Multichannel EEG sonification with ambisonics spatial sound environment

When performing complex analyzes on multivariate processes, it is often convenient to utilize various types of visualizations in order to untangle and interpret spatiotemporal dependencies between mixed information streams, and to perform input variable selection. This is particularly advantageous when a level of noise is high, the target of interest information stream changes its spatial location with time, and also for spatiotemporal processes where several streams contain meaningful information, such as in the case of multichannel recordings of electroencephalogram (EEG) based brain activity monitoring which is of a core interest in neurosciences. To provide insight into the dynamics of brainwave steady-state electrical responses, a sonification of EEG is proposed, whereby the information about the spatiotemporal steady-state response dynamics is modeled using a spatial sound reproducing ambisonics approach. Owing to its data-driven and fully adaptive mode of operation, synchro-squeezing transform (SST) is employed as a time-frequency decomposer, and the brain responses to steady-state visual evoked responses (SSVEP) stimuli are sonified. Such perceptual feedback has enormous potential in multichannel brainwave recording analyzes.