Repository for neurocaps, a Python package to perform Co-Activation Patterns (CAPs) analyses.
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Updated
Jun 20, 2024 - Jupyter Notebook
Repository for neurocaps, a Python package to perform Co-Activation Patterns (CAPs) analyses.
Official AFNI source and documentation
This repository stores image processing pipelines for magnetic resonance neuroimages developed during my PhD in Neuroscience and Imaging.
Explain a black-box module in natural language.
fMRI Imaging Analysis
Scripts used in the "Dynamic Functional Connectivity in Autism Spectrum Disorder" project.
predictive machine learning classification and data processing on neuroscience brain image data
Still a work in progress.
A website version of my PhD dissertation.
This repository contains batch scripts to standardise and automate the processing of single echo (SE-fMRI), multi-echo (ME-fMRI) fMRI and VBM data in SPM12.
This repository contains the files that generate Andy's Brain Book on ReadTheDocs.
This repository is associated with the manuscript: “Graph Ricci Curvatures Reveal Atypical Functional Connectivity in Autism Spectrum Disorder”
Code to analyze audio-visual-tactile high-resolution 7T data
This repository contains the data analysis for my bachelor's degree thesis project. We used optimal transport's induced distances between probability distributions to analyze human neurophysiological data. The full thesis is available at:
Repository for the "Advanced Cognitive Neuroscience" course at Aarhus University, featuring analysis of MEG and fMRI data from thought-reading experiments at Aarhus Skejby Hospital, Denmark. This project delves into the potentials of neuroimaging in cognitive science research.
This provides the code for the multi-level efficiency and clustering coefficient method used to quantify integration-segregation balance of the brain network.
Code for my Master's Thesis "Deep Neural Encoding Models of the Human Visual Cortex to Predict fMRI Responses to Natural Visual Scenes" and my submission for the "Algonauts Project 2023 Challenge".
Generate a package-manager-friendly archive of ABI connectivity maps registered in SAMRI standard space.
Tutorial covering group DCM analyses of fMRI and M/EEG
A novel method for sampling the active and noisy areas is proposed by using the purification of gray and non-gray matter areas of fMRI data. Also, a data-driven network is proposed in a parallel, multi-step and integrated manner for optimal noise reduction of t-fMRI data.
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