Biology subjects

Delorme, R.

Publications and source records attributed to Delorme, R..

8 recordsLinked to original sources

bioRxiv2026

Characterising sleep spindle emergence in infancy: Effects of prematurity and early locomotor intervention

Study objectives: Sleep spindles are thalamocortical oscillations evolving during early brain maturation. In adults, they support memory consolidation and are organised into rhythmic "trains" thought to support memory reactivation. How this temporal organisation emerges in infancy, and whether prematurity or early sensorimotor experience shapes it, remains unclear. This study characterised infant spindles and investigated how prematurity and early locomotor training affect their temporal and spatial organisation, providing insight into early brain maturation. Methods: Daytime high-density EEG sleep recordings were analysed in 50 infants born full-term (n=12) or very preterm (n=38, including 12 who received locomotor training) at 2 months corrected age. Spindle temporal organisation was analysed using a two-step Morlet wavelet transform to quantify slow modulations of spindle-band power (11-16Hz). Time-frequency decomposition around spindle onset was used to identify significant spindle-band scalp-wide activity, and topographical maps were statistically compared between groups. Results: All groups showed rhythmic spindle organisation, three times slower than in adults, with no group differences. Untrained preterm infants showed a more diffuse spindle-band activity than the distinct frontal and central clusters observed in full-term infants. Trained preterm infants exhibited a spatial distribution closely resembling that of full-term infants, although their frontal spindle density was lower than in both other groups. Conclusions: Spindle rhythmic organisation emerged early in infancy and remained unaffected by prematurity or locomotor training. Prematurity was associated with more diffuse spindle-band activity, suggesting reduced cortical specialisation, whereas trained preterm infants showed a spatial distribution resembling that of full-term infants, suggesting that early locomotor experience may influence thalamocortical organisation.

neuroscience↗

bioRxiv2026

Heterogeneity of Brain Dynamics in Genetic and Psychiatric Conditions

Whether the heterogeneity of psychiatric conditions converges on shared neurophysiological alterations or translates into distinct signatures remains unclear. We assembled high-density electroencephalogram (hd-EEG) resting-state recordings from 4,812 individuals aged 5 months to 66 years across 11 psychiatric conditions, a broad spectrum of rare genetic variants, and typically developing (TD) individuals. We established normative developmental trajectories of source-space EEG across spectral organization, connectivity, and signal complexity. Psychiatric conditions showed small deviations, revealing a shared transdiagnostic profile. In contrast, single rare variants showed substantially larger, distinct and sometimes mirror-opposite signatures that collapsed toward the psychiatric profile when pooled. Autism Spectrum Disorder showed some of the smallest group-level effects yet the largest individual deviations, indicating substantial but directionally inconsistent alterations. EEG deviations followed a cortical gradient, with larger effects in sensorimotor regions. We demonstrate that sample sizes in the hundreds are required for robust associations with psychiatric diagnoses. This interactive open resource provides normative scores to benchmark future results.

neuroscience↗

bioRxiv2025

Characterization of aperiodic and theta activity in preterm infants using EEG: Insights into cerebral maturation and inter-individual variability

Disrupting critical processes of brain development, preterm birth interferes with the maturation of brain networks and functional activity, including theta oscillations that are thought to play a key role in early network formation. Traditional EEG spectral analyses have indicated marked development of theta power in early infancy, but these approaches mix oscillatory and non-oscillatory activity, limiting insights into the mechanisms underlying the neural changes. Using spectral parameterization, we aimed to evaluate developmental changes in aperiodic activity and periodic theta power in infants born very preterm compared to full-terms, and to further explore whether clinical factors and brain microstructure could explain the inter-individual variability within preterms. High-density EEG was acquired during active/REM sleep at term-equivalent age (TEA) and 2 months corrected age (2mCA) in 41 very preterm infants (born <32 weeks gestational age [GA]; mean {+/-} standard deviation: 26.9{+/-}1.7 weeks) and 13 full-term controls (born [≥]37 weeks GA; 40.1{+/-}1 weeks). Spectral parameterization was used to extract aperiodic components (offset, exponent) and periodic theta power globally and across spatial clusters of electrodes (anterior, central, posterior). From TEA to 2mCA, offset, exponent, and theta power increased with no differences between preterm and full-term infants. At TEA, metrics of aperiodic activity were stronger in anterior compared with posterior areas, but this regional landscape shifted by 2mCA with pronounced increases in aperiodic offset and exponent in posterior areas from TEA to 2mCA. Within preterms, inter-individual variability in aperiodic and periodic activity at TEA was partly explained by clinical risk factors: male sex, lower gestational-age at birth, small weight at birth, and invasive ventilation were linked to alterations of aperiodic offset, exponent and theta power. Additionally, higher theta power at TEA correlated with lower cortical fractional anisotropy assessed with diffusion MRI at the same age, consistently with more advanced maturation of the brain. Collectively, these findings indicate that EEG spectral parameterization combined with spatial analysis provides a sensitive framework for characterizing the postnatal maturation of brain activity in infants, as well as early vulnerabilities associated with prematurity and perinatal adversity.

neuroscience↗

bioRxiv2025

Maternal immune activation imprints a regulatory T cell deficiency in offspring that drives an autism-like phenotype

