allows recording of cortical activity at high temporal resolution. EEG recordings can be summarized along different dimensions using network-level quantitative measures, such as channel-to-channel correlation, or band power distributions across channels. These reveal network patterns that unfold over a range of different timescales and can be tracked dynamically. Here we describe the dynamics of network state transitions in EEG recordings of spontaneous brain activity in normally developing infants and infants with severe early infantile epileptic encephalopathies (n = 8, age: 1–8 months). We describe differences in measures of EEG dynamics derived from band power, and correlation-based summaries of network-wide brain activity. We further show that EEGs from different patient groups and controls may be distinguishable on a small set of the novel quantitative measures introduced here, which describe dynamic network state switching. Quantitative measures related to the sharpness of switching from one correlation pattern to another show the largest differences between groups. These findings reveal that the early epileptic encephalopathies are associated with characteristic dynamic features at the network level. Quantitative network-based analyses like the one presented here may in the future inform the clinical use of quantitative EEG for diagnosis.

Long-Range Temporal Correlations Reflect Treatment Response in the Electroencephalogram of Patients with Infantile Spasms

Infantile spasms syndrome is an epileptic encephalopathy in which prompt diagnosis and treatment initiation are critical to therapeutic response. Diagnosis of the disease heavily depends on the identification of characteristic electroencephalographic (EEG) patterns, including hypsarrhythmia. However, visual assessment of the presence and characteristics of hypsarrhythmia is challenging because multiple variants of the pattern exist, leading to poor inter-rater reliability. We investigated whether a quantitative measurement of the control of neural synchrony in the EEGs of infantile spasms patients could be used to reliably distinguish the presence of hypsarrhythmia and indicate successful treatment outcomes. We used autocorrelation and Detrended Fluctuation Analysis (DFA) to measure the strength of long-range temporal correlations in 21 infantile spasms patients before and after treatment and 21 control subjects. The strength of long-range temporal correlations was significantly lower in patients with hypsarrhythmia than control patients, indicating decreased control of neural synchrony. There was no difference between patients without hypsarrhythmia and control patients. Further, the presence of hypsarrhythmia could be classified based on the DFA exponent and intercept with 92% accuracy using a support vector machine. Successful treatment was marked by a larger increase in the DFA exponent compared to those in which spasms persisted. These results suggest that the strength of long-range temporal correlations is a marker of pathological cortical activity that correlates with treatment response. Combined with current clinical measures, this quantitative tool has the potential to aid objective identification of hypsarrhythmia and assessment of treatment efficacy to inform clinical decision-making.

EEG-MEG Integration Enhances the Characterization of Functional and Effective Connectivity in the Resting State Network

At the sensor level many aspects, such as spectral power, functional and effective connectivity as well as relative-power-ratio ratio (RPR) and spatial resolution have been comprehensively investigated through both electroencephalography (EEG) and magnetoencephalography (MEG). Despite this, differences between both modalities have not yet been systematically studied by direct comparison. It remains an open question as to whether the integration of EEG and MEG data would improve the information obtained from the above mentioned parameters. Here, EEG (64-channel system) and MEG (275 sensor system) were recorded simultaneously in conditions with eyes open (EO) and eyes closed (EC) in 29 healthy adults. Spectral power, functional and effective connectivity, RPR, and spatial resolution were analyzed at five different frequency bands (delta, theta, alpha, beta and gamma). Networks of functional and effective connectivity were described using a spatial filter approach called the dynamic imaging of coherent sources (DICS) followed by the renormalized partial directed coherence (RPDC). Absolute mean power at the sensor level was significantly higher in EEG than in MEG data in both EO and EC conditions. At the source level, there was a trend towards a better performance of the combined EEG+MEG analysis compared with separate EEG or MEG analyses for the source mean power, functional correlation, effective connectivity for both EO and EC. The network of coherent sources and the spatial resolution were similar for both the EEG and MEG data if they were analyzed separately. Results indicate that the combined approach has several advantages over the separate analyses of both EEG and MEG. Moreover, by a direct comparison of EEG and MEG, EEG was characterized by significantly higher values in all measured parameters in both sensor and source level. All the above conclusions are specific to the resting state task and the specific analysis used in this study to have general conclusion multi-center studies would be helpful.

