The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Cognitive computing building block: A versatile and efficient digital neuron model for neurosynaptic cores
Abstract
Marching along the DARPA SyNAPSE roadmap, IBM unveils a trilogy of innovations towards the TrueNorth cognitive computing system inspired by the brain's function and efficiency. Judiciously balancing the dual objectives of functional capability and implementation/operational cost, we develop a simple, digital, reconfigurable, versatile spiking neuron model that supports one-to-one equivalence between hardware and simulation and is implementable using only 1272 ASIC gates. Starting with the classic leaky integrate-and-fire neuron, we add: (a) configurable and reproducible stochasticity to the input, the state, and the output; (b) four leak modes that bias the internal state dynamics; (c) deterministic and stochastic thresholds; and (d) six reset modes for rich finite-state behavior. The model supports a wide variety of computational functions and neural codes. We capture 50+ neuron behaviors in a library for hierarchical composition of complex computations and behaviors. Although designed with cognitive algorithms and applications in mind, serendipitously, the neuron model can qualitatively replicate the 20 biologically-relevant behaviors of a dynamical neuron model.
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Cites
A logical calculus of the ideas immanent in nervous activity
McCulloch, W. S., & Pitts, W. (1943) · The Bulletin of Mathematical Biophysics · doi:10.1007/bf02478259 · Cited by 18,566
The perceptron: A probabilistic model for information storage and organization in the brain.
Rosenblatt, F. (1958) · Psychological Review · doi:10.1037/h0042519 · Cited by 12,280
Voltage oscillations in the barnacle giant muscle fiber
Morris, C., & Lecar, H. (1981) · Biophysical Journal · doi:10.1016/s0006-3495(81)84782-0 · Cited by 2,302
Network architecture of the long-distance pathways in the macaque brain
Modha, D. S., & Singh, R. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1008054107 · Cited by 283
Self-citation
Cited by
Rueckauer, B., Lungu, I.-A., Hu, Y., Pfeiffer, M., & Liu, S.-C. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00682 · Cited by 1,072
A Low Power, Fully Event-Based Gesture Recognition System
Amir, A., Taba, B., Berg, D., Melano, T., McKinstry, J., Di Nolfo, C., Nayak, T., Andreopoulos, A., Garreau, G., Mendoza, M., et al. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.781 · Cited by 1,017
Self-citationLarge-scale neuromorphic computing systems
Furber, S. (2016) · Journal of Neural Engineering · doi:10.1088/1741-2560/13/5/051001 · Cited by 567
Neuromorphic Electronic Circuits for Building Autonomous Cognitive Systems
Chicca, E., Stefanini, F., Bartolozzi, C., & Indiveri, G. (2014) · Proceedings of the IEEE · doi:10.1109/jproc.2014.2313954 · Cited by 552
Silicon Photonic Modulator Neuron
Tait, A. N., Ferreira de Lima, T., Nahmias, M. A., Miller, H. B., Peng, H.-T., Shastri, B. J., & Prucnal, P. R. (2019) · Physical Review Applied · doi:10.1103/physrevapplied.11.064043 · Cited by 331
Metadata
- Authors
- Cassidy, A. S., Merolla, P., Arthur, J. V., Esser, S. K., Jackson, B., Alvarez-Icaza, R., Datta, P., Sawada, J., Wong, T. M., Feldman, V., Amir, A., Rubin, D. B.-D., Akopyan, F., McQuinn, E., Risk, W. P., & Modha, D. S.
- Venue
- The 2013 International Joint Conference on Neural Networks (IJCNN)
- Publisher
- IEEE
- Published
- 2013-08
- Pages
- 1-10
- ISSN
- 2161-4407 (ISSN-L)
- OpenAlex
- W2060956313
- Cited by
- 237
- References
- 4
- FWCI
- 25.23
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Cassidy, A. S., Merolla, P., Arthur, J. V., Esser, S. K., Jackson, B., Alvarez-Icaza, R., Datta, P., Sawada, J., Wong, T. M., Feldman, V., Amir, A., Rubin, D. B.-D., Akopyan, F., McQuinn, E., Risk, W. P., & Modha, D. S. (2013). Cognitive computing building block: A versatile and efficient digital neuron model for neurosynaptic cores. The 2013 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/ijcnn.2013.6707077
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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