Biophysically detailed representations of neural network models provide substantial insight to underlying neural processing mechanisms in the auditory systems of the brain. For simple biological systems the behavior can be represented by simple equations or flow charts. But for complex systems, more detailed descriptions of individual neurons and their synaptic connectivity are typically required. Creating extensive network models allows us to test hypotheses, apply specific manipulations that cannot be done experimentally and provide supporting evidence for experimental results. Several studies have been made on establishing realistic models of the cochlear nucleus (Manis and Campagnola, 2018; Eager et al., 2004), the part of the brainstem where sound signals enter the brain, both on individual neuron and networked structure levels. These models are based on both in vitro and in vivo physiological data, and they successfully demonstrate certain aspects of the neural processing of sound signals. Even though these models have been tested with tone bursts and isolated phonemes, the representation of speech in the cochlear nucleus and how it may support robust speech intelligibility remains to be explored with these detailed biophysical models.
In this study, the basis of creating a biophysically detailed model of microcircuits in the cochlear nucleus is formed following the approach of Manis and Campagnola
(2018). The focus of this thesis is more on bushy cell microcircuits. We have updated Manis and Campagnola (2018) model to take inputs from the new phenomenological auditory periphery model of Bruce et al. (2018). Different cell types in the cochlear nucleus are modelled by detailed cell models of Rothman and Manis (2003c) and updated Manis and Campagnola (2018) cell models. Networked structures are built out of them according to published anatomical and physiological data. The outputs of these networked structures are used to create post-stimulus-time-histograms (PSTH) and response maps to investigate the representation of tone bursts and average localized synchronized rate (ALSR) of phoneme 'e' and are compared to published physiological data (Blackburn and Sachs, 1990). / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/24212 |
| Date | January 2019 |
| Creators | Yayli, Melih |
| Contributors | Bruce, Ian C., Electrical and Computer Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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