Sandia Neuroscience

Modeling and Simulation

Techniques for modeling large scale neural systems have long been appreciated to be critical to understanding the function of complex neural circuits.  Leveraging Sandia's strengths in large scale modeling and simulation of physical systems, we have a number of efforts focused on improving the technical capabilities available for neuroscientists to robustly and reliably model neural circuits.  These efforts include

  • Uncertainty quantification and sensitivity analysis of neural models
  • Designing codes to enable neural circuit simulations in parallel architectures
  • Developing strategies for implementing systems of varying biological complexity in conventional HPC platforms

Schematic of Modeling Pipeline

Selected References

Vineyard CM, Verzi SJ, James CD, and Aimone JB – “Quantifying Neural Information Content: A Caste Study of the Impact of Hippocampal Adult Neurogenesis” Proceedings of the International Joint Conference on Neural Networks 2016

Dieni CV, Panichi R, Aimone JB, Kuo CT, Wadiche JI, and Overstreet-Wadiche, L - "Low excitatory innervation balances high intrinsic excitability of immature dentate neuronsNature Communications. April 2016

Rothganger F, Warrender CE, Trumbo D, and Aimone JB – “N2A: a novel computational tool for modeling from neurons to algorithms” Frontiers in Neural Circuits. January 2014

Aimone JB and Weick J – “Perspectives for computational modeling of cell replacement for neurological disorders” Frontiers in Computational Neuroscience. October 2013