Abstract
Modelling biological systems is difficult due to insufficient knowledge about the internal components and organisation, and the complexity of the interactions within the system. At cellular level existing computational models of visual neurons can be derived by quantitatively fitting particular sets of physiological data using an input-output analysis where a known input is given to the system and its output is recorded. These models need to capture the full spatio-temporal description of neuron behaviour under natural viewing conditions. At a computational level we aspire to take advantage of state-of-the-art techniques to accurately model non-standard types of retinal ganglion cells. Using neural network techniques we model the highly complex neuronal structures of visual processing retinal cells and represent the mapping between perception and response automatically
Original language | English |
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Title of host publication | Unknown Host Publication |
Publisher | Ulster University |
Pages | 95-100 |
Number of pages | 6 |
Publication status | Published (in print/issue) - 27 Aug 2014 |
Event | Irish Machine Vision and Image Processing 2014 - Duration: 27 Aug 2014 → … |
Conference
Conference | Irish Machine Vision and Image Processing 2014 |
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Period | 27/08/14 → … |