Shallcross, Thomas

English

Classification of cell types in the brain remains a fundamental goal of neuroscience. A systematic classification of cell types is a means to reduce the dimensionality of the brain and is a prerequisite to understanding the nature of the neural codes underlying brain function.Here a method is presented to functionally categorise cells within the optic tectum of larval zebrafish; a midbrain structure involved in guiding attention and movement relative to specific locations in egocentric space. Using an array of visual stimuli and functional imaging of the entire tectum with single neuron resolution, the aim of this thesis is to be able to classify tectal cell types and determine the 3D distribution of these neurons throughout the tectum. To examine whether tectal neurons can be classified by responses to specific combinations of visual features a non-parametric method of classification has been developed based on unsupervised density based clustering of tectal cell responses. From this method a number of biological findings emerged. First, neurons were found which are selective for a of conjunction visual features, namely size and direction. Second, there is evidence for dot selective neurons in the tectum. Third, there appears to be a non-uniform distribution of neuronal subtypes across the tectum, which may have implications for how information is processed across the visual scene.The aim is to provide a cellular resolution description of tectal organisation and because the method is applied to live animals it paves the way for providing an unbiased description of the population codes underlying sensory representations in the tectum and tectally mediated behaviour

King's Research Portal

Functional classification of cell types in the zebrafish optic tectum

https://kclpure.kcl.ac.uk/portal/files/228775650/2020_Shallcross_Thomas_1456737_ethesis.pdf

Functional classification of cell types in the zebrafish optic tectum

Abstract

Similar works

Full text

Available Versions

King's Research Portal