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

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.

Differentiating rhythmic high-amplitude delta with superimposed (poly) spikes from extreme delta brushes: limitations of standardized nomenclature and implications for patient management

BACKGROUND

Following the standardized nomenclature proposed by the American Clinical Neurophysiology Society (ACNS), rhythmic high-amplitude delta activity with superimposed spikes (RHADS) can be reported as an extreme delta brush (EDB). The clinical implications of similar electrographic patterns being reported as RHADS versus EDB are important to highlight. We aim to review the electrographic characteristics of RHADS, evaluate whether RHADS is seen in other neurological disorders, and identify the similar and unique characteristics between RHADS and EDB to ultimately determine the most accurate way to differentiate and report these patterns. We believe that the differentiation of RHADS and EDB is important as there is a vast difference in the diagnostic approach and the medical management of associated underlying etiologies.

DATA SOURCE

We conducted an extensive search on MEDLINE and Pubmed utilizing various combinations of keywords. Searching for "gamma polymerase and EEG", or "RHADS" or "Alpers syndrome and EEG" or "EEG" AND "Alpers-Huttenlocher syndrome".

RESULTS

Three articles were found to be focused on the description of "RHADS" pattern in Alpers Syndrome. No publication to date were found when searching for the terms "EDB" AND "children", AND "infant" AND "adolescent" excluding "encephalitis" and "neonate". Although RHADS and EDB appear as similar EEG patterns, meticulous analysis can differentiate them. RHADS is not exclusive to patients with Alpers-Huttenlocher syndrome and may manifest in regions beyond the posterior head region. Reactivity to eye-opening and response to anesthesia can be two other elements that help in the differentiation of these patterns.

CONCLUSION

RHADS is not exclusive to patients with AHS and may manifest in regions beyond the posterior head region. Reactivity to eye-opening and response to anesthesia are features that help in the differentiation of these patterns.

Electroencephalographic Correlates of Clinical Severity in the Natural history study of RTT and Related Disorders

OBJECTIVE

This study was undertaken to characterize quantitative electroencephalographic (EEG) features in participants from the Natural history study of RTT and Related Disorders and to assess the potential for these features to act as objective measures of cortical function for Rett syndrome (RTT).

METHODS

EEG amplitude and power features were derived from the resting EEG of 60 females with RTT (median age = 10.7 years) and 26 neurotypical females (median age = 10.6 years). Analyses focus on group differences and within the RTT group, associations between the EEG parameters and clinical severity. For a subset of participants (n = 20), follow-up data were available for assessing the reproducibility of the results and the stability in the parameters over 1 year.

RESULTS

Compared to neurotypical participants, participants with RTT had greater amplitude variability and greater low-frequency activity as reflected by greater delta power, more negative 1/f slope, and lower theta/delta, alpha/delta, beta/delta, alpha/theta, and beta/theta ratios. Greater delta power, more negative 1/f slope, and lower power ratios were associated with greater severity. Analyses of year 1 data replicated the associations between 1/f slope and power ratios and clinical severity and demonstrated good within-subject consistency in these measures.

INTERPRETATION

Overall, group comparisons reflected a greater predominance of lower versus higher frequency activity in participants with RTT, which is consistent with prior clinical interpretations of resting EEG in this population. The observed associations between the EEG power measures and clinical assessments and the repeatability of these measures underscore the potential for EEG to provide an objective measure of cortical function and clinical severity for RTT. ANN NEUROL 2024;96:175-186.

Potentiation of the muscarinic acetylcholine receptor 1 modulates neurophysiological features in a mouse model of Rett syndrome

Rett syndrome (RTT) is a neurodevelopmental disorder primarily caused by mutations in the X chromosome-linked gene Methyl-CpG Binding Protein 2 (MECP2). Restoring MeCP2 expression after disease onset in a mouse model of RTT reverses phenotypes, providing hope for development of treatments for RTT. Translatable biomarkers of improvement and treatment responses have the potential to accelerate both preclinical and clinical evaluation of targeted therapies in RTT. Studies in people with and mouse models of RTT have identified neurophysiological features, such as auditory event-related potentials, that correlate with disease severity, suggesting that they could be useful as biomarkers of disease improvement or early treatment response. We recently demonstrated that treatment of RTT mice with a positive allosteric modulator (PAM) of muscarinic acetylcholine subtype 1 receptor (M1) improved phenotypes, suggesting that modulation of M1 activity is a potential therapy in RTT. To evaluate whether neurophysiological features could be useful biomarkers to assess the effects of M1 PAM treatment, we acutely administered the M1 PAM VU0486846 (VU846) at doses of 1, 3, 10 and 30 ​mg/kg in wildtype and RTT mice. This resulted in an inverted U-shaped dose response with maximal improvement of AEP features at 3 ​mg/kg but with no marked effect on basal EEG power or epileptiform discharges in RTT mice and no significant changes in wildtype mice. These findings suggest that M1 potentiation can improve neural circuit synchrony to auditory stimuli in RTT mice and that neurophysiological features have potential as pharmacodynamic or treatment-responsive biomarkers for preclinical and clinical evaluation of putative therapies in RTT.

