Brain connectivity in West syndrome

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.

Epilepsy and Encephalopathy

BACKGROUND

Epilepsy encompasses more than the predisposition to unprovoked seizures. In children, epileptic activity during (ictal) and between (interictal) seizures has the potential to disrupt normal brain development. The term "epileptic encephalopathy (EE)" refers to the concept that such abnormal activity may contribute to cognitive and behavioral impairments beyond that expected from the underlying cause of the epileptic activity.

METHODS

In this review, we survey the concept of EE across a diverse selection of syndromes to illustrate its broad applicability in pediatric epilepsy. We review experimental evidence that provides mechanistic insights into how epileptic activity has the potential to impact normal brain processes and the development of neural networks. We then discuss opportunities to improve developmental outcomes in epilepsy now and in the future.

RESULTS

Epileptic activity in the brain poses a threat to normal physiology and brain development.

CONCLUSION

Until we have treatments that reliably target and effectively treat the underlying causes of epilepsy, a major goal of management is to prevent epileptic activity from worsening developmental outcomes.

Crucial involvement of fast waves and Delta band in the brain network attributes of infantile epileptic spasms syndrome

Objective

This study aims to describe the characteristics of the brain network attributes in children diagnosed with Infantile Epileptic Spasms Syndrome (IESS) and to determine the influence exerted by adrenocorticotrophic hormone (ACTH) or methylprednisolone (MP) on network attributes.

Methods

In this retrospective cohort study, we recruited 19 infants diagnosed with IESS and 10 healthy subjects as the control from the Pediatric Neurology Department at the Third Affiliated Hospital of Zhengzhou University between October 2019 and December 2020. The first thirty-minute processed electroencephalograms (EEGs) were clipped and filtered into EEG frequency bands (2 s each). A comparative assessment was conducted between the IESS group and the controls as well as the pre- and post-treatment in the IESS group. Mutual information values for each EEG channel were collected and compared including characteristic path length (CPL), node degree (ND), clustering coefficient (CC), and betweenness centrality (BC), based on graph theory.

Results

Comparing the control group, in the IESS group, there was an increase in CPL of the Delta band, and a decrease in ND and CC of the Delta band during the waking period, contrary to those during the sleeping period (P < 0.05), a decreased in CPL of the fast waves and an increase in ND and CC (P < 0.05) in the sleep-wake cycle, and a decrease in ND and CC of the Theta band in the waking phase. Post-treatment compared with the pre-treatment, during the waking ictal phase, there was a noted decrease in CPL in the Delta band and fast waves, while an increase was observed in ND and CC (P < 0.05).

Conclusions

The Delta band and fast waves are crucial components of the network attributes in IESS.

Significance

This investigation provides a precise characterization of the brain network in children afflicted with IESS, and lays the groundwork for predicting the prognosis using graph theory.

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.

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.

Brain Complexity Predicts Response to Adrenocorticotropic Hormone in Infantile Epileptic Spasms Syndrome: A Retrospective Study

INTRODUCTION

Infantile epileptic spasms syndrome (IESS) is an age-specific and severe epileptic encephalopathy. Although adrenocorticotropic hormone (ACTH) is currently considered the preferred first-line treatment, it is not always effective and may cause side effects. Therefore, seeking a reliable biomarker to predict the treatment response could benefit clinicians in modifying treatment options.

METHODS

In this study, the complexities of electroencephalogram (EEG) recordings from 15 control subjects and 40 patients with IESS before and after ACTH therapy were retrospectively reviewed using multiscale entropy (MSE). These 40 patients were divided into responders and nonresponders according to their responses to ACTH.

RESULTS

The EEG complexities of the patients with IESS were significantly lower than those of the healthy controls. A favorable response to treatment showed increasing complexity in the γ band but exhibited a reduction in the β/α-frequency band, and again significantly elevated in the δ band, wherein the latter was prominent in the parieto-occipital regions in particular. Greater reduction in complexity was significantly linked with poorer prognosis in general. Occipital EEG complexities in the γ band revealed optimized performance in recognizing response to the treatment, corresponding to the area under the receiver operating characteristic curves as 0.8621, while complexities of the δ band served as a fair predictor of unfavorable outcomes globally.

