Supervised piecewise network connectivity analysis for enhanced confidence of auditory oddball tasks

We present a network connectivity analysis to assess a relevant vector, valuing the contribution of connection node sets in distinguishing between labeled response stimuli. To this end, the piecewise computation of Phase Locking Index is performed, suggesting a combination procedure to reflect the whole recording span with a single relevance value. Further, we use a supervised, statistical thresholding algorithm to reduce the connectivity matrix dimension, holding the links that mostly differentiate the brain responses to each evoked stimulus. Obtained results in an auditory oddball task show that the developed analysis yields a relevant node set for δ and θ waves that becomes more coherent, connected with improved consistency of performed group-level connectivity graphs.