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Macrocephaly has been associated with neurodevelopmental disorders; however, it has been mainly studied in the context of pathological or high-risk populations and little is known about its impact, as an isolated trait, on brain development in general population. Electroencephalographic (EEG) power spectral density (PSD) and signal complexity have shown to be sensitive to neurodevelopment and its alterations. We aimed to investigate the impact of macrocephaly as isolated trait on EEG signal as measured by power spectral density (PSD) and Multiscale Entropy (MSE) during the first year of life. We recorded high density EEG resting state activity of 74 healthy full-term infants, 50 control (26 girls) and 24 macrocephalic (12 girls) aged between 3 and 11 months. We used linear regression models to assess group and age effects on EEG power spectral density (PSD) and signal complexity. Sex and brain volume measures, obtained via a 3D transfontanellar ultrasound, were also included into the models to evaluate their contribution. Our results showed lower PSD of the low alpha (8-10Hz) frequency band and lower complexity in the macrocephalic group compared to the control group. In addition, we found an increase in low alpha (8.5-10Hz) PSD and in the complexity index with age. These findings suggest that macrocephaly as an isolated trait has a significant impact on brain activity during the first year of life.

Background Mutations in the GATOR1 complex genes, DEPDC5 and NPRL3, play a major role in the development of lesional and non-lesional focal epilepsy through increased mTORC1 signalling. We aimed to assess the effects of mTORC1 hyperactivation on GABAergic inhibitory circuits, in 3 and 5 individuals carrying DEPDC5 and NPRL3 mutations respectively using a multimodal approach including transcranial magnetic stimulation (TMS), magnetic resonance spectroscopy (MRS), and electroencephalography (EEG). Results Inhibitory functions probed by TMS and MRS showed no effect of mutations on cortical GABAergic receptor-mediated inhibition and GABA concentration, in both cortical and subcortical regions. However, stronger EEG theta oscillations and stronger and more synchronous gamma oscillations were observed in DEPDC5 and NPRL3 mutations carriers. Conclusions These results suggest that DEPDC5 and NPRL3-related epileptic mTORopathies may not directly modulate GABAergic functions but are nonetheless characterized by a stronger neural entrainment that may be reflective of a cortical hyperexcitability mediated by increased mTORC1 signaling.

Amongst the numerous genes associated with intellectual disability, SYNGAP1 stands out for its frequency and penetrance of loss-of-function variants found in patients, as well as the wide range of co-morbid disorders associated with its mutation. Most studies exploring the pathophysiological alterations caused by Syngap1 haploinsufficiency in mouse models have focused on cognitive problems and epilepsy, however whether and to what extent sensory perception and processing are altered by Syngap1 haploinsufficiency is less clear. By performing EEG recordings in awake mice, we identified specific alterations in multiple aspects of auditory and visual processing, including increased baseline gamma oscillation power, increased theta/gamma phase amplitude coupling following stimulus presentation and abnormal neural entrainment in response to different sensory modality-specific frequencies. We also report lack of habituation to repetitive auditory stimuli and abnormal deviant sound detection. Interestingly, we found that most of these alterations are present in human patients as well, thus making them strong candidates as translational biomarkers of sensory-processing alterations associated with SYNGAP1/Syngap1 haploinsufficiency.

Objective Altered sensory processing is common in intellectual disability (ID). Here, we study electroencephalographic responses to auditory stimulation in human subjects presenting a rare condition (mutations in SYNGAP1) which causes ID, epilepsy and autism. Methods Auditory evoked potentials, time-frequency and inter-trial coherence analyses were used to compare subjects with SYNGAP1 mutations with Down syndrome (DS) and neurotypical (NT) participants (N = 61 ranging from three to 19 years of age). Results Altered synchronization in the brain responses to sound were found in both ID groups. The SYNGAP1 mutations group showed less phase-locking in early time windows and lower frequency bands compared to NT, and in later time windows compared to NT and DS. Time-frequency analysis showed more power in beta-gamma in the SYNGAP1 group compared to NT participants. Conclusions This study indicated reduced synchronization as well as more high frequencies power in SYNGAP1 mutations, while maintained synchronization was found in the DS group. These results might reflect dysfunctional sensory information processing caused by excitation/inhibition imbalance, or an imperfect compensatory mechanism in SYNGAP1 mutations individuals. Significance Our study is the first to reveal brain response abnormalities in auditory sensory processing in SYNGAP1 mutations individuals, that are distinct from DS, another ID condition.

Macrocephaly is present in about 2–5% of the general population. It can be found as an isolated benign trait or as part of a syndromic condition. Brain overgrowth has been associated with neurodevelopmental disorders such as autism during the first year of life, however, evidence remains inconclusive. Furthermore, most of the studies have involved pathological or high-risk populations, but little is known about the effects of brain overgrowth on neurodevelopment in otherwise neurotypical infants. We investigated the impact of brain overgrowth on basic perceptual learning processes (repetition effects and change detection response) during the first year of life. We recorded high density electroencephalograms (EEG) in 116 full-term healthy infants aged between 3 and 11 months, 35 macrocephalic (14 girls) and 81 normocephalic (39 girls) classified according to the WHO head circumference norms. We used an adapted oddball paradigm, time-frequency analyses, and auditory event-related brain potentials (ERPs) to investigate differences between groups. We show that brain overgrowth has a significant impact on repetition effects and change detection response in the 10–20 Hz frequency band, and in N450 latency, suggesting that these correlates of sensorial learning processes are sensitive to brain overgrowth during the first year of life.

[This corrects the article DOI: 10.3389/fpsyt.2021.716707.].

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 77 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.

