Increased aperiodic gamma power in young boys with Fragile X Syndrome is associated with better language ability

Parent-reported outcome measures evaluating communication in individuals with rare neurodevelopmental disorders: A systematic review

BACKGROUND

Communication impairments are a leading concern for parent caregivers of individuals with rare neurodevelopmental disorders (RNDDs). Clinical trials of disease modifying therapies require valid and responsive outcome measures that are relevant to individuals with RNDDs. Identifying and evaluating current psychometric properties for communication measures is a critical step towards the selection and use of appropriate instruments.

AIMS

This systematic review offers (1) a description of parent-reported communication measures and (2) evidence for their psychometric properties, in RNDDs.

METHODS

The systematic review protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO; CRD42022334649). MEDLINE (Ovid), Embase, PsychINFO, Web of Science, CINAHL Plus, Cochrane Library, ClinicalTrials.gov, the Australian New Zealand Clinical Trials Registry were searched from inception to August 2023. Methodological assessment of quality was completed using the COnsensus-based Standards for the selection of health status Measurement INstruments (COSMIN) checklist. Parent-reported measures used in observational studies and clinical trials were identified. Data on utility, reliability and validity for RNDDs were extracted.

MAIN CONTRIBUTION

Sixteen parent-reported communication measures were used in RNDD research, the Vineland Adaptive Behavior Scales being most commonly used. Validation data in RNDDs were identified for six of these measures. Limitations related to sample size or the scope of psychometric testing.

CONCLUSIONS

Many communication measures have been used for RNDDs but there are few data validating their use. Valid and reliable methods of measuring communication in persons with RNDDs is a priority for future high-quality clinical trials.

WHAT THIS PAPER ADDS

What is already known on the subject Communication is a critical domain for families with a child with a rare neurodevelopmental disorder (RNDD). Validated outcome measures are essential for accurate evaluation and interpretation of responses to treatments in clinical trials. What this paper adds to existing knowledge We identified 16 parent-reported communication measures that have been used with RNDDs, but only six measures had validation data for at least one RNDD. High quality evidence is accumulating, with all validation studies in this review published between 2020 to 2023. Modifications of existing measures may be required to assess communication for RNDDs. What are the clinical implications of this work? This systematic review catalogues the available psychometric data for communication measures and indicates an ongoing need for new validation studies to ensure they are fit-for-purpose for upcoming clinical trials in RNDDs. This review will inform the selection of communication measures for clinical trials and research studies.

Measuring neuroplasticity in human development: the potential to inform the type and timing of mental health interventions

Neuroplasticity during sensitive periods, the molecular and cellular process of enduring neural change in response to external stimuli during windows of high environmental sensitivity, is crucial for adaptation to expected environments and has implications for psychiatry. Animal research has characterized the developmental sequence and neurobiological mechanisms that govern neuroplasticity, yet gaps in our ability to measure neuroplasticity in humans limit the clinical translation of these principles. Here, we present a roadmap for the development and validation of neuroimaging and electrophysiology measures that index neuroplasticity to begin to address these gaps. We argue that validation of measures to track neuroplasticity in humans will elucidate the etiology of mental illness and inform the type and timing of mental health interventions to optimize effectiveness. We outline criteria for evaluating putative neuroimaging measures of plasticity in humans including links to neurobiological mechanisms shown to govern plasticity in animal models, developmental change that reflects heightened early life plasticity, and prediction of neural and/or behavior change. These criteria are applied to three putative measures of neuroplasticity using electroencephalography (gamma oscillations, aperiodic exponent of power/frequency) or functional magnetic resonance imaging (amplitude of low frequency fluctuations). We discuss the use of these markers in psychiatry, envision future uses for clinical and developmental translation, and suggest steps to address the limitations of the current putative neuroimaging measures of plasticity. With additional work, we expect these markers will significantly impact mental health and be used to characterize mechanisms, devise new interventions, and optimize developmental trajectories to reduce psychopathology risk.

Aperiodic and Hurst EEG exponents across early human brain development: A systematic review

In electroencephalographic (EEG) data, power-frequency slope exponents (1/f_β) can provide non-invasive markers of in vivo neural activity excitation-inhibition (E:I) balance. E:I balance may be altered in neurodevelopmental conditions; hence, understanding how 1/fβ evolves across infancy/childhood has implications for developing early assessments/interventions. This systematic review (PROSPERO-ID: CRD42023363294) explored the early maturation (0-26 yrs) of resting-state EEG 1/f measures (aperiodic [AE], power law [PLE] and Hurst [HE] exponents), including studies containing ≥1 1/f measures and ≥10 typically developing participants. Five databases (including Embase and Scopus) were searched during March 2023. Forty-two studies were identified (Nparticipants=3478). Risk of bias was assessed using the Quality Assessment with Diverse Studies tool. Narrative synthesis of HE data suggests non-stationary EEG activity occurs throughout development. Age-related trends were complex, with rapid decreases in AEs during infancy and heterogenous changes thereafter. Regionally, AE maxima shifted developmentally, potentially reflecting spatial trends in maturing brain connectivity. This work highlights the importance of further characterising the development of 1/f measures to better understand how E:I balance shapes brain and cognitive development.

Machine learning of brain-specific biomarkers from EEG

BACKGROUND

Electroencephalography (EEG) has a long history as a clinical tool to study brain function, and its potential to derive biomarkers for various applications is far from exhausted. Machine learning (ML) can guide future innovation by harnessing the wealth of complex EEG signals to isolate relevant brain activity. Yet, ML studies in EEG tend to ignore physiological artefacts, which may cause problems for deriving biomarkers specific to the central nervous system (CNS).

METHODS

We present a framework for conceptualising machine learning from CNS versus peripheral signals measured with EEG. A signal representation based on Morlet wavelets allowed us to define traditional brain activity features (e.g. log power) and alternative inputs used by state-of-the-art ML approaches based on covariance matrices. Using more than 2600 EEG recordings from large public databases (TUAB, TDBRAIN), we studied the impact of peripheral signals and artefact removal techniques on ML models in age and sex prediction analyses.

FINDINGS

Across benchmarks, basic artefact rejection improved model performance, whereas further removal of peripheral signals using ICA decreased performance. Our analyses revealed that peripheral signals enable age and sex prediction. However, they explained only a fraction of the performance provided by brain signals.

INTERPRETATION

We show that brain signals and body signals, both present in the EEG, allow for prediction of personal characteristics. While these results may depend on specific applications, our work suggests that great care is needed to separate these signals when the goal is to develop CNS-specific biomarkers using ML.

FUNDING

All authors have been working for F. Hoffmann-La Roche Ltd.

