Discharge Profiles of Identified GABAergic in Comparison to Cholinergic and Putative Glutamatergic Basal Forebrain Neurons across the Sleep–Wake Cycle
Bibliographic record
Abstract
Whereas basal forebrain (BF) cholinergic neurons are known to participate in processes of cortical activation during wake (W) and paradoxical sleep (PS or P, also called REM sleep), codistributed GABAergic neurons have been thought to participate in processes of cortical deactivation and slow-wave sleep (SWS or S). To learn the roles the GABAergic neurons might play, in relation to cholinergic and glutamatergic neurons, we juxtacellularly recorded and labeled neurons during natural sleep-wake states in head-fixed rats. Neurobiotin (Nb)-labeled cells were identified immunohistochemically as choline acetyltransferase (ChAT)+, glutamic acid decarboxylase (GAD)+, or ChAT-/GAD-. Of the latter, some were identified as glutamatergic by immunostaining of their terminals with the vesicular glutamate transporter (VGluT2). In contrast to ChAT+ neurons, which all discharged maximally during W and PS, GAD+ neurons comprised multiple sleep-wake subgroups. Some GABAergic neurons discharged maximally during W and PS, as WP-max active cells (36%), and in positive correlation with gamma electroencephalographic (EEG) activity. Some discharged maximally during SWS, as S-max active cells (28%), and in positive correlation with delta EEG activity. Others increased their discharge progressively during sleep to discharge maximally during PS, as P-max active cells (36%), and in negative association with electromyographic (EMG) activity. ChAT-/GAD- cells comprised WP-max (46%), S-max (17%), P-max (17%), and W-max active cells (14%), whose discharge was positively correlated with EMG activity. GABAergic neurons would thus play similar or reciprocal roles to other cholinergic and glutamatergic BF neurons in regulating cortical activity and muscle tone along with behavior across sleep-wake 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) | 0.001 | 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".