Turn up the noise: Increased visual noise in the M-pathway in older adults
Bibliographic record
Abstract
Visual information in humans is processed by two separate visual pathways. One is the magnocellular visual pathway (M-pathway), which carries high temporal frequency information but low spatial frequency information. The other is the parvocellular visual pathway (P-pathway), which carries low temporal information but high spatial information. Currently, very little is known about how these pathways may change with age. In order to investigate this issue, we presented older and younger adults with low and high spatial frequency gabors under two critical conditions. The first, a pulsed pedestal condition, is known to inhibit the M-pathway, while the second, a steady pedestal condition, leaves both the M and the P-pathways intact. With younger adults, as expected, we found that they are faster at processing low spatial frequency (LSF) information under the steady pedestal condition, in which the M-pathway is unaffected. This replicates previous findings with younger adults. Also as expected, this bias is removed under the pulsed pedestal condition, where no preferential processing is shown between low and high spatial frequency information. These findings replicate earlier work (e.g., (e.g., Abrams & Weidler, 2014; Goodhew et al., 2014). Regarding older adults, we demonstrate the same pattern in the steady pedestal condition; faster processing of LSF information. Interestingly, an even greater inhibition towards LSF information is produced under the pulsed pedestal condition, such that now speeded processing occurs towards HSF information. We argue that this difference in older adults provides evidence that the M-pathway, although very much intact, may contain more internal noise, manifesting itself in a greater inhibition of low spatial frequency processing when the M-pathway is repressed. Meeting abstract presented at VSS 2016
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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".