Computational Neuroscience

BradAimone

Brad Aimone is a Principal Member of the Technical Staff in the Cognitive and Emerging Computing Group (1421) at Sandia National Laboratories, where he is a researcher in computational neuroscience modeling and helps lead the Neural Exploration Research Laboratory (NERL), which is a major R&D program targeting the development of neural based computing algorithms and computing architectures. 

Prior to joining the technical staff at Sandia, Brad was a postdoctoral research associate at the Salk Institute for Biological Studies.  He received his Ph.D. in computational neuroscience from the University of California, San Diego and earned his Bachelor and Master degrees in chemical engineering from Rice University.  His primary research focus has long been adult neurogenesis in the hippocampus, where he was the first to use biologically realistic computational modeling approaches to describe its roles in episodic memory formation.  He has more recently been involved in the development of novel algorithms based on neural circuit dynamics and the development of computational architectures suitable for implementing this novel approach to processing information.  The motivating theme for his work is translational computational neuroscience – using engineering approaches in neuroscience to create applications in fields ranging from neurology and psychiatry to brain-inspired computing. Brad has published over fifty peer-reviewed journal and conference articles in journals including Neuron, Nature Neuroscience, and Nature Reviews Neuroscience as well as several book chapters and a number of invited talks and conference presentations.

Brad helped lead the Hardware Acceleration of Adaptive Neural Algorithms (HAANA) Grand Challenge, which was a major internal R&D effort focused on the development of neuromorphic technologies for DOE applications.  He currently leads several research efforts on designing neural algorithms for scientific computing applications and neuromorphic machine learning implementations.

 

 

Contact Information

jbaimon@sandia.gov

Research Areas

Computational Neuroscience

  • Theoretical and modeling assessments of the function of adult neurogenesis 
  • Computational studies of the dentate gyrus and hippocampus
  • Designing novel theoretical perspective for the computational impact of neuromodulation
  • Developing novel analytical approaches to interpret cortical simulations

Neural Computing

  • Assessing and designing novel neural-inspired computing architectures
  • Developing novel neural algorithms for solving scientific computing applications on neuromorphic hardware
  • Incorporation of brain-inspired techniques for improving adaptability of neural machine learning methods such as deep learning
  • Developing techniques to assess the neural-suitability of novel computing devices such as memristors
  • Identifying areas for neural algorithms to impact cyber security, image processing, and bioinformatics applications

Videos and Presentations

Peer-reviewed Publications

  1. Cardwell S, Vineyard CM, Severa W, Chance F, Rothganger F, Wang F, Musuvathy S, Teeter CM, and Aimone JB – “Truly heterogeneous HPC: co-design to achieve what science needs from HPC” 2020 Smokey Mountains Computational Sciences and Engineering Conference (SMC2020)
  2. Smith JD, Severa W, Hill AJ, Reeder L, Franke B, Lehoucq RB, Parekh O, and Aimone JB – “Solving a steady-state PDE using spiking networks and neuromorphic hardware” 2020 International Conference on Neuromorphic Systems, July 2020
  3. Aimone JB, Ho Y, Parekh O, Phillips CA, Pinar A, Severa W, Wang Y [alphabetical] – “Brief Announcement: Provable Neuromorphic Advantages for Computing Shortest Paths” 2020 Symposium on Parallelism in Algorithms and Architectures (SPAA), July 2020
  4. Kerman, B.E., Genoud, S., Vatandaslar, B.K., Denli, A.M., Ghosh, S.G., Xu, X., Yeo, G.W., Aimone, J.B. and Gage, F.H., “Motoneuron expression profiling identifies an association between an axonal splice variant of HDGF-related protein 3 and peripheral myelination.” Journal of Biological Chemistry,jbc-RA120. July 2020
  5. Chance FS, Aimone JB, Musuvathy SS, Smith MR, Vineyard CM, Wang F. “Crossing the Cleft: Communication Challenges Between Neuroscience and Artificial Intelligence.” Frontiers in Computational Neuroscience. 2020 May 6;14:39.
  6. Bennett CH, Dellana R, Xiao TP, Feinberg B, Agarwal S, Cardwell S, Marinella MJ, Severa W, Aimone B. “Evaluating complexity and resilience trade-offs in emerging memory inference machines”. 2020 Neuro-Inspired Computational Elements (NICE). arXiv preprint arXiv:2003.10396. 2020 Feb 25.
  7. Vineyard CR, Dellana R, Aimone JB, Rothganger F, and Severa WM – “Low-Power Deep Learning Inference using the SpiNNaker Neuromorphic PlatformProceedings of 7th Annual Neuro-Inspired Computational Elements Workshop 2019
  8. Aimone JB, Severa W, and Vineyard CM – “Composing Neural Algorithms with FuguProceedings of the 2019 International Conference on Neuromorphic Systems
  9. Aimone JB, Parekh O, Phillips C, Pinar A, Severa W, and Xu H – “Dynamic Programming with Spiking Neural ComputingProceedings of the 2019 International Conference on Neuromorphic Systems
  10. Aimone JB – " Neural algorithms and computing beyond Moore's law" –Communications of the ACM, 62 (4), April 2019
  11. Severa W, Vineyard CM, Dellana R, Verzi SJ, and Aimone JB – “Training Deep Neural Networks for Binary Communication with the Whetstone MethodNature Machine Intelligence, 1 (2), February 2019
  12. Severa, W., Lehoucq, R., Parekh, O. and Aimone, J.B., 2018. "Spiking Neural Algorithms for Markov Process Random Walk." IJCNN 2018
  13. Parekh, O., Phillips, C.A., James, C.D. and Aimone, J.B., 2018, July. "Constant-Depth and Subcubic-Size Threshold Circuits for Matrix Multiplication". In Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures (pp. 67-76). ACM.
  14. Verzi, S.J., Rothganger, F., Parekh, O.D., Quach, T.T., Miner, N.E., Vineyard, C.M., James, C.D. and Aimone, J.B., 2018. "Computing with spikes: The advantage of fine-grained timing. "Neural computation, 30(10), pp.2660-2690.
  15. Faust, A., Aimone, J.B., James, C.D. and Tapia, L., "Resilient Computing with Reinforcement Learning on a Dynamical System: Case Study in Sorting". arXiv preprint arXiv:1809.09261. 2018
  16. Bouchard, K.E., Aimone, J.B., Chun, M., Dean, T., Denker, M., Diesmann, M., Donofrio, D.D., Frank, L.M., Kasthuri, N., Koch, C. and Rübel, O., "International neuroscience initiatives through the lens of high-performance computing." Computer, 51(4), pp.50-59. 2018
  17. Wang, F., Quach, T.T., Wheeler, J., Aimone, J.B. and James, C.D., 2018. "Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classification". IEEE Transactions on Information Forensics and Security, 13(10), pp.2553-2562.
  18. Aimone JB, Parekh O, and Severa WM – “Neural Computing for HPC – More than Just Machine Learning?” – 2017 Neuromorphic Computing Architectures-Models-Applications Symposium
