Fusion of Region-Of-Interest Signals Improves Connectivity Estimation on Resting State fMRI

Learn how fusion of region-of-interest signals enhances connectivity estimation in resting state functional magnetic resonance imaging through this 12-minute conference presentation by Rodrigo Rojas Leyton from Universidad de Valparaíso. Explore advanced neuroimaging techniques that improve the accuracy of brain connectivity measurements by combining signals from multiple regions of interest. Discover methodological approaches for processing resting state fMRI data and understand how signal fusion strategies can lead to more reliable connectivity estimates in neuroscience research. Gain insights into computational methods that advance our understanding of brain network organization and functional connectivity patterns during rest states.