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Record W3001107821 · doi:10.1101/2020.01.23.916841

Distinct neural variables underlie subjective reports of attention

2020· preprint· en· W3001107821 on OpenAlexfundno aff
Stephen Whitmarsh, Christophe Gitton, Veikko Jousmäki, Jérôme Sackur, Catherine Tallon‐Baudry

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsnot available
FundersAgence Nationale de la RechercheCanadian Institute for Advanced Research
KeywordsPupillometryMagnetoencephalographyPsychologySomatosensory systemStimulus (psychology)AudiologyArousalVigilance (psychology)PupilPupillary responseCognitive psychologySensory stimulation therapyPupil sizeElectroencephalographySensory systemNeuroscience

Abstract

fetched live from OpenAlex

Abstract Attention is subjectively experienced as a unified cognitive effort. This unitary experience of attention contrasts with the diversity of neural and peripheral correlates of attention. While the effects of attention on stimulus-evoked responses, alpha oscillations and pupil diameter, are well-known the relationship between these indices and the subjective experience of attention, has not yet been assessed. Participants performed a sustained (10 s to 30 s) attention task in which rare (10%) targets were detected within continuous tactile stimulation (16 Hz). Trials were followed by attention ratings on an 8-point Likert scale. Steady-state evoked fields (SSEFs) in response to tactile stimulation, as measured by magnetoencephalography, provided an objective measure of sensory processing. Beamformer source analysis of somatosensory alpha power was used as a measure of cortical excitability, while pupillometry provided a peripheral index of arousal. Attention ratings correlated negatively with contralateral somatosensory alpha power, and positively with pupil diameter. The effect of pupil diameter on attention ratings extended into the following trial, reflecting a sustained aspect of attention related to vigilance. The effect of alpha power did not carry over to the next trial, and furthermore mediated the effect of pupil diameter on attention ratings. Variation in SSEF power reflected stimulus processing under the influence of alpha oscillations, but were not readily expressed through subjective ratings of attention. Together, our results show that both alpha power and pupil diameter are reflected in the subjective experience of attention, albeit on different time spans, while continuous stimulus processing might not be metacognitively accessible. 1 Significance Statement Attention is subjectively experienced as a unified cognitive effort, in contrast with a diversity of neural and peripheral measures shown to correlate with attention. We present the first comprehensive study on the complex inter-relationship between the most common bio-physiological indices of attention, and their association with the subjective experience of attention. We show that the subjective experience of attention correlates negatively with cortical alpha oscillations, and positively with pupil diameter. The latter reflected a sustained aspect of attention, spanning several tens of seconds, related to vigilance. Alpha power, representing cortical control, fluctuated faster and mediated the effect of pupil diameter on attention. Tactile steady-state power reflected stimulus processing, also under the influence of alpha oscillations, but did not contribute much to subjective ratings of 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 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)0.001
metaresearch head score (Gemma)0.012
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.229
Teacher spread0.203 · 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".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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