Advanced Connectivity Analysis (ACA): a large scale functional connectivity data mining environment
Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables.
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aca_v1.1_nitrc.tar.gz posted by Rong Chen on Oct 20, 2015
aca_test_dataset.tar.gz posted by Rong Chen on Jul 22, 2015
aca_pipeline.tar.gz posted by Rong Chen on Jul 22, 2015