Abstract
The shape of action potentials plays an important role in synaptic integration. Action potentials of different shapes shunt excitatory potentials differentially and consequently correspond to different probabilities of generating the next spike. Thus two neurons producing different spikes shapes, say Purkinje and pyramidal cells, integrate differently the same excitatory potentials. More interestingly, there is variability in the spike shape of a single neuron when stimulated dynamically, that can then also dynamically affect the synaptic integration. Our recent experiments have shown that this variability in the spike shape is not random but depends on stimulus history. Here we analyze a simple model of cortical neuron to understand the origin of this encoding of stimulus history into spike shape. We find that slow conductances, for example calcium conductances, can be responsible for this rich encoding.
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References
Koch, C.: Biophysics of computation. Oxford Univ. Press, New York (1999)
Häusser, M., Major, G., Stuart, G.J.: Differential shunting of EPSPs by action potentials. Science 291, 138–141 (2001)
de Polavieja, G.G., Harsch, A., Kleppe, I., Robinson, H.P., Juusola, M.: Stimulus history reliably shapes action potential waveforms of cortical neurons (to appear)
Robinson, H.P.C.: Kinetics of synaptic conductances. Neurosci. Res. 16, S6 (1991)
Robinson, H.P.C., Kawai, N.: Injection of digitally synthesized synaptic conductance transients to measure the integrative properties of neurons. J. Neurosci. Methods 49, 157–165 (1993)
Sharp, A.A., O’Neil, M.B., Abbott, L.F., Marder, E.: Dynamic clamp-computer generated conductances in real neurons. J. Neurophysiol. 69, 992–995 (1993)
Wilson, H.R.: Simplified dynamics of human and mammalian neocortical neurons. J. Theor. Biol. 200, 375–388 (1999)
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© 2005 Springer-Verlag Berlin Heidelberg
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de Polavieja, G.G., Harsch, A., Robinson, H., Juusola, M. (2005). Slow Conductances Encode Stimulus History into Spike Shapes. In: Mira, J., Álvarez, J.R. (eds) Mechanisms, Symbols, and Models Underlying Cognition. IWINAC 2005. Lecture Notes in Computer Science, vol 3561. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11499220_16
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DOI: https://doi.org/10.1007/11499220_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26298-5
Online ISBN: 978-3-540-31672-5
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