Development of Neural Response to Novel Sounds in Fragile X Syndrome: Potential Biomarkers

Rodents' visual gamma as a biomarker of pathological neural conditions

Neural gamma oscillations (indicatively 30-100 Hz) are ubiquitous: they are associated with a broad range of functions in multiple cortical areas and across many animal species. Experimental and computational works established gamma rhythms as a global emergent property of neuronal networks generated by the balanced and coordinated interaction of excitation and inhibition. Coherently, gamma activity is strongly influenced by the alterations of synaptic dynamics which are often associated with pathological neural dysfunctions. We argue therefore that these oscillations are an optimal biomarker for probing the mechanism of cortical dysfunctions. Gamma oscillations are also highly sensitive to external stimuli in sensory cortices, especially the primary visual cortex (V1), where the stimulus dependence of gamma oscillations has been thoroughly investigated. Gamma manipulation by visual stimuli tuning is particularly easy in rodents, which have become a standard animal model for investigating the effects of network alterations on gamma oscillations. Overall, gamma in the rodents' visual cortex offers an accessible probe on dysfunctional information processing in pathological conditions. Beyond vision-related dysfunctions, alterations of gamma oscillations in rodents were indeed also reported in neural deficits such as migraine, epilepsy and neurodegenerative or neuropsychiatric conditions such as Alzheimer's, schizophrenia and autism spectrum disorders. Altogether, the connections between visual cortical gamma activity and physio-pathological conditions in rodent models underscore the potential of gamma oscillations as markers of neuronal (dys)functioning.

Validating brain activity measures as reliable indicators of individual diagnostic group and genetically mediated sub-group membership Fragile X Syndrome

Recent failures translating preclinical behavioral treatment effects to positive clinical trial results in humans with Fragile X Syndrome (FXS) support refocusing attention on biological pathways and associated measures, such as electroencephalography (EEG), with strong translational potential and small molecule target engagement. This study utilized guided machine learning to test promising translational EEG measures (resting power and auditory chirp oscillatory variables) in a large heterogeneous sample of individuals with FXS to identify best performing EEG variables for reliably separating individuals with FXS, and genetically-mediated subgroups within FXS, from typically developing controls. Best performing variables included resting relative frontal theta power, all combined whole-head resting power bands, posterior peak alpha frequency (PAF), combined PAF across all measured regions, combined theta, alpha, and gamma power during the chirp, and all combined chirp oscillatory variables. Sub-group analyses best discriminated non-mosaic FXS males via whole-head resting relative power (AUC = .9250), even with data reduced to a 20-channel clinical montage. FXS females were nearly perfectly discriminated by combined theta, alpha, and gamma power during the chirp (AUC = .9522). Results support use of resting and auditory oscillatory tasks to reliably identify neural deficit in FXS, and to identify specific translational targets for genetically-mediated sub-groups, supporting potential points for stratification.

Disease-Targeted Treatment Translation in Fragile X Syndrome as a Model for Neurodevelopmental Disorders

Fragile X syndrome (FXS), the most common monogenic cause of intellectual disability and autism spectrum disorder, has been one of the first neurodevelopmental disorders in which molecular and neuronal mechanisms of disease were identified, leading to the concept of targeting the underlying disease to reverse symptoms. Translating findings in basic science and animal models to humans with FXS has proven difficult. These challenges have prompted the FXS field to organize to build interlocking projects and initiatives to improve consistency of supportive care, make clinical research accessible to families, generate collaborative research on natural history, outcome measures and biomarkers, and create clinical trial consortia and novel trial designs. This work has resulted in improved success in recent clinical trials, providing key steps toward regulatory approval of disease-targeted treatments for FXS. Progress in the FXS field has informed translation of transformative new disease-targeted therapies for other monogenic neurodevelopmental disorders.