Nacc1 Mutation in Mice Models Rare Neurodevelopmental Disorder with Underlying Synaptic Dysfunction

A missense mutation in the transcription repressor Nucleus accumbens-associated 1 (NACC1) gene at c.892C>T (p.Arg298Trp) on chromosome 19 causes severe neurodevelopmental delay ( Schoch et al., 2017). To model this disorder, we engineered the first mouse model with the homologous mutation (Nacc1+/R284W ) and examined mice from E17.5 to 8 months. Both genders had delayed weight gain, epileptiform discharges and altered power spectral distribution in cortical electroencephalogram, behavioral seizures, and marked hindlimb clasping; females displayed thigmotaxis in an open field. In the cortex, NACC1 long isoform, which harbors the mutation, increased from 3 to 6 months, whereas the short isoform, which is not present in humans and lacks aaR284 in mice, rose steadily from postnatal day (P) 7. Nuclear NACC1 immunoreactivity increased in cortical pyramidal neurons and parvalbumin containing interneurons but not in nuclei of astrocytes or oligodendroglia. Glial fibrillary acidic protein staining in astrocytic processes was diminished. RNA-seq of P14 mutant mice cortex revealed over 1,000 differentially expressed genes (DEGs). Glial transcripts were downregulated and synaptic genes upregulated. Top gene ontology terms from upregulated DEGs relate to postsynapse and ion channel function, while downregulated DEGs enriched for terms relating to metabolic function, mitochondria, and ribosomes. Levels of synaptic proteins were changed, but number and length of synaptic contacts were unaltered at 3 months. Homozygosity worsened some phenotypes including postnatal survival, weight gain delay, and increase in nuclear NACC1. This mouse model simulates a rare form of autism and will be indispensable for assessing pathophysiology and targets for therapeutic intervention.

The selfish network: how the brain preserves behavioral function through shifts in neuronal network state

Neuronal networks possess the ability to regulate their activity states in response to disruptions. How and when neuronal networks turn from physiological into pathological states, leading to the manifestation of neuropsychiatric disorders, remains largely unknown. Here, we propose that neuronal networks intrinsically maintain network stability even at the cost of neuronal loss. Despite the new stable state being potentially maladaptive, neural networks may not reverse back to states associated with better long-term outcomes. These maladaptive states are often associated with hyperactive neurons, marking the starting point for activity-dependent neurodegeneration. Transitions between network states may occur rapidly, and in discrete steps rather than continuously, particularly in neurodegenerative disorders. The self-stabilizing, metastable, and noncontinuous characteristics of these network states can be mathematically described as attractors. Maladaptive attractors may represent a distinct pathophysiological entity that could serve as a target for new therapies and for fostering resilience.

A neurophysiological basis for aperiodic EEG and the background spectral trend

Electroencephalograms (EEGs) display a mixture of rhythmic and broadband fluctuations, the latter manifesting as an apparent 1/f spectral trend. While network oscillations are known to generate rhythmic EEG, the neural basis of broadband EEG remains unexplained. Here, we use biophysical modelling to show that aperiodic neural activity can generate detectable scalp potentials and shape broadband EEG features, but that these aperiodic signals do not significantly perturb brain rhythm quantification. Further model analysis demonstrated that rhythmic EEG signals are profoundly corrupted by shifts in synapse properties. To examine this scenario, we recorded EEGs of human subjects being administered propofol, a general anesthetic and GABA receptor agonist. Drug administration caused broadband EEG changes that quantitatively matched propofol's known effects on GABA receptors. We used our model to correct for these confounding broadband changes, which revealed that delta power, uniquely, increased within seconds of individuals losing consciousness. Altogether, this work details how EEG signals are shaped by neurophysiological factors other than brain rhythms and elucidates how these signals can undermine traditional EEG interpretation.

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.

Abnormal spectral and scale-free properties of resting-state EEG in girls with Rett syndrome

Spontaneous EEG contains important information about neuronal network properties that is valuable for understanding different neurological and psychiatric conditions. Rett syndrome (RTT) is a rare neurodevelopmental disorder, caused by mutation in the MECP2 gene. RTT is characterized by severe motor impairments that prevent adequate assessment of cognitive functions. Here we probe EEG parameters obtained in no visual input condition from a 28-channels system in 23 patients with Rett Syndrome and 38 their typically developing peers aged 3-17 years old. Confirming previous results, RTT showed a fronto-central theta power (4-6.25 Hz) increase that correlates with a progression of the disease. Alpha power (6.75-11.75 Hz) across multiple regions was, on the contrary, decreased in RTT, also corresponding to general background slowing reported previously. Among novel results we found an increase in gamma power (31-39.5 Hz) across frontal, central and temporal electrodes, suggesting elevated excitation/inhibition ratio. Long-range temporal correlation measured by detrended fluctuation analysis within 6-13 Hz was also increased, pointing to a more predictable oscillation pattern in RTT. Overall measured EEG parameters allow to differentiate groups with high accuracy, ROC AUC value of 0.92 ± 0.08, indicating clinical relevance.

