Quadratic Encoding Displayed by Primary Auditory Cortical Neurons
Date
2024-04-11
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Abstract
Hearing is a key function to perceive and interact with the environment. For humans, audition is also of particular relevance because of its role in many functions including not only the perception of speech and music, but their production as well. While we have knowledge about the structure and organization of the auditory system, the computations these substructures perform remain to be properly understood. A description of a neuron's activity in response to sound that is common in auditory research is the so-called frequency response area (FRA) of the neuron, which measures neuronal response as a function of the frequency and intensity of evoking acoustic stimuli. However, these FRAs have not yet been modelled computationally. In this thesis, based on experimental recordings of neurons located in the primary auditory cortices (A1s) of mice, we develop a data-driven model of auditory computation that seeks to reproduce the observed FRAs of the neurons, as well as offer a possible mechanism behind the generation of the particular underlying geometry of the FRAs. Our novel, biologically-plausible model posits that auditory neurons encode sound as quadratic forms on the frequency and intensity of sound, which A1 neurons integrate. Specifically, we utilized spiking neurons and advanced optimization and validation techniques to simulate synthetic leaky integrate-and-fire neurons that reproduce the FRAs of recorded neurons. Further, utilizing a network modelling technique known as the neural engineering framework, we show that these FRAs could be produced by a single-layer neural network. We also argue that it is not possible to reproduce the nonlinearities observed in the FRAs with a linear encoding, regardless of the nonlinearity of the A1 neuronal integration. Our work here might inform future modelling, simulations and algorithms of sound processing, as well as eventual human research on auditory encoding mechanisms.
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Keywords
Computational neuroscience, Auditory neuroscience, Primary auditory cortex, Auditory tuning curves, Frequency response area, Data-driven modelling, Biologically plausible
Citation
Ibarra Molinas, J. S. (2024). Quadratic encoding displayed by primary auditory cortical neurons (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.