In vivo Large-Scale Cortical Mapping Using Channelrhodopsin-2 Stimulation in Transgenic Mice Reveals Asymmetric and Reciprocal Relationships between Cortical Areas
Bibliographic record
Abstract
We have mapped intracortical activity in vivo independent of sensory input using arbitrary point channelrhodopsin-2 (ChR2) stimulation and regional voltage sensitive dye imaging in B6.Cg-Tg (Thy1-COP4/EYFP)18Gfng/J transgenic mice. Photostimulation of subsets of deep layer pyramidal neurons within forelimb, barrel, or visual primary sensory cortex led to downstream cortical maps that were dependent on synaptic transmission and were similar to peripheral sensory stimulation. ChR2-evoked maps confirmed homotopic connections between hemispheres and intracortical sensory and motor cortex connections. This ability of optogentically activated subpopulations of neurons to drive appropriate downstream maps suggests that mechanisms exist to allow prototypical cortical maps to self-assemble from the stimulation of neuronal subsets. Using this principle of map self-assembly, we employed ChR2 point stimulation to map connections between cortical areas that are not selectively activated by peripheral sensory stimulation or behavior. Representing the functional cortical regions as network nodes, we identified asymmetrical connection weights in individual nodes and identified the parietal association area as a network hub. Furthermore, we found that the strength of reciprocal intracortical connections between primary and secondary sensory areas are unequal, with connections from primary to secondary sensory areas being stronger than the reciprocal.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".