Blood Capillary Distribution Correlates with Hemodynamic-based Functional Imaging in Cerebral Cortex
Bibliographic record
Abstract
Our study concerns the mechanisms that underlie functional imaging of sensory areas of cortex using hemodynamic-based methods such as optical imaging of intrinsic signals, functional magnetic resonance imaging and positron emission tomography. In temporal cortex of chinchilla, we have used optical imaging of intrinsic signals evoked by acoustic stimulation to define the functionally responsive area and then made (scanning electron microscopy) observations of the corresponding capillary networks prepared by corrosion cast methods. We report that intrinsic signals associated with auditory cortex correlate directly with discrete capillary beds. These capillary beds, within the cortical surface layers, are distributed across the cortex in a non-uniform fashion. Within cortex both the arterial supply and the capillary network contain various flow control structures. Our study suggests a causal relationship between the metabolic demands of local neuronal activity and both the density of the capillary network and the placement of the control structures. Such relationships will affect the ultimate spatial resolution obtainable by hemodynamic-based functional brain imaging studies. These relationships will also affect quantitative comparisons of activity levels in different areas of cortex.
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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 | 0.001 | 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) | 0.001 | 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".