Biology subjects

Calarco, N.

Publications and source records attributed to Calarco, N..

4 recordsLinked to original sources

bioRxiv2025

Multiscale characterisation of the human claustrum from histology to MRI

Though linked to an unusually broad array of functions, the human claustrums complex morphology has hindered in vivo study, resulting in a small MRI literature marked by implausibly large discrepancies in reported characteristics. We constructed the first three-dimensional histological "gold standard" claustrum model, and systematically evaluated in vivo 7-Tesla MRI datasets against it and downsampled derivatives. MRI showed resolution-dependent differences rather than contrast limitations, transforming the claustrums intricate sheet into an artefactually thickened ribbon. However, submillimetre MRI reliably recovered the dorsal "core" that contains most claustral volume and density and houses major corticoclaustral connectivity. At 0.5mm resolution, extension into the temporal lobe, including irregular ventral "puddles", was partially recovered, with uncertainty reflecting boundary imprecision rather than anatomical loss. Our results refute the view that the claustrum is inaccessible in the living human brain, define practical measurement limits, and provide a foundation for future functional investigations.

neuroscience↗

bioRxiv2019

Novel transcriptome-based polygenic risk score for depression is associated with neural processing of social stimuli

Convergent data from imaging and postmortem brain transcriptome studies implicate corticolimbic circuit (CLC) dysregulation in the pathophysiology of depression. To more directly bridge these lines of work, we generated a novel transcriptome-based polygenic risk score (T-PRS), capturing subtle shifts towards depression-like gene expression patterns in key CLC regions, and mapped this T-PRS onto brain function and related depressive symptoms in a non-clinical sample of 478 young adults (225 men; age 19.79+/-1.24) from the Duke Neurogenetics Study. First, T-PRS was generated based on common functional SNPs shifting CLC gene expression towards a depression-like state. Next, we used multivariate partial least squares regression to map T-PRS onto whole-brain activity patterns during perceptual processing of social stimuli (i.e., human faces). For validation, we conducted a comparative analysis with a PRS summarizing depression risk variants identified by the Psychiatric Genomics Consortium (PGC-PRS). Sex was modeled as moderating factor. We showed that T-PRS was associated with widespread reductions in neural response to neutral faces in women and to emotional faces and shapes in men (multivariate p<0.01). This female-specific reductions in neural response to neutral faces was also associated with PGC-PRS (multivariate p<0.03). Reduced reactivity to neutral faces was further associated with increased self-reported anhedonia. We conclude that women with functional alleles mimicking the postmortem transcriptomic CLC signature of depression have blunted neural activity to social stimuli, which may be expressed as higher anhedonia.

neuroscience↗

bioRxiv2018

ciftify: A framework for surface-based analysis of legacy MR acquisitions

The preprocessing pipelines of the Human Connectome Project (HCP) were made publicly available for the neuroimaging community to apply the HCP analytic approach to data from non-HCP sources. The HCP analytic approach is surface-based for the cerebral cortex, uses the CIFTI "grayordinate" file format, provides greater statistical sensitivity than traditional volume-based analysis approaches, and allows for a more neuroanatomically-faithful representation of data. However, the HCP pipelines require the acquisition of specific images (namely T2w and field map) that historically have often not been acquired. Massive amounts of this legacy data could benefit from the adoption of HCP-style methods. However, there is currently no published framework, to our knowledge, for adapting HCP preprocessing to "legacy" data. Here we present the ciftify project, a parsimonious analytic framework for adapting key modules from the HCP pipeline into existing structural workflows using FreeSurfers recon_all structural and existing functional preprocessing workflows. Within this framework, any functional dataset with an accompanying (i.e. T1w) anatomical data can be analyzed in CIFTI format. To simplify usage for new data, the workflow has been bundled with fMRIPrep following the BIDS-app framework. Finally, we present the package and comment on future neuroinformatics advances that may accelerate the movement to a CIFTI-based grayordinate framework. HIGHLIGHTSO_LIthe ciftify package allows for grayordinate-based (CIFTI format) analysis of non-Human Connectome Project (i.e. legacy) MR acquisitions C_LIO_LIThe workflow and dependencies are distributed as a Docker container, following the BIDS-app interface C_LIO_LIAdditional ciftify utilities aid in downstream analysis of CIFTI images C_LIO_LIWe intend for this work to offer bridging solution for legacy data that will allow many researchers to adopt CIFTI format analyses C_LI

neuroscience↗

bioRxiv2017

Personalized intrinsic network topography mapping and functional connectivity deficits in Autism Spectrum Disorder

BackgroundRecent advances demonstrate individually specific variation in brain architecture in healthy individuals using fMRI data. To our knowledge, the effects of individually specific variation in complex brain disorders have not been previously reported.\n\nMethodsWe developed a novel approach (Personalized Intrinsic Network topography, PINT) for localizing individually specific resting state networks using conventional resting state fMRI scans. Using cross-sectional data from participants with ASD (n=393) and TD controls (n=496) across 15 sites we tested: 1) effect of diagnosis and age on the variability of intrinsic network locations and 2) whether prior findings of functional connectivity differences in ASD as compared to TD remain after PINT application.\n\nResultsWe found greater variability in the spatial locations of resting state networks within individuals with ASD as compared to TD. In TD participants, variability decreased from childhood into adulthood, and increased again in late-life, following a U-shaped pattern, which was not present in those with ASD. Comparison of intrinsic connectivity between groups revealed that the application of PINT decreased the number of hypo-connected regions in ASD.\n\nConclusionsOur results provide a new framework for measuring altered brain functioning in neurodevelopmental disorders that may have implications for tracking developmental course, phenotypic heterogeneity, and ultimately treatment response. We underscore the importance of accounting for individual variation in the study of complex brain disorders.

neuroscience↗