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1000 Titel
  • Bayesian model selection favors parametric over categorical fMRI subsequent memory models in young and older adults
1000 Autor/in
  1. Soch, Joram |
  2. Richter, Anni |
  3. Schütze, Hartmut |
  4. Kizilirmak, Jasmin M. |
  5. Assmann, Anne |
  6. Knopf, Lea |
  7. Raschick, Matthias |
  8. Schult, Annika |
  9. Maass, Anne |
  10. Ziegler, Gabriel |
  11. Richardson-Klavehn, Alan |
  12. Düzel, Emrah |
  13. Schott, Björn |
1000 Erscheinungsjahr 2021
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-01-29
1000 Erschienen in
1000 Quellenangabe
  • 230:117820
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1016/j.neuroimage.2021.117820 |
1000 Ergänzendes Material
  • https://www.sciencedirect.com/science/article/pii/S1053811921000975?via%3Dihub#sec0031 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Subsequent memory paradigms allow to identify neural correlates of successful encoding by separating brain responses as a function of memory performance during later retrieval. In functional magnetic resonance imaging (fMRI), the paradigm typically elicits activations of medial temporal lobe, prefrontal and parietal cortical structures in young, healthy participants. This categorical approach is, however, limited by insufficient memory performance in older and particularly memory-impaired individuals. A parametric modulation of encoding-related activations with memory confidence could overcome this limitation. Here, we applied cross-validated Bayesian model selection (cvBMS) for first-level fMRI models to a visual subsequent memory paradigm in young (18-35 years) and older (51-80 years) adults. Nested cvBMS revealed that parametric models, especially with non-linear transformations of memory confidence ratings, outperformed categorical models in explaining the fMRI signal variance during encoding. We thereby provide a framework for improving the modeling of encoding-related activations and for applying subsequent memory paradigms to memory-impaired individuals.
1000 Sacherschließung
lokal parametric fMRI
lokal episodic memory
lokal Bayesian model selection
lokal subsequent memory effect
lokal aging
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/U29jaCwgSm9yYW0=|https://frl.publisso.de/adhoc/uri/UmljaHRlciwgQW5uaQ==|https://frl.publisso.de/adhoc/uri/U2Now7x0emUsIEhhcnRtdXQ=|https://frl.publisso.de/adhoc/uri/S2l6aWxpcm1haywgSmFzbWluIE0u|https://frl.publisso.de/adhoc/uri/QXNzbWFubiwgQW5uZQ==|https://frl.publisso.de/adhoc/uri/S25vcGYsIExlYQ==|https://frl.publisso.de/adhoc/uri/UmFzY2hpY2ssIE1hdHRoaWFz|https://frl.publisso.de/adhoc/uri/U2NodWx0LCBBbm5pa2E=|https://frl.publisso.de/adhoc/uri/TWFhc3MsIEFubmU=|https://frl.publisso.de/adhoc/uri/WmllZ2xlciwgR2FicmllbA==|https://frl.publisso.de/adhoc/uri/UmljaGFyZHNvbi1LbGF2ZWhuLCBBbGFu|https://frl.publisso.de/adhoc/uri/RMO8emVsLCBFbXJhaA==|https://orcid.org/0000-0002-8237-4481
1000 Label
1000 Förderer
  1. State of Saxony-Anhalt |
  2. European Union |
  3. Deutsche Forschungsgemeinschaft |
1000 Fördernummer
  1. -
  2. -
  3. SFB 779, TP A08; A10; RI 2964-1
1000 Förderprogramm
  1. -
  2. Research Alliance “Autonomy in Old Age”
  3. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer State of Saxony-Anhalt |
    1000 Förderprogramm -
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer European Union |
    1000 Förderprogramm Research Alliance “Autonomy in Old Age”
    1000 Fördernummer -
  3. 1000 joinedFunding-child
    1000 Förderer Deutsche Forschungsgemeinschaft |
    1000 Förderprogramm -
    1000 Fördernummer SFB 779, TP A08; A10; RI 2964-1
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6426974.rdf
1000 Erstellt am 2021-04-21T11:00:10.800+0200
1000 Erstellt von 242
1000 beschreibt frl:6426974
1000 Bearbeitet von 25
1000 Zuletzt bearbeitet Thu May 06 09:42:11 CEST 2021
1000 Objekt bearb. Thu May 06 09:41:46 CEST 2021
1000 Vgl. frl:6426974
1000 Oai Id
  1. oai:frl.publisso.de:frl:6426974 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

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