Functional imaging of the rat brain with micro-ultrasound
Bibliographic record
Abstract
Linear array based micro-ultrasound provides 40150um resolution over a significant depth of field at frames rates as high as 1000 fps. Current imaging modalities for investigating in vivo brain function are challenged to provide this combination of imaging parameters. The present experiment was carried out to investigate the potential of micro-ultrasound in neuroimaging of rodents in vivo. Adult male Sprague-Dawley rats were anesthetized with isoflurane. To enable high frequency ultrasound imaging of the brain, stereotaxic surgery was done to prepare a small cranial window. Non-linear Ultrasound imaging (amplitude modulation) was performed using high frequency linear array (Vevo2100, VisualSonics), equipped with a 20 MHz center frequency probe. The probe was positioned appropriately to reveal 3 regions of interest, the forelimb representation in the primary somatosensory cortex (S1FL), primary motor cortex (Ml), and thalamus (Th). Ultrasound contrast agent (Micromarker, VisualSonics) at 40uL/min and 2 ? 109microbubbles/mL was infused through the tail vein. When signal intensity reached a steady state, a contrast disruption pulse was delivered to assess brain reperfusion during electrical stimulation to the forelimb and 10% CO2inhalation. Average signal intensity from S1FL, Ml, and Th regions were acquired and the slope and plateau values of the reperfusion curves were calculated. Slope and plateau are indices of flow and total blood volume in the regions of interest respectively. An increase in both the initial slope and plateau of the reperfusion curve were observed in the S1FL and Th, while only an increase in plateau was observed in Ml during the electrical stimulation to the forepaw (P2inhalation (P<0.05). These data demonstrate the potential micro-ultrasound for functional brain imaging in animal models. The imaging parameters tradeoff afforded by nonlinear contrast Microultrasound with depth penetration sufficient to enclose the entire cerebrum provides a unique window into the study of cerebral hemodynamics, both in the cortex and in the deep grey matter.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".