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1000 Titel
  • Assessment of Metacognition and Reversal Learning in Parkinson’s Disease: Preliminary Results
1000 Autor/in
  1. Trenado, Carlos |
  2. Boschheidgen, Matthias |
  3. Rübenach, Julia |
  4. N'Diaye, Karim |
  5. Schnitzler, Alfons |
  6. Mallet, Luc |
  7. Wojtecki, Lars |
1000 Erscheinungsjahr 2018
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2018-09-11
1000 Erschienen in
1000 Quellenangabe
  • 12:343
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2018
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.3389/fnhum.2018.00343 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6141660/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Reversal learning (RL) has been widely used for assessment of behavioral adaptation, impulsivity, obsession, and compulsion in healthy controls as well as people suffering from psychiatric and neurological disorders such as Parkinson’s disease (PD). Nevertheless, studies addressing high cognitive functions such as metacognition in PD are scarce. Here, we address for the first time the effect of levodopa and PD on metacognition within the framework of a RL paradigm. In agreement with previous reports, PD patients exhibited reversal shifting impairment with respect to healthy controls (CTRL) regardless of medication condition (MED-ON and MED-OFF), which was supported by a well-known model of learning conditioning (Rescorla–Wagner). In spite that we found a significant association between accuracy and decision confidence level for MED-OFF and CTRL, analysis of metacognitive sensitivity assessed by type 2 signal detection theory (SDT) revealed only a significant underperformance for patients without medication (MED-OFF). This finding points toward a non-compromising positive effect of dopaminergic medication on metacognition for PD.
1000 Sacherschließung
lokal reversal learning
lokal levodopa
lokal metacognition
lokal subthalamic nucleus
lokal behavioral adaptation
lokal Parkinson’s disease
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/VHJlbmFkbywgQ2FybG9z|https://frl.publisso.de/adhoc/uri/IEJvc2NoaGVpZGdlbiwgTWF0dGhpYXM=|https://frl.publisso.de/adhoc/uri/UsO8YmVuYWNoLCBKdWxpYQ==|https://frl.publisso.de/adhoc/uri/IE4nRGlheWUsIEthcmlt|https://orcid.org/0000-0002-6414-7939|https://orcid.org/0000-0001-8061-1167|https://orcid.org/0000-0002-6205-4405
1000 Label
1000 Förderer
  1. Bundesministerium für Bildung und Forschung |
  2. European Research Area Networks (ERA-NET) NEURON |
1000 Fördernummer
  1. 01EW1411 to LW
  2. 01EW1411 to LW
1000 Förderprogramm
  1. TYMON
  2. TYMON
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Bundesministerium für Bildung und Forschung |
    1000 Förderprogramm TYMON
    1000 Fördernummer 01EW1411 to LW
  2. 1000 joinedFunding-child
    1000 Förderer European Research Area Networks (ERA-NET) NEURON |
    1000 Förderprogramm TYMON
    1000 Fördernummer 01EW1411 to LW
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6415456.rdf
1000 Erstellt am 2019-07-29T13:17:34.818+0200
1000 Erstellt von 254
1000 beschreibt frl:6415456
1000 Bearbeitet von 25
1000 Zuletzt bearbeitet Thu Jan 30 19:53:16 CET 2020
1000 Objekt bearb. Fri Aug 09 06:54:42 CEST 2019
1000 Vgl. frl:6415456
1000 Oai Id
  1. oai:frl.publisso.de:frl:6415456 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
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