V1 population activity represents global motion velocity of long-range apparent motion in the awake monkey
Bibliographic record
Abstract
Two stationary stimuli successively flashed in spatially separated positions generates the so-called apparent motion illusion. The illusion depends on the precise spatial and temporal separations of the stimuli and is called long-range apparent motion (lrAM) for large spatiotemporal(ST) separations[1]. Since these values extend well beyond the typical selectivity of early visual neurons, it is unclear how the visual system computes motion signals from such sequence of static stimuli. We investigated whether a global motion representation could emerge at the level of V1 population in response to a two-stroke lrAM through lateral interactions[2]. We used voltage-sensitive dye imaging[3] to study in real-time the V1 population activity of two fixating monkeys in response to lrAM stimulations, whose velocity(direction and speed) was manipulated. We observe the emergence of a ST representation of the global motion:a cortical correlate of the illusory motion[4]. This ST representation of V1 population is shaped by non-linear interactions:the apparition of the second stimulus generates a spread of suppression in the direction opposite to the AM at a speed compatible with the horizontal propagation, independent of the stimulus' speed. Such spread of suppression acts as a fast normalization[5] that optimally shapes the ST representation of global motion along the AM path, to accurately represent the stimulus velocity. To validate this hypothesis, we applied an opponent motion energy model[6] on the observed and linearly-predicted V1 activity. The model systematically produced the largest energy for the appropriate direction and speed on the observed activity and failed for the linear prediction. Our results suggest that motion signal can emerge at the level of V1 population in response to lrAM, a signal that could then be decoded by downstream areas. [1] Cavanagh & Mather(1989). Spat.Vis.,4(2-3),2-3. [2] Muller et al.(2014).Nat.Comm.,5. [3] Chemla & Chavane(2010).J.Physiol-Paris,104(1),40-50. [4] Jancke et al.(2004).Nature,428:423-6. [5] Reynaud et al.(2012).J.Neurosci,32(36),12558-12569. [6] Adelson & Bergen (1985).JOpt.Soc.Am.A,2:284-299. Meeting abstract presented at VSS 2015
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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) | 0.000 | 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".