Endogenous activity outside the target location in Area MT predicts perceptual sensitivity in behaving marmosets
Bibliographic record
Abstract
The gain of evoked responses for targets presented at perceptual threshold are predictive of whether or not the target is perceived. It is unknown whether gain modulations are spatially specific as activity in non-target locations are not often studied in the context of sensory processing. Do non-target locations also show gain modulations in spontaneous activity that are correlated with detection sensitivity? To test this, we measured neural activity (single-unit and multi-unit activity) across area MT using chronically implanted Utah arrays in common marmosets (Callithrix jacchus) performing a visual detection task. We measured spike rates (1) for neurons whose receptive fields encompassed the target location and (2) for neurons recorded on adjacent electrodes, whose receptive fields excluded the target location. We find, as expected, that the likelihood that the target is detected increases with the target-evoked spike rate. Further, we find target detection is inversely correlated with magnitude of spontaneous activity on the adjacent electrodes. Not only is the gain modulation spatially specific, but perceptual sensitivity is improved when spontaneous activity is reduced for the surrounding population. How might spontaneous activity around the target location impact detection sensitivity? One possibility is that spontaneous activity masks the evoked response, reducing the discriminability between activity in target-present and target-absent neuronal populations. To test this we next quantified, using Signal Detection Theory, how much more detectable the presence of the target was from the surrounding spontaneous activity on hits and misses. We find that the observed shifts in spontaneous activity increase the difference in d-prime between spontaneous and evoked population activity between hit and miss trials. These results show that, in addition to depending on the spiking response evoked by the target, perceptual sensitivity also depends on the level of spontaneous, undriven activity at topographic locations beyond the target.
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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 | 0.001 |
| 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) | 0.000 | 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".