Abstract
This study presents a computational model to reproduce the biological dynamics of “listening to music.” A biologically plausible model of periodicity pitch detection is proposed and simulated. Periodicity pitch is computed across a range of the auditory spectrum. Periodicity pitch is detected from subsets of activated auditory nerve fibers (ANFs). These activate connected model octopus cells, which trigger model neurons detecting onsets and offsets; thence model interval-tuned neurons are innervated at the right interval times; and finally, a set of common interval-detecting neurons indicate pitch. Octopus cells rhythmically spike with the pitch periodicity of the sound. Batteries of interval-tuned neurons stopwatch-like measure the inter-spike intervals of the octopus cells by coding interval durations as first spike latencies (FSLs). The FSL-triggered spikes synchronously coincide through a monolayer spiking neural network at the corresponding receiver pitch neurons.
Highlights
Pitches span a scale from lowest to highest pitch
Stimulation based on auditory modeling (SAM) – developed at Fraunhofer Institute for Digital Media Technology (IDMT) as a cochlear implant sound-processing strategy – converts sounds to parallel spike trains along the auditory nerve fibers (ANFs) (Harczos et al, 2013b; Harczos, 2015)
Stimulation based on auditory modeling has been extended step by step by further modules of the auditory periphery
Summary
Pitches span a scale from lowest to highest pitch. The frequencies of the pitches are determined by adjusting them to an absolute reference pitch (e.g., the concert pitch A4 = 440 Hz) and the chosen temperament. Very seldom the reciprocal interval duration time is annotated for a given frequency. We recently extended SAM by model octopus cells innervated by ANFs (Harczos and Klefenz, 2018). These models are shortly summarized for better comprehensibility in see section “Materials and Methods.”. Batteries of interval-tuned neurons (ITNs) stopwatchlike measure the inter-spike intervals (ISIs) of assigned octopus cells. An ITN responds to a range of interval durations of a rhythmically spiking octopus cell by coding interval durations as first spike latencies (FSLs) (Aubie et al, 2009, 2012). We model interval-tuned microcircuits by adapting Aubie’s model to be ready for use in the microsecond operating range (Aubie et al, 2012). ITNs are star-wise connected to short-term pitch neurons in a monolayer spiking neural network (SNN), which processes synchronously arriving spikes from the ITNs
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