Neural synchronization, brain networks, and cognitive processes

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Arguably the main task of cognitive neuroscience is to understand how the brain implements cognitive processes such as perception, attention, memory, decision making, and consciousness. My goal in this proposal is to make progress on this general problem by addressing the temporal dynamics of control and information processing within networks of human brain areas that are involved in implementing cognitive processes. I am interested both in specifying the general properties of these networks, which is of fundamental importance, as well as in actually specifying their details, which will be useful in understanding specific processes and in applications such as rehabilitation from brain injuries. I will do this by studying synchronization and Granger causality (predictability across time series) between, and also synchronization within, brain sources of EEG (64-channel) and MEG (151-channel) scalp-recorded signals for a number of cognitive processes, both empirically by conducting experiments that invoke those processes and theoretically by modeling communication between brain areas. Localization of brain sources of EEG- and MEG-recorded signals is a difficult problem and several complementary approaches will be taken, including beamforming (spatial filtering) and independent component analysis (a statistical blind source separation technique), guided to some extent by fMRI studies of similar paradigms. Various approaches to measuring synchronization, including wavelet and Hilbert transform/analytic signal analysis, will be used to obtain time-frequency portraits of phase and amplitude of the activity of the neural sources in various frequency bands. In addition, cross-frequency analysis of phase, amplitude, synchronization, and Granger causality will be accomplished by custom software. Finally, in collaboration with a communications engineer I will model the communications between these areas during various phases of the process in question. Again, the goal is to establish as complete a picture as possible of the temporal dynamics of the networks of brain areas that are involved in implementing canonical cognitive processes.