Electroencephalographic spectral power as a marker of cortical function and disease severity in girls with Rett syndrome

Background

Rett syndrome is a neurodevelopmental disorder caused by a mutation in the X-linked MECP2 gene. Individuals with Rett syndrome typically develop normally until around 18 months of age before undergoing a developmental regression, and the disorder can lead to cognitive, motor, sensory, and autonomic dysfunction. Understanding the mechanism of developmental regression represents a unique challenge when viewed through a neuroscience lens. Are circuits that were previously established erased, and are new ones built to supplant old ones? One way to examine circuit-level changes is with the use of electroencephalography (EEG). Previous studies of the EEG in individuals with Rett syndrome have focused on morphological characteristics, but few have explored spectral power, including power as an index of brain function or disease severity. This study sought to determine if EEG power differs in girls with Rett syndrome and typically developing girls and among girls with Rett syndrome based on various clinical characteristics in order to better understand neural connectivity and cortical organization in individuals with this disorder.

Methods

Resting state EEG data were acquired from girls with Rett syndrome (n = 57) and typically developing children without Rett syndrome (n = 37). Clinical data were also collected for girls with Rett syndrome. EEG power across several brain regions in numerous frequency bands was then compared between girls with Rett syndrome and typically developing children and power in girls with Rett syndrome was compared based on these clinical measures. 1/ƒ slope was also compared between groups.

Results

Girls with Rett syndrome demonstrate significantly lower power in the middle frequency bands across multiple brain regions. Additionally, girls with Rett syndrome that are postregression demonstrate significantly higher power in the lower frequency delta and theta bands and a significantly more negative slope of the power spectrum. Increased power in these bands, as well as a more negative 1/ƒ slope, trended with lower cognitive assessment scores.

Conclusions

Increased power in lower frequency bands is consistent with previous studies demonstrating a “slowing” of the background EEG in Rett syndrome. This increase, particularly in the delta band, could represent abnormal cortical inhibition due to dysfunctional GABAergic signaling and could potentially be used as a marker of severity due to associations with more severe Rett syndrome phenotypes.

BEAPP: The Batch Electroencephalography Automated Processing Platform

Electroencephalography (EEG) offers information about brain function relevant to a variety of neurologic and neuropsychiatric disorders. EEG contains complex, high-temporal-resolution information, and computational assessment maximizes our potential to glean insight from this information. Here we present the Batch EEG Automated Processing Platform (BEAPP), an automated, flexible EEG processing platform incorporating freely available software tools for batch processing of multiple EEG files across multiple processing steps. BEAPP does not prescribe a specified EEG processing pipeline; instead, it allows users to choose from a menu of options for EEG processing, including steps to manage EEG files collected across multiple acquisition setups (e.g., for multisite studies), minimize artifact, segment continuous and/or event-related EEG, and perform basic analyses. Overall, BEAPP aims to streamline batch EEG processing, improve accessibility to computational EEG assessment, and increase reproducibility of results.

Classification of respiratory disturbances in Rett Syndrome patients using Restricted Boltzmann Machine

Rett syndrome (RTT) is a severe neurodevelopmental disorder that can cause pervasive wakeful respiratory disturbances that include tachypnea, breath-holding, and central apnea. Quantitative analysis of these respiratory disturbances in RTT is considered a promising outcome measure for clinical trials. Currently, machine learning methodologies have not been employed to automate the classification of RTT respiratory disturbances. In this paper, we propose using temporal, flow, and autocorrelation features taken from the respiratory inductance plethsymography chest signal. We tested the performance of six classifiers including: Support Vector Machine, Restricted-Boltzmann-Machine, Back-propagation, Levenberg-Marquardt, and Decision-Fusion. We evaluate this classification in two modalities: (1) a subject-independent modality (leave-one-subject-out) obtaining the best F1 score in 93.67%, and (2) a trial-independent modality (leave-one-trial-out per subject) obtaining the best F1 score in 78.21%.

Placebo-controlled crossover assessment of mecasermin for the treatment of Rett syndrome

Objective

To measure the efficacy of mecasermin (recombinant human insulin-like growth factor 1, rhIGF-1), for treating symptoms of Rett syndrome (RTT) in a pediatric population using a double-blind crossover study design.

Methods

Thirty girls with classic RTT in postregression stage were randomly assigned to placebo or rhIGF-1 in treatment period 1 and crossed over to the opposite assignment for period 2 (both 20 weeks), separated by a 28-week washout period. The primary endpoints were as follows: Anxiety Depression and Mood Scale (ADAMS) Social Avoidance subscale, Rett Syndrome Behaviour Questionnaire (RSBQ) Fear/Anxiety subscale, Parent Target Symptom Visual Analog Scale (PTSVAS) top three concerns, Clinical Global Impression (CGI), Parent Global Impression (PGI), and the Kerr severity scale. Cardiorespiratory- and electroencephalography (EEG)-based biomarkers were also analyzed.