CONCLUSION

We suggest that optimizing frequency-specific complexities over critical brain regions may be a promising strategy to facilitate predicting treatment response in IESS.

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.

Brain Magnetic Resonance Imaging Findings in Infantile Spasms

Background: Infantile spasms are an age-specific epileptic disorder. They occur in infancy and early childhood. They can be caused by multiple etiologies. Structural abnormalities represent an important cause of infantile spasms. Brain magnetic resonance imaging (MRI) is one of the integral modalities in the evaluation of this condition. Purpose: The aim of this study is to review and analyze the clinical characteristics and brain MRI findings in a cohort of children diagnosed with infantile spasms. Material and Methods: A cohort of fifty-six children diagnosed with infantile spasms in infancy and early childhood was included. All of them underwent brain MRI for evaluation. The study was conducted in the period from January 2016 to January 2020. Results: Females comprised 57% of the cohort. The mean age for seizure onset was 5.9 months (SD 2.7). Forty-one patients (73%) had active epilepsy, and 51% were diagnosed with global developmental delay. Consanguinity was present in 59% of the cohort. Most of the follow-up MRIs showed structural abnormalities (84%). Hypoxia was reported in 17% of MRIs. Malformations of cortical development were seen in five patients. Brain MRI findings were normal in 16% of patients, and delayed myelination was seen in nineteen patients. Most of the children with active epilepsy (64%) and developmental delay (82%) had an abnormal brain MRI. It was noticed that abnormal second brain MRIs were more likely to be associated with active epilepsy and developmental delay (p = 0.05). Conclusions: Brain MRI is an integral part of infantile spasms’ clinical evaluation. Infantile spasms and abnormal brain MRI can be associated with active epilepsy and global developmental delay.

Early development of sleep and brain functional connectivity in term-born and preterm infants

The proper development of sleep and sleep-wake rhythms during early neonatal life is crucial to lifelong neurological well-being. Recent data suggests that infants who have poor quality sleep demonstrate a risk for impaired neurocognitive outcomes. Sleep ontogenesis is a complex process, whereby alternations between rudimentary brain states-active vs. wake and active sleep vs. quiet sleep-mature during the last trimester of pregnancy. If the infant is born preterm, much of this process occurs in the neonatal intensive care unit, where environmental conditions might interfere with sleep. Functional brain connectivity (FC), which reflects the brain's ability to process and integrate information, may become impaired, with ensuing risks of compromised neurodevelopment. However, the specific mechanisms linking sleep ontogenesis to the emergence of FC are poorly understood and have received little investigation, mainly due to the challenges of studying causal links between developmental phenomena and assessing FC in newborn infants. Recent advancements in infant neuromonitoring and neuroimaging strategies will allow for the design of interventions to improve infant sleep quality and quantity. This review discusses how sleep and FC develop in early life, the dynamic relationship between sleep, preterm birth, and FC, and the challenges associated with understanding these processes. IMPACT: Sleep in early life is essential for proper functional brain development, which is essential for the brain to integrate and process information. This process may be impaired in infants born preterm. The connection between preterm birth, early development of brain functional connectivity, and sleep is poorly understood. This review discusses how sleep and brain functional connectivity develop in early life, how these processes might become impaired, and the challenges associated with understanding these processes. Potential solutions to these challenges are presented to provide direction for future research.

Cortical Activity During Postural Recovery in Response to Predictable and Unpredictable Perturbations in Healthy Young and Older Adults: A Quantitative EEG Assessment

Introduction:

To investigate the effects of predictable and unpredictable external perturbations on cortical activity in healthy young and older adults.

