Skip to main content

Advertisement

Log in

Teaching computational neuroscience

  • Review Paper
  • Published:
Cognitive Neurodynamics Aims and scope Submit manuscript

Abstract

The problems and beauty of teaching computational neuroscience are discussed by reviewing three new textbooks.

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.

Similar content being viewed by others

References

  • Izhikevich E (2007) Dynamical systems in neuroscience. MIT press, Cambridge

    Google Scholar 

  • Anderson B (2014) Computational neuroscience and cognitive modelling. A student’s introduction to methods and procedures. Sage Publ. Ltd, Beverley Hills

    Book  Google Scholar 

  • Arbib M (2002) The handbook of brain theory and neural networks. MIT Press, Cambridge

    Google Scholar 

  • Bower J (2013) 20 Years of computational neuroscience. Springer, Verlag

    Book  Google Scholar 

  • Dayan P, Abbott L (2001) Theoretical neuroscience. MIT Press, Cambridge

    Google Scholar 

  • Ermentrout G, Terman T (2010) Mathematical foundations of neuroscience. Springer, Berlin

    Book  Google Scholar 

  • Gerstein GL, Mandelbrot B (1964) random walk models for the spike activity of a single neuron. Biophys J 4(1):41–68

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Gerstner W, Kistler W, Naud R, Paninski L (2014) Neuronal dynamics—from single neurons to networks and models of cognition. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Grossberg S (1980) How does a brain build a cognitive code? Psychol Rev 87:1–51

    Article  CAS  PubMed  Google Scholar 

  • Hirsch M (1989) Convergent activation dynamics in continuous time networks. Neural Netw 2:331349

    Article  Google Scholar 

  • Hopfield JJ (1982) Neural networks and physical systems with emergent collective computational properties. Proc Nat Acad Sci (USA) 79:2554–2558

    Article  CAS  Google Scholar 

  • Hopfield JJ (1984) Neurons with graded response have collective computational properties like those of two-sate neurons. Proc Natl Acad Sci (USA) 81:3088–3092

    Article  CAS  Google Scholar 

  • Levy W, Steward O (1983) Temporal contiguity requirements for long-term associative potentiation/depression in the hippocampus. Neuroscience 8:791–797

    Article  CAS  PubMed  Google Scholar 

  • Mallot H (2013) Computational neuroscience. A first course. Springer, Berlin

    Book  Google Scholar 

  • Schwartz E (ed) (1990) Computational neuroscience. MIT Press, Cambridge

    Google Scholar 

  • Trappenberg T (2010) Fundamentals of computational neuroscience. Oxford Univ. Press, Oxford

    Google Scholar 

  • Tsuda I (1992) Dynamic link of memorychaotic memory map in nonequilibrium neural networks. Neural Netw 5:313–326

    Article  Google Scholar 

Download references

Acknowledgments

Thanks for my numerous teaching assistants over the years. I had many conversation with them about the method of teaching of this discipline. I also thank to the Henry Luce Foundation to let me to serve as a Henry R Luce Professor. Thank you for Brian Dalluge (who is now in my Computational Neuroscience class) for copy editing the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Péter Érdi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Érdi, P. Teaching computational neuroscience. Cogn Neurodyn 9, 479–485 (2015). https://doi.org/10.1007/s11571-015-9340-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11571-015-9340-6

Keywords

Mathematics Subject Classification

Navigation