Computational EEG attributes predict response to therapy for epileptic spasms.

OBJECTIVE: We set out to evaluate whether response to treatment for epileptic spasms is associated with specific candidate computational EEG biomarkers, independent of clinical attributes. METHODS: We identified 50 children with epileptic spasms, with pre- and post-treatment overnight video-EEG. After EEG samples were preprocessed in an automated fashion to remove artifacts, we calculated amplitude, power spectrum, functional connectivity, entropy, and long-range temporal correlations (LRTCs). To evaluate the extent to which each feature is independently associated with response and relapse, we conducted logistic and proportional hazards regression, respectively. RESULTS: After statistical adjustment for the duration of epileptic spasms prior to treatment, we observed an association between response and stronger baseline and post-treatment LRTCs (P = 0.042 and P = 0.004, respectively), and higher post-treatment entropy (P = 0.003). On an exploratory basis, freedom from relapse was associated with stronger post-treatment LRTCs (P = 0.006) and higher post-treatment entropy (P = 0.044). CONCLUSION: This study suggests that multiple EEG features-especially LRTCs and entropy-may predict response and relapse. SIGNIFICANCE: This study represents a step toward a more precise approach to measure and predict response to treatment for epileptic spasms.

A multi-center comparison of surgical techniques for corpus Callosotomy in pediatric drug-resistant epilepsy.

OBJECTIVES: Corpus callosotomy (CC) is used to reduce seizures, primarily in patients with generalized drug-resistant epilepsy (DRE). The invasive nature of the procedure contributes to underutilization despite its potential superiority to other palliative procedures. The goal of this study was to use a multi-institutional epilepsy surgery database to characterize the use of CC across participating centers. METHODS: Data were acquired from the Pediatric Epilepsy Research Consortium (PERC) Surgery Database, a prospective observational study collecting data on children 0-18 years referred for surgical evaluation of DRE across 22 U.S. pediatric epilepsy centers. Patient, epilepsy, and surgical characteristics were collected across multiple CC modalities. Outcomes and complications were recorded and analyzed statistically. RESULTS: Eighty-three patients undergoing 85 CC procedures at 14 participating epilepsy centers met inclusion criteria. Mean age at seizure onset was 2.3 years (0-9.4); mean age for Phase I evaluation and surgical intervention were 9.45 (.1-20) and 10.46 (.2-20.6) years, respectively. Generalized seizure types were the most common (59%). Complete CC was performed in 88%. The majority of CC procedures (57%) were via open craniotomy, followed by laser interstitial thermal therapy (LiTT) (20%) and mini-craniotomy/endoscopic (mc/e) (22%). Mean operative times were significantly longer for LiTT, whereas mean estimated blood loss was greater in open cases. Complications occurred in 11 cases (13%) and differed significantly between surgical techniques (p < .001). There was no statistically significant difference in length of postoperative stay across approaches. Mean follow-up was 12.8 months (range 1-39). Favorable Engel outcomes were experienced by 37 (78.7%) of the patients who underwent craniotomy, 10 (58.8%) with LiTT, and 12 (63.2%) with mc/e; these differences were not statistically significant. SIGNIFICANCE: CC is an effective surgical modality for children with DRE. Regardless of surgical modality, complication rates are acceptable and seizure outcomes generally favorable. Newer, less-invasive, surgical approaches may lead to increased adoption of this efficacious therapeutic option for pediatric DRE.

Interrater reliability of interictal EEG waveforms in Lennox-Gastaut Syndrome.

OBJECTIVE: Identification of EEG waveforms is critical for diagnosing Lennox-Gastaut Syndrome (LGS) but is complicated by the progressive nature of the disease. Here, we assess the interrater reliability (IRR) among pediatric epileptologists for classifying EEG waveforms associated with LGS. METHODS: A novel automated algorithm was used to objectively identify epochs of EEG with transient high power, which were termed events of interest (EOIs). The algorithm was applied to EEG from 20 LGS subjects and 20 healthy controls during NREM sleep, and 1350 EOIs were identified. Three raters independently reviewed the EOIs within isolated 15-second EEG segments in a randomized, blinded fashion. For each EOI, the raters assigned a waveform label (spike and slow wave, generalized paroxysmal fast activity, seizure, spindle, vertex, muscle, artifact, nothing, or other) and indicated the perceived subject type (LGS or control). RESULTS: Labeling of subject type had 85% accuracy across all EOIs and an IRR of κ =0.790, suggesting that brief segments of EEG containing high-power waveforms can be reliably classified as pathological or normal. Waveform labels were less consistent, with κ =0.558, and the results were highly variable for different categories of waveforms. Label mismatches typically occurred when one reviewer selected "nothing," suggesting that reviewers had different thresholds for applying named labels. SIGNIFICANCE: Classification of EEG waveforms associated with LGS has weak IRR, due in part to varying thresholds applied during visual review. Computational methods to objectively define EEG biomarkers of LGS may improve IRR and aid clinical decision-making.

Hyperventilation and Seizures: Not a New Sense: A Literature Review.

Hyperventilation and seizures have a long association in the clinical literature and were known to have a relationship long before the electroencephalogram (EEG) was used to record changes in brain activity. As the use of EEG recording progressed, hyperventilation was the first activation method used to assist with diagnosis of epilepsy. Along with slowing of brain activity, hyperventilation can activate epileptiform spiking activity in patients with epilepsy. Currently, hyperventilation is used in standard practice to assist with the diagnosis of epilepsy during EEG recording. Hyperventilation activates epileptiform spiking activity more often than seizures but can trigger clinical seizures in up to 50% of patients with generalized epilepsy. It is more likely to trigger events in children with absence seizures than adults, and it acts as a trigger in patients with focal epilepsy far less often. However, while some clinicians suggest that its diagnostic value is limited, especially in adults with focal epilepsies, others suggest that it is simple, safe, and an important diagnostic tool, even in these patients. This review presents the history of hyperventilation and seizures, its use in the clinical practice, and possible mechanisms involved.

Responsive Neurostimulation in Drug-Resistant Pediatric Epilepsy: Findings From the Epilepsy Surgery Subgroup of the Pediatric Epilepsy Research Consortium.

BACKGROUND: Responsive neurostimulation (RNS), a closed-loop intracranial electrical stimulation system, is a palliative surgical option for patients with drug-resistant epilepsy (DRE). RNS is approved by the US Food and Drug Administration for patients aged ≥18 years with pharmacoresistant partial seizures. The published experience of RNS in children is limited. METHODS: This is a combined prospective and retrospective study of patients aged ≤18 years undergoing RNS placement. Patients were identified from the multicenter Pediatric Epilepsy Research Consortium Surgery Registry from January 2018 to December 2021, and additional data relevant to this study were retrospectively collected and analyzed. RESULTS: Fifty-six patients received RNS during the study period. The mean age at implantation was 14.9 years; the mean duration of epilepsy, 8.1 years; and the mean number of previously trialed antiseizure medications, 4.2. Five patients (9%) previously trialed dietary therapy, and 19 patients (34%) underwent prior surgery. Most patients (70%) underwent invasive electroencephalography evaluation before RNS implantation. Complications occurred in three patients (5.3%) including malpositioned leads or transient weakness. Follow-up (mean 11.7 months) was available for 55 patients (one lost), and four were seizure-free with RNS off. Outcome analysis of stimulation efficacy was available for 51 patients: 33 patients (65%) were responders (≥50% reduction in seizure frequency), including five patients (10%) who were seizure free at follow-up. CONCLUSIONS: For young patients with focal DRE who are not candidates for surgical resection, neuromodulation should be considered. Although RNS is off-label for patients aged <18 years, this multicenter study suggests that it is a safe and effective palliative option for children with focal DRE.

A novel method for dynamically altering the surface area of intracranial EEG electrodes.

Objective.Intracranial electroencephalogram (iEEG) plays a critical role in the treatment of neurological diseases, such as epilepsy and Parkinson's disease, as well as the development of neural prostheses and brain computer interfaces. While electrode geometries vary widely across these applications, the impact of electrode size on iEEG features and morphology is not well understood. Some insight has been gained from computer simulations, as well as experiments in which signals are recorded using electrodes of different sizes concurrently in different brain regions. Here, we introduce a novel method to record from electrodes of different sizes in the exact same location by changing the size of iEEG electrodes after implantation in the brain.Approach.We first present a theoretical model and anin vitrovalidation of the method. We then report the results of anin vivoimplementation in three human subjects with refractory epilepsy. We recorded iEEG data from three different electrode sizes and compared the amplitudes, power spectra, inter-channel correlations, and signal-to-noise ratio (SNR) of interictal epileptiform discharges, i.e. epileptic spikes.Main Results.We found that iEEG amplitude and power decreased as electrode size increased, while inter-channel correlation did not change significantly with electrode size. The SNR of epileptic spikes was generally highest in the smallest electrodes, but 39% of spikes had maximal SNR in larger electrodes. This likely depends on the precise location and spatial spread of each spike.Significance.Overall, this new method enables multi-scale measurements of electrical activity in the human brain that can facilitate our understanding of neurophysiology, treatment of neurological disease, and development of novel technologies.

Integrating transition readiness assessment into clinical practice: Adaptation of the UNC TRXANSITION index into the Cerner electronic medical record.

PURPOSE: To describe the process of developing, and evaluating the feasibility and acceptability of, an EMR-based transition readiness assessment. DESIGN AND METHODS: A Cerner-based version of the UNC TRxANSITION Index was implemented across four pediatric subspecialty clinics: epilepsy, inflammatory bowel disease; type 1 diabetes, oncology survivorship. The feasibility was assessed by each's clinic's ability to meet form completion goals and their assessment rate. Acceptability was assessed via family refusal rate, a staff-completed feedback questionnaire, and whether the form was adopted into routine clinical care after completion of the pilot study. RESULTS: All clinics met form completion goals (N = 10/clinic). The assessment rate ranged from 66 to 100% across clinics. No families refused completion of the form. Most staff (70%) reported completing the form in <10 min. Staff reported on challenges experienced and provided recommendations to streamline administration and enhance clinical care. All staff reported the form helped them identify knowledge gaps in their patients. Two clinics continued using the form following completion of the pilot study. CONCLUSIONS: Implementation was most feasible in clinics that were well-staffed and had lengthier patient visits, however, time and staff resources were the biggest challenges to implementation across clinics. Based on staff feedback to improve efficiency and developmentally-tailor assessment, the form will be divided into Beginner Skills and Advanced Skills. PRACTICAL IMPLICATIONS: Integrating transition readiness assessment into the EMR has the potential to improve clinical care by facilitating staff's ability to efficiently identify knowledge gaps in their transition-aged patients and intervene.

Epilepsy surgery in children with genetic etiologies: A prospective evaluation of current practices and outcomes.

OBJECTIVE: This study assesses current practices and outcomes of epilepsy surgery in children with a genetic etiology. It explores the pre-surgical workup, types of surgeries, and post-surgical outcomes in a broad array of disorders. METHODS: Patients ≤18 years who completed epilepsy surgery and had a known genetic etiology prior to surgical intervention were extrapolated from the Pediatric Epilepsy Research Consortium (PERC) surgery database, across 18 US centers. Data were assessed univariably by neuroimaging and EEG results, genetic group (structural gene, other gene, chromosomal), and curative intent. Outcomes were based on a modified International League Against Epilepsy (ILAE) outcome score. RESULTS: Of 81 children with genetic epilepsy, 72 % had daily seizures when referred for surgery evaluation, which occurred a median of 2.2 years (IQR 0.3, 5.2) after developing drug resistance. Following surgery, 68 % of subjects had >50 % seizure reduction, with 33 % achieving seizure freedom [median follow-up 11 months (IQR 6, 17). Seizure freedom was most common in the monogenic structural group, but significant palliation was present across all groups. Presence of a single EEG focus was associated with a greater likelihood of seizure freedom (p=0.02). SIGNIFICANCE: There are meaningful seizure reductions following epilepsy surgery in the majority of children with a genetic etiology, even in the absence of a single structural lesion and across a broad spectrum of genetic causes. These findings highlight the need for expedited referral for epilepsy surgery and support of a broadened view of which children may benefit from epilepsy surgery, even when the intent is palliative.

