Abstract
The striatum is the input nucleus of the basal ganglia and is thought to be involved in reinforcement learning. The striatum receives glutamate input from the cortex, which carries sensory information, and dopamine input from the substantia nigra, which carries reward information. Dopamine-dependent plasticity of cortico-striatal synapses is supposed to play a critical role in reinforcement learning. Recently, a number of labs reported contradictory results of its dependence on the timing of cortical inputs and spike output. To clarify the mechanisms behind spike timing-dependent plasticity of striatal synapses, we investigated spike timing-dependence of intracellular calcium concentration by constructing a striatal neuron model with realistic morphology. Our simulation predicted that the calcium transient will be maximal when cortical spike input and dopamine input precede the postsynaptic spike. The gain of the calcium transient is enhanced during the “up-state” of striatal cells and depends critically on NMDA receptor currents.
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References
Reynolds, J., Wickens, J.: Dopamine-dependent plasticity of corticostriatal synapses. Neural Netw. 15(4-6), 507–521 (2002)
Nakano, T., Doi, T., Yoshimoto, J., Doya, K.: A kinetic model of dopamine and calcium dependent striatal synaptic plasticity (submitted, 2009)
Pawlak, V., Kerr, J.N.D.: Dopamine receptor activation is required for corticostriatal spike-timing-dependent plasticity. J. Neurosci. 28(10), 2435–2446 (2008)
Fino, E., Glowinski, J., Venance, L.: Bidirectional activity-dependent plasticity at corticostriatal synapses. J. Neurosci. 25(49), 11279–11287 (2005)
Lisman, J.: A mechanism for the hebb and the anti-hebb processes underlying learning and memory. Proc. Natl. Acad. Sci. USA 86(23), 9574–9578 (1989)
Artola, A., Singer, W.: Long-term depression of excitatory synaptic transmission and its relationship to long-term potentiation. Trends in Neurosciences 16(11), 480–487 (1993)
Hansel, C., Artola, A., Singer, W.: Relation between dendritic ca2+ levels and the polarity of synaptic long-term modifications in rat visual cortex neurons. Eur. J. Neurosci. 9(11), 2309–2322 (1997)
Zucker, R.S.: Calcium- and activity-dependent synaptic plasticity. Current Opinion in Neurobiology 9(3), 305–313 (1999)
Gong, S., Zheng, C., Doughty, M.L., Losos, K., Didkovsky, N., Schambra, U.B., Nowak, N.J., Joyner, A., Leblanc, G., Hatten, M.E., Heintz, N.: A gene expression atlas of the central nervous system based on bacterial artificial chromosomes. Nature 425(6961), 917–925 (2003)
Wolf, J.A., Moyer, J.T., Lazarewicz, M.T., Contreras, D., Benoit-Marand, M., O’Donnell, P., Finkel, L.H.: NMDA/AMPA ratio impacts state transitions and entrainment to oscillations in a computational model of the nucleus accumbens medium spiny projection neuron. Journal of Neuroscience 25(40), 9080–9095 (2005)
Hines, M.L., Carnevale, N.T.: Neuron: a tool for neuroscientists. The Neuroscientist: a review journal bringing neurobiology, neurology and psychiatry 7(2), 123–135 (2001)
Segev, I.: Single neurone models: oversimple, complex and reduced. Trends in Neurosciences 15(11), 414–421 (1992)
Koch, C.: Biophysics of computation (January 2004)
Catterall, W.A.: Structure and regulation of voltage-gated ca2+ channels. Annu. Rev. Cell. Dev. Biol. 16, 521–555 (2000)
Geit, W.V., Achard, P., Schutter, E.D.: Neurofitter: A parameter tuning package for a wide range of electrophysiological neuron models. Frontiers in Neuroinformatics (January 2007)
Koch, C., Segev, I.: Methods in neuronal modeling: From ions to networks, p. 671 (January 1998)
Surmeier, D.J., Bargas, J., Hemmings, H.C., Nairn, A.C., Greengard, P.: Modulation of calcium currents by a D1 dopaminergic protein kinase/phosphatase cascade in rat neostriatal neurons. Neuron 14(2), 385–397 (1995)
Gruber, A.J., Solla, S.A., Surmeier, D.J., Houk, J.C.: Modulation of striatal single units by expected reward: a spiny neuron model displaying dopamine-induced bistability. J. Neurophysiol. 90(2), 1095–1114 (2003)
Wilson, C.J., Kawaguchi, Y.: The origins of two-state spontaneous membrane potential fluctuations of neostriatal spiny neurons. J. Neurosci. 16(7), 2397–2410 (1996)
Carter, A.G., Sabatini, B.L.: State-dependent calcium signaling in dendritic spines of striatal medium spiny neurons. Neuron 44(3), 483–493 (2004)
Kerr, J.N.D., Plenz, D.: Action potential timing determines dendritic calcium during striatal up-states. J. Neurosci. 24(4), 877–885 (2004)
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Nakano, T., Yoshimoto, J., Wickens, J., Doya, K. (2009). Calcium Responses Model in Striatum Dependent on Timed Input Sources. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds) Artificial Neural Networks – ICANN 2009. ICANN 2009. Lecture Notes in Computer Science, vol 5768. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04274-4_26
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DOI: https://doi.org/10.1007/978-3-642-04274-4_26
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