Biology subjects

Lippe, S.

Publications and source records attributed to Lippe, S..

10 recordsLinked to original sources

bioRxiv2026

The Canadian Pediatric Imaging Platform (C-PIP) Reference Sample: Neuroimaging Protocol and Cross-site Validation for Harmonized Multimodal Pediatric Imaging

Understanding how the human brain matures from infancy through adolescence is essential for identifying factors that influence health outcomes. Magnetic resonance imaging (MRI) provides powerful tools for characterizing structural, microstructural, functional, and metabolic aspects of brain development; however, many pediatric imaging studies are constrained by small sample sizes, limited geographic diversity, lack of longitudinal measurement, restricted age ranges, and heterogeneous acquisition protocols. While recent large-scale neuroimaging consortia have begun to address these challenges, such resources remain limited in the Canadian context, creating a critical gap. The Canadian Pediatric Imaging Platform (C-PIP) has developed a multisite neuroimaging framework across three of Canada's largest pediatric hospitals: Alberta Children's Hospital (Calgary), Centre Hospitalier Universitaire Sainte-Justine (Montreal), and the Hospital for Sick Children (Toronto). These three sites were united through a national initiative, leveraging high-performance MRI systems to accelerate Canadian neurodevelopmental research. In addition, C-PIP has implemented a centralized data sharing infrastructure to facilitate open science and collaborative research across institutions. Here, we describe the development and implementation of a multimodal MRI acquisition protocol designed to support multimodal longitudinal studies of typical and atypical brain development spanning infancy through adolescence. Within-site stability and cross-site stability of C-PIP core MRI sequences were evaluated using a travelling-participant study. The C-PIP MRI protocol establishes a harmonized, multisite imaging framework that supports large-scale investigations of pediatric brain development and disorders.

neuroscience↗

bioRxiv2026

The ovarian cycle and estradiol modulate cortical network state and auditory entrainment in mice and women

The human brain is remarkably dynamic, continuously adapting to internal and external signals across rapid and protracted timescales. While both male and female brains are influenced by sex hormones to drive adaptive behavioural and physiological changes, the ovarian cycle in female mammals represents a conserved naturalistic model to understand how hormones such as estradiol (E2) alter cellular and network states to shape brain function. To understand whether and how the ovarian cycle influences sensory cortical processing, we investigated cortical network activity at rest and upon auditory stimulation across the ovarian cycle in mice and human subjects. We recorded EEG activity in men and women and intracortical local field potentials in male and female mice. Female participants were tested during two phases of their ovarian cycle characterized by low E2 levels (early follicular phase in women; late estrus in mice) and high E2 levels (late follicular phase in women; proestrus in mice). Across species, high endogenous or exogenous estradiol was associated with a steeper aperiodic power spectral slope, indicating decreased excitatory/inhibitory drive and attenuated auditory entrainment following a 40Hz stimulation. At the single-cell level, high E2 selectively increased the baseline and sustained 40-Hz firing of putative fast-spiking interneurons while reducing their temporal coherence during both spontaneous and stimulus-evoked activity, suggesting that E2 enhances inhibitory tone, while disrupting the temporal coordination of inhibitory networks. Altogether, these findings demonstrate that estradiol dynamically modulates cortical network states and auditory responsiveness. This underscores the necessity of investigating hormone-brain coupling as an evolutionarily conserved model essential for yielding translational insights into sex-specific neurobiology.

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↗

bioRxiv2026

Neural feature spaces: characterizing the geometry of brain activity across development

The human brain undergoes profound changes from childhood to adulthood. These changes are foundational to cognitive, affective and social development, and measuring them is essential for identifying atypical development. A common approach consists of analyzing metrics derived from brain activity, such as spectral power, aperiodic activity and signal complexity. However, individual metrics are sensitive to external factors unrelated to development, contributing to inconsistent findings in the literature. Moreover, these metrics are not independent; they show some degree of intrinsic redundancy, which itself evolves across development. Here, we propose a novel approach that focuses on the relationships between neural features rather than their values, defining a "neural feature space" that captures the geometry of brain activity. We analyzed the neural feature spaces of children (4-12 years) and adults (30-45 years), based on 128-channel EEG recordings during naturalistic movie viewing. Specifically, we computed a range of spectral, aperiodic and complexity features and quantified pairwise distances between them using latent variable modeling. Neural feature spaces were significantly different between age groups. Notably, high frequency bands were less differentiated in children and distances between spectral and complexity features differed. Crucially, distances were highly stable across tasks, in contrast to feature values, which varied substantially. These findings suggest that the geometry of neural feature spaces provides robust, interpretable markers of neurodevelopment, offering a complementary approach to feature-based analyses.

neuroscience↗

bioRxiv2026

The Q1K Integrated EEG and Eye-Tracking Experimental Test Battery for Open Autism Science

The Quebec 1000 Families (Q1K) platform has been designed to recruit, phenotype, and collect biospecimens from a large cohort of families with at least one member with autism spectrum disorder or a related neurodevelopmental condition. As part of the Q1K protocol, an experimental test battery was developed and validated using simultaneous high-density electroencephalography (EEG) and eye tracking (ET). We report on the general approach and design principles, multimodal EEG/ET integration, the tasks, and their validation, providing a blueprint for implement such a project. It also describes the cohort and its methods as a reference for future studies using this dataset. By releasing openly this experimental test battery, we aim to support task standardization and multi-project data pooling in autism and related neurodevelopmental disorders.