Results

There were no significant differences between randomization groups. The majority of AEs were mild to moderate, although 12 episodes of serious AEs occurred. The Kerr severity scale, ADAMS Depressed Mood subscale, Visual Analog Scale Hyperventilation, and delta average power change scores significantly increased, implying worsening of symptoms. Electroencephalography (EEG) parameters also deteriorated. A secondary analysis of subjects who were not involved in a placebo recall confirmed most of these findings. However, it also revealed improvements on a measure of stereotypic behavior and another of social communication.

Interpretation

As in the phase 1 trial, rhIGF-1 was safe; however, the drug did not reveal significant improvement, and some parameters worsened.

EEG power at 3 months in infants at high familial risk for autism

BACKGROUND

Alterations in brain development during infancy may precede the behavioral manifestation of developmental disorders. Infants at increased risk for autism are also at increased risk for other developmental disorders, including, quite commonly, language disorders. Here we assess the extent to which electroencephalographic (EEG) differences in infants at high versus low familial risk for autism are present by 3 months of age, and elucidate the functional significance of EEG power at 3 months in predicting later development.

METHODS

EEG data were acquired at 3 months in infant siblings of children with autism (high risk; n = 29) and infant siblings of typically developing children (low risk; n = 19) as part of a prospective, longitudinal investigation. Development across multiple domains was assessed at 6, 9, 12, 18, 24, and 36 months. Diagnosis of autism was determined at 18-36 months. We assessed relationships between 3-month-olds' frontal EEG power and autism risk, autism outcome, language development, and development in other domains.

RESULTS

Infants at high familial risk for autism had reduced frontal power at 3 months compared to infants at low familial risk for autism, across several frequency bands. Reduced frontal high-alpha power at 3 months was robustly associated with poorer expressive language at 12 months.

CONCLUSIONS

Reduced frontal power at 3 months may indicate increased risk for reduced expressive language skills at 12 months. This finding aligns with prior studies suggesting reduced power is a marker for atypical brain function, and infants at familial risk for autism are also at increased risk for altered developmental functioning in non-autism-specific domains.

Detecting autonomic response to pain in Rett syndrome

OBJECTIVE

To quantify pain response in girls affected by Rett syndrome (RTT) using electrodermal activity (EDA), a measure of skin conductance, reflecting sympathetic activity known to be modulated by physical and environmental stress.

METHODS

EDA increase, heart rate (HR) increase and Face Legs Activity Cry Consolability (FLACC) values calculated during venipuncture (invasive) and vital signs collection (non-invasive) events were compared with values calculated during a prior baseline and a RTT clinical severity score (CSS).

RESULTS

EDA and HR increase were significantly higher than baseline during venipuncture only and not significantly correlated with FLACC or CSS. EDA increase was the most sensitive measure of pain response.

CONCLUSIONS

These preliminary findings revealed that motor impairment might bias non-verbal pain scales, underscore the importance of using autonomic measures when assessing pain and warrant further investigation into the utility of using EDA to objectively quantify RTT pain response to inform future RTT pain management.

Anxiety-like behavior in Rett syndrome: characteristics and assessment by anxiety scales

Background

Rett syndrome (RTT) is a severe neurodevelopmental disorder characterized by regression of language and motor skills, cognitive impairment, and frequent seizures. Although the diagnostic criteria focus on communication, motor impairments, and hand stereotypies, behavioral abnormalities are a prevalent and disabling component of the RTT phenotype. Among these problematic behaviors, anxiety is a prominent symptom. While the introduction of the Rett Syndrome Behavioral Questionnaire (RSBQ) represented a major advancement in the field, no systematic characterization of anxious behavior using the RSBQ or other standardized measures has been reported.

Methods

This study examined the profiles of anxious behavior in a sample of 74 girls with RTT, with a focus on identifying the instrument with the best psychometric properties in this population. The parent-rated RSBQ, Anxiety, Depression, and Mood Scale (ADAMS), and Aberrant Behavior Checklist-Community (ABC-C), two instruments previously employed in children with neurodevelopmental disorders, were analyzed in terms of score profiles, relationship with age and clinical severity, reliability, concurrent validity, and functional implications. The latter were determined by regression analyses with the Vineland Adaptive Behavior Scales-Second Edition (Vineland-II) and the Child Health Questionnaire (CHQ), a quality of life measure validated in RTT.

