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Title: The development of neuronal responses in the primate lateral intraparietal area
Author: De Moraes Navarro, Daniel
ISNI:       0000 0004 9355 5952
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2019
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This thesis develops biologically plausible neural network models of how the response properties of certain classes of visual neurons in the primate parietal cortex may emerge through visually-guided learning. We start with an investigation of how different functional forms of gain modulation of neuronal responses, in particular gain modulation by the position of the eye, may develop in the brain. Gain modutalion refers to the modulatory effect that a particular bodily state or posture has on the firing rate of some visual neurons responding in a given reference frame. The remainder of the thesis focuses on the development of neurons with head-centred receptive fields. Such neurons respond maximally to a visual stimulus in the same head-centred location across all eye positions. In this thesis we show that different functional forms of gain modulation deeply affects the self-organisation of head-centred responses using simulated training data. We then recorded simultanous eye and head movements from human participants during a visual search task and used these to train our self-organising model of coordinate transformation. A further contribution of this thesis is the development of an open source scientific tool for Android devices to record rotation movements. Our neural network models were trained using a biologically plausible visually-guided learning process and then tested in simulated conditions similar to the experimental tasks used when the investigated responses were observed in the primate brain. The trained responses of our models showed a broad agreement with neurophysiological observations and our simulations help advance understanding of how the neuronal response properties investigated in this thesis may develop in the visual brain.
Supervisor: Stringer, Simon ; Smithson, Hannah Sponsor: Brazilian National Council for Scientific and Technological Development (CNPq) ; Oxford Foundation for Theoretical Neuroscience and Artificial Intelligence (OFTNAI)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: theoretical neuroscience ; computational neuroscience ; artificial intelligence ; biological neural network