neuroscience↗

bioRxiv2025

Intrinsic Neural Oscillations Predict Verbal Learning Performance and Encoding Strategy Use

Individuals adopt different encoding strategies to facilitate learning. However, few studies have investigated the neurophysiological basis that support these different encoding strategies across individuals. The present work addresses this gap by extending our previous findings on the direct relationship between cortical spectral power, measured via resting-state magnetoencephalography, and performance on standard cognitive test results. Our results highlight the complex interactions between endogenous brain oscillations, learning and verbal encoding strategies assessed by the California Verbal Learning Test (CVLT-2). First, we found that resting-state theta oscillations were significantly associated with verbal learning and subjective clustering strategies. Second, we observed that semantic clustering is facilitated by oscillatory patterns in left sensory-motor brain regions. Finally, our analyses revealed that serial and semantic clustering strategies are related to opposite regression patterns, indicating a competitive interaction. Together, these findings provide novel insights into the neural oscillatory dynamics that support diverse encoding strategies in verbal learning.

neuroscience↗

bioRxiv2023

Using rare genetic mutations to revisit structural brain asymmetry

Asymmetry between the left and right brain is a key feature of brain organization. Hemispheric functional specialization underlies some of the most advanced human-defining cognitive operations, such as articulated language, perspective taking, or rapid detection of facial cues. Yet, genetic investigations into brain asymmetry have mostly relied on common variant studies, which typically exert small effects on brain phenotypes. Here, we leverage rare genomic deletions and duplications to study how genetic alterations reverberate in human brain and behavior. We quantitatively dissected the impact of eight high-effect-size copy number variations (CNVs) on brain asymmetry in a multi-site cohort of 552 CNV carriers and 290 non-carriers. Isolated multivariate brain asymmetry patterns spotlighted regions typically thought to subserve lateralized functions, including language, hearing, as well as visual, face and word recognition. Planum temporale asymmetry emerged as especially susceptible to deletions and duplications of specific gene sets. Targeted analysis of common variants through genome-wide association study (GWAS) consolidated partly diverging genetic influences on the right versus left planum temporale structure. In conclusion, our gene-brain-behavior mapping highlights the consequences of genetically controlled brain lateralization on human-defining cognitive traits.

neuroscience↗

bioRxiv2022

Rare CNVs and phenome-wide profiling: a tale of brain-structural divergence and phenotypical convergence

Copy number variations (CNVs) are rare genomic deletions and duplications that can exert profound effects on brain and behavior. Previous reports of pleiotropy in CNVs imply that they converge on shared mechanisms at some level of pathway cascades, from genes to large-scale neural circuits to the phenome. However, studies to date have primarily examined single CNV loci in small clinical cohorts. It remains unknown how distinct CNVs escalate the risk for the same developmental and psychiatric disorders. Here, we quantitatively dissect the impact on brain organization and behavioral differentiation across eight key CNVs. In 534 clinical CNV carriers from multiple sites, we explored CNV-specific brain morphology patterns. We extensively annotated these CNV-associated patterns with deep phenotyping assays through the UK Biobank resource. Although the eight CNVs cause disparate brain changes, they are tied to similar phenotypic profiles across [~]1000 lifestyle indicators. Our population-level investigation established brain structural divergences and phenotypical convergences of CNVs, with direct relevance to major brain disorders.

genetics↗

bioRxiv2021

Sensory processing dysregulations as reliable translational biomarkers in SYNGAP1 haploinsufficiency

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.

neuroscience↗

bioRxiv2020

Estimating the effect-size of gene dosage on cognitive ability across the coding genome

Genomic Copy Number Variants (CNVs) are routinely identified and reported back to patients with neuropsychiatric disorders, but their quantitative effects on essential traits such as cognitive ability are poorly documented. We have recently shown that the effect-size of deletions on cognitive ability can be statistically predicted using measures of intolerance to haploinsufficiency. However, the effect-sizes of duplications remain unknown. It is also unknown if the effect of multigenic CNVs are driven by a few genes intolerant to haploinsufficiency or distributed across tolerant genes as well. Here, we identified all CNVs >50 kilobases in 24,092 individuals from unselected and autism cohorts with assessments of general intelligence. Statistical models used measures of intolerance to haploinsufficiency of genes included in CNVs to predict their effect-size on intelligence. Intolerant genes decrease general intelligence by 0.8 and 2.6 points of IQ when duplicated or deleted, respectively. Effect-sizes showed no heterogeneity across cohorts. Validation analyses demonstrated that models could predict CNV effect-sizes with 78% accuracy. Data on the inheritance of 27,766 CNVs showed that deletions and duplications with the same effect-size on intelligence occur de novo at the same frequency. We estimated that around 10,000 intolerant and tolerant genes negatively affect intelligence when deleted, and less than 2% have large effect-sizes. Genes encompassed in CNVs were not enriched in any GOterms but gene regulation and brain expression were GOterms overrepresented in the intolerant subgroup. Such pervasive effects on cognition may be related to emergent properties of the genome not restricted to a limited number of biological pathways.

genetics↗