There are 4 repositories under fmri-data-analysis topic.
This repository contains the files that generate Andy's Brain Book on ReadTheDocs.
Python code explaining how to display structural and functional fMRI data.
Standalone MATLAB implementation of permutation TFCE correction
fMRI Imaging Analysis
ASD diagnosis on ABIDE I
Explain a black-box module in natural language.
Improving autism identification with multisite data via site-dependence minimisation and second-order functional connectivity (TMI, 2022)
Multi-voxel pattern analyses methods based on ML & DL to decode the category of visual stimuli viewed by a human subject based on their recorded brain activity in fMRI form
MRI preprocessing and analysis pipelines and tools for the study of disorders of consciousness
Example pipeline for preprocessing, reading in behavioural files, first level and second level analysis
These C/C++ source files consist of 150 classes, 300,000 lines of code, excluding a Qt-based user interface. Its functionality includes: GLM-statistics, hierarchical clustering, (non)-linear optimization, L1 and L2 norm minimization, Hungarian algorithm, EEG/MEG forward and inverse modelling, Boundary Element Method, spatio/temporal covariance modelling, image fusion, triangular meshes, KD-trees, topological error correction, marching cubes & spherical triangulations, sparse matrices and matrix operations, spherical harmonics, wavelets, spectra and spectrograms, Fast Fourier transform (FFTWest), data import for many different EEG/MEG data formats, data import for many image data formats.
A Matlab toolbox for examining the quality of structural (SNR) and functional (tSNR, SFNR) MRI
A toolbox for NIfTI and Analyze medical image visualization, editing, and 3D rendering
[KHBM] Winter School 2022 - Neuroimage Data Analysis using Python and Graph Neural Networks
A Python software package for BWAS
This is the repository for paper `Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks'.
[NeurIPS 2022] "Convergent Representations of Computer Programs in Human and Artificial Neural Networks" by Shashank Srikant*, Benjamin Lipkin*, Anna A. Ivanova, Evelina Fedorenko, Una-May O'Reilly.
This code repository contains a collection of Python scripts for classifying autistic and control conditions using Support Vector Machines (SVM), leveraging preprocessed functional MRI (fMRI) data from the ABIDE dataset.
Personode: a new toolbox for ICA map classification and individualized ROI definition
Estimate the demand of working memory in Social Cognition Tasks using HCP-fMRI dataset
Semi-blind deconvolution for fMRI (BOLD signal)
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.
Kurs zu fMRT-Datenanalyse mit Python (Sommersemester 2019). Eigenständige Erstellung von MRT-Viewern und DIY-Analyse von fMRT-Zeitverläufen und Aktivierungskarten mit Python.
A Python software package for sKPCR
Materials for the "fMRI analysis" workshop at the Cognitive Neuroscience Skills Training In Cambridge-2023 (COGNESTIC-2023).
Source code for brain data processing and analysis in paper <A controller-peripheral architecture and costly energy principle for learning>
Source code for <Thinking Fast and Slow - A novel multi-region computational-modelling framework for conceptual knowledge learning and consolidation> (WIP)
Still a work in progress.
pNet is a Python package for computing personalized, sparse, non-negative large-scale functional networks from functional magnetic resonance imaging (fMRI) data, particularly resting state fMRI data.
This project is my final assignment for the Advanced Hands-on fMRI Analysis course during my master’s degree. It was a great experience! I applied multiclass decoding and representational similarity analysis to the fMRI data by using CoSMoMVPA toolbox.