Event-related potential (ERP) reflections of perceptual requirements during the planning of delayed action
Bibliographic record
Abstract
Kinematic studies have robustly shown that delayed hand actions involve slower and less accurate movements compared to immediate, visually guided actions. Furthermore, converging evidence from neuropsychological and neuroimaging studies suggest that visual perceptual brain mechanisms in the lateral occipital cortex (LOC) are critically recruited during delayed hand actions. In this study we sought to further investigate these issues by directly comparing the amount of perception-based neural activity during the planning phase of visually guided and delayed actions. To this end, twelve paid volunteers were auditorily cued to perform a reaching task to circular targets at varying locations on a nineteen-inch touch sensitive monitor. In the visually guided condition, the targets remained visible for 300 milliseconds after the onset of the auditory movement cue. In the delayed condition, the targets disappeared from view at the same time as the auditory movement cue. We collected scalp recorded event-related potential (ERP) data from 256 electrodes during both conditions of the task, and focused our analysis on the neural activity during the action planning phase of each trial. The behavioral data showed that, as expected, movement time (MT) was slower in the delayed condition compared to the visually guided condition. Moreover, the ERP data showed that the sensory P1 response over occipital electrodes was equivalent in both conditions; and most importantly, the object recognition N170 response was larger during the planning phase of the delayed action condition compared to the visually guided action condition. This effect was robustly observed at 22 electrodes over temporal-occipital sites in both hemispheres. These data suggest that the planning of delayed actions relies more heavily on perception-based information than visually guided action. Furthermore, this difference is not reflected in early visual processing, but involves higher-order perception likely associated with regions in the inferior-temporal cortex.
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 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) | 0.002 | 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".