Mecp2 deletion results in profound alterations of developmental and adult functional connectivity

As a regressive neurodevelopmental disorder with a well-established genetic cause, Rett syndrome and its Mecp2 loss-of-function mouse model provide an excellent opportunity to define potentially translatable functional signatures of disease progression, as well as offer insight into the role of Mecp2 in functional circuit development. Thus, we applied widefield optical fluorescence imaging to assess mesoscale calcium functional connectivity (FC) in the Mecp2 cortex both at postnatal day (P)35 in development and during the disease-related decline. We found that FC between numerous cortical regions was disrupted in Mecp2 mutant males both in juvenile development and early adulthood. Female Mecp2 mice displayed an increase in homotopic contralateral FC in the motor cortex at P35 but not in adulthood, where instead more posterior parietal regions were implicated. An increase in the amplitude of connection strength, both with more positive correlations and more negative anticorrelations, was observed across the male cortex in numerous functional regions. Widespread rescue of MeCP2 protein in GABAergic neurons rescued none of these functional deficits, nor, surprisingly, the expected male lifespan. Altogether, the female results identify early signs of disease progression, while the results in males indicate MeCP2 protein is required for typical FC in the brain.

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.

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.

A circuit-level biomarker of Rett syndrome based on ectopic phase-amplitude coupling during slow-wave-sleep

Rett syndrome (RTT) is a neurodevelopmental disorder characterized by loss of purposeful hand use and spoken language following an initial period of normal development. Although much is known about the genetic and molecular underpinnings of RTT, less is known about the circuit-level etiopathology. Coupling of oscillations during slow-wave-sleep (SWS) underlies important neurocognitive processes in adulthood, yet its emergence has yet to be described in early typical development (TD) or in RTT. We therefore addressed these unknowns by describing SWS cross-frequency coupling in both RTT and early TD using a retrospective study design. We found that in TD, phase-amplitude coupling (PAC) during SWS was dominated by coupling of slow-wave (0.5-2 Hz) phase to theta amplitude (5-8 Hz, "SW:T") as well as slow-wave to spindle-range (12-15 Hz, "SW:S"). Coupling exhibited characteristic vertex-prominent spatial topography, which emerged during an early developmental window. This topography failed to develop in patients with RTT due to persistent ectopic coupling. Furthermore, we found that subtypes of RTT exhibit distinct PAC topographic profiles, and that ectopic PAC correlates with clinical severity. These findings suggest that altered PAC dynamics and spatial organization during SWS may underlie the circuit-level pathophysiology of RTT and suggest that ectopic coupling may contribute to RTT pathogenesis.

Quantitative EEG Analysis in Angelman Syndrome: Candidate Method for Assessing Therapeutics

The goal of these studies was to use quantitative (q)EEG techniques on data from children with Angelman syndrome (AS) using spectral power analysis, and to evaluate this as a potential biomarker and quantitative method to evaluate therapeutics. Although characteristic patterns are evident in visual inspection, using qEEG techniques has the potential to provide quantitative evidence of treatment efficacy. We first assessed spectral power from baseline EEG recordings collected from children with AS compared to age-matched neurotypical controls, which corroborated the previously reported finding of increased total power driven by elevated delta power in children with AS. We then retrospectively analyzed data collected during a clinical trial evaluating the safety and tolerability of minocycline (3 mg/kg/d) to compare pretreatment recordings from children with AS (4-12 years of age) to EEG activity at the end of treatment and following washout for EEG spectral power and epileptiform events. At baseline and during minocycline treatment, the AS subjects demonstrated increased delta power; however, following washout from minocycline treatment the AS subjects had significantly reduced EEG spectral power and epileptiform activity. Our findings support the use of qEEG analysis in evaluating AS and suggest that this technique may be useful to evaluate therapeutic efficacy in AS. Normalizing EEG power in AS therefore may become an important metric in screening therapeutics to gauge overall efficacy. As therapeutics transition from preclinical to clinical studies, it is vital to establish outcome measures that can quantitatively evaluate putative treatments for AS and neurological disorders with distinctive EEG patterns.

Autism Spectrum Disorder and auditory sensory alterations: a systematic review on the integrity of cognitive and neuronal functions related to auditory processing

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition with a wide spectrum of symptoms, mainly characterized by social, communication, and cognitive impairments. Latest diagnostic criteria according to DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, 2013) now include sensory issues among the four restricted/repetitive behavior features defined as "hyper- or hypo-reactivity to sensory input or unusual interest in sensory aspects of environment". Here, we review auditory sensory alterations in patients with ASD. Considering the updated diagnostic criteria for ASD, we examined research evidence (2015-2022) of the integrity of the cognitive function in auditory-related tasks, the integrity of the peripheral auditory system, and the integrity of the central nervous system in patients diagnosed with ASD. Taking into account the different approaches and experimental study designs, we reappraise the knowledge on auditory sensory alterations and reflect on how these might be linked with behavior symptomatology in ASD.