Maternal immune activation (MIA) triggers an IL-17-driven autism spectrum disorder (ASD) in mouse and human offspring. While regulatory T cells (Tregs) regulate Th17 cells, their involvement in MIA and ASD pathogenesis is unknown. At the maternal level, we show that Treg stimulation suppresses interleukin-17 (IL-17) production and prevents ASD-like behaviors in offspring. At the offspring level, we show that MIA imprints a systemic and brain Treg deficiency, as evidenced by alterations in the methylome, transcriptome, and functional assays. This deficiency promotes brain inflammation, characterized by infiltration of IL-17-producing cells and neutrophils into the meninges and alterations in cortical brain structure. Stimulation of offspring Tregs with interleukin-2 reversed brain inflammation and cured established ASD-like behaviors. Thus, MIA-induced ASD is a neuroimmune disorder that can be reversed by immunomodulation. One sentence abstractMaternal immune activation during pregnancy imprints a Treg deficiency in offspring that perpetuates brain inflammation and an autism-like phenotype, which can be reversed by Treg stimulation.

immunology↗

bioRxiv2024

Temporal dynamics and maturation of resting-state activity in preterm infants

By interfering with the normal sequence of mechanisms serving the brain maturation, premature birth and related stress can alter perinatal experiences, with potential long-term consequences on a childs neurodevelopment. The early characterization of brain functioning and maturational changes is thus of critical interest in premature infants who are at high risk of atypical outcomes and could benefit from early diagnosis and dedicated interventions. Using high-density electroencephalography (HD-EEG), we recorded brain activity in extreme and very preterm infants at the equivalent age of pregnancy term (n=43), and longitudinally 2-months later (n=33), compared with full-term born infants (n=14). We characterized the maturation of brain activity by using a dedicated microstate analysis to quantify the spatio-temporal dynamics of the spontaneous transient network activity while controlling for vigilance states. The comparison of premature and full-term infants first showed slower dynamics as well as altered spatio-temporal properties of brain activity in preterm infants. Maturation of functional networks between term-equivalent age and 2 months later in preterms was linked to the emergence of faster dynamics, manifested in part by shorter duration of microstates, as well as an evolution in the spatial organization of the dominant microstates. The inter-individual differences in the temporal dynamics of brain activity at term-equivalent age were further impacted by sex (with slower microstate dynamics in boys) and by gestational age at birth for some microstate dynamics but not by other considered risk factors. This study highlights the potential of the microstate approach to reveal maturational properties of the emerging brain network activity in premature infants.

neuroscience↗

bioRxiv2019

Increased contrast of the grey-white matter boundary in the motor, visual and auditory areas in Autism Spectrum Disorders

The contrast of the interface between the cortical grey matter and the white matter is emerging as an important neuroimaging biomarker for several brain disorders. Differences in grey to white matter contrast could be related to abnormalities in neuronal migration or in intra-cortical myelination, and are an appealing biomarker for ASD. Two previous studies have reported differences in contrast between patients with autism spectrum disorder and non-autistic controls. We aimed at replicating this finding using open data from the ABIDE initiative, phases 1 and 2, gathering data from 2,148 subjects from 26 different centres and on 764 individuals from the EU-AIMS project (6 different centres). We used multiple linear regression to study the effect of the diagnosis of ASD on contrast, and 3 different strategies for controlling for multiple comparisons. We did not find statistically significant differences in the EU-AIMS dataset, and those that we found in the ABIDE dataset were due to a single centre. All the code necessary to replicate our analyses has been made available open source: https://github.com/neuroanatomy/GWPC.

neuroscience↗

bioRxiv2018

Reproducible functional connectivity alterations are associated with autism spectrum disorder

Despite the high clinical burden little is known about pathophysiology underlying autism spectrum disorder (ASD). Recent resting state functional magnetic resonance imaging (rs-fMRI) studies have found atypical synchronization of brain activity in ASD. However, no consensus has been reached on the nature and clinical relevance of these alterations. Here we address these questions in the most comprehensive, large-scale effort to date comprising evaluation of four large ASD cohorts. We followed a strict exploration and replication procedure to identify core rs-fMRI functional connectivity (degree centrality) alterations associated with ASD as compared to typically developing (TD) controls (ASD: N=841, TD: N=984). We then tested for associations of these imaging phenotypes with clinical and demographic factors such as age, sex, medication status and clinical symptom severity. We find reproducible patterns of ASD-associated functional hyper- and hypo-connectivity with hypo-connectivity being primarily restricted to sensory-motor regions and hyper-connectivity hubs being predominately located in prefrontal and parietal cortices. We establish shifts in between-network connectivity from outside to within the identified regions as a key driver of these abnormalities. The magnitude of these alterations is linked to core ASD symptoms related to communication and social interaction and is not affected by age, sex or medication status. The identified brain functional alterations provide a reproducible pathophysiological phenotype underlying the diagnosis of ASD reconciling previous divergent findings. The large effect sizes in standardized cohorts and the link to clinical symptoms emphasize the importance of the identified imaging alterations as potential treatment and stratification biomarkers for ASD.

neuroscience↗

bioRxiv2017

Cerebellar volume in autism: Meta-analysis and analysis of the ABIDE cohort

Cerebellar volume abnormalities have been often suggested as a possible endophenotype for autism spectrum disorder (ASD). We aimed at objectifying this possible alteration by performing a systematic meta-analysis of the literature, and an analysis of the Autism Brain Imaging Data Exchange (ABIDE) cohort. Our meta-analysis sought to determine a combined effect size of ASD diagnosis on different measures of the cerebellar anatomy, as well as the effect of possible factors of variability across studies. We then analysed the cerebellar volume of 328 patients and 353 controls from the ABIDE project. The meta-analysis of the literature suggested a weak but significant association between ASD diagnosis and increased cerebellar volume (p=0.049, uncorrected), but the analysis of ABIDE did not show any relationship. The studies in the literature were generally underpowered, however, the number of statistically significant findings was larger than expected. Although we could not provide a conclusive explanation for this excess of significant findings, our analyses would suggest publication bias as a possible reason. Finally, age, sex and IQ were important sources of cerebellar volume variability, however, independent of autism diagnosis.

neuroscience↗