abstract: Perceptual learning by means of coherent motion training paradigms has been shown to produce plasticity in lower and higher-level visual systems within the human occipital lobe both supra- and subliminally. However, efficiency of training methods that produce consolidation in the visual system via coherent motion has yet to be experimentally determined. Furthermore, the effects of coherent motion training on reading comprehension, in clinical and normal populations, are still nascent. In the present study, 20 participants were randomly assigned to one of four experimental conditions. Two conditions had a participation requirement of four days while two conditions required eight days of participation. These conditions were further divided into 500 or 1000 trials per day (4 x 500, 4 x 1000, 8 x 500, 8 x 1000). Additional pre-test and post-test days were used to attain timed pre- and post-tests on the Wide Range Achievement Test IV (WRAT IV) reading comprehension battery. Furthermore, a critical flicker fusion threshold (CFFT) score was taken on a macular pigment densitometer on the pre-test and post-test day. Participants showed significant improvement in CFFT levels, WRAT IV reading comprehension, and speed of completion between pre-test and post-test; however, degree of improvement did not vary as a function of training condition. An interaction between training condition and degree of improvement was evident in coherent dot motion contrast scores, with significant training plasticity occurring in the 4 x 1000 and 8 x 500 conditions. / Dissertation/Thesis / M.S. Psychology 2013

abstract: Magnocellular-Dorsal pathway’s function had been related to reading ability, and visual perceptual learning can effectively increase the function of this neural pathway. Previous researches training people with a traditional dot motion paradigm and an integrated visual perceptual training “video game” called Ultimeyes pro, all showed improvement with regard to people’s reading performance. This research used 2 paradigms in 2 groups in order to compare the 2 paradigms’ effect on improving people’s reading ability. We also measured participants’ critical flicker fusion threshold (CFFT), which is related to word decoding ability. The result did not show significant improvement of reading performance in each group, but overall the reading speed improved significantly. The result for CFFT in each group only showed significant improvement among people who trained with Ultimeyes pro. This result supports that the beneficial effect of visual perceptual learning training on people’s reading ability, and it suggests that Ultimeyes pro is more efficient than the traditional dot motion paradigm, and might have more application value. / Dissertation/Thesis / Masters Thesis Psychology 2015

The study of neural and behavioural mechanisms of perceptual decision making is often done by experimental tasks involving the categorization of sensory stimuli. Among the key perceptual tasks that decision neuroscience researchers use are motion discrimination paradigms that include tracking and specifying the net direction of a single dot or a group of moving dots. These motion discrimination paradigms, such as the random-dot motion task, allow the measurement of the participant's perceptual decision making abilities in multiple task difficulty levels by varying the amount of noise in the sensory stimuli. Computational models of perceptual decision making, such as the drift-diffusion model, are widely used to analyze the behavioural measurements from these motion discrimination experiments. However, the standard drift-diffusion model can only analyze the average measures like reaction times or the proportion of correct decisions to explain the behavioural data. In the past decade, an emerging computational modeling approach was introduced to analyze the choice behaviour based on precise noise patterns in the sensory stimuli. These computational models that use spatiotemporal stimulus details have shown promise in the single-trial analysis of motion discrimination behaviour. In this thesis, I further develop the advanced computational models of perceptual decision making that use spatiotemporal dynamics of motion stimuli to provide detailed explanations of perceptual choice behaviour. First, I demonstrate the usefulness of equipping an extended Bayesian Model, equivalent to the extended drift-diffusion model, with trial-wise stimulus information leading to a significantly better explanation of behavioural data from a single-dot tracking experiment. Second, I show that the extended drift-diffusion model constrained by spatiotemporal stimulus details can explain the consistent biased choice behaviour in response to stochastic motion stimuli. Based on this model-based analysis, I provide evidence that the source of the observed biased choice behaviour is the presence of subtle motion information in the sensory stimuli. These results further emphasize the effectiveness of using spatiotemporal details of stochastic stimuli in detailed model-based analyses of the experimental data and provide computational interpretations of the data related to underlying mechanisms of perceptual decision making.

