MétaCan
Menu
Back to cohort
Record W2004544614 · doi:10.1037/a0033087

Lesions of the dorsal tegmental nuclei disrupt control of navigation by distal landmarks in cued, directional, and place variants of the Morris water task.

2013· article· en· W2004544614 on OpenAlexfundno aff
Benjamin J. Clark, James P. Rice, Katherine G. Akers, Felicha T. Candelaria‐Cook, Jeffrey S. Taube, Derek A. Hamilton

Bibliographic record

VenueBehavioral Neuroscience · 2013
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsnot available
FundersNational Institute on Deafness and Other Communication DisordersNational Institute of Neurological Disorders and StrokeNational Institute on Alcohol Abuse and AlcoholismNatural Sciences and Engineering Research Council of CanadaNational Institutes of Health
KeywordsCued speechHeading (navigation)LandmarkOrientation (vector space)Ventral tegmental areaPath integrationNeuroscienceMidbrainDorsumTask (project management)Computer scienceArtificial intelligencePsychologyAnatomyBiologyCentral nervous systemGeographyCognitive psychology

Abstract

fetched live from OpenAlex

Navigation depends on a network of neural systems that accurately monitor an animal's spatial orientation in an environment. Within this navigation system are head direction (HD) cells which discharge as a function of an animal's directional heading, providing an animal with a neural compass to guide ongoing spatial behavior. Experiments were designed to test this hypothesis by damaging the dorsal tegmental nucleus (DTN), a midbrain structure that plays a critical role in the generation of the rodent HD cell signal, and evaluating landmark based navigation using variants of the Morris water task. In Experiments 1 and 2, shams and DTN-lesioned rats were trained to navigate toward a cued platform in the presence of a constellation of distal landmarks located outside the pool. After reaching a training criteria, rats were tested in three probe trials in which (a) the cued platform was completely removed from the pool, (b) the pool was repositioned and the cued platform remained in the same absolute location with respect to distal landmarks, or (c) the pool was repositioned and the cued platform remained in the same relative location in the pool. In general, DTN-lesioned rats required more training trials to reach performance criterion, were less accurate to navigate to the platform position when it was removed, and navigated directly to the cued platform regardless of its position in the pool, indicating a general absence of control over navigation by distal landmarks. In Experiment 3, DTN and control rats were trained in directional and place navigation variants of the water task where the pool was repositioned for each training trial and a hidden platform was placed either in the same relative location (direction) in the pool or in the same absolute location (place) in the distal room reference frame. DTN-lesioned rats were initially impaired in the direction task, but ultimately performed as well as controls. In the place task, DTN-lesioned rats were severely impaired and displayed little evidence of improvement over the course of training. Together, these results support the conclusion that the DTN is required for accurate landmark navigation.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.034
GPT teacher head0.283
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations56
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueBehavioral NeuroscienceSame topicMemory and Neural MechanismsFrench-language works237,207