Faculty Opinions recommendation of Hippocampal episode fields develop with learning.
Bibliographic record
Abstract
Several recent studies have shown that hippocampal neurons fire during the delay period in between trials and that these firing patterns differ when different behaviors are required, suggesting that the neuronal responses may be involved in maintaining the memories needed for the upcoming trial. In particular, one study found that hippocampal neurons reliably fired at particular times, referred to as "episode fields" (EFs), during the delay period of a spatial alternation task (Pastalkova et al. (2008) Science 321:1322-1327). The firing of these neurons resulted in distinct sequential firing patterns on left and right turn trials, and these firing patterns could be used to predict the upcoming behavioral response. In this study, we examined neuronal firing during the delay period of a hippocampus-dependent plus maze task, which involved learning to approach two different reward locations (east and west), and we examined the development of these firing patterns with learning. As in the previous study, hippocampal neurons exhibited discrete periods of elevated firing during the delay (EFs) and the firing patterns were distinct on the east and west trials. Moreover, these firing patterns emerged and began to differentiate the east and west conditions during the first training session and continued to develop as the rats learned the task. The finding of similar firing patterns in different tasks suggests that the EFs are a robust phenomenon, which may occur whenever subjects must maintain distinct memory representations during a delay period. Additionally, in the previous study (Pastalkova et al. (2008) Science 321:1322-1327), the distinct firing patterns could have been due to the differing goal locations, behavioral responses (left or right turns), or trajectories. In this study, neuronal firing varied with the goal location regardless of the trajectories or responses, suggesting that the firing patterns encode the behavioral context rather than specific behaviors.Copyright © 2010 Wiley Periodicals, Inc. PMID: 20665593 Funding information This work was supported by: NIMH NIH HHS, United States Grant ID: R56 MH058755 NIMH NIH HHS, United States Grant ID: F32 MH067399 NIMH NIH HHS, United States Grant ID: MH58755 NIMH NIH HHS, United States Grant ID: MH67399 NIMH NIH HHS, United States Grant ID: R01 MH083809 NIMH NIH HHS, United States Grant ID: R01 MH083809-01A2 NIMH NIH HHS, United States Grant ID: R01 MH058755 More Less keyboard_arrow_down
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.716 | 0.576 |
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".