Category-selective phase coding in the superior temporal sulcus
Bibliographic record
Abstract
Object perception and categorization can occur so rapidly that behavioral responses precede or co-occur with the firing rate changes in the object-selective neocortex. Phase coding could, in principle, support rapid representation of object categories, whereby the first spikes evoked by a stimulus would appear at different phases of an oscillation, depending on the object category. To determine whether object-selective regions of the neo-cortex demonstrate phase coding, we presented images of faces and objects to two monkeys while recording local field potentials (LFP) and single unit activity from object-selective regions in the upper bank superior temporal sulcus. Single units showed preferred phases of firing that depended on stimulus category, emerging with the initiation of spiking responses after stimulus onset. Differences in phase of firing were seen below 20 Hz and in the gamma and high-gamma frequency ranges. For all but the <20-Hz cluster, phase differences remained category-specific even when controlling for stimulus-locked activity, revealing that phase-specific firing is not a simple consequence of category-specific differences in the evoked responses of the LFP. In addition, we tested for firing rate-to-phase conversion. Category-specific differences in firing rates accounted for 30-40% of the explained variance in phase occurring at lower frequencies (<20 Hz) during the initial response, but was limited (<20% of the explained variance) in the 30- to 60-Hz frequency range, suggesting that gamma phase-of-firing effects reflect more than evoked LFP and firing rate responses. The present results are consistent with theoretical models of rapid object processing and extend previous observations of phase coding to include object-selective neocortex.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".