Simultaneous Knockouts of the Oxytocin and Vasopressin 1b Receptors in Hippocampal CA2 Impair Social Memory

Oxytocin (Oxt) and vasopressin (Avp) are two neuropeptides with many central actions related to social cognition. The oxytocin (Oxtr) and vasopressin 1b (Avpr1b) receptors are co-expressed in the pyramidal neurons of the hippocampal subfield CA2 and are known to play a critical role in social memory formation. How the neuropeptides perform this function in this region is not fully understood. Here, we report the behavioral effects of a life-long conditional removal (knockout, KO) of either the Oxtr alone or both Avpr1b and Oxtr from the pyramidal neurons of CA2 as well as the resultant changes in synaptic transmission within the different fields of the hippocampus. Surprisingly, the removal of both receptors results in mice that are unable to habituate to a familiar female presented for short duration over short intervals but are able to recognize and discriminate females when presented for a longer duration over a longer interval. Importantly, these double KO mice were unable to discriminate between a male littermate and a novel male. Synaptic transmission between CA3 and CA2 is enhanced in these mice, suggesting a compensatory mechanism is activated to make up for the loss of the receptors. Overall, our results demonstrate that co-expression of the receptors in CA2 is necessary to allow intact social memory processing.

Clinical EEG of Rett Syndrome: Group Analysis Supplemented with Longitudinal Case Report

Rett syndrome (RTT), a severe neurodevelopmental disorder caused by MECP2 gene abnormalities, is characterized by atypical EEG activity, and its detailed examination is lacking. We combined the comparison of one-time eyes open EEG resting state activity from 32 girls with RTT and their 41 typically developing peers (age 2-16 years old) with longitudinal following of one girl with RTT to reveal EEG parameters which correspond to the RTT progression. Traditional measures, such as epileptiform abnormalities, generalized background activity, beta activity and the sensorimotor rhythm, were supplemented by a new frequency rate index measured as the ratio between high- and low-frequency power of sensorimotor rhythm. Almost all studied EEG parameters differentiated the groups; however, only the elevated generalized background slowing and decrease in our newly introduced frequency rate index which reflects attenuation in the proportion of the upper band of sensorimotor rhythm in RTT showed significant relation with RTT progression both in longitudinal case and group analysis. Moreover, only this novel index was linked to the breathing irregularities RTT symptom. The percentage of epileptiform activity was unrelated to RTT severity, confirming previous studies. Thus, resting EEG can provide information about the pathophysiological changes caused by MECP2 abnormalities and disease progression.

Ultrafast simulation of large-scale neocortical microcircuitry with biophysically realistic neurons

Understanding the activity of the mammalian brain requires an integrative knowledge of circuits at distinct scales, ranging from ion channel gating to circuit connectomics. Computational models are regularly employed to understand how multiple parameters contribute synergistically to circuit behavior. However, traditional models of anatomically and biophysically realistic neurons are computationally demanding, especially when scaled to model local circuits. To overcome this limitation, we trained several artificial neural network (ANN) architectures to model the activity of realistic multicompartmental cortical neurons. We identified an ANN architecture that accurately predicted subthreshold activity and action potential firing. The ANN could correctly generalize to previously unobserved synaptic input, including in models containing nonlinear dendritic properties. When scaled, processing times were orders of magnitude faster compared with traditional approaches, allowing for rapid parameter-space mapping in a circuit model of Rett syndrome. Thus, we present a novel ANN approach allowing for rapid, detailed network experiments using inexpensive and commonly available computational resources.

Auditory processing in rodent models of autism: a systematic review

Autism is a complex condition with many traits, including differences in auditory sensitivity. Studies in human autism are plagued by the difficulty of controlling for aetiology, whereas studies in individual rodent models cannot represent the full spectrum of human autism. This systematic review compares results in auditory studies across a wide range of established rodent models of autism to mimic the wide range of aetiologies in the human population. A search was conducted in the PubMed and Web of Science databases to find primary research articles in mouse or rat models of autism which investigate central auditory processing. A total of 88 studies were included. These used non-invasive measures of auditory function, such as auditory brainstem response recordings, cortical event-related potentials, electroencephalography, and behavioural tests, which are translatable to human studies. They also included invasive measures, such as electrophysiology and histology, which shed insight on the origins of the phenotypes found in the non-invasive studies. The most consistent results across these studies were increased latency of the N1 peak of event-related potentials, decreased power and coherence of gamma activity in the auditory cortex, and increased auditory startle responses to high sound levels. Invasive studies indicated loss of subcortical inhibitory neurons, hyperactivity in the lateral superior olive and auditory thalamus, and reduced specificity of responses in the auditory cortex. This review compares the auditory phenotypes across rodent models and highlights those that mimic findings in human studies, providing a framework and avenues for future studies to inform understanding of the auditory system in autism.

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.

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).

Cognitive stimulation has potential for brain activation in individuals with Rett syndrome

BACKGROUND

Knowledge regarding neuropsychological training in Rett syndrome (RS) is scarce. The aim of this study was to assess the outcome and the duration of the effect of cognitive stimulation on topographic electroencephalography (EEG) data in RS.