Developmental trajectories of EEG aperiodic and periodic components in children 2-44 months of age

The development of neural circuits has long-lasting effects on brain function, yet our understanding of early circuit development in humans remains limited. Here, periodic EEG power features and aperiodic components were examined from longitudinal EEGs collected from 592 healthy 2-44 month-old infants, revealing age-dependent nonlinear changes suggestive of distinct milestones in early brain maturation. Developmental changes in periodic peaks include (1) the presence and then absence of a 9-10 Hz alpha peak between 2-6 months, (2) nonlinear changes in high beta peaks (20-30 Hz) between 4-18 months, and (3) the emergence of a low beta peak (12-20 Hz) in some infants after six months of age. We hypothesized that the emergence of the low beta peak may reflect maturation of thalamocortical network development. Infant anesthesia studies observe that GABA-modulating anesthetics do not induce thalamocortical mediated frontal alpha coherence until 10-12 months of age. Using a small cohort of infants (n = 23) with EEG before and during GABA-modulating anesthesia, we provide preliminary evidence that infants with a low beta peak have higher anesthesia-induced alpha coherence compared to those without a low beta peak.

Resting state EEG in young children with Tuberous Sclerosis Complex

Background

Tuberous Sclerosis Complex (TSC) manifests behaviorally with features of autism, epilepsy, and intellectual disability. Resting state electroencephalography (EEG) offers a window into neural oscillatory activity and may serve as an intermediate biomarker between gene expression and behavioral manifestations. Such a biomarker could be useful in clinical trials as an endpoint or predictor of treatment response. However, seizures and antiepileptic medications also affect resting neural oscillatory activity and could undermine the utility of resting state EEG features as biomarkers in neurodevelopmental disorders such as TSC.

Methods

This paper compares resting state EEG features in a cross-sectional cohort of young children with TSC (n=49, ages 12-37 months) to 49 age- and sex-matched typically developing controls. Within children with TSC, associations were examined between resting state EEG features, seizure severity composite score, and use of GABA agonists.

Results

Compared to matched typically developing controls, children with TSC showed significantly greater alpha and beta power in permutation cluster analyses iterated across a broad frequency range (2-50Hz). Children with TSC also showed significantly greater aperiodic offset after power spectra were parameterized using SpecParam into aperiodic and periodic components. Within children with TSC, greater seizure severity was significantly related to increased periodic peak beta power. Use of GABA agonists was also independently and significantly associated with increased periodic peak beta power; the interaction between seizure severity and GABA agonist use had no significant effect on peak beta power.

Conclusions

The elevated peak beta power observed in children with TSC compared to matched typically developing controls may be driven by both seizures and GABA agonist use. It is recommended to collect seizure and mediation data alongside EEG data for clinical trials. These results highlight the challenge of using resting state EEG features as biomarkers in trials with neurodevelopmental disabilities when epilepsy and anti-epileptic medication are common.

Frontal Cortex Hyperactivation and Gamma Desynchrony in Fragile X Syndrome: Correlates of Auditory Hypersensitivity

Fragile X syndrome (FXS) is an X-linked disorder that often leads to intellectual disability, anxiety, and sensory hypersensitivity. While sound sensitivity (hyperacusis) is a distressing symptom in FXS, its neural basis is not well understood. It is postulated that hyperacusis may stem from temporal lobe hyperexcitability or dysregulation in top-down modulation. Studying the neural mechanisms underlying sound sensitivity in FXS using scalp electroencephalography (EEG) is challenging because the temporal and frontal regions have overlapping neural projections that are difficult to differentiate. To overcome this challenge, we conducted EEG source analysis on a group of 36 individuals with FXS and 39 matched healthy controls. Our goal was to characterize the spatial and temporal properties of the response to an auditory chirp stimulus. Our results showed that males with FXS exhibit excessive activation in the frontal cortex in response to the stimulus onset, which may reflect changes in top-down modulation of auditory processing. Additionally, during the chirp stimulus, individuals with FXS demonstrated a reduction in typical gamma phase synchrony, along with an increase in asynchronous gamma power, across multiple regions, most strongly in temporal cortex. Consistent with these findings, we observed a decrease in the signal-to-noise ratio, estimated by the ratio of synchronous to asynchronous gamma activity, in individuals with FXS. Furthermore, this ratio was highly correlated with performance in an auditory attention task. Compared to controls, males with FXS demonstrated elevated bidirectional frontotemporal information flow at chirp onset. The evidence indicates that both temporal lobe hyperexcitability and disruptions in top-down regulation play a role in auditory sensitivity disturbances in FXS. These findings have the potential to guide the development of therapeutic targets and back-translation strategies.

Abnormalities in both stimulus-induced and baseline MEG alpha oscillations in the auditory cortex of children with Autism Spectrum Disorder

The neurobiology of Autism Spectrum Disorder (ASD) is hypothetically related to the imbalance between neural excitation (E) and inhibition (I). Different studies have revealed that alpha-band (8-12 Hz) activity in magneto- and electroencephalography (MEG and EEG) may reflect E and I processes and, thus, can be of particular interest in ASD research. Previous findings indicated alterations in event-related and baseline alpha activity in different cortical systems in individuals with ASD, and these abnormalities were associated with core and co-occurring conditions of ASD. However, the knowledge on auditory alpha oscillations in this population is limited. This MEG study investigated stimulus-induced (Event-Related Desynchronization, ERD) and baseline alpha-band activity (both periodic and aperiodic) in the auditory cortex and also the relationships between these neural activities and behavioral measures of children with ASD. Ninety amplitude-modulated tones were presented to two groups of children: 20 children with ASD (5 girls, Mage = 10.03, SD = 1.7) and 20 typically developing controls (9 girls, Mage = 9.11, SD = 1.3). Children with ASD had a bilateral reduction of alpha-band ERD, reduced baseline aperiodic-adjusted alpha power, and flattened aperiodic exponent in comparison to TD children. Moreover, lower raw baseline alpha power and aperiodic offset in the language-dominant left auditory cortex were associated with better language skills of children with ASD measured in formal assessment. The findings highlighted the alterations of E / I balance metrics in response to basic auditory stimuli in children with ASD and also provided evidence for the contribution of low-level processing to language difficulties in ASD.

The relationship between gamma-band neural oscillations and language skills in youth with Autism Spectrum Disorder and their first-degree relatives

BACKGROUND

Most children with Autism Spectrum Disorder (ASD) have co-occurring language impairments and some of these autism-specific language difficulties are also present in their non-autistic first-degree relatives. One of the possible neural mechanisms associated with variability in language functioning is alterations in cortical gamma-band oscillations, hypothesized to be related to neural excitation and inhibition balance.

METHODS

We used a high-density 128-channel electroencephalography (EEG) to register brain response to speech stimuli in a large sex-balanced sample of participants: 125 youth with ASD, 121 typically developing (TD) youth, and 40 unaffected siblings (US) of youth with ASD. Language skills were assessed with Clinical Evaluation of Language Fundamentals.

