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Striosomes Mediate Value-Based Learning Vulnerable in Age and a Huntington's Disease Model.
Friedman, Alexander; Hueske, Emily; Drammis, Sabrina M; Toro Arana, Sebastian E; Nelson, Erik D; Carter, Cody W; Delcasso, Sebastien; Rodriguez, Raimundo X; Lutwak, Hope; DiMarco, Kaden S; Zhang, Qingyang; Rakocevic, Lara I; Hu, Dan; Xiong, Joshua K; Zhao, Jiajia; Gibb, Leif G; Yoshida, Tomoko; Siciliano, Cody A; Diefenbach, Thomas J; Ramakrishnan, Charu; Deisseroth, Karl; Graybiel, Ann M.
Afiliação
  • Friedman A; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Hueske E; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Drammis SM; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Toro Arana SE; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Nelson ED; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Carter CW; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Delcasso S; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Rodriguez RX; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Lutwak H; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • DiMarco KS; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Zhang Q; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Rakocevic LI; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Hu D; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Xiong JK; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Zhao J; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Gibb LG; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Yoshida T; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Siciliano CA; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Diefenbach TJ; Ragon Institute of MGH, MIT and Harvard, Cambridge, MA 02139, USA.
  • Ramakrishnan C; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
  • Deisseroth K; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
  • Graybiel AM; McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: graybiel@mit.edu.
Cell ; 183(4): 918-934.e49, 2020 11 12.
Article em En | MEDLINE | ID: mdl-33113354
ABSTRACT
Learning valence-based responses to favorable and unfavorable options requires judgments of the relative value of the options, a process necessary for species survival. We found, using engineered mice, that circuit connectivity and function of the striosome compartment of the striatum are critical for this type of learning. Calcium imaging during valence-based learning exhibited a selective correlation between learning and striosomal but not matrix signals. This striosomal activity encoded discrimination learning and was correlated with task engagement, which, in turn, could be regulated by chemogenetic excitation and inhibition. Striosomal function during discrimination learning was disturbed with aging and severely so in a mouse model of Huntington's disease. Anatomical and functional connectivity of parvalbumin-positive, putative fast-spiking interneurons (FSIs) to striatal projection neurons was enhanced in striosomes compared with matrix in mice that learned. Computational modeling of these findings suggests that FSIs can modulate the striosomal signal-to-noise ratio, crucial for discrimination and learning.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Envelhecimento / Doença de Huntington / Corpo Estriado / Aprendizagem Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Envelhecimento / Doença de Huntington / Corpo Estriado / Aprendizagem Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article