Neuronal Networks during Burst Suppression as Revealed by Source Analysis

Introduction

Burst-suppression (BS) is an electroencephalography (EEG) pattern consisting of alternant periods of slow waves of high amplitude (burst) and periods of so called flat EEG (suppression). It is generally associated with coma of various etiologies (hypoxia, drug-related intoxication, hypothermia, and childhood encephalopathies, but also anesthesia). Animal studies suggest that both the cortex and the thalamus are involved in the generation of BS. However, very little is known about mechanisms of BS in humans. The aim of this study was to identify the neuronal network underlying both burst and suppression phases using source reconstruction and analysis of functional and effective connectivity in EEG.

Material/Methods

Dynamic imaging of coherent sources (DICS) was applied to EEG segments of 13 neonates and infants with burst and suppression EEG pattern. The brain area with the strongest power in the analyzed frequency (1–4 Hz) range was defined as the reference region. DICS was used to compute the coherence between this reference region and the entire brain. The renormalized partial directed coherence (RPDC) was used to describe the informational flow between the identified sources.

Results/Conclusion

Delta activity during the burst phases was associated with coherent sources in the thalamus and brainstem as well as bilateral sources in cortical regions mainly frontal and parietal, whereas suppression phases were associated with coherent sources only in cortical regions. Results of the RPDC analyses showed an upwards informational flow from the brainstem towards the thalamus and from the thalamus to cortical regions, which was absent during the suppression phases. These findings may support the theory that a “cortical deafferentiation” between the cortex and sub-cortical structures exists especially in suppression phases compared to burst phases in burst suppression EEGs. Such a deafferentiation may play a role in the poor neurological outcome of children with these encephalopathies.

Neuroimaging of drug resistance in epilepsy

PURPOSE OF REVIEW

Drug resistance is an important clinical problem: it is associated with higher rates of somatic and psychiatric comorbidities and cognitive/memory decline, with seizures being just the 'tip of the iceberg'. This review summarizes recent developments in imaging research, focusing specifically on the functional consequence of chronic epilepsies and mechanisms of drug resistance, restricted to work published in 2013.

RECENT FINDINGS

Functional imaging approaches reliably identify underlying specific networks in patients with different epileptic syndromes, show specific responses to certain antiepileptic drugs and differentiate between responder and nonresponder. Functional MRI (fMRI) and the intracarotid amobarbital test (IAT) are generally congruent, but fMRI may be more sensitive than IAT to right hemisphere language processing. In addition, memory fMRI supports the functional adequacy of ipsilateral structures rather than functional reserve of the contralateral hemisphere. There is further evidence from group analysis of fMRI data for a node within the ipsilateral piriform cortex to be important for seizure modulation in focal refractory epilepsies of different cortical origin. Molecular imaging with verapamil-PET identifies P-glycprotein overexpression as a mechanism contributing to drug resistance in individual patients.

SUMMARY

Neuroimaging in epilepsy has progressed from correlations with demographic, semiologic, neuropsychological and other observational data primarily in patients undergoing presurgical investigations to imaging network connectivity changes in epilepsy syndromes, and testing specific mechanisms underlying drug-resistant epilepsy.

Association between long non-coding RNA and human rare diseases (Review)

Long non-coding RNAs (lncRNAs) are untranslated transcripts with longer than 200 nucleotides (nt), which possess many of the structural characteristics of mRNAs, including a poly A tail, 5'-capping, and a promoter structure, but no conserved open reading frame. Moreover, lncRNA expression patterns change during differentiation and exhibit a variety of splicing patterns. Many lncRNAs are expressed at specific times and in specific tissues during development. It has been proposed that lncRNAs are involved in the epigenetic regulation of coding genes, and thus exert a powerful effect on a number of physiological and pathological processes, including the pathogenesis of many human rare diseases.

