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Visual neurons must efficiently encode visual information that is relevant to the animals' behaviour in an ever-changing visual environment. One of the ways animals are able to adapt to these changes is to alter their behaviour. Another, the topic of this thesis is to alter the processing properties of their visual neurons. I investigate the effect of changing the stimulus on the response properties of single neurons at three stages of visual processing. A reverse-correlation technique is used to measure spatiotemporal receptive fields (STRFs) which measure how the neuron spatially and temporally integrates the linear and nonlinear contrast stimuli presented to it in space and time.This analysis is performed for stimuli with different contrast, colour and sparsity and the changes in the STRFs are analysed in terms of their ability to improve neural performance. I study the processing of ultraviolet (UV) and green light in photoreceptors of an insect simple-lens eye, the median (middle) ocellus of a dragonfly. For the first time I present physiological evidence which shows these eyes are capable of a moderate level of spatial resolution and reveal differences in the way UV and green light sequences are processed. At the next level of processing, large second-order ocellar neurons (L-neurons) were studied. By presenting monochromatic (UV or green) moving bars and gratings I demonstrate, for the first time, that ocellar L-neurons are directionally selective in UV light but not in green light. Using a novel random stimulus I show that for most L-neurons the linear STRFs alter in structure significantly with changes in the stimulus density. With decreases in the stimulus density these cells become lower latency, have better spatial resolution and are spatiotemporally tuned to faster velocities. These new STRFs account significantly better for the response of L-neurons to fast moving bars.In the last section of my thesis I investigate whether the visual stimulus can also influence the receptive fields of neurons further along the visual pathway. To achieve this goal I map the changes in spatiotemporal tuning with changes in contrast of a subset of neurons within the cat primary visual cortex. I provide further evidence that at low contrasts, particular types of neurons, known as complex cells, have response properties similar to the other major type of cortical neuron, simple-cells. These results are combined with theoretical modelling to investigate the theory that complex STRFs are composed of simple-cell components.In summary, this thesis demonstrates at three levels of visual processing how neural STRFs are altered depending on the properties of the stimulus that is driving their response.
"This is a book about what the science of perception can tell us about visualization. There is a gold mine of information about how we see to be found in more than a century of work by vision researchers. The purpose of this book is to extract from that large body of research literature those design principles that apply to displaying information effectively"--
A synthesis of current approaches to adapting engineering tools to the study of neurobiological systems.
Some of the best vision scientists in the world in their respective fields have contributed to chapters in this book. They have expertise in a wide variety of fields, including bioengineering, basic and clinical visual science, medicine, neurophysiology, optometry, and psychology. Their combined efforts have resulted in a high quality book that covers modeling and quantitative analysis of optical, neurosensory, oculomotor, perceptual and clinical systems. It includes only those techniques and models that have such fundamentally strong physiological, control system, and perceptual bases that they will serve as foundations for models and analysis techniques in the future. The book is aimed first towards seniors and beginning graduate students in biomedical engineering, neurophysiology, optometry, and psychology, who will gain a broad understanding of quantitative analysis of the visual system. In addition, it has sufficient depth in each area to be useful as an updated reference and tutorial for graduate and post-doctoral students, as well as general vision scientists.
This open access book constitutes revised selected papers from the 4th International Workshop on Brain-Inspired Computing, BrainComp 2019, held in Cetraro, Italy, in July 2019. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures.