FPGA-based biophysically-meaningful modeling of olivocerebellar neurons

ACM/SIGDA International Symposium on Field Programmable Gate Arrays - FPGA

Volumn , Issue , 2014, Pages 89-98

  Smaragdos, Georgios ^a   Isaza, Sebastian ^b   Van Eijk, Martijn ^c   Sourdis, Ioannis ^d   Strydis, Christos ^a  

^a ERASMUS MEDICAL CENTER   (Netherlands)

^b UNIVERSIDAD DE ANTIOQUIA   (Colombia)

^c Delft University of Technology   (Netherlands)

^d CHALMERS UNIVERSITY OF TECHNOLOGY   (Sweden)

Author keywords

Cerebellum; Computational Neuroscience; Hodgkin Huxley; Inferior Olive; Spiking Neural Networks

Indexed keywords

COMPUTER SIMULATION; IONS; MATLAB; NEURAL NETWORKS; NEUROLOGY; NEURONS;

CEREBELLUM; COMPUTATIONAL NEUROSCIENCE; HODGKIN HUXLEY; INFERIOR OLIVE; SPIKING NEURAL NETWORKS;

FIELD PROGRAMMABLE GATE ARRAYS (FPGA);

EID: 84898957720     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2554688.2554790     Document Type: Conference Paper

References (20)

1. P. Bazzigaluppi, J. R. De Gruijl, R. S. Van Der Giessen, S. Khosrovani, C. I. De Zeeuw, and M. T. G. De Jeu. Olivary subthreshold oscillations and burst activity revisited. Frontiers in Neural Circuits, 6(91), 2012.
2. M. Beuler, A. Tchaptchet, W. Bonath, S. Postnova, and H. A. Braun. Real-Time Simulations of Synchronization in a Conductance-Based Neuronal Network with a Digital FPGA Hardware-Core. In Artificial Neural Networks and Machine Learning-ICANN 2012, September 2012.
3. D. Bruderle. PyNN and the FACETS Hardware. www.neuralensemble.org/media/ slides/CodeJam2-Bruederle-FacetsHardware.pdf, [Online; accessed 18-December-2013] 2008.
4. K. Cheung, S. R. Schultz, and P. H. W. Leong. A Parallel Spiking Neural Network Simulator. In Int. Conf. on FPT, pages 47-254, Dec. 2009.
5. K. Cheung, S. R. Schultz, and W. Luk. A large-scale spiking neural network accelerator for FPGA systems. In Int. conf. on Artificial Neural Networks and Machine Learning, ICANN'12, pages 113-120, 2012.
6. C.I. De Zeeuw, F.E. Hoebeek , L.W.J. Bosman, M. Schonewille, L. Witter, and S.K. Koekkoek. Spatiotemporal firing patterns in the cerebellum. Nat Rev Neurosci, 12(6):327-344, jun 2011.
7. H. de Garis, M. Korkin, and G. Fehr. The CAM-Brain Machine CBM: An FPGA Based Tool for Evolving a 75 Million Neuron Artificial Brain to Control a Lifesized Kitten Robot. Auton. Robots, 10(3):235-249, May 2001.
8. H. Du Nguyen. GPU-based simulation of brain neuron models. Master's thesis, Delft Technical University, Aug. 2013.
9. G. Ermentrout and N. Kopell. Parabolic Bursting in an Excitable System Coupled With a Slow Oscillation. SIAM J on Applied Mathematics, 46:233-253, 1986.
10. G. B. Ermentrout. Type I membranes, phase resetting curves, and synchrony. Neural Computation, 83:979-1001, 1996.
11. A. L. Hodgkin and A. F. Huxley. Quantitative description of membrane current and application to conduction and excitation in nerve. Journal Physiology, 117:500-544, 1954.
12. E. Izhikevich. Simple Model of Spiking Neurons. IEEE Trans. on Neural Networks, 14(6), 2003.
13. E. Izhikevich. Which Model to Use for Cortical Spiking Neurons? IEEE Trans on Neural Net., 15(5), 2004.
14. W. Maass. Noisy Spiking Neurons with Temporal Coding have more Computational Power than Sigmoidal Neurons. In Neural Information Processing Systems, pages 211-217, 1996.
15. S. W. Moore, P. J. Fox, S. J. Marsh, A. T. Markettos, and A. Mujumdar. Bluehive-A Field-Programable Custom Computing Machine for Extreme-Scale Real-Time Neural Network Simulation. In IEEE Int. Symp. on FCCM, pages 133-140, 2012.
16. National Academy of Engineering (nae.edu). Grand Challenges for Engineering, 2010.
17. H. Shayani, P. Bentley, and A. M. Tyrrell. A Cellular Structure for Online Routing of Digital Spiking Neuron Axons and Dendrites on FPGAs. In ICES '08, Int. Conf. on Evolvable Systems: From Biology to Hardware, pages 273-284, 2008.
18. H. Shayani, P. Bentley, and A. M. Tyrrell. Hardware Implementation of a Bio-plausible Neuron Model for Evolution and Growth of Spiking Neural Networks on FPGA. In NASA/ESA Conf. on Adaptive Hardware and Systems, pages 236-243, June 2008.
19. G. Wulfram and W. Werner. Spiking Neuron Models. Cambridge University Press, 2002.
20. Y. Zhang, J. P. McGeehan, E. M. Regan, S. Kelly, and J. L. Nunez-Yanez. Biophysically Accurate Floating Point Neuroprocessors for Reconfigurable Logic. IEEE Trans on Computers, 62(3):599-608, march 2013.