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

Flow charts going through different graphs. Models at abstractions from biologically realistic to coarse networks, simulations at biologically realistic scales, sensitivity analysis to ascertain parameter influences, and guided model reduction to abstract theoretical descriptions.

Featured Project

Neuromodulation in Cortical Circuits

Although the influence of slow-acting neuromodulators, such as acetylcholine, serotonin, and dopamine, are widely considered to be critical in both healthy cognitive function (e.g., sleep versus wake, learning versus recollection) and psychiatric and neurological disorders, their computational role in neural circuits is relatively poorly understood.  Sandia neuroscientists have been using a large scale neural circuit modeling approach to examine how these modulators can affect neuronal circuit dynamics, specifically identifying a methodological approach for identifying how the underlying dynamics and correlational structure of network activity can be changed by modulation even if coarse behavior is unaffected.

For a brief talk on this research, see this YouTube presentation from the 2016 NICE workshop

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 neurons" Nature 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. January2014

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