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Reward Enhances Memory via Age-Varying Online and Offline Neural Mechanisms across Development

2022· article· en· W4283824956 on OpenAlexfundno aff
Alexandra O. Cohen, Morgan M. Glover, Xinxu Shen, Camille V. Phaneuf, Kristen N. Avallone, Lila Davachi, Catherine A. Hartley

Bibliographic record

VenueJournal of Neuroscience · 2022
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsnot available
FundersNational Institute on Drug AbuseNational Institute of Mental HealthYork UniversityNational Science Foundation
KeywordsPsychologyNeuroscienceVentral tegmental areaEpisodic memoryPrefrontal cortexContent-addressable memoryHippocampusEncoding (memory)Hippocampal formationCognitive psychologyDopamineCognitionArtificial neural networkDopaminergicComputer science

Abstract

fetched live from OpenAlex

Reward motivation enhances memory through interactions between mesolimbic, hippocampal, and cortical systems, both during and after encoding. Developmental changes in these distributed neural circuits may lead to age-related differences in reward-motivated memory and the underlying neural mechanisms. Converging evidence from cross-species studies suggests that subcortical dopamine signaling is increased during adolescence, which may lead to stronger memory representations of rewarding, relative to mundane, events and changes in the contributions of underlying subcortical and cortical brain mechanisms across age. Here, we used fMRI to examine how reward motivation influences the “online” encoding and “offline” postencoding brain mechanisms that support long-term associative memory from childhood to adulthood in human participants of both sexes. We found that reward motivation led to both age-invariant enhancements and nonlinear age-related differences in associative memory after 24 h. Furthermore, reward-related memory benefits were linked to age-varying neural mechanisms. During encoding, interactions between the prefrontal cortex (PFC) and ventral tegmental area (VTA) were associated with better high-reward memory to a greater degree with increasing age. Preencoding to postencoding changes in functional connectivity between the anterior hippocampus and VTA were also associated with better high-reward memory, but more so at younger ages. Our findings suggest that there may be developmental differences in the contributions of offline subcortical and online cortical brain mechanisms supporting reward-motivated memory. SIGNIFICANCE STATEMENT A substantial body of research has examined the neural mechanisms through which reward influences memory formation in adults. However, despite extensive evidence that both reward processing and associative memory undergo dynamic change across development, few studies have examined age-related changes in these processes. We found both age-invariant and nonlinear age-related differences in reward-motivated memory. Moreover, our findings point to developmental differences in the processes through which reward modulates the prioritization of information in long-term memory, with greater early reliance on offline subcortical consolidation mechanisms and increased contribution of systems-level online encoding circuitry with increasing age. These results highlight dynamic developmental changes in the cognitive and neural mechanisms through which motivationally salient information is prioritized in memory from childhood to adulthood.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.103
GPT teacher head0.339
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations25
Published2022
Admission routes1
Has abstractyes

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