Functional Connectivity (Neural Network Method)

Some classes of neural networks are well-suited for analyzing functional connectivity because they are sensitive to patterns of co-occurrences within the input data. If the data are composed of fMRI activations across a brain regions, then weights within the network that encodes these activations will encode the regularity with which regions coactivate. In McNorgan & Joanisse (2014), I demonstrated that a neural network can arrive at a similar functional connectivity solution to the conventional cross-correlational approach.