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.

Evolution of Cortical Functional Networks in Healthy Infants.

During normal childhood development, functional brain networks evolve over time in parallel with changes in neuronal oscillations. Previous studies have demonstrated differences in network topology with age, particularly in neonates and in cohorts spanning from birth to early adulthood. Here, we evaluate the developmental changes in EEG functional connectivity with a specific focus on the first 2 years of life. Functional connectivity networks (FCNs) were calculated from the EEGs of 240 healthy infants aged 0-2 years during wakefulness and sleep using a cross-correlation-based measure and the weighted phase lag index. Topological features were assessed via network strength, global clustering coefficient, characteristic path length, and small world measures. We found that cross-correlation FCNs maintained a consistent small-world structure, and the connection strengths increased after the first 3 months of infancy. The strongest connections in these networks were consistently located in the frontal and occipital regions across age groups. In the delta and theta bands, weighted phase lag index networks decreased in strength after the first 3 months in both wakefulness and sleep, and a similar result was found in the alpha and beta bands during wakefulness. However, in the alpha band during sleep, FCNs exhibited a significant increase in strength with age, particularly in the 21-24 months age group. During this period, a majority of the strongest connections in the networks were located in frontocentral regions, and a qualitatively similar distribution was seen in the beta band during sleep for subjects older than 3 months. Graph theory analysis suggested a small world structure for weighted phase lag index networks, but to a lesser degree than those calculated using cross-correlation. In general, graph theory metrics showed little change over time, with no significant differences between age groups for the clustering coefficient (wakefulness and sleep), characteristics path length (sleep), and small world measure (sleep). These results suggest that infant FCNs evolve during the first 2 years with more significant changes to network strength than features of the network structure. This study quantifies normal brain networks during infant development and can serve as a baseline for future investigations in health and neurological disease.

Surgical evaluation in children <3 years of age with drug-resistant epilepsy: Patient characteristics, diagnostic utilization, and potential for treatment delays.

OBJECTIVE: Drug-resistant epilepsy (DRE) occurs at higher rates in children <3 years old. Epilepsy surgery is effective, but rarely utilized in young children despite developmental benefits of early seizure freedom. The present study aims to identify unique patient characteristics and evaluation strategies in children <3 years old who undergo epilepsy surgery evaluation as a means to assess contributors and potential solutions to health care disparities in this group. METHODS: The Pediatric Epilepsy Research Consortium Epilepsy Surgery Database, a multicentered, cross-sectional collaboration of 21 US pediatric epilepsy centers, collects prospective data on children <18 years of age referred for epilepsy surgery evaluation. We compared patient characteristics, diagnostic utilization, and surgical treatment between children <3 years old and those older undergoing initial presurgical evaluation. We evaluated patient characteristics leading to delayed referral (>1 year) after DRE diagnosis in the very young. RESULTS: The cohort included 437 children, of whom 71 (16%) were <3 years of age at referral. Children evaluated before the age of 3 years more commonly had abnormal neurological examinations (p = .002) and daily seizures (p = .001). At least one ancillary test was used in 44% of evaluations. Fifty-nine percent were seizure-free following surgery (n = 34), with 35% undergoing limited focal resections. Children with delayed referrals more often had focal aware (p < .001) seizures and recommendation for palliative surgeries (p < .001). SIGNIFICANCE: There are relatively few studies of epilepsy surgery in the very young. Surgery is effective, but may be disproportionally offered to those with severe presentations. Relatively low utilization of ancillary testing may contribute to reduced surgical therapy for those without evident lesions on magnetic resonance imaging. Despite this, a sizeable portion of patients have favorable outcome after focal epilepsy surgery resections.

Scalp EEG markers of normal infant development using visual and computational approaches.

