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Lundquist, J. T.

Publications and source records attributed to Lundquist, J. T..

6 recordsLinked to original sources

Cortical Thickness and Curvature in Autism and ADHD: A Mega-Analysis

BackgroundExisting evidence suggests cortical morphometric alterations occur in people with autism and ADHD. However, these findings remain tentative due to small sample sizes, heterogeneous imaging pipelines, varied statistical approaches, and limited harmonization across acquisition sites. Few studies have applied standardized processing to large, clinically enriched datasets or addressed site-related batch effects. MethodsWe leveraged six large-scale brain imaging datasets (n = 9,647; male=5,835; female=3,812; ages 5-64 years), including 1,533 individuals with ADHD, 1,080 with autism spectrum disorder, and 7,034 matched controls. All imaging data were processed using the validated ABCD-HCP pipeline, with cortical parcellation into 360 regions based on the Human Connectome Project (HCP) atlas, and ComBat harmonization was applied to account for variability across 67 acquisition sites. Group-level differences in cortical thickness and sulcal curvature were examined with ANCOVAs, controlling for covariates and using Bonferroni correction for multiple comparisons. ResultsOur analyses revealed distinct neuroanatomical signatures for both autism and ADHD. Individuals with autism exhibited regionally thinner cortex and curvature alterations particularly in the Cingulo-Opercular network. In contrast, individuals with ADHD displayed regionally thicker cortex, particularly in the default mode and somatomotor networks, alongside curvature differences. Control participants showed intermediate patterns, suggesting that autism and ADHD may represent diverging extremes of cortical maturation. ConclusionsCortical thickness and curvature emerge as potential biomarkers that can advance understanding of neurodevelopmental conditions and disentangle heterogeneity across diagnostic groups. These findings highlight the value of harmonized, large-scale, standardized analyses for resolving inconsistencies in the literature.

neuroscience↗

Precision functional imaging in infants using multi-echo fMRI at 7T

Personalized functional brain developmental trajectories can be studied with Precision Functional Mapping (PFM). Our previous work has demonstrated that PFM can be achieved in infants despite rapid brain growth. However, even with extensive data collection (up to 1 hour of fMRI), the reliability and precision of these maps remain lower than those observed in youth and adults - particularly within subcortical structures. In this work we demonstrate the utility of high-field 7T MRI compared to 3T MRI for facilitating PFM in infants. We showcase data from multi-echo fMRI acquisitions in the same infants at both 7T and 3T and demonstrate that 7T imaging in infants is safe and feasible with our subject-specific safety workflow. Moreover, we demonstrate that the use of a higher magnetic field strength affords a spatial resolution more appropriately matched to infants smaller head and brain sizes, yielding notable improvements in data quality, especially for PFM. The increase in both spatial precision and reliability also suggests that 7T MRI can reduce the amount of data required for PFM. Last, we show how ultra-high field imaging can help us study the development of subcortical-to-cortical connectivity patterns, crucial for understanding brain development during this developmental window. 7T MRI is a promising new avenue for developmental cognitive neuroscience.

neuroscience↗

Precision Functional Neuroimaging Reveals Individually Specific Auditory Responses in Infants

Adaptively responding to salient stimuli in the environment is a fundamental feature of cognitive development in early life, which is enabled by the developing brain. Understanding individual variability in how the brain supports this fundamental process is essential for uncovering neurodevelopmental trajectories and potential neurodevelopmental risks. In the present study, we used a precision functional imaging approach to probe activation in response to salient auditory stimuli and its relation to brain functional networks in individual infants. A minimum of 60 minutes of fMRI BOLD data with an auditory oddball paradigm were collected in ten infants with a mean postmenstrual age of 48 weeks. Results demonstrate the feasibility of performing a precision functional imaging study to investigate individual specific responses to salient stimuli in infants. While responses to the auditory oddball were consistent between individuals in auditory processing areas, responses across the rest of the brain differed across individuals in their magnitude and shape. Individual specific response patterns appeared to be relatively stable and differed from other participants response patterns, despite fluctuations across runs. Commonalities and differences between individuals demonstrated in this sample contribute to our understanding of how the developing brain instantiates processing of salient stimuli. Our findings suggest that during early development, early unimodal processing is well conserved across individuals, however subsequent perceptual processing is still being personally defined. In this context, individual specific response patterns could be a promising target for biomarkers of normative brain and cognitive development.

