On the cognitive neurodynamics of listening effort: a phase clustering analysis of large-scale neural correlates

An increased listening effort represents a major problem in humans with hearing impairment. Neurodiagnostic methods for an objective listening effort estimation could revolutionize auditory rehabilitation. However the cognitive neurodynamics of listening effort is not understood and research related its neural correlates is still in its infancy. In this paper we present a phase clustering analysis of large-scale listening effort correlates in auditory late responses (ALRs). For this we apply the complex wavelet transform as well as tight Gabor Frame (TGF) operators. We show (a) that phase clustering on the unit circle can separate ALR data from auditory paradigms which require a graduated effort for their solution; (b) the application of TGFs for an inverse artificial phase stabilization at the alpha/theta-border enlarges the endogenously driven listening effort correlates in the reconstructed time- domain waveforms. It is concluded that listening effort correlates can be extracted from ALR sequences using an instantaneous phase clustering analysis, at least by means of the applied experimental pure tone paradigm.