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@ARTICLE{Morita:826548,
      author       = {Morita, Kenji and Jitsev, Jenia and Morrison, Abigail},
      title        = {{C}orticostriatal circuit mechanisms of value-based action
                      selection: {I}mplementation of reinforcement learning
                      algorithms and beyond},
      journal      = {Behavioural brain research},
      volume       = {311},
      issn         = {0166-4328},
      address      = {Amsterdam},
      publisher    = {Elsevier},
      reportid     = {FZJ-2017-00771},
      pages        = {110 - 121},
      year         = {2016},
      abstract     = {Value-based action selection has been suggested to be
                      realized in the corticostriatal local circuits through
                      competition among neural populations. In this article, we
                      review theoretical and experimental studies that have
                      constructed and verified this notion, and provide new
                      perspectives on how the local-circuit selection mechanisms
                      implement reinforcement learning (RL) algorithms and
                      computations beyond them. The striatal neurons are mostly
                      inhibitory, and lateral inhibition among them has been
                      classically proposed to realize “Winner-Take-All (WTA)”
                      selection of the maximum-valued action (i.e., ‘max’
                      operation). Although this view has been challenged by the
                      revealed weakness, sparseness, and asymmetry of lateral
                      inhibition, which suggest more complex dynamics, WTA-like
                      competition could still occur on short time scales. Unlike
                      the striatal circuit, the cortical circuit contains
                      recurrent excitation, which may enable retention or temporal
                      integration of information and probabilistic “soft-max”
                      selection. The striatal “max” circuit and the cortical
                      “soft-max” circuit might co-implement an RL algorithm
                      called Q-learning; the cortical circuit might also similarly
                      serve for other algorithms such as SARSA. In these
                      implementations, the cortical circuit presumably sustains
                      activity representing the executed action, which negatively
                      impacts dopamine neurons so that they can calculate
                      reward-prediction-error. Regarding the suggested more
                      complex dynamics of striatal, as well as cortical, circuits
                      on long time scales, which could be viewed as a sequence of
                      short WTA fragments, computational roles remain open: such a
                      sequence might represent (1) sequential state-action-state
                      transitions, constituting replay or simulation of the
                      internal model, (2) a single state/action by the whole
                      trajectory, or (3) probabilistic sampling of state/action.},
      cin          = {INM-6 / IAS-6},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)IAS-6-20130828},
      pnm          = {574 - Theory, modelling and simulation (POF3-574) / 571 -
                      Connectivity and Activity (POF3-571) / SMHB - Supercomputing
                      and Modelling for the Human Brain (HGF-SMHB-2013-2017) /
                      RL-BRD-J - Neural network mechanisms of reinforcement
                      learning (BMBF-01GQ1343) / W2Morrison - W2/W3 Professorinnen
                      Programm der Helmholtzgemeinschaft (B1175.01.12)},
      pid          = {G:(DE-HGF)POF3-574 / G:(DE-HGF)POF3-571 /
                      G:(DE-Juel1)HGF-SMHB-2013-2017 / G:(DE-Juel1)BMBF-01GQ1343 /
                      G:(DE-HGF)B1175.01.12},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000380418200012},
      pubmed       = {pmid:27173430},
      doi          = {10.1016/j.bbr.2016.05.017},
      url          = {https://juser.fz-juelich.de/record/826548},
}