Are There Place Cells in the Avian Hippocampus?
Bibliographic record
Abstract
Birds possess a hippocampus that serves many of the same spatial and mnemonic functions as the mammalian hippocampus but achieves these outcomes with a dramatically different neuroanatomical organization. The properties of spatially responsive neurons in birds and mammals are also different. Much of the contemporary interest in the role of the mammalian hippocampus in spatial representation dates to the discovery of place cells in the rat hippocampus. Since that time, cells that respond to head direction and cells that encode a grid-like representation of space have been described in the rat brain. Research with homing pigeons has discovered hippocampal cells, including location cells, path cells, and pattern cells, that share some but not all properties of spatially responsive neurons in the rodent brain. We have recently used patterns of immediate-early gene expression, visualized by the catFISH method, to investigate how neurons in the hippocampus of brood-parasitic brown-headed cowbirds respond to spatial context. We have found cells that discriminate between different spatial environments and are re-activated when the same spatial environment is re-experienced. Given the differences in habitat and behaviour between birds and rodents, it is not surprising that spatially responsive cells in their hippocampus and other brain regions differ. The enormous diversity of avian habitats and behaviour offers the potential for understanding the general principles of neuronal representation of space.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".