Conn : A Functional Connectivity Toolbox for Correlated and Anticorrelated Brain Networks
McGovern Institute for Brain Research · Massachusetts Institute of Technology
Abstract
Resting state functional connectivity reveals intrinsic, spontaneous networks that elucidate the functional architecture of the human brain. However, valid statistical analysis used to identify such networks must address sources of noise in order to avoid possible confounds such as spurious correlations based on non-neuronal sources. We have developed a functional connectivity toolbox Conn ( www.nitrc.org/projects/conn ) that implements the component-based noise correction method (CompCor) strategy for physiological and other noise source reduction, additional removal of movement, and temporal covariates, temporal filtering and windowing of the residual blood oxygen level-dependent (BOLD) contrast signal,…
Citation impact
- FWCI
- 33.72
- Percentile
- 100%
- References
- 74
Authors
2Topics & keywords
- Computer science
- Artificial intelligence
- Functional magnetic resonance imaging
- Voxel
- Pattern recognition (psychology)
- Human Connectome Project
- Communication noise
- Resting state fMRI