Methods:

Twenty healthy older and 19 healthy young adults were exposed to predictable and unpredictable external perturbations, and their cortical activity upon postural recovery was measured using a 32-channel quantitative encephalography. The absolute spectral power and coherence z-scores of cortical waves were analyzed through a 3-way mixed ANOVA.

Results:

During postural recovery from predictable perturbations, older adults exhibited higher frontoparietal beta power and higher alpha and beta coherence during the late-phase recovery than the young individuals. After unpredictable perturbations, the older group showed lower alpha power in the early phase and higher beta power in the late phase as compared to the young group. Results for the group × time and group × location interactions in the older group showed a higher alpha and beta coherence over the late phase, a higher alpha coherence in F3–P3 and F4–P4 regions, and a higher beta coherence in the F4–P4 region compared to the younger group.

Conclusion:

Our results revealed that the cortical activation after external perturbations increases with aging, particularly in frontoparietal areas. A shift from automatic (subcortical level) to attentional (cortical level) processing may reflect the contribution of attentional resources for postural recovery from an external threat in older individuals.

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.

Infant functional networks are modulated by state of consciousness and circadian rhythm

Functional connectivity networks are valuable tools for studying development, cognition, and disease in the infant brain. In adults, such networks are modulated by the state of consciousness and the circadian rhythm; however, it is unknown if infant brain networks exhibit similar variation, given the unique temporal properties of infant sleep and circadian patterning. To address this, we analyzed functional connectivity networks calculated from long-term EEG recordings (average duration 20.8 hr) from 19 healthy infants. Networks were subject specific, as intersubject correlations between weighted adjacency matrices were low. However, within individual subjects, both sleep and wake networks were stable over time, with stronger functional connectivity during sleep than wakefulness. Principal component analysis revealed the presence of two dominant networks; visual sleep scoring confirmed that these corresponded to sleep and wakefulness. Lastly, we found that network strength, degree, clustering coefficient, and path length significantly varied with time of day, when measured in either wakefulness or sleep at the group level. Together, these results suggest that modulation of healthy functional networks occurs over ∼24 hr and is robust and repeatable. Accounting for such temporal periodicities may improve the physiological interpretation and use of functional connectivity analysis to investigate brain function in health and disease.

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.

Electroencephalography complexity in infantile spasms and its association with treatment response

OBJECTIVE

To investigate the potential of EEG multiscale entropy and complexity as biomarkers in infantile spasms.

METHODS

We collected EEG data retrospectively from 16 newly diagnosed patients, 16 age- and gender-matched healthy controls, and 15 drug-resistant patients. The multiscale entropy (MSE) and total EEG complexity before anti-epileptic drug (AED) treatment, before adrenocorticotropic hormone (ACTH) treatment, 14 days after ACTH therapy, and after 6 months of follow-up were calculated.

RESULTS

The total EEG complexity of 16 newly diagnosed infantile spasms patients was lower than the 16 healthy controls (median [IQR]: 351.5 [323.1-388.1] vs 461.6 [407.7-583.4]). The total EEG complexity before treatment was higher in the six patients with good response to AED than the 10 patients without response (median [IQR]: 410.0 [388.1-475.0] vs 344.5 [319.6-352.0]). The total EEG complexity before and after 14-days of ACTH therapy was not different between 13 ACTH therapy responders and nine non-responders. After 6-months follow-up, the total EEG complexity of ACTH therapy responders were higher than non-responders (median [IQR]: 598.5 [517.4-623.3] vs 448.6 [347.1-536.3]).

CONCLUSIONS

The total EEG complexity before AED and 6 months after ACTH are associated with spasm-freedom.

SIGNIFICANCE

The total EEG complexity is a potential biomarker to predict and monitor the treatment effect in infantile spasms.

Improvement of brain function after surgery in infants with posterior quadrant cortical dysplasia

OBJECTIVE

To reveal whether neurodevelopmental outcome of infants after epilepsy surgery can be quantitatively assessed by electroencephalography (EEG) functional connectivity analysis.

METHODS

We enrolled 13 infants with posterior quadrant dysplasia aged <2 years who were treated using posterior quadrantectomy and 21 age-matched infants. EEG was performed both before and one year after surgery. Developmental quotient (DQ) was assessed both before and 3 years after surgery. The phase lag index (PLI) of three different pairs of electrodes in the nonsurgical hemisphere, i.e., the anterior short distance (ASD), posterior short distance (PSD), and long distance (LD) pairs, were calculated as indices of brain connectivity. The relationship between the PLI and DQ was evaluated.

RESULTS

Overall, 77% infants experienced seizure freedom after surgery. The beta- and gamma- range PLI of PSD pairs increased preoperatively. All these pairs normalized postoperatively. Simple linear regression analysis revealed a significant relationship between the postoperative DQ and the postoperative beta-band PLI of ASD pairs.

CONCLUSION

Preoperative abnormal hyper-connectivity was normalized to the control level after surgery. The postoperative hyperconnectivity was associated with long-term neurodevelopmental improvement.

SIGNIFICANCE

PLI quantifies neurodevelopmental improvements after posterior quadrantectomy.

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.

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.

Increased electroencephalography connectivity precedes epileptic spasm onset in infants with tuberous sclerosis complex

OBJECTIVE

To identify whether abnormal electroencephalography (EEG) connectivity is present before the onset of epileptic spasms (ES) in infants with tuberous sclerosis complex (TSC).

METHODS

Scalp EEG recordings were collected prospectively in infants diagnosed with TSC in the first year of life. This study compared the earliest recorded EEG from infants prior to ES onset (n = 16) and from infants who did not develop ES (n = 28). Five minutes of stage II or quiet sleep was clipped and filtered into canonical EEG frequency bands. Mutual information values between each pair of EEG channels were compared directly and used as a weighted graph to calculate graph measures of global efficiency, characteristic path length, average clustering coefficient, and modularity.

RESULTS

At the group level, infants who later developed ES had increased EEG connectivity in sleep. They had higher mutual information values between most EEG channels in all frequency bands adjusted for age. Infants who later developed ES had higher global efficiency and average clustering coefficients, shorter characteristic path lengths, and lower modularity across most frequency bands adjusted for age. This suggests that infants who went on to develop ES had increased local and long-range EEG connectivity with less segregation of graph regions into distinct modules.

SIGNIFICANCE

This study suggests that increased neural connectivity precedes clinical ES onset in a cohort of infants with TSC. Overconnectivity may reflect progressive pathologic network synchronization culminating in generalized ES. Further research is needed before scalp EEG connectivity measures can be used as a potential biomarker of ES risk and treatment response in pre-symptomatic infants with TSC.

Functional Connectivity in Term Neonates With Hypoxic-Ischemic Encephalopathy Undergoing Therapeutic Hypothermia

BACKGROUND

We investigated whether therapeutic hypothermia and rewarming impact functional connectivity using electroencephalography (EEG) as a measure in neonates with hypoxic-ischemic encephalopathy. We hypothesized that EEG coherence and voltage correlations would be lower and phase lag greater in infants with hypoxic-ischemic encephalopathy than control subjects and that functional connectivity would evolve during therapeutic hypothermia with the greatest improvement occurring during rewarming.

METHODS

This study was a retrospective study of 14 term neonates (greater than 37 weeks) with moderate hypoxic-ischemic encephalopathy who underwent therapeutic hypothermia and rewarming. Continuous EEG and video monitoring was conducted for 96 hours during therapeutic hypothermia and rewarming. The primary quantitative EEG measures of functional connectivity were coherence, phase lag, and voltage correlations. These EEG parameters were compared with a cohort of normal age-matched neonates.

RESULTS

Neonates with hypoxic-ischemic encephalopathy had marked decreases in power, coherences, and voltage correlation and increases in phase lag when compared with control neonates. However, there were no significant changes in these measures between therapeutic hypothermia and rewarming.