Absence of the Fragile X messenger ribonucleoprotein alters response patterns to sounds in the auditory midbrain

Among the different autism spectrum disorders, Fragile X syndrome (FXS) is the most common inherited cause of intellectual disability. Sensory and especially auditory hypersensitivity is a key symptom in patients, which is well mimicked in the Fmr1 -/- mouse model. However, the physiological mechanisms underlying FXS’s acoustic hypersensitivity in particular remain poorly understood. Here, we categorized spike response patterns to pure tones of different frequencies and intensities from neurons in the inferior colliculus (IC), a central integrator in the ascending auditory pathway. Based on this categorization we analyzed differences in response patterns between IC neurons of wild-type (WT) and Fmr1 -/- mice. Our results report broadening of frequency tuning, an increased firing in response to monaural as well as binaural stimuli, an altered balance of excitation-inhibition, and reduced response latencies, all expected features of acoustic hypersensitivity. Furthermore, we noticed that all neuronal response types in Fmr1 -/- mice displayed enhanced offset-rebound activity outside their excitatory frequency response area. These results provide evidence that the loss of Fmr1 not only increases spike responses in IC neurons similar to auditory brainstem neurons, but also changes response patterns such as offset spiking. One can speculate this to be an underlying aspect of the receptive language problems associated with Fragile X syndrome.

Independent evaluation of the harvard automated processing pipeline for Electroencephalography 1.0 using multi-site EEG data from children with Fragile X Syndrome

BACKGROUND

The Harvard Automatic Processing Pipeline for Electroencephalography (HAPPE) is a computerized EEG data processing pipeline designed for multiple site analysis of populations with neurodevelopmental disorders. This pipeline has been validated in-house by the developers but external testing using real-world datasets remains to be done.

NEW METHOD

Resting and auditory event-related EEG data from 29 children ages 3-6 years with Fragile X Syndrome as well as simulated EEG data was used to evaluate HAPPE's noise reduction techniques, data standardization features, and data integration compared to traditional manualized processing.

RESULTS

For the real EEG data, HAPPE pipeline showed greater trials retained, greater variance retained through independent component analysis (ICA) component removal, and smaller kurtosis than the manual pipeline; the manual pipeline had a significantly larger signal-to-noise ratio (SNR). For simulated EEG data, correlation between the pure signal and processed data was significantly higher for manually-processed data compared to HAPPE-processed data. Hierarchical linear modeling showed greater signal recovery in the manual pipeline with the exception of the gamma band signal which showed mixed results.

COMPARISON WITH EXISTING METHODS

SNR and simulated signal retention was significantly greater in the manually-processed data than the HAPPE-processed data. Signal reduction may negatively affect outcome measures.

CONCLUSIONS

The HAPPE pipeline benefits from less active processing time and artifact reduction without removing segments. However, HAPPE may bias toward elimination of noise at the cost of signal. Recommended implementation of the HAPPE pipeline for neurodevelopmental populations depends on the goals and priorities of the research.

Fragile X Syndrome: Supportive Treatment, Unmet Needs, and Paths to Novel Interventions and Disease-Targeted Therapies

Fragile X syndrome (FXS), as a monogenic cause of intellectual disability and autism spectrum disorder, has been one of the first neurodevelopmental disorders in which molecular and neuronal mechanisms of disease have been identified, leading to the concept of targeting the underlying disease to reverse symptoms. Translating findings in basic science and animal models to humans with FXS has proven difficult. These challenges have prompted the FXS field to organize to build interlocking projects to support initiatives to improve supportive care, make clinical research accessible to families, generate collaborative research on natural history and outcome measures, and create clinical trial consortia and novel trial designs.

EEG as a translational biomarker and outcome measure in fragile X syndrome

Targeted treatments for fragile X syndrome (FXS) have frequently failed to show efficacy in clinical testing, despite success at the preclinical stages. This has highlighted the need for more effective translational outcome measures. EEG differences observed in FXS, including exaggerated N1 ERP amplitudes, increased resting gamma power and reduced gamma phase-locking in the sensory cortices, have been suggested as potential biomarkers of the syndrome. These abnormalities are thought to reflect cortical hyper excitability resulting from an excitatory (glutamate) and inhibitory (GABAergic) imbalance in FXS, which has been the target of several pharmaceutical remediation studies. EEG differences observed in humans also show similarities to those seen in laboratory models of FXS, which may allow for greater translational equivalence and better predict clinical success of putative therapeutics. There is some evidence from clinical trials showing that treatment related changes in EEG may be associated with clinical improvements, but these require replication and extension to other medications. Although the use of EEG characteristics as biomarkers is still in the early phases, and further research is needed to establish its utility in clinical trials, the current research is promising and signals the emergence of an effective translational biomarker.

Neural response to repeated auditory stimuli and its association with early language ability in male children with Fragile X syndrome

Background

Fragile X syndrome (FXS) is the most prevalent form of inherited intellectual disability and is commonly associated with autism. Previous studies have linked the structural and functional alterations in FXS with impaired sensory processing and sensory hypersensitivity, which may hinder the early development of cognitive functions such as language comprehension. In this study, we compared the P1 response of the auditory evoked potential and its habituation to repeated auditory stimuli in male children (2-7 years old) with and without FXS, and examined their association with clinical measures in these two groups.

Methods

We collected high-density electroencephalography (EEG) data in an auditory oddball paradigm from 12 male children with FXS and 11 age- and sex-matched typically developing (TD) children. After standardized EEG pre-processing, we conducted a spatial principal component (PC) analysis and identified two major PCs-a frontal PC and a temporal PC. Within each PC, we compared the P1 amplitude and inter-trial phase coherence (ITPC) between the two groups, and performed a series of linear regression analysis to study the association between these EEG measures and several clinical measures, including assessment scores for language abilities, non-verbal skills, and sensory hypersensitivity.

Results

At the temporal PC, both early and late standard stimuli evoked a larger P1 response in FXS compared to TD participants. For temporal ITPC, the TD group showed greater habituation than the FXS group. However, neither group showed significant habituation of the frontal or temporal P1 response. Despite lack of habituation, exploratory analysis of brain-behavior associations observed that within the FXS group, reduced frontal P1 response to late standard stimuli, and increased frontal P1 habituation were both associated with better language scores.

Conclusion

We identified P1 amplitude and ITPC in the temporal region as a contrasting EEG phenotype between the FXS and the TD groups. However, only frontal P1 response and habituation were associated with language measures. Larger longitudinal studies are required to determine whether these EEG measures could be used as biomarkers for language development in patients with FXS.

Neural Correlates of Auditory Hypersensitivity in Fragile X Syndrome

The mechanisms underlying the common association between autism spectrum disorders (ASD) and sensory processing disorders (SPD) are unclear, and treatment options to reduce atypical sensory processing are limited. Fragile X Syndrome (FXS) is a leading genetic cause of intellectual disability and ASD behaviors. As in most children with ASD, atypical sensory processing is a common symptom in FXS, frequently manifesting as sensory hypersensitivity. Auditory hypersensitivity is a highly debilitating condition in FXS that may lead to language delays, social anxiety and ritualized repetitive behaviors. Animal models of FXS, including Fmr1 knock out (KO) mouse, also show auditory hypersensitivity, providing a translation relevant platform to study underlying pathophysiological mechanisms. The focus of this review is to summarize recent studies in the Fmr1 KO mouse that identified neural correlates of auditory hypersensitivity. We review results of electroencephalography (EEG) recordings in the Fmr1 KO mice and highlight EEG phenotypes that are remarkably similar to EEG findings in humans with FXS. The EEG phenotypes associated with the loss of FMRP include enhanced resting EEG gamma band power, reduced cross frequency coupling, reduced sound-evoked synchrony of neural responses at gamma band frequencies, increased event-related potential amplitudes, reduced habituation of neural responses and increased non-phase locked power. In addition, we highlight the postnatal period when the EEG phenotypes develop and show a strong association of the phenotypes with enhanced matrix-metalloproteinase-9 (MMP-9) activity, abnormal development of parvalbumin (PV)-expressing inhibitory interneurons and reduced formation of specialized extracellular matrix structures called perineuronal nets (PNNs). Finally, we discuss how dysfunctions of inhibitory PV interneurons may contribute to cortical hyperexcitability and EEG abnormalities observed in FXS. Taken together, the studies reviewed here indicate that EEG recordings can be utilized in both pre-clinical studies and clinical trials, while at the same time, used to identify cellular and circuit mechanisms of dysfunction in FXS. New therapeutic approaches that reduce MMP-9 activity and restore functions of PV interneurons may succeed in reducing FXS sensory symptoms. Future studies should examine long-lasting benefits of developmental vs. adult interventions on sensory phenotypes.

