Discipline: Computer Sciences and Information Management
Subcategory: Computer Science & Information Systems
Karla Miletti - Delaware State University
Co-Author(s): Joseph Lombardo and Melissa Harrington, Delaware State University, Dover, DE
Plasticity is a defining feature of the brain that allows it to undergo changes in response to stimuli. It is therefore important to study how nerve cells’ behavior can be modified for the advancement of basic science, prosthetics, and therapy. We hypothesize that the alteration in the function of the Kv7.2 channel (which carries the M current) and changes in the axonal initial segment (AIS) properties are the primary mechanisms of adaptation of spinal motoneurons to prolonged network activation. This hypothesis is supported by literature and our own experimental data. To further test our hypothesis, we developed a realistic computational model of a spinal motoneuron, accounting for its attributes before and after persistent network activation. This computational approach allowed us to employ an evolutionary algorithm, which uses mechanisms inspired by biological evolution, such as reproduction, mutation, recombination, and selection, to generate biologically feasible models. We adjusted the range of model parameter values to reflect the experimental data to anchor our methods in biology, and to take advantage of the algorithm’s ability to create many different models fitting that biological description. Our algorithm matched multiple selection criteria simultaneously (e.g., input resistance, current threshold) and generated entire collections of neuronal models that could be mined for rules elucidating the behavior captured experimentally, including those describing relationships between neuronal activity and model parameters. Furthermore, we parallelized the evolutionary algorithm by utilizing the OpenACC programming paradigm, which enabled us to employ the speed of Graphics Processing Units (GPUs) for scientific computing.
Funder Acknowledgement(s): NIH NCRR 5P20RR016472-12 and NIGMS 8P20GM103446-12 to KM and TGS, NIH 1R15HD075207 to JL and MAH, NIH 5 P20 GM103653 toMAH, NSF EPSCoR 0814251 to TGS, and NSF IOS 1608147 TO KM, JL, MAH, and TGS
Faculty Advisor: Tomasz Smolinski, email@example.com
Role: Developing the project, programming, running algorithm, debugging errors, creating poster.