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@ARTICLE{Nickchen:139641,
      author       = {Nickchen, Katharina and Boehme, Rebecca and Del Mar Amador,
                      Maria and Hälbig, Thomas D and Dehnicke, Katharina and
                      Panneck, Patricia and Behr, Joachim and Prass, Konstantin
                      and Heinz, Andreas and Deserno, Lorenz and Schlagenhauf,
                      Florian and Priller, Josef},
      title        = {{R}eversal learning reveals cognitive deficits and altered
                      prediction error encoding in the ventral striatum in
                      {H}untington's disease.},
      journal      = {Brain imaging and behavior},
      volume       = {11},
      number       = {6},
      issn         = {1931-7557},
      address      = {New York, NY [u.a.]},
      publisher    = {Springer},
      reportid     = {DZNE-2020-05963},
      pages        = {1862-1872},
      year         = {2017},
      abstract     = {Huntington's disease (HD) is an autosomal dominant
                      neurodegenerative condition characterized by a triad of
                      movement disorder, neuropsychiatric symptoms and cognitive
                      deficits. The striatum is particularly vulnerable to the
                      effects of mutant huntingtin, and cell loss can already be
                      found in presymptomatic stages. Since the striatum is well
                      known for its role in reinforcement learning, we
                      hypothesized to find altered behavioral and neural responses
                      in HD patients in a probabilistic reinforcement learning
                      task performed during functional magnetic resonance imaging.
                      We studied 24 HD patients without central nervous system
                      (CNS)-active medication and 25 healthy controls. Twenty HD
                      patients and 24 healthy controls were able to complete the
                      task. Computational modeling was used to calculate
                      prediction error values and estimate individual parameters.
                      We observed that gray matter density and prediction error
                      signals during the learning task were related to disease
                      stage. HD patients in advanced disease stages appear to use
                      a less complex strategy in the reversal learning task. In
                      contrast, HD patients in early disease stages show intact
                      encoding of learning signals in the degenerating left
                      ventral striatum. This effect appears to be lost with
                      disease progression.},
      keywords     = {Adult / Algorithms / Brain Mapping / Cognitive Dysfunction:
                      diagnostic imaging / Cognitive Dysfunction: physiopathology
                      / Cohort Studies / Computer Simulation / Disease Progression
                      / Female / Functional Laterality / Gray Matter: diagnostic
                      imaging / Gray Matter: physiopathology / Humans / Huntington
                      Disease: diagnostic imaging / Huntington Disease: genetics /
                      Huntington Disease: physiopathology / Huntington Disease:
                      psychology / Magnetic Resonance Imaging / Male / Middle Aged
                      / Neuropsychological Tests / Probability Learning / Reversal
                      Learning: physiology / Ventral Striatum: diagnostic imaging
                      / Ventral Striatum: physiopathology},
      cin          = {AG Priller},
      ddc          = {150},
      cid          = {I:(DE-2719)5000007},
      pnm          = {344 - Clinical and Health Care Research (POF3-344)},
      pid          = {G:(DE-HGF)POF3-344},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:27917451},
      doi          = {10.1007/s11682-016-9660-0},
      url          = {https://pub.dzne.de/record/139641},
}