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Record W3111908834

The Role of Automaticity in the Cognitive Control of Human Action - A Magnetoencephalographic Study

2020· dissertation· en· W3111908834 on OpenAlexfundno aff
Silvia L. Isabella

Bibliographic record

VenueTSpace · 2020
Typedissertation
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAutomaticityCognitionAction (physics)PsychologyCognitive psychologyNeuroscienceCognitive sciencePhysics
DOInot available

Abstract

fetched live from OpenAlex

Prominent theories on human action control propose two parallel brain processes: one fast and automatic, the other slow and deliberative. The slow, conscious processes are thought to be mediated by frontal theta (4-8 Hz) oscillations. One theory suggests that theta acts as an alarm signaling the need for control, and that frontal areas simply maintain action goals, without sensitivity to behavioural differences for achieving those goals. In order to test these hypotheses of frontal theta and executive function, three experiments were conducted. First, to examine the sensitivity of theta to behavioural differences in goal-directed actions, we compared magnetoencephalographic (MEG) recordings of theta activity in twelve healthy adults during two similar tasks: Go/No-Go and Go/Switch, requiring global and selective inhibition, respectively. We observed no differences between these two types of inhibitory control, but did observe differences during error responses. We hypothesized that error-related theta differences may have reflected covert differences in cognitive requirements between the two types of inhibition. Based on these results, a second study was designed to modulate cognitive requirements using the well-defined measure of cognitive effort, pupil diameter (PD), in twelve healthy adults. We developed a novel task combining implicit stimulus pattern learning with a Go/Switch task. The results demonstrated that subjects quickly learned the pattern without conscious awareness. Furthermore, a distinction between PD and behaviour was observed, highlighting the limitations of behavioural measures alone in capturing cognitive processes during task performance. Finally, in order to quantify theta during modulations in cognitive control, the third experiment was conducted on sixteen healthy adults performing the implicit Go/Switch task during MEG and PD recordings. Theta modulations were strongly correlated (r = 0.91) with PD, and therefore inferred to reflect cognitive effort. Furthermore, theta demonstrated a relationship with signals in the sensorimotor cortex. These results suggest a functional role for frontal theta oscillations in cognitive processes, including sensitivity to cognitive load but not behavioural differences while coordinating responses within the sensorimotor cortex. Furthermore, increased theta during implicitly learned unconscious responding demonstrated that conscious awareness was not required for cognitive effort. These results are discussed with respect to theories of action control.

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)0.002
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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.033
GPT teacher head0.357
Teacher spread0.325 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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