neuroscience↗

fMRIPrep Lifespan: Extending A Robust Pipeline for Functional MRI Preprocessing to Developmental Neuroimaging

The adoption of a standardized preprocessing workflow is vital for fostering community, sharing, and reproducibility. fMRIPrep has been a critical advancement towards this end, however, it is limited in its capacity to be applied to data across the lifespan, starting from infancy. Here, we introduce fMRIPrep Lifespan, an extension of fMRIPrep that extends the standardized processing from childhood to senescence to include neonatal, infant, and toddler structural and functional MRI data preprocessing. This effort involves a NiPreps integration of 1) a workflow akin to fMRIPrep optimized for MRI data in the first years of life (previously NiBabies) and 2) upstream enhancements to the entire NiPreps suite, including multi-echo data processing, modularization of workflow components, and convergence of processing with other popular workflows (ABCD-BIDS, Human Connectome Project Pipelines). Using data from the Baby Connectome Project (participants 1-43 months of age), we demonstrate that fMRIPrep Lifespan produces high-quality outputs across a wide age range. Moving forward, the scalable, modular infrastructure of fMRIPrep Lifespan will ensure adaptability to data from birth to old age while maintaining robust and reproducible frameworks for functional MRI research across the lifespan.

bioinformatics↗

Baby Open Brains: An Open-Source Repository of Infant Brain Segmentations

Reproducibility of neuroimaging research on infant brain development remains limited due to highly variable protocols and processing approaches. Progress towards reproducible pipelines is limited by a lack of benchmarks such as gold standard brain segmentations. Addressing this core limitation, we constructed the Baby Open Brains (BOBs) Repository, an open source resource comprising manually curated and expert-reviewed infant brain segmentations. Markers and expert reviewers manually segmented anatomical MRI data from 71 infant imaging visits across 51 participants, using both T1w and T2w images per visit. Anatomical images showed dramatic differences in myelination and intensities across the 1 to 9 month age range, emphasizing the need for densely sampled gold standard manual segmentations in these ages. The BOBs repository is publicly available through the Masonic Institute for the Developing Brain (MIDB) Open Data Initiative, which links S3 storage, Datalad for version control, and BrainBox for visualization. This repository represents an open-source paradigm, where new additions and changes can be added, enabling a community-driven resource that will improve over time and extend into new ages and protocols. These manual segmentations and the ongoing repository provide a benchmark for evaluating and improving pipelines dependent upon segmentations in the youngest populations. As such, this repository provides a vitally needed foundation for early-life large-scale studies such as HBCD.

neuroscience↗

Heritability estimation of subcortical volumes in a multi-ethnic multi-site cohort study

Heritability of regional subcortical brain volumes (rSBVs) describes the role of genetics in middle and inner brain development. rSBVs are highly heritable in adults but are not characterized well in adolescents. The Adolescent Brain Cognitive Development study (ABCD), taken over 22 US sites, provides data to characterize the heritability of subcortical structures in adolescence. In ABCD, site-specific effects co-occur with genetic effects which can bias heritability estimates. Existing methods adjusting for site effects require additional steps to adjust for site effects and can lead to inconsistent estimation. We propose a random-effect model-based method of moments approach that is a single step estimator and is a theoretically consistent estimator even when sites are imbalanced and performs well under simulations. We compare methods on rSBVs from ABCD. The proposed approach yielded heritability estimates similar to previous results derived from single-site studies. The cerebellum cortex and hippocampus were the most heritable regions (>50%).

genomics↗