  19. Follett DR, Townsend DCM, Karpman GD, Naegle JH, Suppona RA, Aimone JB, and James CD – “Neuromorphic Data Microscope” – 2017 Neuromorphic Computing Architectures-Models-Applications Symposium
  20. Hill AJ, Donaldson JW, Rothganger F, Vineyard CM, Follett DR, Follett PL, Smith MR, Verzi SJ, Severa W, Wang F, Aimone JB, Naegle JH, and James CD – “A Spike-Timing Neuromorphic Architecture” – 2017 IEEE International Conference on Rebooting Computing
  21. Draelos TJ, Miner NE, Lamb CC, Vineyard CM, Carlson KD, James CD, and Aimone JB – “Neurogenesis Deep Learning”– IJCNN 2017 May 2017
  22. Smith M, Hill A, Carlson KD, Vineyard CM, Donaldson J, Follett DJ, Follett P, Naegle J, James CD, and Aimone JB – “A Novel Digital Neuromorphic Architecture Efficiently Facilitating Neural Networks with Complex Synaptic Response Functions” – Accepted to IJCNN 2017 May 2017
  23. Verzi SJ, Vineyard CM, Vugrin E, Galiardi M, James CD, Aimone JB – “Optimization-based Computation with Spiking Neurons” – Accepted to IJCNN 2017 May 2017
  24. James CD, Aimone JB, Miner NE, Vineyard CM, Rothganger FH, Carlson KD, Mulder SA, Draelos TJ, Faust A, Marinella MJ, Naegle JH, and Plimpton SJ – “A historical survey of algorithms and hardware architectures for neural-inspired and neuromorphic computing applicationsBiologically Inspired Cognitive Architectures, January 2017
  25. Bouchard KE, Aimone JB, Chun M, Dean T, Denker T, Diesmann M, Donofrio DD, Frank LM, Kasturi N, Koch C, Ruebel O, Simon HD, Sommer FT – “High-performance computing in Neuroscience for data-driven discovery, integration, and dissemination” Neuron November 2016 
  26. Severa W, Parekh O, James CD, and Aimone JB– “A Combinatorial Model for Dentate Gyrus Sparse Coding” – Neural Computation, October 2016
  27. Du H*, Deng W*, Aimone JB*, Ge M, Parylak S, Walch K, Cook J, Zhang W, Song H, Wang L, Gage FH, and Mu Y – “Dopaminergic Inputs in the Dentate Gyrus Direct the Choice of Memory Encoding”PNAS, September 2016
  28. Severa W, Parekh O, Carlson KD, James CD, and Aimone JB – “Spiking Network Algorithms for Scientific Computing” – Proceedings of the IEEE International Conference on Rebooting Computing October 2016
  29. Draelos TJ, Miner NE, Cox JA, Lamb CC, James CD, and Aimone JB – “Neurogenic Deep LearningProceedings of the International Conference on Learning Representations 2016
  30. 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
  31. 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
  32. Agarwal S, Quach T, Parekh OD, Hsia AH, Debenedictis EP, James CD, Marinella M, and Aimone JB“Energy Scaling Advantages of Resistive Memory Crossbar Based Computation and its Application to Sparse Coding” Frontiers in Neuromorphic Engineering. January 2016
  33. Cox JA, James CD, and Aimone JB“A Signal Processing Approach for Cyber Data Classification with Deep Neural Networks” Complex Adaptive Systems - Procedia Computer Science. 61, November 2015
  34. Vineyard CM, Verzi SJ, James CD, Aimone JB, and Heileman GL – “MapReduce SVM Game” INNS Conference on Big Data - Procedia Computer Science. 53, August 2015
  35. Vineyard CM, Verzi SJ, James CD, Aimone JB, and Heileman GL – “Repeated Play of the SVM Game as a Means of Adaptive Classification” Proceedings of International Joint Conference on Neural Networks July 2015
  36. PhysRev_CoverRothganger F, Evans BR, Aimone JB, and DeBenedictis EP – “Training neural hardware with noisy components” Proceedings of International Joint Conference on Neural Networks July 2015
  37. Aimone JB, Li Y, Lee SW, Clemenson GD, Deng W, and Gage FH – “Regulation and Function of Adult Neurogenesis: from Genes to Cognition” Physiological Reviews October 2014 (Cover Article)
  38. 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