METHODS

Twenty female children diagnosed with RS were included in the analysis. Girls with RS conducted a cognitive task using an eye-tracker designed to evaluate access and choice skills. EEG data were acquired during the experimental procedure including two 10-min baseline stages before and after the task. Topographical changes of several EEG spectral markers including absolute and relative powers, Brain Symmetry Index and entropy were assessed.

RESULTS

Topographic significance probability maps suggested statistical decreases on delta activity and increases on beta rhythm associated with the cognitive task. Entropy increased during and after the task, likely related to more complex brain activity. A significant positive interaction was obtained between Brain Symmetry Index and age showing that the improvement of interhemispheric symmetry was higher in younger girls (5-10 years).

CONCLUSIONS

According to our findings, significant alterations of brain rhythms were observed during and after cognitive stimulation, suggesting that cognitive stimulation may have effects on brain activity beyond the stimulation period. Finally, our promising results also showed an increase brain symmetry that was especially relevant for the younger group. This could suggest an interaction of the eye-tracking cognitive task; however, further studies in this field are needed to assess the relation between brain asymmetries and age.

Emotion depends on context, culture and their interaction: evidence from effective connectivity

Situated models of emotion hypothesize that emotions are optimized for the context at hand, but most neuroimaging approaches ignore context. For the first time, we applied Granger causality (GC) analysis to determine how an emotion is affected by a person's cultural background and situation. Electroencephalographic recordings were obtained from mainland Chinese (CHN) and US participants as they viewed and rated fearful and neutral images displaying either social or non-social contexts. Independent component analysis and GC analysis were applied to determine the epoch of peak effect for each condition and to identify sources and sinks among brain regions of interest. We found that source-sink couplings differed across culture, situation and culture × situation. Mainland CHN participants alone showed preference for an early-onset source-sink pairing with the supramarginal gyrus as a causal source, suggesting that, relative to US participants, CHN participants more strongly prioritized a scene's social aspects in their response to fearful scenes. Our findings suggest that the neural representation of fear indeed varies according to both culture and situation and their interaction in ways that are consistent with norms instilled by cultural background.

Electrophysiological biomarkers of brain function in CDKL5 deficiency disorder

CDKL5 deficiency disorder is a debilitating developmental and epileptic encephalopathy for which no targeted treatment exists. A number of promising therapeutics are under development for CDKL5 deficiency disorder but a lack of validated biomarkers of brain function and clinical severity may limit the ability to objectively assess the efficacy of new treatments as they become available. To address this need, the current study quantified electrophysiological measures in individuals with CDKL5 deficiency disorder and the association between these parameters and clinical severity. Visual and auditory evoked potentials, as well as resting EEG, were acquired across 5 clinical sites from 26 individuals with CDKL5 deficiency disorder. Evoked potential and quantitative EEG features were calculated and compared with typically developing individuals in an age- and sex-matched cohort. Baseline and Year 1 data, when available, were analysed and the repeatability of the results was tested. Two clinician-completed severity scales were used for evaluating the clinical relevance of the electrophysiological parameters. Group-level comparisons revealed reduced visual evoked potential amplitude in CDKL5 deficiency disorder individuals versus typically developing individuals. There were no group differences in the latency of the visual evoked potentials or in the latency or amplitude of the auditory evoked potentials. Within the CDKL5 deficiency disorder group, auditory evoked potential amplitude correlated with disease severity at baseline as well as Year 1. Multiple quantitative EEG features differed between CDKL5 deficiency disorder and typically developing participants, including amplitude standard deviation, 1/f slope and global delta, theta, alpha and beta power. Several quantitative EEG features correlated with clinical severity, including amplitude skewness, theta/delta ratio and alpha/delta ratio. The theta/delta ratio was the overall strongest predictor of severity and also among the most repeatable qEEG measures from baseline to Year 1. Together, the present findings point to the utility of evoked potentials and quantitative EEG parameters as objective measures of brain function and disease severity in future clinical trials for CDKL5 deficiency disorder. The results also underscore the utility of the current methods, which could be similarly applied to the identification and validation of electrophysiological biomarkers of brain function for other developmental encephalopathies.

Expression of 4E-BP1 in juvenile mice alleviates mTOR-induced neuronal dysfunction and epilepsy

Hyperactivation of the mechanistic target of rapamycin (mTOR) pathway during fetal neurodevelopment alters neuron structure and function, leading to focal malformation of cortical development (FMCD) and intractable epilepsy. Recent evidence suggests a role for dysregulated cap-dependent translation downstream of mTOR in the formation of FMCD and seizures. However, it is unknown whether modifying translation once the developmental pathologies are established can reverse neuronal abnormalities and seizures. Addressing these issues is crucial with regards to therapeutics since these neurodevelopmental disorders are predominantly diagnosed during childhood, when patients present with symptoms. Here, we report increased phosphorylation of the mTOR effector and translational repressor, 4E-BP1, in patient FMCD tissue and in a mouse model of FMCD. Using temporally regulated conditional gene expression systems, we found that expression of a constitutively active form of 4E-BP1 that resists phosphorylation by mTOR in juvenile mice reduced neuronal cytomegaly and corrected several neuronal electrophysiological alterations, including depolarized resting membrane potential, irregular firing pattern, and aberrant expression of HCN4 channels. Further, 4E-BP1 expression in juvenile FMCD mice after epilepsy onset resulted in improved cortical spectral activity and decreased spontaneous seizure frequency in adults. Overall, our study uncovered a remarkable plasticity of the juvenile brain that facilitates novel therapeutic opportunities to treat FMCD-related epilepsy during childhood with potentially long-lasting effects in adults.