The infant brain is rapidly developing, and these changes are reflected in scalp electroencephalography (EEG) features, including power spectrum and sleep spindle characteristics. These biomarkers not only mirror infant development, but they are also altered by conditions such as epilepsy, autism, developmental delay, and trisomy 21. Prior studies of early development were generally limited by small cohort sizes, lack of a specific focus on infancy (0-2 years), and exclusive use of visual marking for sleep spindles. Therefore, we measured the EEG power spectrum and sleep spindles in 240 infants ranging from 0-24 months. To rigorously assess these metrics, we used both clinical visual assessment and computational techniques, including automated sleep spindle detection. We found that the peak frequency and power of the posterior dominant rhythm (PDR) increased with age, and a corresponding peak occurred in the EEG power spectra. Based on both clinical and computational measures, spindle duration decreased with age, and spindle synchrony increased with age. Our novel metric of spindle asymmetry suggested that peak spindle asymmetry occurs at 6-9 months of age.Clinical Relevance- Here we provide a robust characterization of the development of EEG brain rhythms during infancy. This can be used as a basis of comparison for studies of infant neurological disease, including epilepsy, autism, developmental delay, and trisomy 21.

Automated preprocessing and phase-amplitude coupling analysis of scalp EEG discriminates infantile spasms from controls during wakefulness.

OBJECTIVE: Delta-gamma phase-amplitude coupling in EEG is useful for localizing epileptic sources and to evaluate severity in children with infantile spasms. We (1) develop an automated EEG preprocessing pipeline to clean data using artifact subspace reconstruction (ASR) and independent component (IC) analysis (ICA) and (2) evaluate delta-gamma modulation index (MI) as a method to distinguish children with epileptic spasms (cases) from normal controls during sleep and awake. METHODS: Using 400 scalp EEG datasets (200 sleep, 200 awake) from 100 subjects, we calculated MI after applying high-pass and line-noise filters (Clean 0), and after ASR followed by either conservative (Clean 1) or stringent (Clean 2) artifactual IC rejection. Classification of cases and controls using MI was evaluated with Receiver Operating Characteristics (ROC) to obtain area under curve (AUC). RESULTS: The artifact rejection algorithm reduced raw signal variance by 29-45% and 38-60% for Clean 1 and Clean 2, respectively. MI derived from sleep data, with or without preprocessing, robustly classified the groups (all AUC > 0.98). In contrast, group classification using MI derived from awake data was successful only after Clean 2 (AUC = 0.85). CONCLUSIONS: We have developed an automated EEG preprocessing pipeline to perform artifact rejection and quantify delta-gamma modulation index.

Underrepresented Populations in Pediatric Epilepsy Surgery.

As awareness of pediatric epilepsy increases, accompanied by advancements in technology and research, it is important to identify certain types of patients that are overlooked for surgical management of epilepsy. Identifying these populations will allow us to study and elucidate the factors contributing to the underutilization and/or delayed application of surgical interventions. Demographically, African-American and Hispanic patients, as well as patients of certain Asian ethnicities, have relatively lower rates of undergoing epilepsy surgery than non-Hispanic and white patients. Among patients with epilepsy, those with higher odds of seizure-freedom following surgery are more likely to be referred for surgical evaluation by their neurologists, with the most common diagnosis being lesional focal epilepsy. However, patients with multifocal or generalized epilepsy, genetic etiologies, or normal (non-lesional) brain magnetic resonance imaging (MRI) are less likely be to referred for evaluation for resective surgery. With an increasing number of high-quality imaging modalities to help localize the epileptogenic zone as well as new techniques for both curative and palliative epilepsy surgery, there are very few populations of patients and/or types of epilepsy that should be precluded from evaluation to determine the suitability of epilepsy surgery. Ultimately, a clearer understanding of the populations who are underrepresented among those considered for epilepsy surgery, coupled with further study of the underlying reasons for this trend, will lead to less disparity in access to this critical treatment among patients with epilepsy.

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.

Recurrent seizure-related GRIN1 variant: Molecular mechanism and targeted therapy.

