AUTHOR=Ladd Alexander , Kim Kyung Geun , Balewski Jan , Bouchard Kristofer , Ben-Shalom Roy TITLE=Scaling and Benchmarking an Evolutionary Algorithm for Constructing Biophysical Neuronal Models JOURNAL=Frontiers in Neuroinformatics VOLUME=16 YEAR=2022 URL=https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2022.882552 DOI=10.3389/fninf.2022.882552 ISSN=1662-5196 ABSTRACT=

Single neuron models are fundamental for computational modeling of the brain's neuronal networks, and understanding how ion channel dynamics mediate neural function. A challenge in defining such models is determining biophysically realistic channel distributions. Here, we present an efficient, highly parallel evolutionary algorithm for developing such models, named NeuroGPU-EA. NeuroGPU-EA uses CPUs and GPUs concurrently to simulate and evaluate neuron membrane potentials with respect to multiple stimuli. We demonstrate a logarithmic cost for scaling the stimuli used in the fitting procedure. NeuroGPU-EA outperforms the typically used CPU based evolutionary algorithm by a factor of 10 on a series of scaling benchmarks. We report observed performance bottlenecks and propose mitigation strategies. Finally, we also discuss the potential of this method for efficient simulation and evaluation of electrophysiological waveforms.