Inhibitory control elicited by physical activity and inactivity stimuli: an EEG study
Bibliographic record
Abstract
The theory of effort minimization in physical activity (TEMPA) argues that individuals have an automatic attraction toward effort minimization. To engage in a physically active behavior, this automatic attraction needs to be overridden by controlled processes. However, direct evidence showing that inhibitory control is required to avoid effort minimization is lacking. Here, we used go/no-go tasks and electroencephalography (EEG) to assess the neural correlates of inhibitory control associated with visual stimuli depicting physical inactivity, physical activity, or that were neutral in 50 healthy young adults. The N2 event-related potential (ERP) component amplitude was used as a physiological index of inhibitory control. Results showed significant two-way interactions between the type of trials (i.e., go vs. no-go trials) and the type of stimuli on N2, revealing a significantly more pronounced no-go effect (i.e., higher N2 in no-go relative to go trials) for neutral and physical inactivity stimuli compared with physical activity stimuli. Simple tests further revealed that N2 amplitude was more negative in no-go than go trials for neutral stimuli (b=-.91 µV, 95%CI=-1.42 to -.40 µV, p<.001) and for stimuli depicting physical inactivity (b=-.58 µV, 95%CI=-1.08 to -.08 µV, p=.025). By contrast, we found no evidence of significant differences in N2 amplitude between no-go and go trials for stimuli depicting physical activity (b=.20 µV, 95%CI=-1.08 to –.08 µV, p=.445). These findings provide evidence that inhibiting responses to physical inactivity stimuli requires significantly higher inhibitory control than inhibiting responses to physical activity stimuli. The study pre-registration form can be found at https://doi.org/10.17605/OSF.IO/RKYHB.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".