Evaluation and calibration of functional network modeling methods based on known anatomical connections

1Montreal Neurolog. Inst., Dept. of Neurol. and Neurosurg.; 2McGill Vision Res. Unit; 3McGill Univ., Montreal, QC, Canada Introduction: Recent studies have identified large scale brain networks based on the spatio-temporal structure of spontaneous fluctuations in resting-state fMRI data. The corresponding analysis involves defining a set of functional “nodes” (e.g., spatial regions of interest (ROIs)), and then conducting a connectivity analysis between these nodes based on their associated fMRI time-series. Here we tested and compared network connectivity analysis methods by applying them to fMRI resting-state data obtained from the human visual cortex. We based our analysis on the „ground-truth‟, thoroughly studied, anatomical connectivity in the monkey visual cortex. The methods tested here are those previously tested against simulated data in Smith et al. (Neuroimage, 2011) where we measured the so called “c-sensitivity”: The fractional rate of detecting true connections.