RESULTS

First, during speech processing, we identified significantly elevated gamma power in ASD participants compared to TD controls. Second, across all youth, higher gamma power was associated with lower language skills. Finally, the US group demonstrated an intermediate profile in both language and gamma power, with nonverbal IQ mediating the relationship between gamma power and language skills.

LIMITATIONS

We only focused on one of the possible neural contributors to variability in language functioning. Also, the US group consisted of a smaller number of participants in comparison to the ASD or TD groups. Finally, due to the timing issue in EEG system we have provided only non-phase-locked analysis.

CONCLUSIONS

Autistic youth showed elevated gamma power, suggesting higher excitation in the brain in response to speech stimuli and elevated gamma power was related to lower language skills. The US group showed an intermediate pattern of gamma activity, suggesting that the broader autism phenotype extends to neural profiles.

The Pathophysiological Underpinnings of Gamma-Band Alterations in Psychiatric Disorders

Investigating the biophysiological substrates of psychiatric illnesses is of great interest to our understanding of disorders' etiology, the identification of reliable biomarkers, and potential new therapeutic avenues. Schizophrenia represents a consolidated model of γ alterations arising from the aberrant activity of parvalbumin-positive GABAergic interneurons, whose dysfunction is associated with perineuronal net impairment and neuroinflammation. This model of pathogenesis is supported by molecular, cellular, and functional evidence. Proof for alterations of γ oscillations and their underlying mechanisms has also been reported in bipolar disorder and represents an emerging topic for major depressive disorder. Although evidence from animal models needs to be further elucidated in humans, the pathophysiology of γ-band alteration represents a common denominator for different neuropsychiatric disorders. The purpose of this narrative review is to outline a framework of converging results in psychiatric conditions characterized by γ abnormality, from neurochemical dysfunction to alterations in brain rhythms.

Developmental trajectories of EEG aperiodic and periodic components: Implications for understanding thalamocortical development during infancy

The development of neural circuits has long-lasting effects on brain function, yet our understanding of early circuit development in humans remains limited. Here, periodic EEG power features and aperiodic components were examined from longitudinal EEGs collected from 592 healthy 2-44 month-old infants, revealing age-dependent nonlinear changes suggestive of distinct milestones in early brain maturation. Consistent with the transient developmental progression of thalamocortical circuitry, we observe the presence and then absence of periodic alpha and high beta peaks across the three-year period, as well as the emergence of a low beta peak (12-20Hz) after six months of age. We present preliminary evidence that the emergence of the low beta peak is associated with higher thalamocortical-dependent, anesthesia-induced alpha coherence. Together, these findings suggest that early age-dependent changes in alpha and beta periodic peaks may reflect the state of thalamocortical network development.

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.

Resting EEG correlates of neurodevelopment in a socioeconomically and linguistically diverse sample of toddlers: Wave 1 of the Kia Tīmata Pai best start New Zealand study

Development of communication and self-regulation skills is fundamental to psychosocial maturation in childhood. The Kia Tīmata Pai Best Start (KTP) longitudinal study aims to promote these skills through interventions delivered at early childcare centers across New Zealand. In addition to evaluating effects of the interventions on behavioral and cognitive outcomes, the study utilizes electroencephalography (EEG) to characterize cortical development in a subsample of participating children. Here, we present results of the baseline resting EEG assessment with 193 children aged 15 to 33 months. We identified EEG correlates of individual differences in demographics, communication abilities, and temperament. We obtained communication and behavior ratings from multiple informants, and we applied contemporary analytic methods to the EEG data. Periodic spectral power adjusted for aperiodic activity was most closely associated with demographic, language, and behavioral measures. As in previous studies, gamma power was positively associated with verbal language. Alpha power was positively associated with effortful control. Nonverbal and verbal language measures showed distinct associations with EEG indices, as did the three temperament domains. Our results identified a number of candidate EEG measurements for use as longitudinal markers of optimal cortical development and response to interventions in the KTP cohort.

Evaluating early EEG correlates of restricted and repetitive behaviors for toddlers with or without autism

Background

Restricted and repetitive behaviors (RRB) are among the primary characteristics of autism spectrum disorder (ASD). Despite the potential impact on later developmental outcomes, our understanding of the neural underpinnings of RRBs is limited. Alterations in EEG alpha activity have been observed in ASD and implicated in RRBs, however, developmental changes within the alpha band requires careful methodological considerations when studying its role in brain-behavior relationships during infancy and early childhood. Novel approaches now enable the parameterization of the power spectrum into periodic and aperiodic components. This study aimed to characterize the neural correlates of RRBs in infancy by (1) comparing infant resting-state measures (periodic alpha and aperiodic activity) between infants who develop ASD, elevated likelihood infants without ASD, and low likelihood infants without ASD, and (2) evaluate whether these infant EEG measures are associated with frequency of RRBs measured at 24 months.

Methods

Baseline non-task related EEG data were collected from 12-to-14-month-old infants with and without elevated likelihood of autism (N=160), and periodic alpha activity (periodic alpha power, individual peak alpha frequency and amplitude), and aperiodic activity measures (aperiodic exponent) were calculated. Parent-reported RRBs were obtained at 24 months using the Repetitive Behavior Scale-Revised questionnaire. Group differences in EEG measures were evaluated using ANCOVA, and multiple linear regressions were conducted to assess relationships between EEG and RRB measures.

Results

No group-level differences in infant EEG measures were observed. Marginal effects analysis of linear regressions revealed significant associations within the ASD group, such that higher periodic alpha power, lower peak alpha frequency, and lower aperiodic exponent, were associated with elevated RRBs at 24 months. No significant associations were observed for non-ASD outcome groups.

Limitations

The sample size for ASD (N=19) was modest for examining brain-behavior relations. Larger sample sizes are needed to increase statistical power.

Conclusion

For infants with later ASD diagnoses, measures of alpha and aperiodic activity measured at 1-year of age were associated with later manifestation of RRBs at 2-years. Longitudinal studies are needed to elucidate whether the early trajectory of these EEG measures and their dynamic relations in development influence manifestations of RRBs in ASD.

In Utero Exposure to Alcohol and Tobacco and Electroencephalogram Power During Childhood

Importance

Prenatal alcohol exposure (PAE) and prenatal tobacco exposure (PTE) are risk factors associated with adverse neurobehavioral and cognitive outcomes.

Objective

To quantify long-term associations of PAE and PTE with brain activity in early and middle childhood via electroencephalography (EEG).

Design, Setting, and Participants

This cohort study included participants enrolled in the Safe Passage Study (August 2007 to January 2015), from which a subset of 649 participants were followed up in the Environmental Influences on Child Health Outcomes Program. From September 2018 through November 2022, EEG recordings were obtained at ages 4, 5, 7, 9, or 11 years. Data were analyzed from November 2022 to November 2023.

