Discharge Properties of Juxtacellularly Labeled and Immunohistochemically Identified Cholinergic Basal Forebrain Neurons Recorded in Association with the Electroencephalogram in Anesthetized Rats
Bibliographic record
Abstract
Multiple lines of evidence indicate that cholinergic basal forebrain neurons play an important role in the regulation of cortical activity and state. However, the discharge properties of cholinergic cells in relation to the electroencephalogram (EEG) are not yet known. In the present study, cells were recorded in the basal forebrain in association with cortical EEG activity in urethane-anesthetized rats, and their discharge was examined during EEG irregular slow activity and during stimulation-induced cortical activation, characterized by rhythmic slow (theta) and high-frequency (gamma) activities. Recorded cells were labeled with Neurobiotin (Nb), using the juxtacellular technique and identified as cholinergic by immunohistochemical staining for choline acetyltransferase (ChAT). Nb-positive/ChAT-positive neurons were distinctive and significantly different from Nb-positive/ChAT-negative neurons, which were heterogeneous in their discharge properties. All Nb(+)/ChAT(+) cells increased their discharge rate with stimulation, and most shifted from an irregular tonic discharge during EEG slow irregular activity to a rhythmic burst discharge during rhythmic slow activity. The stimulation-induced rhythmic discharge was cross-correlated with the EEG rhythmic slow activity. In some units the rhythmic discharge matched the rhythmic slow activity of the retrosplenial cortex; in others, it matched that of the prefrontal cortex, which occurred at a slower frequency, suggesting that subsets of cholinergic neurons may influence their cortical target areas rhythmically at particular frequencies. Cholinergic basal forebrain neurons thus may evoke and enhance cortical activation via both an increase in rate and a change in pattern to rhythmic bursting that would stimulate rhythmic slow (theta-like) activity in cortical fields during active waking and paradoxical sleep states.
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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".