Functional Organization of Envelope-Responsive Neurons in Early Visual Cortex: Organization of Carrier Tuning Properties
Bibliographic record
Abstract
It is well established that visual cortex neurons having similar selectivity for orientation, direction of motion, ocular dominance, and other properties of first-order (luminance-defined) stimuli are clustered into a columnar organization. However, the cortical architecture of neuronal responses to second-order (contrast/texture-defined) stimuli is poorly understood. A useful second-order stimulus is a contrast envelope, consisting of a finely detailed pattern (carrier) whose contrast varies on a coarse spatial scale (envelope). In this study, we analyzed the cortical organization of carrier tuning properties of neurons, which responded to contrast-modulated stimuli. We examined whether neurons tuned to similar carrier properties are clustered spatially and whether such spatial clusters are arranged in columns. To address these questions, we recorded single-unit activity, multiunit activity, and local field potentials simultaneously from area 18 of anesthetized cats, using single-channel microelectrodes and multielectrode arrays. Our data showed that neurons tuned to similar carrier spatial frequency are distributed in a highly clustered manner; neurons tuned to similar carrier orientation are also significantly clustered. Neurons along linear arrays perpendicular to the brain surface always exhibited similar optimal carrier spatial frequency, indicating a columnar organization. Multi-pronged tetrode recordings indicated that the diameter of these columns is ≥450 μm. Optimal carrier orientation was also significantly clustered but with finer-grain organization and greater scatter. These results indicate a fine anatomical structure of cortical organization of second-order information processing and suggest that there are probably more maps in cat area 18 than previously believed.
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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".