La tâche de kinématogramme de points aléatoires est utilisée avec le paradigme de choix forcé entre deux alternatives pour étudier les prises de décisions perceptuelles. Les modèles décisionnels supposent que les indices de mouvement pour les deux alternatives sont encodés dans le cerveau. Ainsi, la différence entre ces deux signaux est accumulée jusqu’à un seuil décisionnel. Cependant, aucune étude à ce jour n’a testé cette hypothèse avec des stimuli contenant des mouvements opposés. Ce mémoire présente les résultats de deux expériences utilisant deux nouveaux stimuli avec des indices de mouvement concurrentiels. Parmi une variété de combinaisons d’indices concurrentiels, la performance des sujets dépend de la différence nette entre les deux signaux opposés. De plus, les sujets obtiennent une performance similaire avec les deux types de stimuli. Ces résultats supportent un modèle décisionnel basé sur l’accumulation des indices de mouvement net et suggèrent que le processus décisionnel peut intégrer les signaux de mouvement à partir d’une grande gamme de directions pour obtenir un percept global de mouvement. / Random dot kinematograms are used in visual psychophysics with the two-alternative forced-choice paradigm to study the process of simple perceptual decisions. Mathematical models of this process assume that stochastic motion evidence for the two alternative choices is encoded in the brain, and that the difference in evidence is accumulated towards a decision bound. However, no study to date has tested this assumption using stimuli with different levels of mutually opposing evidence in both directions. This thesis presents the results of two experiments using two novel stimuli with opposing coherent motion evidence. Over a variety of competing evidence combinations, subject performance was based on the net difference in the opposing signals. Furthermore, task performance was similar with both types of stimuli. These results support a decision model based on the accumulation of net evidence, and suggest that the decision process is capable of integrating motion evidence from a wide range of directions to obtain a global percept of motion.

In the study of perceptual decision making, it has been widely assumed that random fluctuations of motion stimuli are irrelevant for a participant’s choice. Recently, evidence was presented that these random fluctuations have a measurable effect on the relationship between neuronal and behavioral variability, the so-called choice probability. Here, we test, in a behavioral experiment, whether stochastic motion stimuli influence the choices of human participants. Our results show that for specific stochastic motion stimuli, participants indeed make biased choices, where the bias is consistent over participants. Using a computational model, we show that this consistent choice bias is caused by subtle motion information contained in the motion noise. We discuss the implications of this finding for future studies of perceptual decision making. Specifically, we suggest that future experiments should be complemented with a stimulus-informed modeling approach to control for the effects of apparent decision evidence in random stimuli.

La prise de décision est un processus computationnel fondamental dans de nombreux aspects du comportement animal. Le modèle le plus souvent rencontré dans les études portant sur la prise de décision est appelé modèle de diffusion. Depuis longtemps, il explique une grande variété de données comportementales et neurophysiologiques dans ce domaine. Cependant, un autre modèle, le modèle d’urgence, explique tout aussi bien ces mêmes données et ce de façon parcimonieuse et davantage encrée sur la théorie. Dans ce travail, nous aborderons tout d’abord les origines et le développement du modèle de diffusion et nous verrons comment il a été établi en tant que cadre de travail pour l’interprétation de la plupart des données expérimentales liées à la prise de décision. Ce faisant, nous relèveront ses points forts afin de le comparer ensuite de manière objective et rigoureuse à des modèles alternatifs. Nous réexaminerons un nombre d’assomptions implicites et explicites faites par ce modèle et nous mettrons alors l’accent sur certains de ses défauts. Cette analyse servira de cadre à notre introduction et notre discussion du modèle d’urgence. Enfin, nous présenterons une expérience dont la méthodologie permet de dissocier les deux modèles, et dont les résultats illustrent les limites empiriques et théoriques du modèle de diffusion et démontrent en revanche clairement la validité du modèle d'urgence. Nous terminerons en discutant l'apport potentiel du modèle d'urgence pour l'étude de certaines pathologies cérébrales, en mettant l'accent sur de nouvelles perspectives de recherche. / Decision‐making is a computational process of fundamental importance to many aspects of animal behavior. The prevailing model in the experimental study of decision‐making is the drift‐diffusion model, which has a long history and accounts for a broad range of behavioral and neurophysiological data. However, an alternative model – called the urgency‐gating model – has been offered which can account equally well for much of the same data in a more parsimonious and theoretically‐sound manner. In what follows, we will first trace the origins and development of the DDM, as well as give a brief overview of the manner in which it has supplied an explanatory framework for a large number of behavioral and physiological studies in the domain of decision‐making. In so doing, we will attempt to build a strong and clear case for its strengths so that it can be fairly and rigorously compared to potential alternative models. We will then re‐examine a number of the implicit and explicit theoretical assumptions made by the drift‐diffusion model, as well as highlight some of its empirical shortcomings. This analysis will serve as the contextual backdrop for our introduction and discussion of the urgency‐gating model. Finally, we present a novel experiment, the methodological design of which uniquely affords a decisive empirical dissociation of the models, the results of which illustrate the empirical and theoretical shortcomings of the drift‐diffusion model and instead offer clear support for the urgency‐gating model. We finish by discussing the potential for the urgency gating model to shed light on a number of clinical disorders, highlighting a number of future directions for research.