Exposures

Maternal self-reported consumptions of alcohol and tobacco during pregnancy were captured at the recruitment interview and at up to 3 visits during pregnancy (20-24, 28-32, and ≥34 weeks' gestation). Classifications of PAE (continuous drinking, quit-early drinking, and nondrinking) and PTE (continuous smoking, quit-early smoking, and nonsmoking) were previously obtained.

Main Outcomes and Measures

EEG band powers (theta, alpha, beta, gamma) were extracted from the EEG recordings. Linear regression models were used to estimate the associations of PAE and PTE with EEG estimates.

Results

The final sample included 649 participants (333 [51.3%] female) aged 4, 5, 7, 9, or 11 years. Children whose mothers were in the quit-early drinking cluster had increased alpha power (0.116 [95% CI, 0.023 to 0.209] μV2; P = .02) compared with individuals without PAE. The magnitude of this increase was approximately double for children exposed to continuous drinking (0.211 [95% CI, 0.005 to 0.417] μV2; P = .04). Children whose mothers were in the continuous smoking cluster had decreased beta power (-0.031 [95% CI, -0.059 to -0.003] μV2; P = .03) and gamma power (-0.020 [95% CI, -0.039 to -0.000] μV2; P = .04) compared with the nonsmoking cluster. In exploratory sex-stratified models, male participants in the quit-early PAE cluster had greater EEG power in the alpha band (0.159 [95% CI, 0.003 to 0.315] μV2; P = .04) compared with those with no PAE, and the difference was approximately double for male participants with continuous PAE (0.354 [95% CI, 0.041 to 0.667] μV2; P = .03). Male participants in the continuous PTE cluster had decreased beta (-0.048 [95% CI, -0.090 to - 0.007] μV2; P = .02) and gamma (-0.032 [95% CI, -0.061 - 0.002] μV2; P = .04) power compared with those with no PTE.

Conclusions and Relevance

These findings suggest that even low levels of PAE and PTE were associated with long-term alterations of brain activity.

Slope of the power spectral density flattens at low frequencies (<150 Hz) with healthy aging but also steepens at higher frequency (>200 Hz) in human electroencephalogram

The power spectral density (PSD) of the brain signals is characterized by two distinct features: oscillations, which are represented as distinct "bumps," and broadband aperiodic activity, that reduces in power with increasing frequency and is characterized by the slope of the power falloff. Recent studies have shown a change in the slope of the aperiodic activity with healthy aging and mental disorders. However, these studies analyzed slopes over a limited frequency range (<100 Hz). To test whether the PSD slope is affected over a wider frequency range with aging and mental disorder, we analyzed the slope till 800 Hz in electroencephalogram data recorded from elderly subjects (>49 years) who were healthy (n = 217) or had mild cognitive impairment (MCI; n = 11) or Alzheimer's Disease (AD; n = 5). Although the slope reduced up to ~ 150 Hz with healthy aging (as shown previously), surprisingly, at higher frequencies (>200 Hz), it increased with age. These results were observed in all electrodes, for both eyes open and eyes closed conditions, and for different reference schemes. However, slopes were not significantly different in MCI/AD subjects compared with healthy controls. Overall, our results constrain the biophysical mechanisms that are reflected in the PSD slopes in healthy and pathological aging.

Electroencephalographic (EEG) Biomarkers in Genetic Neurodevelopmental Disorders

Collectively, neurodevelopmental disorders are highly prevalent, but more than a third of neurodevelopmental disorders have an identifiable genetic etiology, each of which is individually rare. The genes associated with neurodevelopmental disorders are often involved in early brain development, neuronal signaling, or synaptic plasticity. Novel treatments for many genetic neurodevelopmental disorders are being developed, but disease-relevant clinical outcome assessments and biomarkers are limited. Electroencephalography (EEG) is a promising noninvasive potential biomarker of brain function. It has been used extensively in epileptic disorders, but its application in neurodevelopmental disorders needs further investigation. In this review, we explore the use of EEG in 3 of the most prevalent genetic neurodevelopmental disorders-Angelman syndrome, Rett syndrome, and fragile X syndrome. Quantitative analyses of EEGs, such as power spectral analysis or measures of connectivity, can quantify EEG signatures seen on qualitative review and potentially correlate with phenotypes. In both Angelman syndrome and Rett syndrome, increased delta power on spectral analysis has correlated with clinical markers of disease severity including developmental disability and seizure burden, whereas spectral power analysis on EEG in fragile X syndrome tends to demonstrate abnormalities in gamma power. Further studies are needed to establish reliable relationships between quantitative EEG biomarkers and clinical phenotypes in rare genetic neurodevelopmental disorders.

Empirical Frequency Bound Derivation Reveals Prominent Mid-Frontal Alpha Associated with Neurosensory Dysfunction in Fragile X Syndrome

The FMR1 gene is inactive in Fragile X syndrome (FXS), resulting in low levels of FMRP and consequent neurochemical, synaptic, and local circuit neurophysiological alterations in the fmr1 KO mouse. In FXS patients, electrophysiological studies have demonstrated a marked reduction in global alpha activity and regional increases in gamma oscillations associated with intellectual disability and sensory hypersensitivity. Since alpha activity is associated with a thalamocortical function with widely distributed modulatory effects on neocortical excitability, insight into alpha physiology may provide insight into systems-level disease mechanisms. Herein, we took a data-driven approach to clarify the temporal and spatial properties of alpha and theta activity in participants with FXS. High-resolution resting-state EEG data were collected from participants affected by FXS (n = 65) and matched controls (n = 70). We used a multivariate technique to empirically classify neural oscillatory bands based on their coherent spatiotemporal patterns. Participants with FXS demonstrated: 1) redistribution of lower-frequency boundaries indicating a "slower" dominant alpha rhythm, 2) an anteriorization of alpha frequency activity, and 3) a correlation of increased individualized alpha power measurements with auditory neurosensory dysfunction. These findings suggest an important role for alterations in thalamocortical physiology for the well-established neocortical hyper-excitability in FXS and, thus, a role for neural systems level disruption to cortical hyperexcitability that has been studied primarily at the local circuit level in animal models.

Pattern dynamics and stochasticity of the brain rhythms

Our current understanding of brain rhythms is based on quantifying their instantaneous or time-averaged characteristics. What remains unexplored is the actual structure of the waves-their shapes and patterns over finite timescales. Here, we study brain wave patterning in different physiological contexts using two independent approaches: The first is based on quantifying stochasticity relative to the underlying mean behavior, and the second assesses "orderliness" of the waves' features. The corresponding measures capture the waves' characteristics and abnormal behaviors, such as atypical periodicity or excessive clustering, and demonstrate coupling between the patterns' dynamics and the animal's location, speed, and acceleration. Specifically, we studied patterns of θ, γ, and ripple waves recorded in mice hippocampi and observed speed-modulated changes of the wave's cadence, an antiphase relationship between orderliness and acceleration, as well as spatial selectiveness of patterns. Taken together, our results offer a complementary-mesoscale-perspective on brain wave structure, dynamics, and functionality.

Glutamatergic and GABAergic Receptor Modulation Present Unique Electrophysiological Fingerprints in a Concentration-Dependent and Region-Specific Manner

Brain function depends on complex circuit interactions between excitatory and inhibitory neurons embedded in local and long-range networks. Systemic GABAA-receptor (GABAAR) or NMDA-receptor (NMDAR) modulation alters the excitatory-inhibitory balance (EIB), measurable with electroencephalography (EEG). However, EEG signatures are complex in localization and spectral composition. We developed and applied analytical tools to investigate the effects of two EIB modulators, MK801 (NMDAR antagonist) and diazepam (GABAAR modulator), on periodic and aperiodic EEG features in freely-moving male Sprague Dawley rats. We investigated how, across three brain regions, EEG features are correlated with EIB modulation. We found that the periodic component was composed of seven frequency bands that presented region-dependent and compound-dependent changes. The aperiodic component was also different between compounds and brain regions. Importantly, the parametrization into periodic and aperiodic components unveiled correlations between quantitative EEG and plasma concentrations of pharmacological compounds. MK-801 exposures were positively correlated with the slope of the aperiodic component. Concerning the periodic component, MK-801 exposures correlated negatively with the peak frequency of low-γ oscillations but positively with those of high-γ and high-frequency oscillations (HFOs). As for the power, θ and low-γ oscillations correlated negatively with MK-801, whereas mid-γ correlated positively. Diazepam correlated negatively with the knee of the aperiodic component, positively to β and negatively to low-γ oscillatory power, and positively to the modal frequency of θ, low-γ, mid-γ, and high-γ. In conclusion, correlations between exposures and pharmacodynamic effects can be better-understood thanks to the parametrization of EEG into periodic and aperiodic components. Such parametrization could be key in functional biomarker discovery.

Age-related trends in aperiodic EEG activity and alpha oscillations during early- to middle-childhood

Age-related structural and functional changes that occur during brain development are critical for cortical development and functioning. Previous electroencephalography (EEG) and magnetoencephalography (MEG) studies have highlighted the utility of power spectra analyses and have uncovered age-related trends that reflect perceptual, cognitive, and behavioural states as well as their underlying neurophysiology. The aim of the current study was to investigate age-related change in aperiodic and periodic alpha activity across a large sample of pre- and school-aged children (N = 502, age range 4 -11-years-of-age). Power spectra were extracted from baseline EEG recordings (eyes closed, eyes open) for each participant and parameterized into aperiodic activity to derive the offset and exponent parameters and periodic alpha oscillatory activity to derive the alpha peak frequency and the associated power estimates. Multilevel models were run to investigate age-related trends and condition-dependent changes for each of these measures. We found quadratic age-related effects for both the aperiodic offset and exponent. In addition, we observed increases in periodic alpha peak frequency as a function of age. Aperiodic measures and periodic alpha power were larger in magnitude during eyes closed compared to the eyes open baseline condition. Taken together, these results advance our understanding of the maturational patterns/trajectories of brain development during early- to middle-childhood.

Neuromagnetic 40 Hz Auditory Steady-State Response in the left auditory cortex is related to language comprehension in children with Autism Spectrum Disorder

Language impairment is comorbid in most children with Autism Spectrum Disorder (ASD), but its neural mechanisms are still poorly understood. Some studies hypothesize that the atypical low-level sensory perception in the auditory cortex accounts for the abnormal language development in these children. One of the potential non-invasive measures of such low-level perception can be the cortical gamma-band oscillations registered with magnetoencephalography (MEG), and 40 Hz Auditory Steady-State Response (40 Hz ASSR) is a reliable paradigm for eliciting auditory gamma response. Although there is research in children with and without ASD using 40 Hz ASSR, nothing is known about the relationship between this auditory response in children with ASD and their language abilities measured directly in formal assessment. In the present study, we used MEG and individual brain models to investigate 40 Hz ASSR in primary-school-aged children with and without ASD. It was also used to assess how the strength of the auditory response is related to language abilities of children with ASD, their non-verbal IQ, and social functioning. A total of 40 children were included in the study. The results demonstrated that 40 Hz ASSR was reduced in the right auditory cortex in children with ASD when comparing them to typically developing controls. Importantly, our study provides the first evidence of the association between 40 Hz ASSR in the language-dominant left auditory cortex and language comprehension in children with ASD. This link was domain-specific because the other brain-behavior correlations were non-significant.

FPT, a 2-Aminotetralin, Is a Potent Serotonin 5-HT1A, 5-HT1B, and 5-HT1D Receptor Agonist That Modulates Cortical Electroencephalogram Activity in Adult Fmr1 Knockout Mice

There are no approved medicines for fragile X syndrome (FXS), a monogenic, neurodevelopmental disorder. Electroencephalogram (EEG) studies show alterations in resting-state cortical EEG spectra, such as increased gamma-band power, in patients with FXS that are also observed in Fmr1 knockout models of FXS, offering putative biomarkers for drug discovery. Genes encoding serotonin receptors (5-HTRs), including 5-HT1A, 5-HT1B, and 5-HT1DRs, are differentially expressed in FXS, providing a rationale for investigating them as pharmacotherapeutic targets. Previously we reported pharmacological activity and preclinical neurotherapeutic effects in Fmr1 knockout mice of an orally active 2-aminotetralin, (S)-5-(2'-fluorophenyl)-N,N-dimethyl-1,2,3,4-tetrahydronaphthalen-2-amine (FPT). FPT is a potent (low nM), high-efficacy partial agonist at 5-HT1ARs and a potent, low-efficacy partial agonist at 5-HT7Rs. Here we report new observations that FPT also has potent and efficacious agonist activity at human 5-HT1B and 5-HT1DRs. FPT's Ki values at 5-HT1B and 5-HT1DRs were <5 nM, but it had nil activity (>10 μM Ki) at 5-HT1FRs. We tested the effects of FPT (5.6 mg/kg, subcutaneous) on EEG recorded above the somatosensory and auditory cortices in freely moving, adult Fmr1 knockout and control mice. Consistent with previous reports, we observed significantly increased relative gamma power in untreated or vehicle-treated male and female Fmr1 knockout mice from recordings above the left somatosensory cortex (LSSC). In addition, we observed sex effects on EEG power. FPT did not eliminate the genotype difference in relative gamma power from the LSSC. FPT, however, robustly decreased relative alpha power in the LSSC and auditory cortex, with more pronounced effects in Fmr1 KO mice. Similarly, FPT decreased relative alpha power in the right SSC but only in Fmr1 knockout mice. FPT also increased relative delta power, with more pronounced effects in Fmr1 KO mice and caused small but significant increases in relative beta power. Distinct impacts of FPT on cortical EEG were like effects caused by certain FDA-approved psychotropic medications (including baclofen, allopregnanolone, and clozapine). These results advance the understanding of FPT's pharmacological and neurophysiological effects.