OBJECTIVE: Genetic variants in the GRIN genes that encode N-methyl-D-aspartate receptor (NMDAR) subunits have been identified in various neurodevelopmental disorders, including epilepsy. We identified a GRIN1 variant from an individual with early-onset epileptic encephalopathy, evaluated functional changes to NMDAR properties caused by the variant, and screened FDA-approved therapeutic compounds as potential treatments for the patient. METHODS: Whole exome sequencing identified a missense variant in GRIN1. Electrophysiological recordings were made from Xenopus oocytes and transfected HEK cells to determine the NMDAR biophysical properties as well as the sensitivity to agonists and FDA-approved drugs that inhibit NMDARs. A beta-lactamase reporter assay in transfected HEK cells evaluated the effects of the variant on the NMDAR surface expression. RESULTS: A recurrent de novo missense variant in GRIN1 (c.1923G>A, p.Met641Ile), which encodes the GluN1 subunit, was identified in a pediatric patient with drug-resistant seizures and early-onset epileptic encephalopathy. In vitro analysis indicates that GluN1-M641I containing NMDARs showed enhanced agonist potency and reduced Mg2+ block, which may be associated with the patient's phenotype. Results from screening FDA-approved drugs suggested that GluN1-M641I containing NMDARs are more sensitive to the NMDAR channel blockers memantine, ketamine, and dextromethorphan compared to the wild-type receptors. The addition of memantine to the seizure treatment regimen significantly reduced the patient's seizure burden. INTERPRETATION: Our finding contributes to the understanding of the phenotype-genotype correlations of patients with GRIN1 gene variants, provides a molecular mechanism underlying the actions of this variant, and explores therapeutic strategies for treating GRIN1-related neurological conditions.

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.

Automated detection of ripple oscillations in long-term scalp EEG from patients with infantile spasms.

Objective.Scalp high-frequency oscillations (HFOs) are a promising biomarker of epileptogenicity in infantile spasms (IS) and many other epilepsy syndromes, but prior studies have relied on visual analysis of short segments of data due to the prevalence of artifacts in EEG. Here we set out to robustly characterize the rate and spatial distribution of HFOs in large datasets from IS subjects using fully automated HFO detection techniques.Approach.We prospectively collected long-term scalp EEG data from 12 subjects with IS and 18 healthy controls. For patients with IS, recording began prior to diagnosis and continued through initiation of treatment with adrenocorticotropic hormone (ACTH). The median analyzable EEG duration was 18.2 h for controls and 84.5 h for IS subjects (∼1300 h total). Ripples (80-250 Hz) were detected in all EEG data using an automated algorithm.Main results.HFO rates were substantially higher in patients with IS compared to controls. In IS patients, HFO rates were higher during sleep compared to wakefulness (median 5.5 min-1and 2.9 min-1, respectively;p = 0.002); controls did not exhibit a difference in HFO rate between sleep and wakefulness (median 0.98 min-1and 0.82 min-1, respectively). Spatially, IS patients exhibited significantly higher rates of HFOs in the posterior parasaggital region and significantly lower HFO rates in frontal channels, and this difference was more pronounced during sleep. In IS subjects, ACTH therapy significantly decreased the rate of HFOs.Significance.Here we provide a detailed characterization of the spatial distribution and rates of HFOs associated with IS, which may have relevance for diagnosis and assessment of treatment response. We also demonstrate that our fully automated algorithm can be used to detect HFOs in long-term scalp EEG with sufficient accuracy to clearly discriminate healthy subjects from those with IS.

Management of Infantile Spasms During the COVID-19 Pandemic.

Circumstances of the COVID-19 pandemic have mandated a change to standard management of infantile spasms. On April 6, 2020, the Child Neurology Society issued an online statement of immediate recommendations to streamline diagnosis and treatment of infantile spasms with utilization of telemedicine, outpatient studies, and selection of first-line oral therapies as initial treatment. The rationale for the recommendations and specific guidance including follow-up assessment are provided in this manuscript. These recommendations are indicated as enduring if intended to outlast the pandemic, and limited if intended only for the pandemic health care crisis but may be applicable to future disruptions of health care delivery.