Analysis of Recordings of Single-Unit Firing and Population Activity in the Dorsal Subiculum of Unrestrained, Freely Moving Rats
Bibliographic record
Abstract
We examined neuronal activity in the dorsal subiculum of unrestrained, male adult Wistar rats, which were implanted with a moveable eight-electrode microdrive. The subiculum is the primary hippocampal formation output area and is comparatively uninvestigated neurophysiologically. We compared subicular unit activity and the subicular EEG while rats occupied a small, restricted environment and also correlated neuronal activity with the ongoing behavior of the animal. Units were separated using their electrophysiological characteristics into bursting units, regular spiking units, theta-modulated units, and fast spiking units. The bursting and regular spiking unit classes are similar to hippocampal CA1 units, whereas the fast spiking units appear to be interneurons. Bursting units were variable in their behavior: some units bursted regularly, and others bursted only occasionally. Theta-modulated units have not been described before; these were similar to regular spiking units in all respects except that they increased their firing significantly when theta oscillations were present in the simultaneous EEG record. Subicular EEG was similar to hippocampal EEG, with theta oscillations dominating "alert, moving" behaviors, while large amplitude irregular activity (LIA), which included sharp waves, predominated when theta oscillations were not present, mainly during "alert, still" and "quiet" behaviors. A relatively small proportion of subicular recordings (approximately 32%) were phase-locked to theta; this is a smaller proportion than in areas from which the subiculum takes major inputs. The relative lack of entrainment of subicular neurons by this important intrinsic rhythm is suggestive of a limit to which theta might be capable of affecting both subicular and hippocampal information processing more generally.
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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".