Skip to main content
Log in

Mihalas–Niebur model implementation using Sinh-Domain integrators

  • Mixed Signal Letter
  • Published:
Analog Integrated Circuits and Signal Processing Aims and scope Submit manuscript

Abstract

A realization of the Mihalas–Niebur neuron model using the concept of the Sinh-Domain filtering is introduced in this Letter. This is achieved through the utilization of Sinh-Domain lossy integrator stages which offer the benefits of electronic tuning of the realized time-constants, while the inherent class-AB nature allows the handling of signals with amplitude greater than the dc bias current. The behavior of the proposed model for various patterns of stimuli is evaluated through the Analog Design Environment of the Cadence software and MOS transistor models provided by the AMS C35 0.35 µm process.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

References

  1. Hodgkin, A. L., & Huxley, A. F. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. The Journal of Physiology, 117(4), 500–544.

    Article  Google Scholar 

  2. Izhikevich, E. M. (2003). Simple model of spiking neurons. IEEE Transactions on Neural Networks, 14(6), 1569–1572.

    Article  MathSciNet  Google Scholar 

  3. Mihalas, S., & Niebur, N. (2009). A generalized linear integrate-and-fire neural model produces diverse spiking behaviors. Neural Computation, 21(3), 704–718.

    Article  MathSciNet  MATH  Google Scholar 

  4. Folowosele, F., Hamilton, T. J., Harrison, A., Mihalas, S., Niebur, E., Cassidy, A., Andreou, A., & Etienne-Cummings, R. (2009). A switched-capacitor implementation of the generalized linear integrate-and-fire neuron. In Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS). Taipei, Taiwan, pp. 2149–2152.

  5. Folowosele, F., Etienne-Cummings, R., & Hamilton, T. J. (2009). A switched-capacitor implementation of the Mihalas–Niebur neuron. In Proceedings of the IEEE Biomedical Circuits and Systems Conference (BioCAS). Beijing, China, pp. 105–108.

  6. Folowosele, F., Hamilton, T. J., & Etienne-Cummings, R. (2011). Silicon modeling of the Mihalas–Niebur neuron. IEEE Transactions on Neural Networks, 22(12), 1915–1927.

    Article  Google Scholar 

  7. van Schaik, A., Jin, C., Mc Ewan, A., Hamilton, T.J., Mihalas, S., & Niebur, E. (2010). A log-domain implementation of the Mihalas–Niebur neuron model. In Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS). Paris, Grance, pp. 4253–4256.

  8. Tsirimokou, G., Laoudias, C., & Psychalinos, C. (2013). Tinnitus detector realization using Sinh-Domain circuits. Journal of Low Power Electronics, 9(4), 458–470.

    Article  Google Scholar 

  9. Kafe, F., & Psychalinos, C. (2014). Realization of companding filters with large time-constants for biomedical applications. Analog Integrated Circuits and Signal Processing, 78(1), 217–231.

    Article  Google Scholar 

  10. Lin, H., Huang, J. H., & Wong, S. C. (2000). A simple high-speed low current comparator. In IEEE International Symposium on Circuits and Systems (ISCAS). Geneva, Switzerland, pp. 713–716.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Costas Psychalinos.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Diamantopoulos, C., Psychalinos, C. Mihalas–Niebur model implementation using Sinh-Domain integrators. Analog Integr Circ Sig Process 88, 161–171 (2016). https://doi.org/10.1007/s10470-016-0751-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10470-016-0751-z

Keywords

Navigation