Looking for consistency in an uncertain world: test-retest reliability of neurophysiological and behavioral readouts in autism

BACKGROUND

Autism spectrum disorders (ASD) are associated with altered sensory processing and perception. Scalp recordings of electrical brain activity time-locked to sensory events (event-related potentials; ERPs) provide precise information on the time-course of related altered neural activity, and can be used to model the cortical loci of the underlying neural networks. Establishing the test-retest reliability of these sensory brain responses in ASD is critical to their use as biomarkers of neural dysfunction in this population.

METHODS

EEG and behavioral data were acquired from 33 children diagnosed with ASD aged 6-9.4 years old, while they performed a child-friendly task at two different time-points, separated by an average of 5.2 months. In two blocked conditions, participants responded to the occurrence of an auditory target that was either preceded or not by repeating visual stimuli. Intraclass correlation coefficients (ICCs) were used to assess test-retest reliability of measures of sensory (auditory and visual) ERPs and performance, for the two experimental conditions. To assess the degree of reliability of the variability of responses within individuals, this analysis was performed on the variance of the measurements, in addition to their means. This yielded a total of 24 measures for which ICCs were calculated.

RESULTS

The data yielded significant good ICC values for 10 of the 24 measurements. These spanned across behavioral and ERPs data, experimental conditions, and mean as well as variance measures. Measures of the visual evoked responses accounted for a disproportionately large number of the significant ICCs; follow-up analyses suggested that the contribution of a greater number of trials to the visual compared to the auditory ERP partially accounted for this.

CONCLUSIONS

This analysis reveals that sensory ERPs and related behavior can be highly reliable across multiple measurement time-points in ASD. The data further suggest that the inter-trial and inter-participant variability reported in the ASD literature likely represents replicable individual participant neural processing differences. The stability of these neuronal readouts supports their use as biomarkers in clinical and translational studies on ASD. Given the minimum interval between test/retest sessions across our cohort, we also conclude that for the tested age-range of ~ 6 to 9.4 years, these reliability measures are valid for at least a 3-month interval. Limitations related to EEG task demands and study length in the context of a clinical trial are considered.

EEG Signal Complexity Is Reduced During Resting-State in Fragile X Syndrome

Introduction: Fragile X syndrome (FXS) is a genetic disorder caused by a mutation of the fragile X mental retardation 1 gene (FMR1). FXS is associated with neurophysiological abnormalities, including cortical hyperexcitability. Alterations in electroencephalogram (EEG) resting-state power spectral density (PSD) are well-defined in FXS and were found to be linked to neurodevelopmental delays. Whether non-linear dynamics of the brain signal are also altered remains to be studied. Methods: In this study, resting-state EEG power, including alpha peak frequency (APF) and theta/beta ratio (TBR), as well as signal complexity using multi-scale entropy (MSE) were compared between 26 FXS participants (ages 5-28 years), and 7 neurotypical (NT) controls with a similar age distribution. Subsequently a replication study was carried out, comparing our cohort to 19 FXS participants independently recorded at a different site. Results: PSD results confirmed the increased gamma, decreased alpha power and APF in FXS participants compared to NT controls. No alterations in TBR were found. Importantly, results revealed reduced signal complexity in FXS participants, specifically in higher scales, suggesting that altered signal complexity is sensitive to brain alterations in this population. The replication study mostly confirmed these results and suggested critical points of stagnation in the neurodevelopmental curve of FXS. Conclusion: Signal complexity is a powerful feature that can be added to the electrophysiological biomarkers of brain maturation in FXS.