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Full-Text Articles in Computational Neuroscience
Biophysical Model Of Retraction Motor Neurons And Their Modification By Operant Conditioning, Maria Rasheed
Biophysical Model Of Retraction Motor Neurons And Their Modification By Operant Conditioning, Maria Rasheed
Dissertations & Theses (Open Access)
Operant conditioning (OC) is a form of associative learning in which an animal modifies its behavior based on the consequences that follow that behavior. Despite its ubiquity, the underlying mechanisms of OC are poorly understood. Insights into the mechanisms of OC can be obtained by studying Aplysia feeding behavior as it can be modified by OC. This behavior is mediated by a central pattern generator (CPG) network in the buccal ganglia that contains a relatively small number of neurons. This CPG generates rhythmic motor patterns (BMPs) that move food into the gut by closing a tongue-like structure (i.e., radula) during …
Phenotyping Regression In A Female Mouse Model For Rett Syndrome Using Computational Neuroethology Tools, Michael J. Mykins
Phenotyping Regression In A Female Mouse Model For Rett Syndrome Using Computational Neuroethology Tools, Michael J. Mykins
Doctoral Dissertations
Regression is defined as loss of acquired skills over time and is a key feature of many neurodevelopmental disorders such as Rett syndrome (RTT). RTT is caused by mutations in the X-linked gene Methyl CpG-Binding Protein 2 (MECP2) and is characterized by a period of typical development with subsequent regression of previously acquired motor and speech skills in girls. In human and animal models, it is clear syndromic phenotypes are dynamic over time but phenotyping regression over time in animal models has remained elusive. Lack of established timelines to study the molecular, cellular, and behavioral features of regression in female …
Using Machine Learning To Identify Neural Mechanisms Underlying The Development Of Cognition In Children And Adolescents With Adhd, Brian Pho
Electronic Thesis and Dissertation Repository
Childhood and adolescence are marked by improvements to cognition and by the emergence of neurodevelopmental disorders such as attention deficit hyperactivity disorder (ADHD). What neural mechanisms are associated with cognitive development in ADHD? In this study, I applied machine learning models to functional connectivity profiles to identify patterns of network connectivity that predict various cognitive abilities in a group of participants ages 6 to 16 with ADHD. The models successfully predicted IQ, visual spatial, verbal comprehension, and fluid reasoning in children ages 6 to 11, but not adolescents. Furthermore, the models identified connections with the default mode, memory retrieval, and …
Computational Modeling Of Biological Neural Networks On Gpus: Strategies And Performance, Byron Galbraith
Computational Modeling Of Biological Neural Networks On Gpus: Strategies And Performance, Byron Galbraith
Master's Theses (2009 -)
Simulating biological neural networks is an important task for computational neuroscientists attempting to model and analyze brain activity and function. As these networks become larger and more complex, the computational power required grows significantly, often requiring the use of supercomputers or compute clusters. An emerging low-cost, highly accessible alternative to many of these resources is the Graphics Processing Unit (GPU) - specialized massively-parallel graphics hardware that has seen increasing use as a general purpose computational accelerator thanks largely due to NVIDIA's CUDA programming interface. We evaluated the relative benefits and limitations of GPU-based tools for large-scale neural network simulation and …