Results

We found that scores on anxiety subscales were intermediate in range with respect to other behavioral constructs measured by the RSBQ, ADAMS, and ABC-C. Age did not affect scores, and severity of general anxiety was inversely correlated with clinical severity. We demonstrated that the internal consistency of the anxiety-related subscales were among the highest. Test-retest and intra-rater reliability was superior for the ADAMS subscales. Convergent and discriminant validity were measured by inter-scale correlations, which showed the best profile for the social anxiety subscales. Of these, only the ADAMS Social Avoidance showed correlation with quality of life.

Conclusions

We conclude that anxiety-like behavior is a prominent component of RTT’s behavioral phenotype, which affects predominantly children with less severe neurologic impairment and has functional consequences. Based on available data on standardized instruments, the ADAMS and in particular its Social Avoidance subscale has the best psychometric properties and functional correlates that make it suitable for clinical and research applications.

Continuous quantitative monitoring of cerebral oxygen metabolism in neonates by ventilator-gated analysis of NIRS recordings

Oxidative stress during fetal development, delivery, or early postnatal life is a major cause of neuropathology, as both hypoxic and hyperoxic insults can significantly damage the developing brain. Despite the obvious need for reliable cerebral oxygenation monitoring, no technology currently exists to monitor cerebral oxygen metabolism continuously and noninvasively in infants at high risk for developing brain injury. Consequently, a rational approach to titrating oxygen supply to cerebral oxygen demand - and thus avoiding hyperoxic or hypoxic insults - is currently lacking. We present a promising method to close this crucial technology gap in the important case of neonates on conventional ventilators. By using cerebral near-infrared spectroscopy and signals from conventional ventilators, along with arterial oxygen saturation, we derive continuous (breath-by-breath) estimates of cerebral venous oxygen saturation, cerebral oxygen extraction fraction, cerebral blood flow, and cerebral metabolic rate of oxygen. The resultant estimates compare very favorably to previously reported data obtained by non-continuous and invasive means from preterm infants in neonatal critical care.

REPRODUCIBILITY OF TRIAL-BASED FUNCTIONAL MRI ON MOTOR IMAGERY

The investigation of the reproducibility in functional MRI (fMRI) is an important step in the quantification and analysis of paradigm-related brain activation. This article reports on reproducibility of cortical activation characterized by repeated fMRI runs (10 times) during the performance of a motor imagery and a passive auditory stimulation as a control task. Two parameters, the size of activation and BOLD signal contrast, were measured from regions-of-interest for 10 subjects across different threshold conditions. The variability of these parameters was normalized with respect to the mean obtained from 10 runs, and represented as the intrasession variability. It was found that the variability was significantly lower in the measurement of BOLD signal contrast as compared to the measurement of the size of activation. The variability of the activation volume measurement was greater in the motor imagery task than in the auditory tasks across all thresholds. This task-dependent difference was not apparent from the measurement of the BOLD signal contrast. The presence of threshold dependence in the variability measurement was also examined, but no such dependency was found. The results suggest that a measurement of BOLD signal itself is a more reliable indicator of paradigm-related brain activation during repeated fMRI scans.

Atlas-based multichannel monitoring of functional MRI signals in real-time: automated approach

We report an automated method to simultaneously monitor blood-oxygenation-level-dependent (BOLD) MR signals from multiple cortical areas in real-time. Individual brain anatomy was normalized and registered to a pre-segmented atlas in standardized anatomical space. Subsequently, using real-time fMRI (rtfMRI) data acquisition, localized BOLD signals were measured and displayed from user-selected areas labeled with anatomical and Brodmann's Area (BA) nomenclature. The method was tested on healthy volunteers during the performance of hand motor and internal speech generation tasks employing a trial-based design. Our data normalization and registration algorithm, along with image reconstruction, movement correction and a data display routine were executed with enough processing and communication bandwidth necessary for real-time operation. Task-specific BOLD signals were observed from the hand motor and language areas. One of the study participants was allowed to freely engage in hand clenching tasks, and associated brain activities were detected from the motor-related neural substrates without prior knowledge of the task onset time. The proposed method may be applied to various applications such as neurofeedback, brain-computer-interface, and functional mapping for surgical planning where real-time monitoring of region-specific brain activity is needed.

Increasing cortical activity in auditory areas through neurofeedback functional magnetic resonance imaging

We report a functional magnetic resonance imaging method to deliver task-specific brain activities as biofeedback signals to guide individuals to increase cortical activity in auditory areas during sound stimulation. A total of 11 study participants underwent multiple functional magnetic resonance imaging scan sessions, while the changes in the activated cortical volume within the primary and secondary auditory areas were fed back to them between scan sessions. On the basis of the feedback information, participants attempted to increase the number of significant voxels during the subsequent trial sessions by adjusting their level of attention to the auditory stimuli. Results showed that the group of individuals who received the feedback were able to increase the activation volume and blood oxygenation level-dependent signal to a greater degree than the control group.