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Record W2291995232 · doi:10.1162/jocn_a_00935

Assessing the Neural Correlates of Task-unrelated Thoughts during Episodic Encoding and Their Association with Subsequent Memory in Young and Older Adults

2016· article· en· W2291995232 on OpenAlexafffund
David Maillet, M. Natasha Rajah

Bibliographic record

VenueJournal of Cognitive Neuroscience · 2016
Typearticle
Languageen
FieldNeuroscience
TopicMind wandering and attention
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsPsychologyPrecuneusEpisodic memoryForgettingEncoding (memory)Neural correlates of consciousnessAssociation (psychology)Task (project management)Developmental psychologyYoung adultAudiologyCognitive psychologyCognitionNeuroscience

Abstract

fetched live from OpenAlex

Recent evidence indicates that young adults frequently exhibit task-unrelated thoughts (TUTs) such as mind-wandering during episodic encoding tasks and that TUTs negatively impact subsequent memory. In the current study, we assessed age-related differences in the frequency and neural correlates of TUTs during a source memory encoding task, as well as age-related differences in the relationship between the neural correlates of TUTs and subsequent source forgetting effects (i.e., source misses). We found no age-related differences in frequency of TUTs during fMRI scanning. Moreover, TUT frequency at encoding was positively correlated with source misses at retrieval across age groups. In both age groups, brain regions including bilateral middle/superior frontal gyri and precuneus were activated to a greater extent during encoding for subsequent source misses versus source hits and during TUTs versus on-task episodes. Overall, our results reveal that, during a source memory encoding task in an fMRI environment, young and older adults exhibit a similar frequency of TUTs and that experiencing TUTs at encoding is associated with decreased retrieval performance. In addition, in both age groups, experiencing TUTs at encoding is associated with increased activation in some of the same regions that exhibit subsequent source forgetting effects.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.503
Threshold uncertainty score0.255

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.261
Teacher spread0.243 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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".

Quick stats

Citations32
Published2016
Admission routes2
Has abstractyes

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