Thesis (M.A.)--York University, 2004. Graduate Programme in Psychology. / Typescript. Includes bibliographical references (leaves 90-111). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://wwwlib.umi.com/cr/yorku/fullcit?pMQ99375

To predict the final eye position in the middle of a saccadic eye movement will require long-range prediction. This dissertation investigated techniques for doing this. Many important results about saccadic eye movements and current prediction techinques were reviewed. New prediction techinques have been developed and tested for real saccadic data in computer. Three block processing predictors, two-point linear predictor (TPLP), five-point quadratic predictor (FPQP), and nine-point cubic predictor (NPCP), were derived based on the matrix approach. A different approach to deriving the TPLP, FPQP, and NPCP based on the difference equation was also developed. The difference equation approach is better than the matrix approach because it is not necessary to compute the matrix inversion. Two polynomial predictors: the polynomial-filter predictor 1 (PFP1), which is a linear combination of a TPLP and an FPQP, and the polynomial-filter predictor 2 (PFP2), which is a linear combination of a TPLP, and FPQP, and an NPCP, were also derived. Two recursive predictors: the recursive-least-square (RLS) predictor and the least-mean-square (LMS) predictor, were derived. Results show that the RLS and LMS predictors perform better than TPLP, FPQP, NPCP, PFP1, and PFP2 in the prediction of saccadic eye movements. A mathematical way of verifying the accuracy of the recursive-least-square predictor was developed. This technique also shows that the RLS predictor can be used to identify a signal. Results show that a sinusoidal signal can be described as a second-order difference equation with coefficients 2cosω and -1. In the same way, a cubic signal can be realized as a fourth-order difference equation with coefficients 4, -6, 4, and -1. A parabolic signal can be written as a third-order difference equation with coefficients 3, -3, and 1. And a triangular signal can be described as a second-order difference equation with coefficients 2 and -1. In this dissertation, all predictors were tested with various signals such as saccadic eye movements, ECG, sinusoidal, cubic, triangular, and parabolic signals. The FFT of these signals were studied and analyzed. Computer programs were written in systems language C and run on UNIX supported minicomputer VAX11/750. Results were discussed and compared to that of short-range prediction problems.

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Chapter 1 introduces the notions of multisensory integration (the binding of information coming from different modalities into a unitary percept) and multisensory response enhancement (the improvement of the response to multisensory stimuli, relative to the response to the most efficient unisensory stimulus), as well as the general goal of the present thesis, which is to investigate different aspects of the multisensory integration of auditory and visual stimuli in manual and saccadic responses. The subsequent chapters report experimental evidence of different factors affecting the multisensory response: spatial discrepancy, stimulus salience, congruency between cross-modal attributes, and the inhibitory influence of concurring distractors. Chapter 2 reports three experiments on the role of the superior colliculus (SC) in multisensory integration. In order to achieve this, the absence of S-cone input to the SC has been exploited, following the method introduced by Sumner, Adamjee, and Mollon (2002). I found evidence that the spatial rule of multisensory integration (Meredith & Stein, 1983) applies only to SC-effective (luminance-channel) stimuli, and does not apply to SC-ineffective (S-cone) stimuli. The same results were obtained with an alternative method for the creation of S-cone stimuli: the tritanopic technique (Cavanagh, MacLeod, & Anstis, 1987; Stiles, 1959; Wald, 1966). In both cases significant multisensory response enhancements were obtained using a focused attention paradigm, in which the participants had to focus their attention on the visual modality and to inhibit responses to auditory stimuli. Chapter 3 reports two experiments showing the influence of shape congruency between auditory and visual stimuli on multisensory integration; i.e. the correspondence between structural aspects of visual and auditory stimuli (e.g., spiky shape and “spiky” sounds). Detection of audio-visual events was faster for congruent than incongruent pairs, and this congruency effect occurred also in a focused attention task, where participants were required to respond only to visual targets and could ignore irrelevant auditory stimuli. This particular type of cross-modal congruency was been evaluated in relation to the inverse effectiveness rule of multisensory integration (Meredith & Stein, 1983). In Chapter 4, the locus of the cross-modal shape congruency was evaluated applying the race model analysis (Miller, 1982). The results showed that the violation of the model is stronger for some congruent pairings in comparison to incongruent pairings. Evidence of multisensory depression was found for some pairs of incongruent stimuli. These data imply a perceptual locus for the cross-modal shape congruency effect. Moreover, it is evident that multisensoriality does not always induce an enhancement, and in some cases, when the attributes of the stimuli are particularly incompatible, a unisensory response may be more effective that the multisensory one. Chapter 5 reports experiments centred on saccadic generation mechanisms. Specifically, the multisensoriality of the saccadic inhibition (SI; Reingold&Stampe, 2002) phenomenon is investigated. Saccadic inhibition refers to a characteristic inhibitory dip in saccadic frequency beginning 60-70 ms after onset of a distractor. The very short latency of SI suggests that the distractor interferes directly with subcortical target selection processes in the SC. The impact of multisensory stimulation on SI was studied in four experiments. In Experiments 7 and 8, a visual target was presented with a concurrent audio, visual or audio-visual distractor. Multisensory audio-visual distractors induced stronger SI than did unisensory distractors, but there was no evidence of multisensory integration (as assessed by a race model analysis). In Experiments 9 and 10, visual, auditory or audio-visual targets were accompanied by a visual distractor. When there was no distractor, multisensory integration was observed for multisensory targets. However, this multisensory integration effect disappeared in the presence of a visual distractor. As a general conclusion, the results from Chapter 5 results indicate that multisensory integration occurs for target stimuli, but not for distracting stimuli, and that the process of audio-visual integration is itself sensitive to disruption by distractors.

Thesis (Ph. D.)--University of California, San Diego, 2002. / Vita. Includes bibliographical references (leaves 174-182).

Thesis (M.A.)--York University, 2008. Graduate Programme in Psychology. / Typescript. Includes bibliographical references (leaves72-76). 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:MR45969

Visual search can simply be defined as the task of looking for an object of interest in a visual environment. Due to its foveated nature, the human visual system succeeds at such task by making many discrete fixations linked by rapid eye movements called saccades. However, very little is known about how saccadic targets (fixation loci) are selected by the brain in such naturalistic tasks. Discoveries to be made are not only invaluable to the field of vision science but are very important in designing automated vision systems, which to this day lag in performance vis-à-vis human observers. What I have sought to accomplish in this dissertation has been to reveal previously unknown saccadic targeting and target selection strategies used by human observers in naturalistic visual search tasks. My driving goal has been to understand how the brain selects fixation loci and target candidates upon fixation, with the objective of using these findings for automated fixation selection algorithms employed for visual search. I have proposed a novel and efficient technique akin to psychophysical reverse correlation to study human observer strategies in locating low-contrast targets under a variety of experimental conditions. My technique has successfully been used to study saccadic programming and target selection in various experimental conditions, including visual searches for targets with known characteristics, targets whose orientation attributes are not known a priori, and targets containing multiple orientations. I have found visual guidance in saccadic targeting and target selection under all experimental conditions, revealed by observers' selectivity for spatial frequencies and/or orientations of stimuli close to that of the target. I have shown that under uncertainty, observers rely on known target characteristics to direct their saccades and to select target candidates upon foveal scrutiny. Moreover, I have demonstrated that multiple orientation characteristics of targets are represented in observer search strategies, modulated by their sensitivity / selectivity for each orientation. Some of my findings have been applied towards applications for automated visual search algorithms.

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