Altered frontal connectivity as a mechanism for executive function deficits in fragile X syndrome

BACKGROUND

Fragile X syndrome (FXS) is the leading inherited monogenic cause of intellectual disability and autism spectrum disorder. Executive function (EF), necessary for adaptive goal-oriented behavior and dependent on frontal lobe function, is impaired in individuals with FXS. Yet, little is known how alterations in frontal lobe neural activity is related to EF deficits in FXS.

METHODS

Sixty-one participants with FXS (54% males) and 71 age- and sex-matched typically-developing controls (TDC; 58% males) completed a five-minute resting state electroencephalography (EEG) protocol and a computerized battery of tests of EF, the Test of Attentional Performance for Children (KiTAP). Following source localization (minimum-norm estimate), we computed debiased weighted phase lag index (dWPLI), a phase connectivity value, for pairings between 18 nodes in frontal regions for gamma (30-55 Hz) and alpha (10.5-12.5 Hz) bands. Linear models were generated with fixed factors of group, sex, frequency, and connection. Relationships between frontal connectivity and EF variables also were examined.

RESULTS

Individuals with FXS demonstrated increased gamma band and reduced alpha band connectivity across all frontal regions and across hemispheres compared to TDC. After controlling for nonverbal IQ, increased error rates on EF tasks were associated with increased gamma band and reduced alpha band connectivity.

LIMITATIONS

Frontal connectivity findings are limited to intrinsic brain activity during rest and may not generalize to frontal connectivity during EF tasks or everyday function.

CONCLUSIONS

We report gamma hyper-connectivity and alpha hypo-connectivity within source-localized frontal brain regions in FXS compared to TDC during resting-state EEG. For the first time in FXS, we report significant associations between EF and altered frontal connectivity, with increased error rate relating to increased gamma band connectivity and reduced alpha band connectivity. These findings suggest increased phase connectivity within gamma band may impair EF performance, whereas greater alpha band connectivity may provide compensatory support for EF. Together, these findings provide important insight into neurophysiological mechanisms of EF deficits in FXS and provide novel targets for treatment development.

Quantitative electroencephalographic analysis as a potential biomarker of response to treatment with cannabidiol

PURPOSE

Pharmaceutical grade cannabidiol (CBD) is one of the newest anti-seizure medications for refractory epilepsy, and the effects of CBD on EEG have not been fully described.

METHODS

Patients enrolled in a CBD expanded access study had EEGs prior to and 12 weeks after initiation of CBD treatment for their refractory epilepsy. In addition to evaluating the clinical EEG reports, a nonbiased quantitative EEG (qEEG) analysis of background EEG was performed to determine whether consistent changes occur in the EEG in response to administration of CBD.

RESULTS

No significant qualitative changes were seen, nor changes in quantitative markers of EEG amplitude (RMS amplitude, standard deviation of the amplitude, skewness, or kurtosis), frequency (relative delta, theta, or alpha power), Spearman correlation, or coherence between brain regions. However, relative beta power and 1/f slope, a measure of signal noise increased with the addition of CBD. When patients were separated into responders and nonresponders based on seizure reduction with CBD, responders also had decreased Spearman correlation between the frontopolar and occipital regions after addition of CBD, suggesting that responders may have quantitatively improved EEG background organization after CBD initiation. The differences in beta and 1/f slope were also seen more robustly in CBD responders compared with nonresponders after CBD initiation. These differences disappeared when analyzing only patients not taking benzodiazepines, suggesting that the effect of CBD on seizures was related to the ability of the brain to further increase beta in response to CBD in patients already taking benzodiazepines. We noted that even before initiation of CBD, 1/f slope was also significantly different in responders compared to nonresponders. Therefore, to explore the baseline EEG in responders and nonresponders, we utilized a variable selection procedure to identify baseline EEG features that could predict whether a patient's seizures would improve with CBD. In the optimal multivariable logistic model, baseline coherence, Spearman correlation, and patient sex jointly predicted whether a patient in this cohort would respond to CBD (defined as a seizure reduction of 40% or greater) with 74% accuracy. This model performed less well on a data set of reduced duration and variability, highlighting the importance of real-world testing of any clinically relevant model.

CONCLUSION

These results suggest that there are subtle changes in certain metrics detected by qEEG even at baseline that may not be perceived during qualitative EEG analysis and that could be used in the future as a biomarker to predict a patient's clinical response to CBD administration. Development of such a predictive EEG biomarker, especially before the initiation of a medication trial, could reduce unnecessary ASM exposure and improve outcomes for patients with epilepsy facing new medication selection.

Separating the aperiodic and periodic components of neural activity in Parkinson's disease

Most studies on electrophysiology have not separated aperiodic activity from the spectra but have rather evaluated a combined periodic oscillatory component and the aperiodic component. As the understanding of aperiodic activity gradually deepens, its potential physiological significance has acquired increased appreciation. Herein, we investigated the two components in scalp electroencephalogram in 16 healthy controls and 15 patients with Parkinson's disease (PD); the results revealed that aperiodic parameters were approximately symmetrically distributed in topography in patients with PD and were significantly modulated by dopaminergic medication in channels C4, C3, CP5 and FC5. In sum, our findings might provide indicators for evaluating treatment response in PD and highlight the importance of re-evaluating the neuronal power spectra parameterization.

Spatially resolved neural slowing predicts impairment and amyloid burden in Alzheimer's disease

An extensive electrophysiological literature has proposed a pathological 'slowing' of neuronal activity in patients on the Alzheimer's disease spectrum. Supported by numerous studies reporting increases in low-frequency and decreases in high-frequency neural oscillations, this pattern has been suggested as a stable biomarker with potential clinical utility. However, no spatially resolved metric of such slowing exists, stymieing efforts to understand its relation to proteinopathy and clinical outcomes. Further, the assumption that this slowing is occurring in spatially overlapping populations of neurons has not been empirically validated. In the current study, we collected cross-sectional resting state measures of neuronal activity using magnetoencephalography from 38 biomarker-confirmed patients on the Alzheimer's disease spectrum and 20 cognitively normal biomarker-negative older adults. From these data, we compute and validate a new metric of spatially resolved oscillatory deviations from healthy ageing for each patient on the Alzheimer's disease spectrum. Using this Pathological Oscillatory Slowing Index, we show that patients on the Alzheimer's disease spectrum exhibit robust neuronal slowing across a network of temporal, parietal, cerebellar and prefrontal cortices. This slowing effect is shown to be directly relevant to clinical outcomes, as oscillatory slowing in temporal and parietal cortices significantly predicted both general (i.e. Montreal Cognitive Assessment scores) and domain-specific (i.e. attention, language and processing speed) cognitive function. Further, regional amyloid-β accumulation, as measured by quantitative 18F florbetapir PET, robustly predicted the magnitude of this pathological neural slowing effect, and the strength of this relationship between amyloid-β burden and neural slowing also predicted attentional impairments across patients. These findings provide empirical support for a spatially overlapping effect of oscillatory neural slowing in biomarker-confirmed patients on the Alzheimer's disease spectrum, and link this effect to both regional proteinopathy and cognitive outcomes in a spatially resolved manner. The Pathological Oscillatory Slowing Index also represents a novel metric that is of potentially high utility across a number of clinical neuroimaging applications, as oscillatory slowing has also been extensively documented in other patient populations, most notably Parkinson's disease, with divergent spectral and spatial features.

