This reading list is centered around the practical application of linear dynamical systems models to predict neural data
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Updated
Dec 1, 2021 - Shell
This reading list is centered around the practical application of linear dynamical systems models to predict neural data
Generate a package-manager-friendly mouse brain atlases collection.
Ironsmith is a comprehensive, fully automated pipeline for creating and processing Quantitative Susceptibility Maps (QSM), extracting QSM based iron concentrations from subcortical and cortical brain regions and evaluating the quality of QSM data using SNR measures and assessment of outlier regions on phase images.
A Python distribution for neuroscience based on conda 🧠🐍
Data and tools from the publication "Evolution of Cortical Geometry and its Link to Function, Behaviour and Ecology" by Schwartz et al. for mapping values defined on cortical surfaces between species based on their phylogenetic relationship
A modified FSL version for use with Slurm
Updated documentation for the Open Source Brain platform using Jupyter Book
A sample neuroimaging pipeline for the fMRI data collected by the Aging Brain Cohort.
Scripts related to "Longitudinal changes of ADHD symptoms in association with white matter microstructure: A tract-specific fixel-based analysis"
The idea behind this website is to make available all the resources I have gathered/created over the years make other people's life easier.
Scripts related to "White Matter Microstructure in Attention-Deficit/Hyperactivity Disorder: A Systematic Tractography Study in 654 Individuals"
Pipeline computing volumes statistics for different brain lobes according to a atlas.
Common Docker Image for the Dosenbach and Greene Labs
Scripts related to "Associations between attention-deficit hyperactivity disorder (ADHD) symptom remission and white matter microstructure: A longitudinal analysis"
Scripts and pipeline for the handling of scripts from DICOMS to 4DFP and then analysis.
Docker container for FiberNavigator for Brainlife.io
An innovative and collaborative solution for setting up and executing Jupyter Notebooks on High-Performance Computing (HPC) clusters, tailored for neuroscience data processing workflows.
Software for use at the University of Arizona SCAN Lab
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