Spectral changes following resective epilepsy surgery and neurocognitive function in children with epilepsy

Decelerated resting cortical oscillations, high-frequency activity, and enhanced cross-frequency interactions are features of focal epilepsy. The association between electrophysiological signal properties and neurocognitive function, particularly following resective surgery, is, however, unclear. In the current report, we studied intraoperative recordings from intracranial electrodes implanted in seven children with focal epilepsy and analyzed the spectral dynamics both before and after surgical resection of the hypothesized seizure focus. The associations between electrophysiological spectral signatures and each child's neurocognitive profiles were characterized using a partial least squares analysis. We find that extent of spectral alteration at the periphery of surgical resection, as indexed by slowed resting frequency and its acceleration following surgery, is associated with baseline cognitive deficits in children. The current report provides evidence supporting the relationship between altered spectral properties in focal epilepsy and neuropsychological deficits in children. In particular, these findings suggest a critical role of disrupted thalamocortical rhythms, which are believed to underlie the spectral alterations we describe, in both epileptogenicity and neurocognitive function.NEW & NOTEWORTHY Spectral alterations marked by decelerated resting oscillations and ectopic high-frequency activity have been noted in focal epilepsy. We leveraged intraoperative recordings from chronically implanted electrodes pre- and postresection to understand the association between these electrophysiological phenomena and neuropsychological function. We find that the extent of spectral alteration, indexed by slowed resting frequency and its acceleration following resection, is associated with baseline cognitive deficits. These findings provide novel insights into neurocognitive impairments in focal epilepsy.

Choosing Strategies to Deal with Artifactual EEG Data in Children with Cognitive Impairment

Rett syndrome is a disease that involves acute cognitive impairment and, consequently, a complex and varied symptomatology. This study evaluates the EEG signals of twenty-nine patients and classify them according to the level of movement artifact. The main goal is to achieve an artifact rejection strategy that performs well in all signals, regardless of the artifact level. Two different methods have been studied: one based on the data distribution and the other based on the energy function, with entropy as its main component. The method based on the data distribution shows poor performance with signals containing high amplitude outliers. On the contrary, the method based on the energy function is more robust to outliers. As it does not depend on the data distribution, it is not affected by artifactual events. A double rejection strategy has been chosen, first on a motion signal (accelerometer or EEG low-pass filtered between 1 and 10 Hz) and then on the EEG signal. The results showed a higher performance when working combining both artifact rejection methods. The energy-based method, to isolate motion artifacts, and the data-distribution-based method, to eliminate the remaining lower amplitude artifacts were used. In conclusion, a new method that proves to be robust for all types of signals is designed.

Electrophysiological Biomarkers in Genetic Epilepsies

Precision treatments for epilepsy targeting the underlying genetic diagnoses are becoming a reality. Historically, the goal of epilepsy treatments was to reduce seizure frequency. In the era of precision medicine, however, outcomes such as prevention of epilepsy progression or even improvements in cognitive functions are both aspirational targets for any intervention. Developing methods, both in clinical trial design and in novel endpoints, will be necessary for measuring, not only seizures, but also the other neurodevelopmental outcomes that are predicted to be targeted by precision treatments. Biomarkers that quantitatively measure disease progression or network level changes are needed to allow for unbiased measurements of the effects of any gene-level treatments. Here, we discuss some of the promising electrophysiological biomarkers that may be of use in clinical trials of precision therapies, as well as the difficulties in implementing them.

Reviewing Evidence for the Relationship of EEG Abnormalities and RTT Phenotype Paralleled by Insights from Animal Studies

Rett syndrome (RTT) is a rare neurodevelopmental disorder that is usually caused by mutations of the MECP2 gene. Patients with RTT suffer from severe deficits in motor, perceptual and cognitive domains. Electroencephalogram (EEG) has provided useful information to clinicians and scientists, from the very first descriptions of RTT, and yet no reliable neurophysiological biomarkers related to the pathophysiology of the disorder or symptom severity have been identified to date. To identify consistently observed and potentially informative EEG characteristics of RTT pathophysiology, and ascertain areas most worthy of further systematic investigation, here we review the literature for EEG abnormalities reported in patients with RTT and in its disease models. While pointing to some promising potential EEG biomarkers of RTT, our review identify areas of need to realize the potential of EEG including (1) quantitative investigation of promising clinical-EEG observations in RTT, e.g., shift of mu rhythm frequency and EEG during sleep; (2) closer alignment of approaches between patients with RTT and its animal models to strengthen the translational significance of the work (e.g., EEG measurements and behavioral states); (3) establishment of large-scale consortium research, to provide adequate Ns to investigate age and genotype effects.

