Functionally imaging the magno- and parvocellular layers of the human LGN during binocular rivalry
Bibliographic record
Abstract
Introduction. Binocular rivalry occurs when conflicting images are presented to the eyes dichoptically. Rather than being perceived as one cohesive image, the two images compete for perceptual dominance, resulting in the images alternating in perceptual awareness. Neural explanations for this phenomenon have been debated; our interest was to determine the involvement of the magnocellular (M) and parvocellular (P) processing streams in rivalry. The lateral geniculate nucleus (LGN) is involved in dominance and suppression of visual input, consists of two ventral M layers and four dorsal P layers, and is the only place in the brain where these streams are spatially disjoint. Previous research has shown that activity in the LGN layers innervated by the suppressed eye is also suppressed during rivalry, but it is not clear whether both M and P streams are equally involved. Methods. Participants were scanned using a Siemens 3T MRI scanner. Functional EPI data were registered to a mean series of high-resolution proton density weighted images on which it is possible to measure the boundaries of the LGN and thus localize the M and P layers. Stimuli were presented through an Avotec binocular goggle system that allowed independent stimulation of each eye. The rivalrous stimuli were two rotating (1 Hz period) discs of high-contrast sinusoidal gratings that varied with regards to colour (red vs. green) and direction of rotation. Subjects held down a button to indicate which of the two stimuli was currently being perceived. Event-related averages were calculated from the functional data within the LGN. Results. The activation strengths of the M and P streams were compared. Both streams were found to participate equally in rivalry. Discussion. These results have implications for potential treatments for clinical disorders that result from M-cell deficits (e.g., dyslexia) and attentional disorders (e.g., attention deficit hyperactivity disorder, neglect syndromes). Meeting abstract presented at VSS 2013
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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 | 0.000 |
| 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".