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Comparing the Information Encoded by Different Brain Areas with Functional Imaging Techniques

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2415))

Abstract

We study the suitability of estimating the information conveyed by the responses of the populations of neurons in the brain by using the signal provided by imaging techniques like functional Magnetic Resonance Imaging (fMRI). The fMRI signal is likely to reflect a spatial averaging of the neuronal population activity. On the other hand, knowledge of the activity of each single neuron is needed in order to calculate the information. We explore this potential limitation by means of a simple computational model based on known tuning properties of individual neurons. We investigate the relationship between the information transmitted by the population, the signal change and the signal information as a function of the neuronal parameters. We find that the relationship is in general very different from linear. This result should be taken into account when comparing the information encoded by different brain areas with functional imaging techniques.

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References

  1. N. Brunel and J.-P. Nadal, Mutual information, Fisher information and population coding. Neural Computation 10 (1998) 1731–1757.

    Article  Google Scholar 

  2. T. Cover and J. Thomas, Elements of information theory (1991). John Wiley.

    Google Scholar 

  3. K.J. Friston, A. Mechelli, R. Turner and C.J. Price, Nonlinear responses in fMRI: Balloon models, Volterra kernels and other hemodynamics. Neuroimage 12 (2000) 466–477.

    Article  Google Scholar 

  4. D.J. Heeger, A.C. Huck, W.S. Geisler and D.G. Albrecht, Spikes versus BOLD: what does neuroimaging tell us about neuronal activity? Nature Neuroscience 3 (2000) 631–633

    Article  Google Scholar 

  5. N.K. Logothetis, J. Pauls, M. Augath, T. Trinath and A. Oeltermann, Neurophysiological investigation of the basis of the fMRI signal, Nature 412 (2001) 150–157

    Article  Google Scholar 

  6. A. Nevado, M. P. Young and S. Panzeri, Functional imaging and information processing. Neurocomputing, in press.

    Google Scholar 

  7. G. Rees, K. Friston and C. Koch, A direct quantitative relationship between the functional properties of human and macaque V5. Nature Neuroscience 3 (2000) 716–723

    Article  Google Scholar 

  8. J.W. Scannell and M.P. Young, Neuronal population activity and functional imaging, Proc. R. Soc. B 266 (1999) 875–881

    Article  Google Scholar 

  9. B.A. Wandell, Computational neuroimaging of human visual cortex. Ann. Rev. Neurosci. 22 (1999) 145–173.

    Article  Google Scholar 

  10. K. Zhang and T.J. Sejnowski, Neuronal tuning: to sharpen or to broaden? Neural Computation 11 (1999) 75–84.

    Article  Google Scholar 

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© 2002 Springer-Verlag Berlin Heidelberg

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Nevado, A., Young, M.P., Panzeri, S. (2002). Comparing the Information Encoded by Different Brain Areas with Functional Imaging Techniques. In: Dorronsoro, J.R. (eds) Artificial Neural Networks — ICANN 2002. ICANN 2002. Lecture Notes in Computer Science, vol 2415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46084-5_18

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  • DOI: https://doi.org/10.1007/3-540-46084-5_18

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44074-1

  • Online ISBN: 978-3-540-46084-8

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