Consciousness among delta waves: a paradox?

A common observation in EEG research is that consciousness vanishes with the appearance of delta (1 - 4 Hz) waves, particularly when those waves are high amplitude. High amplitude delta oscillations are very frequently observed in states of diminished consciousness, including slow wave sleep, anaesthesia, generalised epileptic seizures, and disorders of consciousness such as coma and vegetative state. This strong correlation between loss of consciousness and high amplitude delta oscillations is thought to stem from the widespread cortical deactivation that occurs during the "down states" or troughs of these slow oscillations. Recently, however, many studies have reported the presence of prominent delta activity during conscious states, which casts doubt on the hypothesis that high amplitude delta oscillations are an indicator of unconsciousness. These studies include work in Angelman syndrome, epilepsy, behavioural responsiveness during propofol anaesthesia, postoperative delirium, and states of dissociation from the environment such as dreaming and powerful psychedelic states. The foregoing studies complement an older, yet largely unacknowledged, body of literature that has documented awake, conscious patients with high amplitude delta oscillations in clinical reports from Rett syndrome, Lennox-Gastaut syndrome, schizophrenia, mitochondrial diseases, hepatic encephalopathy, and nonconvulsive status epilepticus. At the same time, a largely parallel body of recent work has reported convincing evidence that the complexity or entropy of EEG and magnetoencephalogram or MEG signals strongly relates to an individual's level of consciousness. Having reviewed this literature, we discuss plausible mechanisms that would resolve the seeming contradiction between high amplitude delta oscillations and consciousness. We also consider implications concerning theories of consciousness, such as integrated information theory and the entropic brain hypothesis. Finally, we conclude that false inferences of unconscious states can be best avoided by examining measures of electrophysiological complexity in addition to spectral power.

Exploring the reliability and sensitivity of the EEG power spectrum as a biomarker

INTRODUCTION

The slope of the electroencephalography (EEG) power spectrum (also referred to as 1/f noise) is an important consideration when calculating narrow-band power. However, psychophysiological data also suggest this slope is a meaningful signal itself, not merely background activity or noise. We present two different methods for quantifying the slope of the power spectrum and assess their reliability and sensitivity.

METHODS

We used data from N = 60 participants who had EEG collected during rest, a videogame task, and a second period of rest. At all phases of the experiment, we calculated the "spectral slope" (a regression-based method fit to all datapoints) and the "aperiodic slope" (estimated with the fitting oscillations with 1/f algorithm FOOOF). For both methods we assessed: their reliability, their sensitivity to the transition from rest to task, their sensitivity to changes during the videogame task itself, and the agreement between the two measures.

RESULTS

Across resting phases, both spectral and aperiodic slopes showed a high degree of reliability. Both methods also showed a steepening of the power spectrum on-task compared to rest. There was also a high degree of consistency between the two methods in their estimate of the underlying slope, but FOOOF explained more variance in the power spectra across regions and type of activity (rest versus task).

CONCLUSION

The slope of the power spectrum is a highly reliable individual difference and sensitive to within-subject changes across two different methods of estimation. Moving forward, we generally recommend the use of the FOOOF algorithm for its ability to account for narrow-band signals, but these data show how regression-based approaches produce similar estimates of the spectral slope, which may be useful in some applications.

Detection of neurophysiological features in female R255X MeCP2 mutation mice

Rett syndrome (RTT) is a severe neurodevelopmental disorder (NDD) that is nearly always caused by loss of function mutations in Methyl-CpG-binding Protein 2 (MECP2) and shares many clinical features with other NDD. Genetic restoration of Mecp2 in symptomatic mice lacking MeCP2 expression can reverse symptoms, providing hope that disease modifying therapies can be identified for RTT. Effective and rapid clinical trial completion relies on well-defined clinical outcome measures and robust biomarkers of treatment responses. Studies on other NDD have found evidence of differences in neurophysiological measures that correlate with disease severity. However, currently there are no well-validated biomarkers in RTT to predict disease prognosis or treatment responses. To address this, we characterized neurophysiological features in a mouse model of RTT containing a knock-in nonsense mutation (p.R255X) in the Mecp2 locus. We found a variety of changes in heterozygous female Mecp2^R255X/X mice including age-related changes in sleep/wake architecture, alterations in baseline EEG power, increased incidence of spontaneous epileptiform discharges, and changes in auditory evoked potentials. Furthermore, we identified association of some neurophysiological features with disease severity. These findings provide a set of potential non-invasive and translatable biomarkers that can be utilized in preclinical therapy trials in animal models of RTT and eventually within the context of clinical trials.

