Biology subjects

Garin, C. M.

Publications and source records attributed to Garin, C. M..

3 recordsLinked to original sources

bioRxiv2019

An Automated Open-Source Workflow for Standards-Compliant Integration of Small Animal Magnetic Resonance Imaging Data

Large-scale research integration is contingent on seamless access to data in standardized formats. Standards enable researchers to understand external experiment structures, pool results, and apply homogeneous preprocessing and analysis workflows. Particularly, they facilitate these features without the need for numerous potentially confounding compatibility add-ons. In small animal magnetic resonance imaging, an overwhelming proportion of data is acquired via the ParaVision software of the Bruker Corporation. The original data structure is predominantly transparent, but fundamentally incompatible with modern pipelines. Additionally, it sources metadata from free-field operator input, which diverges strongly between laboratories and researchers. In this article we present an open-source workflow which automatically converts and reposits data from the ParaVision structure into the widely supported and openly documented Brain Imaging Data Structure (BIDS). Complementing this workflow we also present operator guidelines for appropriate ParaVision data input, and a programmatic walk-through detailing how preexisting scans with uninterpretable metadata records can easily be made compliant after the acquisition.

neuroscience↗

bioRxiv2019

Resting state cerebral networks in mouse lemur primates: from multilevel validation to comparison with humans

Measures of resting-state functional connectivity allow the description of neuronal networks in humans and provide a window on brain function in normal and pathological conditions. Animal models are critical to further address experimentally the function of brain networks and their roles in pathologies. Here we describe for the first time brain network organization in the mouse lemur (Microcebus murinus), a small primate attracting increased attention as a model for neuroscience. Resting-state functional MR images were recorded at 11.7 Tesla. Forty-eight functional regions were identified and used to identify networks using graph theory, dictionary learning and seed-based analyses. Comparison of results issued from these three complementary methods allowed the description of the most robust networks from mouse lemurs. Large scale networks were then identified from resting-state functional MR images of humans using the same method as for lemurs. Strong homologies were outlined between cerebral networks in mouse lemurs and humans.

neuroscience↗

bioRxiv2019

Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories world-wide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a murine default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations.

neuroscience↗