CONCLUSIONS

Neonates with hypoxic-ischemic encephalopathy demonstrate significant abnormalities in functional connectivity compared with control subjects. These abnormalities persist through therapeutic hypothermia and rewarming and are not altered after rewarming. Although hypoxic-ischemic encephalopathy is associated with impaired functional brain connectivity, there is no evidence, using quantitative EEG measures, that therapeutic hypothermia or rewarming either improves or exacerbates these abnormalities in connectivity.

Functional brain connectivity in electrical status epilepticus in sleep

Electrical status epilepticus in sleep (ESES) is an age-related, self-limited epileptic encephalopathy. The syndrome is characterized by cognitive and behavioral abnormalities and a specific EEG pattern of continuous spikes and waves during slow-wave sleep. While spikes and sharp waves are known to result in transient cognitive impairment during learning and memory tasks performed during the waking state, the effect of epileptiform discharges during sleep on cognition and behavior is unclear. There is increasing evidence that abnormalities of coherence, a measure of the consistency of the phase difference between two EEG signals when compared over time, is an important feature of brain oscillations and plays a role in cognition and behavior. The objective of this study was to determine whether coherence of EEG activity is altered during slow-wave sleep in children with ESES when compared to typically developing children. We examined coherence during epochs of ESES versus epochs when ESES was not present. In addition, we compared coherence during slow-wave sleep between typically developing children and children with ESES. ESES was associated with remarkably high coherences at all bandwidths and most electrode pairs. While the high coherence was largely attributed to the spikes and spike-and-wave discharge, activity between spikes and spike-and-wave discharge also demonstrated high coherence. This study indicates that EEG coherence during ESES is relatively high. Whether these increases in coherence correlate with the cognitive and behavioral abnormalities seen in children with this EEG pattern remains to be determined.

Longitudinal brain functional and structural connectivity changes after hemispherotomy in two pediatric patients with drug-resistant epilepsy

The main focus of the present study was to explore the longitudinal changes in the brain executive control system and default mode network after hemispherotomy. Resting-state functional magnetic resonance imaging and diffusion tensor imaging were collected in two children with drug-resistnt epilepsy underwent hemispherotomy. Two patients with different curative effects showed different trajectories of brain connectivity after surgery. The failed hemispherotomy might be due to the fact that the synchrony of epileptic neurons in both hemispheres is preserved by residual neural pathways. Loss of interhemispheric correlations with increased intrahemispheric correlations can be considered as neural marker for evaluating the success of hemispherotomy.

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.

Intrinsic Functional Hypoconnectivity in Core Neurocognitive Networks Suggests Central Nervous System Pathology in Patients with Myalgic Encephalomyelitis: A Pilot Study

Exact low resolution electromagnetic tomography (eLORETA) was recorded from nineteen EEG channels in nine patients with myalgic encephalomyelitis (ME) and 9 healthy controls to assess current source density and functional connectivity, a physiological measure of similarity between pairs of distributed regions of interest, between groups. Current source density and functional connectivity were measured using eLORETA software. We found significantly decreased eLORETA source analysis oscillations in the occipital, parietal, posterior cingulate, and posterior temporal lobes in Alpha and Alpha-2. For connectivity analysis, we assessed functional connectivity within Menon triple network model of neuropathology. We found support for all three networks of the triple network model, namely the central executive network (CEN), salience network (SN), and the default mode network (DMN) indicating hypo-connectivity in the Delta, Alpha, and Alpha-2 frequency bands in patients with ME compared to controls. In addition to the current source density resting state dysfunction in the occipital, parietal, posterior temporal and posterior cingulate, the disrupted connectivity of the CEN, SN, and DMN appears to be involved in cognitive impairment for patients with ME. This research suggests that disruptions in these regions and networks could be a neurobiological feature of the disorder, representing underlying neural dysfunction.

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.

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

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