Functional Network Mapping Reveals State-Dependent Response to IGF1 Treatment in Rett Syndrome

Rett Syndrome (RTT) is a neurodevelopmental disorder associated with mutations in the gene MeCP2, which is involved in the development and function of cortical networks. The clinical presentation of RTT is generally severe and includes developmental regression and marked neurologic impairment. Insulin-Like growth factor 1 (IGF1) ameliorates RTT-relevant phenotypes in animal models and improves some clinical manifestations in early human trials. However, it remains unclear whether IGF1 treatment has an impact on cortical electrophysiology in line with MeCP2’s role in network formation, and whether these electrophysiological changes are related to clinical response. We performed clinical assessments and resting-state electroencephalogram (EEG) recordings in eighteen patients with classic RTT, nine of whom were treated with IGF1. Among the treated patients, we distinguished those who showed improvements after treatment (responders) from those who did not show any changes (nonresponders). Clinical assessments were carried out for all individuals with RTT at baseline and 12 months after treatment. Network measures were derived using statistical modelling techniques based on interelectrode coherence measures. We found significant interaction between treatment groups and timepoints, indicating an effect of IGF1 on network measures. We also found a significant effect of responder status and timepoint, indicating that these changes in network measures are associated with clinical response to treatment. Further, we found baseline variability in network characteristics, and a machine learning model using these measures applied to pretreatment data predicted treatment response with 100% accuracy (100% sensitivity and 100% specificity) in this small patient group. These results highlight the importance of network pathology in RTT, as well as providing preliminary evidence for the potential of network measures as tools for the characterisation of disease subtypes and as biomarkers for clinical trials.

Evoked Potentials and EEG Analysis in Rett Syndrome and Related Developmental Encephalopathies: Towards a Biomarker for Translational Research

Rett syndrome is a debilitating neurodevelopmental disorder for which no disease-modifying treatment is available. Fortunately, advances in our understanding of the genetics and pathophysiology of Rett syndrome has led to the development of promising new therapeutics for the condition. Several of these therapeutics are currently being tested in clinical trials with others likely to progress to clinical trials in the coming years. The failure of recent clinical trials for Rett syndrome and other neurodevelopmental disorders has highlighted the need for electrophysiological or other objective biological markers of treatment response to support the success of clinical trials moving forward. The purpose of this review is to describe the existing studies of electroencephalography (EEG) and evoked potentials (EPs) in Rett syndrome and discuss the open questions that must be addressed before the field can adopt these measures as surrogate endpoints in clinical trials. In addition to summarizing the human work on Rett syndrome, we also describe relevant studies with animal models and the limited research that has been carried out on Rett-related disorders, particularly methyl-CpG binding protein 2 (MECP2) duplication syndrome, CDKL5 deficiency disorder, and FOXG1 disorder.

Seizures in Mouse Models of Rare Neurodevelopmental Disorders

Genetic neurodevelopmental disorders - that often include epilepsy as part of their phenotype - are a heterogeneous and clinically challenging spectrum of disorders in children. Although seizures often contribute significantly to morbidity in these affected populations, the mechanisms of epileptogenesis in these conditions remain poorly understood. Different model systems have been developed to aid in unraveling these mechanisms, which include a number of specific mutant mouse lines which genocopy specific general types of mutations present in patients. These mouse models have not only allowed for assessments of behavioral and electrographic seizure phenotypes to be ascertained, but also have allowed effects on the neurodevelopmental alterations and cognitive impairments associated with these disorders to be examined. In addition, these models play a role in advancing our understanding of these epileptic processes and developing preclinical therapeutics. The concordance of seizure phenotypes - in a select group of rare, genetic, neurodevelopmental disorders and epileptic encephalopathies - found between human patients and their model counterparts will be summarized. This review aims to assess whether models of Rett syndrome, CDKL5 deficiency disorder, Fragile-X syndrome, Dravet syndrome, and Ohtahara syndrome phenocopy the seizures seen in human patients.

Multielectrode array analysis of EEG biomarkers in a mouse model of Fragile X Syndrome

Fragile X Syndrome (FXS) is a leading known genetic cause of intellectual disability with symptoms that include increased anxiety and social and sensory processing deficits. Recent EEG studies in humans with FXS have identified neural oscillation deficits that include increased resting state gamma power, increased amplitude of auditory evoked potentials, and reduced inter-trial phase coherence of sound-evoked gamma oscillations. Identification of comparable EEG biomarkers in mouse models of FXS could facilitate the pre-clinical to clinical therapeutic pipeline. However, while human EEG studies have involved 128-channel scalp EEG acquisition, no mouse studies have been performed with more than three EEG channels. In the current study, we employed a recently developed 30-channel mouse multielectrode array (MEA) system to record and analyze resting and stimulus-evoked EEG signals in WT vs. Fmr1 KO mice. Using this system, we now report robust MEA-derived phenotypes including higher resting EEG power, altered event-related potentials (ERPs) and reduced inter-trial phase coherence to auditory chirp stimuli in Fmr1 KO mice that are remarkably similar to those reported in humans with FXS. We propose that the MEA system can be used for: (i) derivation of higher-level EEG parameters; (ii) EEG biomarkers for drug testing; and (ii) mechanistic studies of FXS pathophysiology.