Two stages of bandwidth scaling drives efficient neural coding of natural sounds
Fig 5
Cochlear model bandwidth scaling whitens the power spectrum of natural sounds and maximizes spectral entropy.
(A) Violin plots showing the distribution of normalized slopes of the best regression fits to both the Fourier and cochlear models (from Fig 4). For both vocalization and background sounds, normalized spectral slopes for the Fourier decomposition are negative and not significantly different (t-test, p = 0.58). By comparison, vocalizations have positive and negative slopes for vocalizations and background sounds, respectively, with an average slope near zero (0.2) indicating a whitened average spectrum. (B and C) The cochlear model entropy is higher than Fourier-based entropy regardless of the Fourier filter resolution used (30, 120 or 480 Hz). (D) Bandwidth scaling predicts the cochlear filter whitening. The average Fourier power spectrum has a decreasing trend (black) whereas the cochlear power spectrum is substantially flatter (red, continuous). The gain provided by the cochlear filter bandwidths (green curve) increases and counteracts the decreasing power trend of the Fourier power spectrum. The cochlear power spectrum is accurately predicted by considering the bandwidth dependent gain (dotted red lines; bandwidth gain + Fourier power spectrum).