NEURON as a Means to Reverse Engineer the Brain: A Computational Approach to Modeling Neurons and Action Potentials
Mentor 1
James Moyer, Jr.
Location
Union Wisconsin Room
Start Date
27-4-2018 1:00 PM
Description
Computational neuroscience is an interdisciplinary field that incorporates an analysis of brain functions in direct relation to information processing within the nervous system. By use of exploratory modeling techniques and mathematical application, the field of neuroscience has revealed a method of reverse engineering the brain by means of quantitative analysis. In exploring the capacity of NEURON, an open-source neuronal network simulation environment, a foundation for introductory theoretical and computational neuroscience has been implemented. The NEURON Guided User Interface (GUI) allows for an intuitive grasp on experimental data input and model construction. By introducing Python to NEURON, a breadth of analysis tools and familiarity of language can be made available for ease of the user. The research aims to broaden the perspective of computational neuroscience to the engineering discipline and to apply rudimentary computer science techniques, including persistency to the goal of sufficiently accurate computer models based in mathematical roots. This research project involves not only learning how to use NEURON to create computational models of neurons, but also to create a 3D drawing of a neuron from which neurophysiological data were experimentally collected. After generating the 3D reconstruction, I will then create a computational model that captures the neurophysiological characteristics of the neuron. Data from these types of studies will then be used to ask questions associated with how the intrinsic properties of neurons change during learning and memory, and how aging can impact these capabilities.
NEURON as a Means to Reverse Engineer the Brain: A Computational Approach to Modeling Neurons and Action Potentials
Union Wisconsin Room
Computational neuroscience is an interdisciplinary field that incorporates an analysis of brain functions in direct relation to information processing within the nervous system. By use of exploratory modeling techniques and mathematical application, the field of neuroscience has revealed a method of reverse engineering the brain by means of quantitative analysis. In exploring the capacity of NEURON, an open-source neuronal network simulation environment, a foundation for introductory theoretical and computational neuroscience has been implemented. The NEURON Guided User Interface (GUI) allows for an intuitive grasp on experimental data input and model construction. By introducing Python to NEURON, a breadth of analysis tools and familiarity of language can be made available for ease of the user. The research aims to broaden the perspective of computational neuroscience to the engineering discipline and to apply rudimentary computer science techniques, including persistency to the goal of sufficiently accurate computer models based in mathematical roots. This research project involves not only learning how to use NEURON to create computational models of neurons, but also to create a 3D drawing of a neuron from which neurophysiological data were experimentally collected. After generating the 3D reconstruction, I will then create a computational model that captures the neurophysiological characteristics of the neuron. Data from these types of studies will then be used to ask questions associated with how the intrinsic properties of neurons change during learning and memory, and how aging can impact these capabilities.
