A TIME-VARYING PHASE COHERENCE MEASURE FOR QUANTIFYING FUNCTIONAL INTEGRATION IN THE BRAIN

The functional integration between the different parts of the brain is usually quanti¿ed through a measure of coherence. Most of the existing measures de¿ne coherence based on the spectral energy distribution of the signals rather than the phase, and therefore cannot be reliably used as measures of neural synchrony. Moreover, the most common methods for quanti-fying coherence are formulated in the frequency domain and thus, do not take into account the time-varying nature of brain activity. Recently, coherence measures have been extended to account for the energy and the phase relationships between the given signals and the time-varying nature of the signals using the wavelet transform. In this paper, we extend this idea by introducing a new time-varying phase coherence measure based on Cohen’s class of time-frequency distributions. This new measure is applied to both synthesized signals and elec-troencephalogram (EEG) data to show the effectiveness of the proposed measure in estimating phase changes and in quanti-fying the neural synchrony in the brain. Index Terms — Time-frequency analysis, Electroencepha-lography, Phase synchronizatio