Dynamic imaging of coherent sources reveals different network connectivity underlying the generation and perpetuation of epileptic seizures

The concept of focal epilepsies includes a seizure origin in brain regions with hyper synchronous activity (epileptogenic zone and seizure onset zone) and a complex epileptic network of different brain areas involved in the generation, propagation, and modulation of seizures. The purpose of this work was to study functional and effective connectivity between regions involved in networks of epileptic seizures. The beginning and middle part of focal seizures from ictal surface EEG data were analyzed using dynamic imaging of coherent sources (DICS), an inverse solution in the frequency domain which describes neuronal networks and coherences of oscillatory brain activities. The information flow (effective connectivity) between coherent sources was investigated using the renormalized partial directed coherence (RPDC) method. In 8/11 patients, the first and second source of epileptic activity as found by DICS were concordant with the operative resection site; these patients became seizure free after epilepsy surgery. In the remaining 3 patients, the results of DICS / RPDC calculations and the resection site were discordant; these patients had a poorer post-operative outcome. The first sources as found by DICS were located predominantly in cortical structures; subsequent sources included some subcortical structures: thalamus, Nucl. Subthalamicus and cerebellum. DICS seems to be a powerful tool to define the seizure onset zone and the epileptic networks involved. Seizure generation seems to be related to the propagation of epileptic activity from the primary source in the seizure onset zone, and maintenance of seizures is attributed to the perpetuation of epileptic activity between nodes in the epileptic network. Despite of these promising results, this proof of principle study needs further confirmation prior to the use of the described methods in the clinical praxis.

Simultaneous EEG and fMRI recordings (EEG-fMRI) in children with epilepsy

By combining electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) it is possible to describe blood oxygenation level-dependent (BOLD) signal changes related to EEG patterns. This way, EEG-pattern-associated networks of hemodynamic changes can be detected anywhere in the brain with good spatial resolution. This review summarizes EEG-fMRI studies that have been performed in children with epilepsy. EEG-fMRI studies in focal epilepsy (structural and nonlesional cases, benign epilepsy with centrotemporal spikes), generalized epilepsy (especially absence epilepsy), and epileptic encephalopathies (West syndrome, Lennox-Gastaut syndrome, continuous spike and waves during slow sleep, and Dravet syndrome) are presented. Although EEG-fMRI was applied mainly to localize the region presumably generating focal interictal discharges in focal epilepsies, EEG-fMRI identified underlying networks in patients with generalized epilepsies and thereby contributed to a better understanding of these epilepsies. In epileptic encephalopathies a specific fingerprint of hemodynamic changes associated with the particular syndrome was detected. The value of the EEG-fMRI technique for diagnosis and investigation of pathogenetic mechanisms of different forms of epilepsy is discussed.

Local MEG networks: the missing link between protein expression and epilepsy in glioma patients?

Connectivity and network analysis in neuroscience has been applied to multiple spatial scales, but the links between these different scales have rarely been investigated. In tumor-related epilepsy, altered network topology is related to behavior, but the molecular basis of these observations is unknown. We elucidate the associations between microscopic features of brain tumors, local network topology, and functional patient status. We hypothesize that expression of proteins related to tumor-related epilepsy is directly correlated with network characteristics of the tumor area. Glioma patients underwent magnetoencephalography, and functional network topology of the tumor area was used to predict tissue protein expression patterns of tumor tissue collected during neurosurgery. Protein expression and network topology were interdependent; in particular between-module connectivity was selectively associated with two epilepsy-related proteins. Total number of seizures was related to both the role of the tumor area in the functional network and to protein expression. Importantly, classification of protein expression was predicted by between-module connectivity with up to 100% accuracy. Thus, network topology may serve as an intermediate level between molecular features of tumor tissue and symptomatology in brain tumor patients, and can potentially be used as a non-invasive marker for microscopic tissue characteristics.