Resting state EEG power spectrum and functional connectivity in autism: a cross-sectional analysis

BACKGROUND

Understanding the development of the neuronal circuitry underlying autism spectrum disorder (ASD) is critical to shed light into its etiology and for the development of treatment options. Resting state EEG provides a window into spontaneous local and long-range neuronal synchronization and has been investigated in many ASD studies, but results are inconsistent. Unbiased investigation in large and comprehensive samples focusing on replicability is needed.

METHODS

We quantified resting state EEG alpha peak metrics, power spectrum (PS, 2-32 Hz) and functional connectivity (FC) in 411 children, adolescents and adults (n = 212 ASD, n = 199 neurotypicals [NT], all with IQ > 75). We performed analyses in source-space using individual head models derived from the participants' MRIs. We tested for differences in mean and variance between the ASD and NT groups for both PS and FC using linear mixed effects models accounting for age, sex, IQ and site effects. Then, we used machine learning to assess whether a multivariate combination of EEG features could better separate ASD and NT participants. All analyses were embedded within a train-validation approach (70%-30% split).

RESULTS

In the training dataset, we found an interaction between age and group for the reactivity to eye opening (p = .042 uncorrected), and a significant but weak multivariate ASD vs. NT classification performance for PS and FC (sensitivity 0.52-0.62, specificity 0.59-0.73). None of these findings replicated significantly in the validation dataset, although the effect size in the validation dataset overlapped with the prediction interval from the training dataset.

LIMITATIONS

The statistical power to detect weak effects-of the magnitude of those found in the training dataset-in the validation dataset is small, and we cannot fully conclude on the reproducibility of the training dataset's effects.

CONCLUSIONS

This suggests that PS and FC values in ASD and NT have a strong overlap, and that differences between both groups (in both mean and variance) have, at best, a small effect size. Larger studies would be needed to investigate and replicate such potential effects.

Globally elevated excitation-inhibition ratio in children with autism spectrum disorder and below-average intelligence

Background

Altered neuronal excitation–inhibition (E–I) balance is strongly implicated in ASD. However, it is not known whether the direction and degree of changes in the E–I ratio in individuals with ASD correlates with intellectual disability often associated with this developmental disorder. The spectral slope of the aperiodic 1/f activity reflects the E–I balance at the scale of large neuronal populations and may uncover its putative alternations in individuals with ASD with and without intellectual disability.

Methods

Herein, we used magnetoencephalography (MEG) to test whether the 1/f slope would differentiate ASD children with average and below–average (< 85) IQ. MEG was recorded at rest with eyes open/closed in 49 boys with ASD aged 6–15 years with IQ ranging from 54 to 128, and in 49 age-matched typically developing (TD) boys. The cortical source activity was estimated using the beamformer approach and individual brain models. We then extracted the 1/f slope by fitting a linear function to the log–log-scale power spectra in the high-frequency range.

Results

The global 1/f slope averaged over all cortical sources demonstrated high rank-order stability between the two conditions. Consistent with previous research, it was steeper in the eyes-closed than in the eyes-open condition and flattened with age. Regardless of condition, children with ASD and below-average IQ had flatter slopes than either TD or ASD children with average or above-average IQ. These group differences could not be explained by differences in signal-to-noise ratio or periodic (alpha and beta) activity.

Limitations

Further research is needed to find out whether the observed changes in E–I ratios are characteristic of children with below-average IQ of other diagnostic groups.

Conclusions

The atypically flattened spectral slope of aperiodic activity in children with ASD and below-average IQ suggests a shift of the global E–I balance toward hyper-excitation. The spectral slope can provide an accessible noninvasive biomarker of the E–I ratio for making objective judgments about treatment effectiveness in people with ASD and comorbid intellectual disability.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13229-022-00498-2.

Neocortical localization and thalamocortical modulation of neuronal hyperexcitability contribute to Fragile X Syndrome

Fragile X Syndrome (FXS) is a monogenetic form of intellectual disability and autism in which well-established knockout (KO) animal models point to neuronal hyperexcitability and abnormal gamma-frequency physiology as a basis for key disorder features. Translating these findings into patients may identify tractable treatment targets. Using source modeling of resting-state electroencephalography data, we report findings in FXS, including 1) increases in localized gamma activity, 2) pervasive changes of theta/alpha activity, indicative of disrupted thalamocortical modulation coupled with elevated gamma power, 3) stepwise moderation of low and high-frequency abnormalities based on female sex, and 4) relationship of this physiology to intellectual disability and neuropsychiatric symptoms. Our observations extend findings in Fmr1-/- KO mice to patients with FXS and raise a key role for disrupted thalamocortical modulation in local hyperexcitability. This systems-level mechanism has received limited preclinical attention but has implications for understanding fundamental disease mechanisms.

Aperiodic electrophysiological activity in preterm infants is linked to subsequent autism risk

Approximately 7% of preterm infants receive an autism spectrum disorder (ASD) diagnosis. Yet, there is a significant gap in the literature in identifying prospective markers of neurodevelopmental risk in preterm infants. The present study examined two electroencephalography (EEG) parameters during infancy, absolute EEG power and aperiodic activity of the power spectral density (PSD) slope, in association with subsequent autism risk and cognitive ability in a diverse cohort of children born preterm in South Africa. Participants were 71 preterm infants born between 25 and 36 weeks gestation (34.60 ± 2.34 weeks). EEG was collected during sleep between 39 and 41 weeks postmenstrual age adjusted (40.00 ± 0.42 weeks). The Bayley Scales of Infant Development and Brief Infant Toddler Social Emotional Assessment (BITSEA) were administered at approximately 3 years of age adjusted (34 ± 2.7 months). Aperiodic activity, but not the rhythmic oscillatory activity, at multiple electrode sites was associated with subsequent increased autism risk on the BITSEA at three years of age. No associations were found between the PSD slope or absolute EEG power and cognitive development. Our findings highlight the need to examine potential markers of subsequent autism risk in high-risk populations other than infants at familial risk.

