The week's pick
Random Articles
Reseach Article
Information Processing in Brain Modeling: Challenges and Opportunities
| International Conference on Advances in Computer Engineering and Applications |
| Foundation of Computer Science USA |
| ICACEA - Number 6 |
| April 2014 |
| Authors: Aakanksha Tyagi, Sanjeev Kumar, Anu Yadav |
| 649c2c44-b21c-4192-b189-d3726c60c5a5 |
Aakanksha Tyagi, Sanjeev Kumar, Anu Yadav . Information Processing in Brain Modeling: Challenges and Opportunities. International Conference on Advances in Computer Engineering and Applications. ICACEA, 6 (April 2014), 27-31.
Abstract
Computational Neuroscience deals with the study of information dynamics inside brain. Neuron as unit of the brain is modeled through different assumptions by researchers. Challenges of neuronal modeling and analysis are discussed; a mathematical framework of information theory is presented in context of characterizing neuronal behavior.
References
- Dayan P and Abbott L. F "Theoretical Neuroscience-computational and Mathematical Modeling of neural system" MIT press, 2001.
- Koch C. , "Biophysics of Computation" oxford: Oxford university press, 1999.
- Hemmen J. Leovan and Sejnowski Terrence J "23 problems in Systems Neuroscience", Oxford university press, 2006.
- Shepherd G. M. , "The Synaptic Organization of the Brain", New York: Oxford university press, 1990.
- Becker S. , "Modelling the mind: From circuits to systems" Chapter 2 in "New Directions in Statistical Signal Processing: From Systems to brain", Haykin S. et. al. MIT Press, 2005.
- Deco G. et al. , "Stochastic dynamics as a principle of brain function", Progress in Neurobiology, 88, 2009.
- Deco G. , Schürmann B. , "Information dynamics: foundations and applications", Springer-Verlag, 2001.
- Deco G. and Schürmann B. , "Information Transmission and Temporal Code in Central Spiking Neurons", Phys. Rev. Lett. 79, 4697–4700, 1997.
- Gardiner C. W. , "Handbook of stochastic methods", 2ed. Springer, 1997.
- Karmeshu (Ed. ), "Entropy measures, maximum entropy principle and emerging applications", Springer-Verlag, 2003.
- Koch C , Gabbiani F. , "Principles of spike train analysis", Methods in neuronal modeling, MIT Press, 1998.
- Koch C et. al, "Feature extraction by burst-like spike patterns in multiple sensory maps", The Journal of Neuroscience, 1998.
- Shanon C. E. , "A Mathematical Theory of Communication", Bell System Technical Journal, Vol. 27, October, 1948.
- Sejnowski T J, Koch C and Churchland P S, "Computational Neuroscience", Science, New Series, Vol. 241, No. 4871, 1299-1306 (1988).
- Salinas E and Sejnowski T J, "Integrate-and-Fire Neuron driven by Correlated Stochastic input", Neural Computation, Vol. 14, 2111-2155, 2002.
Index Terms
Keywords