Literature DB >> 35556232

Sluggish retrieval of positive memories in depressed adults.

Arkadiy L Maksimovskiy1,2, Christopher Okine3, Andrea M Cataldo4,5, Daniel G Dillon4,5.   

Abstract

Although depression is associated with poor memory for positive material, the underlying mechanisms remain unclear. We used the Hierarchical Drift Diffusion Model (HDDM) to determine whether slow evidence accumulation at retrieval contributes to depressed individuals' difficulty remembering positive events. Participants completed the Beck Depression Inventory-II and were stratified into High BDI (HBDI; BDI-II > 20, n = 49) and Low BDI (LBDI; BDI-II < 6, n = 46) groups. Next, participants completed an oddball task in which neutral, negative, and positive pictures served as rare targets. One day later, recognition memory was tested by presenting the encoded ("old") pictures along with closely matched ("new") lures. Recognition accuracy was analyzed with a generalized linear model, and choice and response time data were analyzed with the HDDM. Recognition accuracy for old positive pictures was lower in HBDI versus LBDI participants, and the HDDM highlighted slow evidence accumulation during positive memory retrieval in the HBDI group. Impaired memory for positive material in depressed adults was related to slow evidence accumulation at retrieval. Because oddballs should elicit prediction errors that normally strengthen memory formation, these retrieval findings may reflect weak positive prediction errors, at encoding, in depressed adults.
© 2022. The Psychonomic Society, Inc.

Entities:  

Keywords:  Depression; Drift Diffusion Model; Emotion; Memory; Oddball

Mesh:

Year:  2022        PMID: 35556232      PMCID: PMC9464714          DOI: 10.3758/s13415-022-01010-2

Source DB:  PubMed          Journal:  Cogn Affect Behav Neurosci        ISSN: 1530-7026            Impact factor:   3.526


  48 in total

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Review 5.  Cognition and depression: current status and future directions.

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8.  Positive reward prediction errors during decision-making strengthen memory encoding.

Authors:  Anthony I Jang; Matthew R Nassar; Daniel G Dillon; Michael J Frank
Journal:  Nat Hum Behav       Date:  2019-05-06

9.  HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python.

Authors:  Thomas V Wiecki; Imri Sofer; Michael J Frank
Journal:  Front Neuroinform       Date:  2013-08-02       Impact factor: 4.081

10.  The neuroscience of positive memory deficits in depression.

Authors:  Daniel G Dillon
Journal:  Front Psychol       Date:  2015-09-07
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