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Computational Neuroscience

Neuroscience

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Articles 31 - 41 of 41

Full-Text Articles in Neuroscience and Neurobiology

Geometric Analysis Of Synchronization In Neuronal Networks With Global Inhibition And Coupling Delays, Hwayeon Ryu, Sue Ann Campbell May 2018

Geometric Analysis Of Synchronization In Neuronal Networks With Global Inhibition And Coupling Delays, Hwayeon Ryu, Sue Ann Campbell

Biology and Medicine Through Mathematics Conference

No abstract provided.


Balanced Excitation And Inhibition Shapes The Dynamics Of A Neuronal Network For Movement And Reward, Anca R. Radulescu May 2017

Balanced Excitation And Inhibition Shapes The Dynamics Of A Neuronal Network For Movement And Reward, Anca R. Radulescu

Biology and Medicine Through Mathematics Conference

No abstract provided.


Applying Fmri Complexity Analyses To The Single-Subject: A Case Study For Proposed Neurodiagnostics, Anca R. Radulescu, Emily R. Hannon May 2017

Applying Fmri Complexity Analyses To The Single-Subject: A Case Study For Proposed Neurodiagnostics, Anca R. Radulescu, Emily R. Hannon

Biology and Medicine Through Mathematics Conference

No abstract provided.


An Interdisciplinary Approach To Computational Neurostimulation, Madison Guitard May 2017

An Interdisciplinary Approach To Computational Neurostimulation, Madison Guitard

Biology and Medicine Through Mathematics Conference

No abstract provided.


Rules And Mechanisms For Efficient Two-Stage Learning In Neural Circuits, Tiberiu Teşileanu, Bence Ölveczky, Vijay Balasubramanian Jan 2017

Rules And Mechanisms For Efficient Two-Stage Learning In Neural Circuits, Tiberiu Teşileanu, Bence Ölveczky, Vijay Balasubramanian

Publications and Research

Trial-and-error learning requires evaluating variable actions and reinforcing successful variants. In songbirds, vocal exploration is induced by LMAN, the output of a basal ganglia-related circuit that also contributes a corrective bias to the vocal output. This bias is gradually consolidated in RA, a motor cortex analogue downstream of LMAN. We develop a new model of such two-stage learning. Using stochastic gradient descent, we derive how the activity in ‘tutor’ circuits (e.g., LMAN) should match plasticity mechanisms in ‘student’ circuits (e.g., RA) to achieve efficient learning. We further describe a reinforcement learning framework through which the tutor can build its teaching …


Symmetries Constrain Dynamics In A Family Of Balanced Neural Networks, Andrea Barreiro, J Nathan Kutz, Eli Shlizerman May 2016

Symmetries Constrain Dynamics In A Family Of Balanced Neural Networks, Andrea Barreiro, J Nathan Kutz, Eli Shlizerman

Biology and Medicine Through Mathematics Conference

No abstract provided.


Wilson-Cowan Coupled Dynamics In A Model Of The Cortico-Striato-Thalamo-Cortical Circuit, Anca R. Radulescu May 2016

Wilson-Cowan Coupled Dynamics In A Model Of The Cortico-Striato-Thalamo-Cortical Circuit, Anca R. Radulescu

Biology and Medicine Through Mathematics Conference

No abstract provided.


Scalar Short-Term Memory, Tyler D. Bancroft Jan 2016

Scalar Short-Term Memory, Tyler D. Bancroft

Theses and Dissertations (Comprehensive)

The location of the brain’s working and short-term memory (WM/STM) “system” is unclear. The existence of a dedicated WM/STM system is itself under debate. Recently, it has been proposed that WM/STM storage relies not on a dedicated system in prefrontal cortex, but rather that it is an emergent function of interaction between attentional and representational systems (e.g., sensory cortex) in the brain. However, mnemonic representations of very simple stimuli have repeatedly been shown to exist in frontal cortex. In this manuscript, I use computational and behavioural methods to demonstrate similarities between the representations of different types of very simple stimuli …


Design, Programming, And User-Experience, Kaila G. Manca May 2015

Design, Programming, And User-Experience, Kaila G. Manca

Honors Scholar Theses

This thesis is a culmination of my individualized major in Human-Computer Interaction. As such, it showcases my knowledge of design, computer engineering, user-experience research, and puts into practice my background in psychology, com- munications, and neuroscience.

I provided full-service design and development for a web application to be used by the Digital Media and Design Department and their students.This process involved several iterations of user-experience research, testing, concepting, branding and strategy, ideation, and design. It lead to two products.

The first product is full-scale development and optimization of the web appli- cation.The web application adheres to best practices. It was …


Neural Synchrony In The Zebra Finch Brain, Sydney Pia Goings Apr 2012

Neural Synchrony In The Zebra Finch Brain, Sydney Pia Goings

Scripps Senior Theses

I am interested in discovering the role of field potential oscillations in producing synchrony within the song system of the male zebra finch brain. An important function attributed to neural synchrony is sensorimotor integration. In the production of birdsong, sensorimotor integration is crucial, as auditory feedback is necessary for the maintenance of the song. A cortical-thalamic-cortical feedback loop is thought to play a role in the integration of auditory and motor information for the purpose of producing song. Synchronous activity has been observed between at least two nuclei in this feedback loop, MMAN and HVC. Since low frequency field potential …


Computational Modeling Of Biological Neural Networks On Gpus: Strategies And Performance, Byron Galbraith Jul 2010

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 …