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.
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Showing 1 to 20 of 26 for “"neural computation"”.
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Massively parallel neural computation
… science. This thesis focusses on real-time computation of large neural networks using the Izhikevich spiking neuron model. Neural computation has been described as “embarrassingly parallel” as each neuron can be thought of as an independent system, with behaviour described by a mathematical …
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The Neural Computation of Trust and Reputation
… thesis combines for the first time behavioral, computational, psychophysiological and neural models in a direct comparison of interaction-based and prior-based decision-to-trust mechanisms. Three studies are presented, in which participants played repeated and single trust games with anonymous …
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Neural computation of depth from binocular disparity
… is a par excellence demonstration of the computational power that neural systems can encapsulate. How is the brain capable of swiftly transforming a stream of binocular two-dimensional signals into a cohesive three-dimensional percept? Many brain regions have been implicated in …
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Neural Computation Through Synaptic Dynamics in Serotonergic Networks
Synapses are a fundamental unit of computation in the brain. Far from being passive connections between spiking neurons, synapses display striking short-term dynamics, undergo long-term changes in strength, and sculpt network-level processes in a complex manner. These synaptic dynamics, both in …
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Machine Learning As Tool And Theory For Computational Neuroscience
Computational neuroscience is in the midst of constructing a new framework for understanding the brain based on the ideas and methods of machine learning. This is effort has been encouraged, in part, by recent advances in neural network models. It is also driven by a recognition of the complexity …
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Application of capsule networks for image classification on complex datasets
… community and offers a paradigm shift in neural computation. In CapsNet, Sabour et. al. replace classical notions of scalar neural computation with a vectorised approach. This allows CapsNet to describe input images not only by the presence of constituent features but also by the pose of …
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To attract or to oscillate: Validating dynamics with behavior
In recent years, the `computation-through-dynamics' framework has gained traction within the neuroscience community as a means of describing how neurological processes implement behavioral computations. The framework argues that computations in neural systems are best explained through dynamical …
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Mixed Selectivity via Unsupervised Learning in Neural Networks
… and are hypothesised to play important roles in neural computation. Recently, both experimental and theoretical work demonstrated the importance of mixed selectivity in context-dependent decision tasks. This thesis extends existing theoretical work on mixed selectivity, arguing for a general and …
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Tools for connectomics in C. elegans
Efforts to model computation in biological neural networks require knowledge of the structure of the network, the dynamics that play across it, and a network simple enough to be tractable to our incipient analyses. The simplicity of the 302-node nervous system of the nematode C. elegans and its …
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A system for scalable 3D visualization and editing of connectomic data
… using technological advances in microscopy and neural computation to form a detailed understanding of structure and connectivity of neurons. Using the vast amounts of imagery generated by light and electron microscopes, connectomic analysis segments the image data to define 3D regions, forming …
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Facial hacking: the twisted logic of electro-facial choreography
This research addresses the development of a computational facial language that enables systematic exploration of the external controlled human face with the aim to identify fundamental electro-facial choreographic patterns. Rewiring the human face to an external digital control system, has sparked …
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C. elegans as a Platform for Multimodal Neural Data Integration
… gaps that hinder unified understanding of neural function. This thesis examines the nematode Caenorhabditis elegans as a platform for integrating diverse neural data modalities, offering a pathway to bridge these gaps. The hermaphrodite C. elegans, with its completely mapped connectome, …
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Pattern Separation in the Ventral Visual Stream
Pattern separation is a neural computation thought to underlie our ability to form distinct memories of similar events. It involves transforming overlapping inputs into less overlapping outputs. In the ventral visual stream (VVS) there is considerable evidence for hierarchical transformation from …
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Temporal dynamics of MEG phase information during speech perception: Segmentation and neural communication using mutual information and phase locking
… a privileged role for these timescales for neural communication between brain regions. Taken together these results suggest that timescales that correspond linguistically to important aspects of the speech stream also facilitate segmentation of the incoming signal and communication between …
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Understanding computation through low-dimensional dynamics with recurrent neural networks
… way to understand the brain is in terms of the computations it performs that allow an organism to survive in the world. Models of cognition and behavior can be useful for describing the computations that might be performed, but often provide little insight into how they are realized in neural …
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Development of extracellular electrophysiology methods for scalable neural recording
In order to map the dynamics of neural circuits in mammalian brains, there is a need for tools that can record activity over large volumes of tissue and correctly attribute the recorded signals to the individual neurons that generated them. High-resolution neural activity maps will be critical for …
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Inhibitory Control of Contextual Fear Memory and Memory Specificity
… and inhibition. Inhibition contributes to neural computation by gating information flow, tuning the gain of the network, and modulating the output strength of the system. The inhibition in the brain is mainly achieved by GABAergic inhibitory neurons which exert their effect by acting on …
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A neural-symbolic system for temporal reasoning with application to model verification and learning
… reasoning and learning into a robust computational model is one of the key challenges in Computer Science and Artificial Intelligence. In particular, temporal models have been fundamental in describing the behaviour of Computational and Neural-Symbolic Systems. Furthermore, knowledge …
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