Retrograde tracing of the subset of afferent connections in mouse barrel cortex provided by zincergic neurons
Bibliographic record
Abstract
The barrel cortex of rodents is densely innervated by a prominent subclass of glutamatergic neurons that sequester and release zinc from their synaptic boutons. These neurons may play an important role in barrel cortex function and plasticity, as zinc has been shown to modulate synaptic function by regulating neurotransmitter release, excitatory and inhibitory amino acid receptors, and second messenger signaling cascades. Here, we utilized intracortical infusions of sodium selenite to identify the source of the zincergic innervation to the mouse barrel cortex. Our results demonstrate that the majority of zincergic projections to the barrel cortex arose from ipsilateral and callosal neurons, situated in cortical layers 2/3 and 6. Regionally, these labeled neurons were most abundant within the barrel cortex itself, posterior parietal association cortex, secondary somatosensory cortex, and motor cortex. Labeled neurons were also found in other somatosensory regions corresponding to the trunk, fore- and hindlimb, as well as more distant regions such as the visual, rhinal, dorsal peduncular and insular cortices, the claustrum, and lateral and basolateral amygdaloid nuclei. Further, some mice were injected with the retrograde tracer cholera toxin subunit B to compare retrograde labeling of zincergic neurons with that of the general population of neurons innervating the barrel cortex. Our data indicate that all cortical regions providing inputs to the barrel cortex possess a zincergic component, whereas those from thalamic or brainstem structures do not. These findings demonstrate that zincergic pathways comprise a chemospecific associational network that reciprocally interconnects the barrel cortex with other cortical and limbic structures.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".