title: Differential cortical activation of the striatal direct and indirect pathway cells: reconciling the anatomical and optogenetic results by using a computational method.
abstract: The corticostriatal system is considered to be crucially involved in learning and action selection. Anatomical studies have shown that two types of corticostriatal neurons, intratelencephalic (IT) and pyramidal tract (PT) cells, preferentially project to dopamine D1 or D2 receptor-expressing striatal projection neurons, respectively. In contrast, an optogenetic study has shown that stimulation of IT axons evokes comparable responses in D1 and D2 cells and that stimulation of PT axons evokes larger responses in D1 cells. Since the optogenetic study applied brief stimulation only, however, the overall impacts of repetitive inputs remain unclear. Moreover, the apparent contradiction between the anatomical and optogenetic results remains to be resolved. I addressed these issues by using a computational approach. Specifically, I constructed a model of striatal response to cortical inputs, with parameters regarding short-term synaptic plasticity and anatomical connection strength for each connection type. Under the constraint of the optogenetic results, I then explored the parameters that best explain the previously reported paired-pulse ratio of response in D1 and D2 cells to cortical and intrastriatal stimulations, which presumably recruit different compositions of IT and PT fibers. The results indicate that 1) IT→D1 and PT→D2 connections are anatomically stronger than IT→D2 and PT→D1 connections, respectively, consistent with the previous findings, and that 2) IT→D1 and PT→D2 synapses entail short-term facilitation, whereas IT→D2 and PT→D1 synapses would basically show depression, and thereby 3) repetitive IT or PT inputs have larger overall impacts on D1 or D2 cells, respectively, supporting a recently proposed hypothesis on the roles of corticostriatal circuits in reinforcement learning.
authors.affiliation: Physical and Health Education, Graduate School of Education, The University of Tokyo, Tokyo, Japan morita@p.u-tokyo.ac.jp.
authors.forename: Kenji
authors.initials: K
authors.lastname: Morita
mesh_terms: D000465:Algorithms; D000818:Animals; D002540:Cerebral Cortex / Q000166:cytology / Q000502:physiology*; D003342:Corpus Striatum / Q000166:cytology / Q000502:physiology*; D059290:Dopaminergic Neurons / Q000378:metabolism / Q000502:physiology*; D019706:Excitatory Postsynaptic Potentials; D008959:Models, Neurological; D009473:Neuronal Plasticity; D062308:Optogenetics; D011712:Pyramidal Tracts / Q000166:cytology / Q000502:physiology*; D013569:Synapses / Q000378:metabolism / Q000502:physiology; D005680:gamma-Aminobutyric Acid / Q000378:metabolism
chemical_list: D005680:gamma-Aminobutyric Acid
keywords: computational modeling; corticostriatal circuit; paired-pulse ratio; reinforcement learning; short-term synaptic plasticity