Abstract
According to the experimental result of signal transmission with energetic demand tightly coupled to the information coding in cerebral cortex and electric structural property in neuronal activities, we present a brand-new scientific theory with mechanism of brain information processing. According to the new theory, we discover that neural coding under action of stimulation in brain is complete with way of energy coding. Due to energy coding to be able to reveal mechanism of brain information processing in physical essence, we can not only finely reappear various experimental results of neuro-electrophysiology, but also quantitatively explain the experimental results from neuroscientists at Yale University in recently by means of the principle of energy coding.
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References
Levy, W.B., Baxter, R.A.: Energy Efficient Neural Codes. Neural Comp. 8, 531–543 (1996)
Levy, W.B., Baxter, R.A.: Energy-Efficient Neuronal Computational via Quantal Synaptic Failures. The Journal of Neuroscience 22, 4746–4755 (2002)
Laughlin, S.B., Sejnowski, T.J.: Communication in Neuronal Networks. Science 301, 1870–1874 (2003)
Quiroga, R.Q., Reddy, L., Kreiman, G., Koch, C., Fried, I.: Invariant Visual Representation by Single Neurons in the Human Brain. Nature 435, 1102–1107 (2005)
Stein, R.B., Gossen, E.R., Jones, K.E.: Neuronal Variability: Noise or Part of the Signal? Nature Reviews Neuroscience 6, 389–397 (2005)
Wang, R.-B., Zhang, Z.-K.: Nonlinear Stochastic Models of Neurons Activities. Neurocomputing 51C, 401–411 (2003)
Wang, R.-B., Jiao, X.-F.: A Stochastic Nonlinear Evolution Model and Neural Coding on Neuronal Population Possessing Variable Coupling Intensity in Spontaneous Behavior. Neurocomputing 69, 778–785 (2006)
Jiao, X.-F., Wang, R.-B.: Nonlinear Dynamic Model and Neural Coding of Neuronal Network with the Variable Coupling Strength in the Presence of External Stimuli. Applied Physics Letters 87, 083901 (2005)
Arbib, M.A.: The Handbook of Brain Theory and Neural Networks. The MIT Press, Cambridge (2002)
Wilson, R.A., Keil, F.C.: The MIT Encyclopedia of the Cognitive Sciences. The MIT Press, Cambridge (1999)
Freeman, W.J.: Neurodynamics. Springer, Berlin (2000)
Nicholls, J.G., Martin, A.R., Wallace, B.G.: From Neuron to Brain, 3rd edn. Sinauer, Sunderland (2000)
Wang, R.-B., Hayashi, H., Zhang, Z.-K.: An Exploration of Dynamics on Moving Mechanism of the Growth Cone. Molecules 8, 127–138 (2003)
Schwartz, W.J., et al.: Metabolic Mapping of Functional Activity in the Hypothalamo -Neurohypophysial System of the Rat. Science 205, 723–725 (1979)
Mata, M., et al.: Activity-Dependent Energy Metab-Olism in Rat Posterior Pituitary Primarily Reflects Sodium Pump Activity. J. Neurochem. 34, 213–215 (1980)
Haken, H.: Principles of Brain Functioning. Springer, Berlin (1996)
Koch, C., Segev, I.: Methods in Neuronal Modeling. The MIT Press, Cambridge (1998)
Wang, R.-B., Zhang, Z.-K.: On Energy Principle of Couple Neuron Activities. Acta Biophysica Sinica 21, 436–442 (2005)
Wang, R.-B., Zhang, Z.-K.: Preparing for submission (2006)
Wang, R.-B.: Some Advances in Nonlinear Stochastic Evolution Models of Neuron Population. In: Proceedings 5th International Conference of Stochastic Structural Dynamics. ICSSD, pp. 453–461. CRC Press, Boca Raton (2003)
Zhu, W.-Q.: Nonlinear Stochastic Dynamics and Control. Science Press, Beijing (2003)
Purushothman, G., Bradley, D.C.: Neural Population Code for Fine Perceptual Decisions in Area MT. Nature Neuroscience 8, 99–106 (2005)
Mayhew, J.E.W.: A Measured Look at Neuronal Oxygen Consumption. Science 299, 1023–1024 (2003)
Crotty, P., Levy, W.B.: Energy-Efficient Interspike Interval Codes. Neurocomputing 65, 371–378 (2005)
Taylor, J.G.: Paying Attention to Consciousness. Progress in Neurobiology 71, 305–335 (2003)
Raichle, M.E., Gusnard, D.A.: Appraising the Brain’s Energy Budget. Proc. Natl. Acad. Sci. PNAS USA 99, 10237–10239 (2002)
Hyder, F., Rothman, D.L., Shulman, R.G.: Total Neuroenergetics Support Localized Brain Activity: Implications for the Interpretation of fMRI. Proc. Natl. Acad. Sci. PNAS USA 99, 10771–10776 (2002)
Smith, A.J., et al.: Cerebral Energetics and Spiking Frequency: The Neurophysiological Basis of fMRI. Proc. Natl. Acad. Sci. PNAS USA 99, 10765–10770 (2002)
Jiao, X.-F., Wang, R.-B.: Synchronization in Neuronal Population with the Variable Coupling Strength in the Presence of External Stimulus. Applied Physics Letters (2006) (in press)
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Wang, R., Zhang, Z. (2006). A New Mechanism on Brain Information Processing—Energy Coding. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4232. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893028_35
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DOI: https://doi.org/10.1007/11893028_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46479-2
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