Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 24 for “"sequence learning"”.
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Predatory sequence learning for synthetic characters
The process of mammalian predatory sequence development offers a number of insights relevant to the goal of designing synthetic characters that can quickly and easily learn complicated and interesting behavior. We propose a number of principles for designing such learning systems, inspired by a …
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MOTOR SEQUENCE LEARNING IN ADULTS WITH ADHD
… dopaminergic system. This study used the motor sequence learning paradigm to examine the selection of movement kinematics and force production and modulation in adults with ADHD. A two-by-three mixed design ANOVA, post-hoc independent measure t-tests and Pearson's correlations were performed. …
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Compositional Models for Few Shot Sequence Learning
Flexible neural sequence models outperform grammar- and automaton-based counterparts on a variety of tasks. However, neural models perform poorly in settings requiring compositional generalization beyond the training data—particularly to rare or unseen subsequences. Past work has found symbolic …
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Identifying the Neural Correlates of Motor Sequence Learning and Movement Automaticity
… for evaluating the neural correlates of motor learning. Currently, the understanding is that motor sequence learning engages the cortico-cerebellar and cortico-striatal networks and that their contributions differ depending on the stage of learning. The prefrontal cortex (PFC), in particular, …
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Preliminary investigation of the temporal specificity of sequence learning in the primary visual cortex through predictive coding
… computations. Nominally, the phenomenon of sequence learning relies on the ability of V1 to encode the serial order and temporal frequency of a spatiotemporal visual sequence. Investigating the mechanisms driving this phenomenon through the lens of predictive coding will further the …
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The Nature of the Processes, Representations, and Neural Substrates Which Support and Contribute to Motor Sequence Learning
… patients performed normally on both motor sequence learning tasks despite clear evidence of motor impairments demonstrable through independent clinical and neuropsychological testing. The results from the Parkinson's disease patients are the first to demonstrate normal motor sequence …
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Evidence for dissociable learning processes from the SRT task
… suggests that it may be fruitful to model learning using dissociable rule-based and associative processes. Such an account would predict that people should be able to learn the same sequences qualitatively differently under hypothesis-testing and incidental conditions. The aim of this …
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Neural representations used by brain regions underlying speech production
Speech utterances are phoneme sequences but may not always be represented as such in the brain. For instance, electropalatography evidence indicates that as speaking rate increases, gestures within syllables are manipulated separately but those within consonant clusters act as one motor unit. …
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The role of frontal cortical-basal ganglia circuits in simple and sequential visuomotor learning
… related regions of frontal cortex in visuomotor learning. Two experiments were conducted to elucidate the role of frontal cortex and striatum in visuomotor learning. Several tasks were used to characterize motor function including: a visuomotor reaction time (VSRT) task, measuring response speed …
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Associative implicit learning in adult dyslexic readers
This thesis examined associative implicit learning in dyslexic young adults. Dyslexic adults' associative implicit learning has been examined from three perspectives: what, when, and how. More specifically, it has been investigated if dyslexics have deficit in learning more complex knowledge, such …
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The Art of Deep Connection - Towards Natural and Pragmatic Conversational Agent Interactions
… language conversation with the human. Using deep learning techniques like recurrent neural networks and sequence-to-sequence learning, we demonstrate scalable and reasonable performances on both the tasks.
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Development of a Co-participatory and Reflexive Approach to Teaching and Learning Instructional Design
… program. The model supports co-participatory learning of instructional design and mutual examination of one's learning and participation by both instructor and students. A design and development framework is used to describe the design decisions, model implementation, and evaluation of the …
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Generating regular expressions from natural language specifications: A semantics-based approach and an empirical study
… the problem. These approaches typically train a sequence-to-sequence learning model using a syntax-based objective: maximum likelihood estimation (MLE). Such syntax-based approaches do not effectively address the goal of generating semantically correct programs, because these approaches fail to …
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Structural and functional brain plasticity for statistical learning
… from navigating in a new environment to learning a language. These skills rely on our ability to extract spatial and temporal regularities, often with minimal explicit feedback, that is known as statistical learning. Despite the importance of statistical learning for making perceptual …
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Learning in dynamic temporal domains using contextual prediction entropy as a guiding principle.
Temporal sequence learning facilitates the near-term prediction of future events, a skill that is essential in order for intelligent agents to function in a dynamic world. Agents acting in real-time dynamic environments must anticipate the movement of other agents/objects to avoid collisions and …
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The Effects of Visuospatial Sequence Training with Children who are Deaf or Hard of Hearing
… development but for cognitive functions such as sequence memory and learning ability. This study investigated a variety of cognitive functions with two major aims in mind: 1) to verify differences between children who are deaf or hard of hearing and typically hearing children on variety of …
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Machine Learning for Predicting Prosthetic Limb Movements
<p>This thesis develops and evaluates a deep learning-based prediction model capable of identifying intended limb movement from surfaced electromyography (sEMG) signals using sequence learning techniques. sEMG signals change over time due to multiple factors such as muscle fatigue or user …
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Designing Better Scaffolding in Teaching Complex Systems with Graphical Simulations
… scaffolding is a critical factor for effective learning. This dissertation study was conducted around two complementary research questions on scaffolding: (1) How can we chunk and sequence learning activities in teaching complex systems? (2) How can we help students make connections among system …
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The neurocognitive mechanisms of perceptual inference in autism
… from a visuomotor probabilistic reversal learning task used to examine how adults with varying levels of autistic traits evaluate sensory information, build, and update sensory expectations. A positive relationship was found between autistic traits and the learning of probable sequences …
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An Analysis of Functional Differences in Implicit Learning
This thesis analysed whether functional implicit learning differences existed in two areas that have produced promising, but equivocal, findings: individual differences in typical populations (e.g., Gebauer & Mackintosh, 2010) and group differences between Autism Spectrum Condition (ASC) and …
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