PIRACY: An Optimized Pipeline for Functional Connectivity Analysis in the Rat Brain.

ABSTRACT: Resting state functional MRI (rs-fMRI) is a widespread and powerful tool for investigating functional connectivity (FC) and brain disorders. However, FC analysis can be seriously affected by random and structured noise from non-neural sources, such as physiology. Thus, it is essential to first reduce thermal noise and then correctly identify and remove non-neural artifacts from rs-fMRI signals through optimized data processing methods. However, existing tools that correct for these effects have been developed for human brain and are not readily transposable to rat data. Therefore, the aim of the present study was to establish a data processing pipeline that can robustly remove random and structured noise from rat rs-fMRI data. It includes a novel denoising approach based on the Marchenko-P

SUBMITTER: Diao Y 

PROVIDER: S-EPMC8032956 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature