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Thesis (M.Sc.)--York University, 2006. Graduate Programme in Computer Science and Engineering. / Typescript. Includes bibliographical references (leaves 124-134). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:MR29617

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Healthy ageing in the absence of neurodegenerative diseases is accompanied by a variety of perceptual and cognitive changes, which can occur on various distinct but interacting levels. Much research has been devoted to understanding how basic cognitive functions such as working memory and attention change with age. However, only more recently has age-related changes on perceptual functions been investigated, thus less is understood. My thesis aimed to address this gap in the literature, by exploring age-related changes in visual perception, specifically changes related to visual temporal processing of natural and biological stimuli. Also investigated was the extent to which age-related changes in perceptual and cognitive functions affect each other. Chapter 2 investigated the time course of visual processing of natural scene categorisation in older adults. Younger, young-old and old-old adults performed a go/no-go task, in which they had to respond to images of animals whilst ignoring images of landscapes. The results showed that the temporal processing of complex scenes is impaired in healthy older adults and this deficit becomes more pronounced with increasing age. Chapter 3 assessed whether age-related decline in biological motion perception is mediated by impaired attentional abilities. Younger and older adults performed a series of tasks assessing biological motion perception and visual attention. The results indicated that age-related changes in biological motion perception are not driven by general attentional decline. Lastly, Chapter 4 explored whether age-related changes in biological motion and attention tasks can be explained by differences in the allocation of attention. Younger and older adults performed a conjunctive visual search, and two biological motion tasks, while their eye movements were being tracked. The results illustrated that differences in the allocation of attention cannot explain age-related differences found on biological motion perception and attention tasks. Overall, my findings provide substantial evidence to suggest that both visual perceptual and cognitive abilities change with healthy ageing. However, my results also indicate that certain aspects of these two functions remain relatively preserved in older adulthood.

Thesis (Ph. D.)--University of Washington, 1999. / Vita. Includes bibliographical references (leaves 78-82).

Making a robot autonomous has been a common challenge to be overcome since the very beginning. To be an autonomous system, the robot should collect environmental data, interpret them, and act accordingly. In order to accomplish these, some resource management should be conducted. That is, the resources, which are time, and computation power in our case, should be allocated to more important areas. Existing researches and approaches, however, are not always human like. Indeed they don&rsquo / t give enough importance on this. Starting from this point of view, the system proposed in this thesis supplies the resource management trying to be more &rsquo / human like&rsquo / . It directs the focus of attention to where higher resolution algorithms are really needed. This &rsquo / real need&rsquo / is determined by the visual features of the scene, and current importance levels (or weight values) of each of these features. As a further attempt, the proposed system is compared with human subjects&rsquo / characteristics. With unbiased subjects, a set of parameters which resembles a normal human is obtained. Then, in order to see the effect of the guidance, the subjects are asked to concentrate on a single predetermined feature. Finally, an artificial neural network based learning mechanism is added to learn to mimic a single human or a group of humans. The system can be used as a preattentive stage module, or some more feature channels can be introduced for better performance in the future.

Thesis (Ph. D.)--Carleton University, 2004. / Includes bibliographical references (p. 202-217). Also available in electronic format on the Internet.

Thesis (Ph. D.)--University of California, San Diego and San Diego State University, 2003. / Vita. Includes bibliographical references.

Diss. (sammanfattning) Stockholm : Karol. inst., 2002. / Härtill 6 uppsatser.

Our brains handle vast amounts of information incoming through our senses. Continuously exposed to sensory input, the sense of touch, however, may miss tactile stimuli, no matter how much attention we pay to them. In four empirical studies, this thesis tested (1) the feasibility of investigating undetectable stimulation by electrical finger nerve pulses, (2) how its neural correlates dissociate from detectable stimulation and (3) whether and how selective somatosensory attention nevertheless affects the neural representation of undetectable stimuli. The first two studies showed that there is a natural range of electrical stimulation intensities that cannot be detected. A rigorous statistical evaluation with Bayes factor analysis indicated that the evidence of chance performance after undetectable stimulation reliably outweighed evidence of above-chance performance. A subsequent study applying electroencephalography (EEG) revealed qualitative differences between the processing of detectable and undetectable stimulation, which is evident in altered event-related potentials (ERP). Specifically, undetectable stimulation evokes a single component that is not predictive of stimulus detectability but lacks a subsequent component, which correlates with upcoming stimulus detection. The final study showed that attention nevertheless affects neural processing of undetectable stimuli in a top-down manner as it does for detectable stimuli and fosters the view of attention and awareness being two separate and mostly independent mechanisms. The influence of the pre-stimulus oscillatory (~10 Hz) alpha amplitude—a putative marker of attentional deployment—on the ERP depended on the current attentional state and indicates that both processes are interacting but not functionally matching.:1 Touch, Consciousness, And Attention – Theoretical Considerations ........ 1-11 1.1 A Neural Account To (Un-) Consciousness ............................................ 1-12 1.2 Controlling detectability of external stimulation ...................................... 1-14 1.3 Thresholds in the light of signal detection theory ................................... 1-17 1.4 Selective attention in touch .................................................................... 1-19 1.5 Research questions ............................................................................... 1-21 2 Empirical Evidence .................................................................................... 2-25 2.1 General methods .................................................................................... 2-25 2.1.1 Stimulation ........................................................................................... 2-25 2.1.2 Threshold assessment procedure ....................................................... 2-25 2.1.3 Behavioral analysis .............................................................................. 2-26 2.1.4 Electrophysiological measurement ...................................................... 2-28 2.1.5 Analysis of event-related potentials ..................................................... 2-30 2.1.6 Spectral Analysis resolved over time ................................................... 2-30 2.2 Psychophysical assessment of subthreshold stimulation ........................ 2-33 2.2.1 A method for assessing the individual absolute detection threshold (ADTH) ......................................................................................................... 2-33 2.2.2 Validation of absolute detection threshold assessment by signal detection theory measures and Bayesian Null-Hypothesis testing ................ 2-39 2.3 Non-invasive neural markers of unconscious perception ....................... 2-47 2.3.1 Neural Correlates of Undetectable Somatosensory Stimulation in EEG and fMRI ...................................................................................................... 2-47 2.3.2 Prediction of stimulus perception by features of the evoked potential for different stimulation intensities along the psychometric function ................. 2-51 2.4 The role of Rolandic Alpha Activity in Somatosensation and its Relation to Attention ................................................................................................. 2-75 3 General Discussion and Conclusions ...................................................... 3-101 3.1 Summary of empirical results ................................................................ 3-101 3.2 Neural processing of undetectable stimulation ..................................... 3-102 3.3 Attention, awareness and neural oscillatory activity ............................. 3-104 3.4 Limits of the current studies and future perspectives ........................... 3-109 References .................................................................................................... 113 Summary ....................................................................................................... 137 Zusammenfassung ........................................................................................ 143 Curriculum Vitae ............................................................................................ 151 Selbständigkeitserklärung ............................................................................. 155 Nachweis über die Anteile der Co-Autoren .................................................... 157