Early cortical processing of coherent vs. non-coherent motion stimuli in younger and older adults: An event-related potential (ERP) study investigating visually induced vection
Bibliographic record
Abstract
The neurophysiological basis of vection (i.e., the illusion of self-motion) is not well understood. Preliminary evidence suggests that neural predictors of vection can be identified through event-related potentials (ERPs) and that these markers may correlate with vection intensity. The current study examined age-related differences in neurocortical activity during the early stages of sensory processing of vection-inducing stimuli. Twenty-two younger (age range: 20–35 years) and 25 older adults (age range: 65–83) observed optokinetic stimuli in two blocks, a short (∼3s) presentation block and a long (35s) presentation block. In both types of blocks, the optokinetic stimuli varied in motion coherence (coherent vs. non-coherent motion). During the short presentation block, EEG was used to measure neural activity in the form of ERPs time-locked to the onset of visual motion, whereas subjective ratings of vection intensity, duration, and onset latency were collected during the long presentation block. Vection was significantly stronger following coherent vs. non-coherent motion for both age groups. ERP analyses revealed differences between coherent and non-coherent motion at parietal-occipital electrodes around 100–150 ms (P1) and 150–230 ms (P2), with greater area under the curve (AUC) during non-coherent vs. coherent motion. Neither vection ratings nor ERPs showed significant age differences for coherent visual motion; however, age differences in ERPs were observed during the processing of non-coherent visual motion. These findings indicate that the subjective experience of vection and the neurophysiological mechanisms underlying visual processing preceding vection remain relatively stable with age. However, they also reveal age-related differences in the processing of non-coherent motion. • Neurocortical activity of visual motion stimuli preceding vection were investigated. • Age-related differences in processing of coherent/non-coherent stimuli were tested. • ERPs showed differences in P1 & P2 between coherent vs non-coherent stimuli. • Age-related differences only showed in the processing of non-coherent stimuli. • Neurocortical mechanisms of visual stimuli preceding vection remain stable with age.
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 | 0.001 |
| 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".