Electrophysiological and Behavioral Evidence for Hyper- and Hyposensitivity in Rare Genetic Syndromes Associated with Autism

Our study reviewed abnormalities in spontaneous, as well as event-related, brain activity in syndromes with a known genetic underpinning that are associated with autistic symptomatology. Based on behavioral and neurophysiological evidence, we tentatively subdivided the syndromes on primarily hyper-sensitive (Fragile X, Angelman) and hypo-sensitive (Phelan-McDermid, Rett, Tuberous Sclerosis, Neurofibromatosis 1), pointing to the way of segregation of heterogeneous idiopathic ASD, that includes both hyper-sensitive and hypo-sensitive individuals. This segmentation links abnormalities in different genes, such as FMR1, UBE3A, GABRB3, GABRA5, GABRG3, SHANK3, MECP2, TSC1, TSC2, and NF1, that are causative to the above-mentioned syndromes and associated with synaptic transmission and cell growth, as well as with translational and transcriptional regulation and with sensory sensitivity. Excitation/inhibition imbalance related to GABAergic signaling, and the interplay of tonic and phasic inhibition in different brain regions might underlie this relationship. However, more research is needed. As most genetic syndromes are very rare, future investigations in this field will benefit from multi-site collaboration with a common protocol for electrophysiological and event-related potential (EEG/ERP) research that should include an investigation into all modalities and stages of sensory processing, as well as potential biomarkers of GABAergic signaling (such as 40-Hz ASSR).

Spectral parameterization for studying neurodevelopment: How and why

A growing body of literature suggests that the explicit parameterization of neural power spectra is important for the appropriate physiological interpretation of periodic and aperiodic electroencephalogram (EEG) activity. In this paper, we discuss why parameterization is an imperative step for developmental cognitive neuroscientists interested in cognition and behavior across the lifespan, as well as how parameterization can be readily accomplished with an automated spectral parameterization ("specparam") algorithm (Donoghue et al., 2020a). We provide annotated code for power spectral parameterization, via specparam, in Jupyter Notebook and R Studio. We then apply this algorithm to EEG data in childhood (N = 60; Mage = 9.97, SD = 0.95) to illustrate its utility for developmental cognitive neuroscientists. Ultimately, the explicit parameterization of EEG power spectra may help us refine our understanding of how dynamic neural communication contributes to normative and aberrant cognition across the lifespan. Data and annotated analysis code for this manuscript are available on GitHub as a supplement to the open-access specparam toolbox.

Periodic and aperiodic neural activity displays age-dependent changes across early-to-middle childhood

The neurodevelopmental period spanning early-to-middle childhood represents a time of significant growth and reorganisation throughout the cortex. Such changes are critical for the emergence and maturation of a range of social and cognitive processes. Here, we utilised both eyes open and eyes closed resting-state electroencephalography (EEG) to examine maturational changes in both oscillatory (i.e., periodic) and non-oscillatory (aperiodic, '1/f-like') activity in a large cohort of participants ranging from 4-to-12 years of age (N = 139, average age=9.41 years, SD=1.95). The EEG signal was parameterised into aperiodic and periodic components, and linear regression models were used to evaluate if chronological age could predict aperiodic exponent and offset, as well as well as peak frequency and power within the alpha and beta ranges. Exponent and offset were found to both decrease with age, while aperiodic-adjusted alpha peak frequency increased with age; however, there was no association between age and peak frequency for the beta band. Age was also unrelated to aperiodic-adjusted spectral power within either the alpha or beta bands, despite both frequency ranges being correlated with the aperiodic signal. Overall, these results highlight the capacity for both periodic and aperiodic features of the EEG to elucidate age-related functional changes within the developing brain.

EEG spectral exponent as a synthetic index for the longitudinal assessment of stroke recovery

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The Spectral Exponent (SE) indexes power-law features of the resting EEG in stroke patients.

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SE is consistently steeper in the affected hemisphere of patients after middle cerebral artery stroke.

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SE is linked to clinical status and seems to be a good predictor of clinical outcome.

Objective

Quantitative Electroencephalography (qEEG) can capture changes in brain activity following stroke. qEEG metrics traditionally focus on oscillatory activity, however recent findings highlight the importance of aperiodic (power-law) structure in characterizing pathological brain states. We assessed neurophysiological alterations and recovery after mono-hemispheric stroke by means of the Spectral Exponent (SE), a metric that reflects EEG slowing and quantifies the power-law decay of the EEG Power Spectral Density (PSD).

Methods

Eighteen patients (n = 18) with mild to moderate mono-hemispheric Middle Cerebral Artery (MCA) ischaemic stroke were retrospectively enrolled for this study. Patients underwent EEG recording in the sub-acute phase (T0) and after 2 months of physical rehabilitation (T1). Sixteen healthy controls (HC; n = 16) matched by age and sex were enrolled as a normative group. SE values and narrow-band PSD were estimated for each recording. We compared SE and band-power between patients and HC, and between the affected (AH) and unaffected hemisphere (UH) at T0 and T1 in patients.

Results

At T0, stroke patients showed significantly more negative SE values than HC (p = 0.003), reflecting broad-band EEG slowing. Most important, in patients SE over the AH was consistently more negative compared to the UH and showed a renormalization at T1. This SE renormalization significantly correlated with National Institute of Health Stroke Scale (NIHSS) improvement (R = 0.63, p = 0.005).

Conclusions

SE is a reliable readout of the neurophysiological and clinical alterations occurring after an ischaemic cortical lesion.

Significance

SE promise to be a robust method to monitor and predict patients’ functional outcome.

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.

Stability of spectral estimates in resting-state magnetoencephalography: Recommendations for minimal data duration with neuroanatomical specificity

The principle of resting-state paradigms is appealing and practical for collecting data from impaired patients and special populations, especially if data collection times can be minimized. To achieve this goal, researchers need to ensure estimated signal features of interest are robust. In electro- and magnetoencephalography (EEG, MEG) we are not aware of any studies of the minimal length of data required to yield a robust one-session snapshot of the frequency-spectrum derivatives that are typically used to characterize the complex dynamics of the brain’s resting-state. We aimed to fill this knowledge gap by studying the stability of common spectra measures of resting-state MEG source time series obtained from large samples of single-session recordings from shared data repositories featuring different recording conditions and instrument technologies (OMEGA: N = 107; Cam-CAN: N = 50). We discovered that the rhythmic and arrhythmic spectral properties of intrinsic brain activity can be robustly estimated in most cortical regions when derived from relatively short segments of 30-s to 120-s of resting-state data, regardless of instrument technology and resting-state paradigm. Using an adapted leave-one-out approach and Bayesian analysis, we also provide evidence that the stability of spectral features over time is unaffected by age, sex, handedness, and general cognitive function. In summary, short MEG sessions are sufficient to yield robust estimates of frequency-defined brain activity during resting-state. This study may help guide future empirical designs in the field, particularly when recording times need to be minimized, such as with patient or special populations.

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.

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.