Revisiting the Neurocognitive Correlates of the Behavioral Inhibition and Activation Systems
Bibliographic record
Abstract
The Behavioral Inhibition System (BIS) and the Behavioral Activation System (BAS) are cornerstones of neurobehavioral research. Personality scales have been developed to capture the behavioral and motivational tendencies associated with these systems, and many studies have attempted to link these scales with basic neurocognitive processes. The results, however, have been inconclusive. Here, we aim to replicate a seminal study on this topic by Amodio et al. (2008), in which the authors used a Go/No-Go task to test the association of the trait BIS with cognitive control and the BAS trait with approach tendency. The authors found significant correlations that were mutually exclusive from each other; BAS did not correlate with measures of cognitive control, and BIS did not correlated with measures of approach tendency. Despite the paper’s high citation frequency and influence on the field, there has been no direct replication to date. These factors motivated the inclusion of this study in the #EEGManyLabs project, an international community-driven effort to replicate influential EEG results and this registered report forms a part of this initiative. Following the original study, a Go/No-Go experiment will be performed with a total of 320 participants across eight replicating labs. EEG will be recorded both during the experiment and in an eight-minute resting period. Target variables are the amplitude of the N2 during a successfully inhibited response, the amplitude of the error-related negativity (ERN) after an erroneous response, left frontal asymmetry (LFA) during rest, and trait BIS/BAS measured by the Carver and White questionnaire. Both Pearson’s and Spearman rank sum correlations, as well as regression analyses will be used to test the hypotheses that trait BIS is associated with ERN and N2 amplitudes, and that trait BAS is associated with LFA during rest.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".