Neural modelling of the encoding of fast frequency modulation
Alejandro Tabas, Katharina von Kriegstein

TL;DR
This paper introduces a novel neural model with feedback mechanisms to explain frequency modulation encoding in auditory processing, successfully accounting for perceptual effects and experimental data, highlighting the importance of predictive interactions.
Contribution
The study presents a new predictive feedback model of FM encoding that surpasses traditional feedforward models in explaining perceptual phenomena.
Findings
The model explains the sweep pitch shift effect.
Predictive feedback is crucial for FM encoding.
Experimental data supports the model's predictions.
Abstract
Frequency modulation (FM) is a basic constituent of vocalisation in many animals as well as in humans. In human speech, short rising and falling FM-sweeps called formant transitions characterise individual speech sounds. There are two representations of FM in the ascending auditory pathway: a spectral representation, holding the instantaneous frequency of the stimuli; and a sweep representation, consisting of neurons that respond selectively to FM direction. To-date computational models use feedforward mechanisms to explain FM encoding. However, from neuroanatomy we know that there are massive feedback projections in the auditory pathway. Here, we found that a classical FM-sweep perceptual effect, the sweep pitch shift, cannot be explained by standard feedforward processing models. We hypothesised that the sweep pitch shift is caused by a predictive interaction between the sweep and the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
