Frontiers

Robust automated preclinical fMRI preprocessing via a multi-stage dilated convolutional Swin Transformer affine registration

Introduction: Accurate preprocessing of functional magnetic resonance imaging (fMRI) data is crucial for effective analysis in preclinical studies. Key steps such as denoising, skull-stripping, and ...
Frontiers

Global signal regression reduces connectivity patterns related to physiological signals and does not alter EEG-derived connectivity

Introduction: Functional brain connectivity measures extracted from resting-state functional magnetic resonance imaging (fMRI) scans have generated wide interest as potential noninvasive biomarkers.
GitHub

Inquiry about your excellent fMRI preprocessing scripts

I have recently come across your excellent set of MATLAB scripts for fMRI data preprocessing, which utilize DPARSF and SPM. I am incredibly impressed by the modular and well-structured workflow you've ...
GitHub

--anat_only option does not output normalized structural MRI

I found that when using DeepPrep to preprocess structural MRI with the --anat_only option, the normalized structural MRI is not generated. It seems that the normalization step for structural MRI is ...
IEEE

Preprocessing FMRI Data In SPM12

Abstract: Functional magnetic resonance imaging (fMRI) has ended up the most famous technique for imaging brain functions. Currently, there is a giant range of software packages for the analysis of ...
Live Science

AI 'brain decoder' can read a person's thoughts with just a quick brain scan and almost no training

An improvement to an existing AI-based brain decoder can translate a person's thoughts into text without hours of training. When you purchase through links on our site, we may earn an affiliate ...