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CONN includes a user-friendly GUI to manage all aspects of functional connectivity analyses, [1] including preprocessing of functional and anatomical volumes, [2] elimination of subject-movement and physiological noise, [3] outlier scrubbing, [4] estimation of multiple connectivity and network measures, and population-level hypothesis testing.
Resting state fMRI (rs-fMRI or R-fMRI), also referred to as task-independent fMRI or task-free fMRI, is a method of functional magnetic resonance imaging (fMRI) that is used in brain mapping to evaluate regional interactions that occur in a resting or task-negative state, when an explicit task is not being performed.
Functional connectivity software is used to study functional properties of the connectome using functional Magnetic Resonance Imaging (fMRI) data in the resting state and during tasks. To access many of these software applications visit the NIH funded Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) site.
CONN (functional connectivity toolbox) Diffusion Imaging in Python (DIPY) [1] DL+DiReCT [2] EEGLAB; FMRIB Software Library (FSL) FreeSurfer; Computational anatomy toolbox; Imaris Imaris for Neuroscientists; ISAS (Ictal-Interictal SPECT Analysis by SPM) LONI Pipeline, Laboratory of Neuro Imaging, USC; Lead-DBS; Mango [3]
Analysis of Functional NeuroImages (AFNI) is an open-source environment for processing and displaying functional MRI data—a technique for mapping human brain activity.. AFNI is an agglomeration of programs that can be used interactively or flexibly assembled for batch processing using shell script.
Functional connectivity analyses allow the characterization of interregional neural interactions during particular cognitive or motor tasks or merely from spontaneous activity during rest. FMRI and PET enable creation of functional connectivity maps of distinct spatial distributions of temporally correlated brain regions called functional networks.
Functional MRI FABBER FABBER is a Bayesian model fitting tool intended for use in task modelling of ASL data.: FEAT Model-based FMRI analysis with straightforward but powerful GUI: data preprocessing (including slice timing correction, MCFLIRT motion correction and PRELUDE+FUGUE EPI unwarping); FILM GLM timeseries analysis with prewhitening; registration to structural and/or standard space ...
The study was used to highlight the need for more careful statistical analyses in fMRI research, given the large number of voxels in a typical fMRI scan and the multiple comparisons problem. [ 124 ] [ 125 ] Before the controversies were publicized in 2010, between 25 and 40% of studies on fMRI being published were not using the corrected ...