Background Neurofibromatosis type 1 (NF1) is a genetic disorder often associated with cognitive dysfunctions, including a high occurrence of deficits in visuoperceptual skills. The neural underpinnings of these visuoperceptual deficits are not fully understood. We used steady-state visual evoked potentials (SSVEPs) to investigate possible alterations in the synchronization of neural activity in the occipital cortex of children with NF1. Methods SSVEPs were measured using electroencephalography and compared between children with NF1 (n = 28) and neurotypical controls (n = 28) aged between 4 and 13 years old. SSVEPs were recorded during visual stimulation with coloured icons flickering at three different frequencies (6 Hz, 10 Hz, and 15 Hz) and analyzed in terms of signal-to-noise ratios. A mixed design ANCOVA was performed to compare SSVEP responses between groups at the three stimulation frequencies. Pearson’s correlations with levels of intellectual functioning as well as with symptoms of ADHD, ASD and emotional/behavioral problems were performed. The impact of psychostimulant medication on the SSVEP responses was analyzed in a subset of the NF1 group (n = 8) with paired t-tests. Results We observed reduced signal-to-noise ratios of the SSVEP responses in children with NF1. The SSVEP responses were negatively correlated with symptoms of inattention and with symptoms of emotional/behavioral problems in the NF1 group. The SSVEP response generated by the lowest stimulation frequency (i.e., 6 Hz) was rescued with the intake of psychostimulant medication. Conclusions Impaired processing of rhythmic visual stimulation was evidenced in children with NF1 through measures of SSVEP responses. Those responses seem to be more reduced in children with NF1 who exhibit more symptoms of inattention and emotional/behavioral problems in their daily life. SSVEPs are potentially sensitive electrophysiological markers that could be included in future studies investigating the impact of medication on brain activity and cognitive functioning in children with NF1.

Repetition effects and change detection response have been proposed as neuro-electrophysiological correlates of fundamental learning processes. As such, they could be a good predictor of brain maturation and cognitive development. We recorded high density EEG in 71 healthy infants (32 females) aged between 3 and 9 months, while they listened to vowel sequences (standard /a/a/a/i/ [80%] and deviant /a/a/a/a/ [20%]). Adaptive skills, a surrogate of cognitive development, were measured via the parent form of the Adaptive Behavior Assessment System Second Edition (ABAS-II). Cortical auditory-evoked potentials (CAEPs) analyses, time-frequency analyses and a statistical approach using linear mixed models (LMMs) and linear regression models were performed. Age and adaptive skills were tested as predictors. Age modulation of repetition effects and change detection response was observed in theta (3-5 Hz), alpha (5-10 Hz) and high gamma (80-90 Hz) oscillations and in all CAEPs. Moreover, adaptive skills modulation of repetition effects was evidenced in theta (3-5 Hz), high gamma oscillations (80-90 Hz), N250/P350 peak-to-peak amplitude and P350 latency. Finally, adaptive skills modulation of change detection response was observed in the N250/P350 peak-to-peak amplitude. Our results confirm that repetition effects and change detection response evolve with age. Moreover, our results suggest that repetition effects and change detection response vary according to adaptive skills displayed by infants during the first year of life, demonstrating their predictive value for neurodevelopment.

Investigating the relationships between two sets of variables helps to understand their interactions and can be done with canonical correlation analysis (CCA). However, the correlation between the two sets can sometimes depend on a third set of covariates, often subject-related ones such as age, gender, or other clinical measures. In this case, applying CCA to the whole population is not optimal and methods to estimate conditional CCA, given the covariates, can be useful. We propose a new method called Random Forest with Canonical Correlation Analysis (RFCCA) to estimate the conditional canonical correlations between two sets of variables given subject-related covariates. The individual trees in the forest are built with a splitting rule specifically designed to partition the data to maximize the canonical correlation heterogeneity between child nodes. We also propose a significance test to detect the global effect of the covariates on the relationship between two sets of variables. The performance of the proposed method and the global significance test is evaluated through simulation studies that show it provides accurate canonical correlation estimations and well-controlled Type-1 error. We also show an application of the proposed method with EEG data., Comment: 27 pages, 8 figures, 1 table

Sensory processing is the gateway to information processing and more complex processes such as learning. Alterations in sensory processing is a common phenotype of many genetic syndromes associated with intellectual disability (ID). It is currently unknown whether sensory processing alterations converge or diverge on brain responses between syndromes. Here, we compare for the first time four genetic conditions with ID using the same basic sensory learning paradigm. One hundred and five participants, aged between 3 and 30 years old, composing four clinical ID groups and one control group, were recruited: Fragile X syndrome (FXS; n = 14), tuberous sclerosis complex (TSC; n = 9), Down syndrome (DS; n = 19), SYNGAP1 mutations (n = 8) and Neurotypical controls (NT; n = 55)). All groups included female and male participants. Brain responses were recorded using electroencephalography (EEG) during an audio-visual task that involved three repetitions of the pronunciation of the phoneme /a/. Event Related Potentials (ERP) were used to: 1) compare peak-to-peak amplitudes between groups, 2) evaluate the presence of repetition suppression within each group and 3) compare the relative repetition suppression between groups. Our results revealed larger overall amplitudes in FXS. A repetition suppression (RS) pattern was found in the NT group, FXS and DS, suggesting spared repetition suppression in a multimodal task in these two ID syndromes. Interestingly, FXS presented a stronger RS on one peak-to-peak value in comparison with the NT. The results of our study reveal the distinctiveness of ERP and RS brain responses in ID syndromes. Further studies should be conducted to understand the molecular mechanisms involved in these patterns of responses.