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Dynamics of neural recruitment surrounding the spontaneous arising of thoughts in experienced mindfulness practitioners

2016· article· en· W2335853028 on OpenAlexafffund
Melissa Ellamil, Kieran C. R. Fox, Matthew L. Dixon, Sean Pritchard, Rebecca M. Todd, Evan Thompson, Kalina Christoff

Bibliographic record

VenueNeuroImage · 2016
Typearticle
Languageen
FieldNeuroscience
TopicMind wandering and attention
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsMindfulnessPsychologyDynamics (music)PsychotherapistCognitive psychologyNeuroscienceCognitive sciencePedagogy

Abstract

fetched live from OpenAlex

Thoughts arise spontaneously in our minds with remarkable frequency, but tracking the brain systems associated with the early inception of a thought has proved challenging. Here we addressed this issue by taking advantage of the heightened introspective ability of experienced mindfulness practitioners to observe the onset of their spontaneously arising thoughts. We found subtle differences in timing among the many regions typically recruited by spontaneous thought. In some of these regions, fMRI signal peaked prior to the spontaneous arising of a thought - most notably in the medial temporal lobe and inferior parietal lobule. In contrast, activation in the medial prefrontal, temporopolar, mid-insular, lateral prefrontal, and dorsal anterior cingulate cortices peaked together with or immediately following the arising of spontaneous thought. We propose that brain regions that show antecedent recruitment may be preferentially involved in the initial inception of spontaneous thoughts, while those that show later recruitment may be preferentially involved in the subsequent elaboration and metacognitive processing of spontaneous thoughts. Our findings highlight the temporal dynamics of neural recruitment surrounding the emergence of spontaneous thoughts and may help account for some of spontaneous thought's peculiar qualities, including its wild diversity of content and its links to memory and attention.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.237

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.075
GPT teacher head0.318
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

Citations150
Published2016
Admission routes2
Has abstractyes

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