  39. Rangel LM, Alexander AS, Aimone JB, Wiles J, Gage FH, Chiba AA, and Quinn LK – “Temporally selective contextual encoding in the dentate gyrus of the hippocampus” Nature Communications.  January 2014
  40. Aimone JB and Weick J – “Perspectives for computational modeling of cell replacement for neurological disorders” Frontiers in Computational Neuroscience. October 2013
  41. Rangel LM, Quinn L, Chiba AA, Gage FH and Aimone JB -“A Hypothesis for Temporal Coding of Young and Mature Granule Cells” Frontiers in Neurogenesis. 7(75), May 2013
  42. Li Y, Stam FJ, Aimone JB, Goulding M, Callaway EM, and Gage FH – “Molecular layer perforant path-associated cells contribute to feed-forward inhibition in the adult dentate gyrus” PNAS. 110(22), May 2013
  43. Li Y*, Aimone JB*, Xu X, Callaway EM, and Gage FH – “Development of GABAergic inputs controls the contribution of maturing neurons to the adult hippocampal network” PNAS. 109(11), March 2012.
  44. Aimone JB, Deng W, and Gage FH – “Resolving New Memories: A Critical Look at the Dentate Gyrus, Adult Neurogenesis, and Pattern Separation” Neuron. 70(4), May 2011.
  45. Aimone JB and Gage FH – “Modeling new neuron function: a history of using computational neuroscience to study adult neurogenesis” European Journal of Neuroscience. 33(6), March 2011.
  46. Aimone JB, Deng W, and Gage FH – “Put Them Out to Pasture?  What Are Old Granule Cells Good for, Anyway…?” Hippocampus. 20(10), October 2010.
  47. Aimone JB*, Deng W*, and Gage FH – “Adult neurogenesis: integrating theories and separating functions” Featured Review for Trends in Cognitive Sciences. 14(7), July 2010 (Cover Article).TICS_cover
  48. Deng W*, Aimone JB*, and Gage FH – “New neurons and new memories: How does adult hippocampal neurogenesis affect learning and memory?” Nature Reviews Neuroscience. 11(5), May 2010.
  49. Aimone JB, Wiles J, and Gage FH – “Computational Influence of Adult Neurogenesis on Memory Encoding” Neuron, 61(2), January 2009.  (Faculty of 1000 Biology)
  50. Smrt RD, Eaves-Egenes J, Barkho BZ, Santistevan NJ, Zhao C, Aimone JB, Gage FH, and Zhao X - “Mecp2 deficiency leads to delayed maturation and altered gene expression in hippocampal neurons” Neurobiology of Disease, 27(1), April 2007.
  51. Toni N, Teng EM, Bushong EA, Aimone JB, Zhao C, van Pragg H, Martone ME, Ellisman MH, and Gage FH – “Synapse formation on neurons born in the adult hippocampus.” Nature Neuroscience. 10(6), June 2007.  (Faculty of 1000 Biology)
  52. Aimone JB, Wiles J, and Gage FH - “Potential Role for Adult Neurogenesis in the Encoding of Time in New Memories.” Nature Neuroscience, 9(6), June 2006. (Faculty of 1000 Biology)
  53. Barkho BZ, Song H, Aimone JB, Smrt RD, Kuwabara T, Nakashima K, Gage FH, and Zhao X - “Identification of astrocyte-expressed factors that modulate neural stem/progenitor cell differentiation.” Stem Cell and Development, 15(3), June 2006.
  54. Myers CP, Lewcock JW, Hanson MG, Gosgnach S, Aimone JB, Gage FH, Lee KF, Landmesser LT, and Pfaff SL – “Cholinergic Input is Required during Embryonic Development to Mediate Proper Assemby of Spinal Locomotor Circuits.” Neuron, 46(1), April 2005.
  55. Aimone JB*, Leasure JL*, Perreau VM*, Thallmair M* and the Christopher Reeve Paralysis Foundation – “Spatial and Temporal Gene Expression Profiling of the Contused Rat Spinal Cord” Experimental Neurology, 189(2), October 2004 (Cover Article).ExpNeuro_Cover
  56. Aimone JB and Gage FH,– “Unbiased Characterization of High-densisty Oligonucleotide Microarrays Using Probe-Level Statistics” Journal of Neuroscience Methods, 135(1-2), May 2004.
  57. Hsieh J, Aimone JB, Kaspar BK, Kuwabara T, Nakashima K and Gage FH– “IGF-1 Instructs Multipotent Adult Stem Cells to Become Oligodendrocytes” Journal of Cell Biology, 164(1). January 2004.
  58. Coffer JL, Montchamp JL, Aimone JB, and Weis RP – “Routes to Calcified Porous Silicon: Implications for Drug Delivery and Biosensing” Physica. Status. Solidi. (a) 197, No.2.  2003.