Calcium responses model in striatum dependent on timed input sources

Takashi Nakano, Junichiro Yoshimoto, Jeff Wickens, Kenji Doya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


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.

Original languageEnglish
Title of host publicationArtificial Neural Networks - ICANN 2009 - 19th International Conference, Proceedings
Number of pages10
EditionPART 1
Publication statusPublished - 2009
Externally publishedYes
Event19th International Conference on Artificial Neural Networks, ICANN 2009 - Limassol, Cyprus
Duration: 14-09-200917-09-2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5768 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference19th International Conference on Artificial Neural Networks, ICANN 2009

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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