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Record W7028130812

The Development of an Object-Recognition Task for Rats and the Evaluation of the Internal Validity of the Novel-Object-Preference Test

2020· dissertation· en· W7028130812 on OpenAlexfundno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2020
Typedissertation
Languageen
FieldMedicine
TopicBiomedical and Chemical Research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTask (project management)Set (abstract data type)InterchangeabilityReliability (semiconductor)Test (biology)Measure (data warehouse)
DOInot available

Abstract

fetched live from OpenAlex

Object-recognition—the ability to discriminate the familiarity of previously presented stimuli—is assessed in laboratory rats using the delayed nonmatching-to-sample (DNMS) task and the novel-object-preference (NOP) test. The DNMS task provides a fairly precise measure of a rat’s object-recognition abilities, however, it suffers from certain drawbacks. In particular, rats require extensive training and it cannot be used to assess memory for objects following periods lasting longer than several minutes. For these reasons, most researchers have abandoned it in favour of the NOP test. The NOP test is easy to use, as it relies on measuring a rat’s natural tendency to spend more time investigating a novel object over a familiar one when both are presented in a familiar context. Some concerns have been raised, however, regarding the internal validity of the NOP test. Accordingly, the goal of the present thesis was to develop a new object-recognition task that addresses the known limitations of the existent tests. A secondary goal of the thesis was to evaluate rats’ performance on the new task to that on the NOP test as a means to validate the latter. The first experiment describes rats’ performance on the new task –the modified DNMS (mDNMS) task. Rats required significantly fewer trials to learn the nonmatching rule compared to conventional DNMS tasks, and their scores showed good test re-test reliability. The same rats’ exhibited significant novelty-preference scores on the NOP test, however their scores showed poor test re-test reliability and were not significantly correlated with mDNMS scores. The latter finding suggests that the two tasks may not tax similar underlying cognitive processes. In the experiment presented in Chapter 3, memory for objects was assessed following delays lasting 72 hr, 3 weeks, and ~45 weeks on both the mDNMS task and NOP test. Rats successfully discriminated between novel and sample objects on the mDNMS task following all three delays, however, the same rats failed to exhibit significant novelty preferences following all three delays on the NOP test. These findings reveal that the mDNMS task can be used to assess long-term memory for objects, and that a failure to exhibit a novelty preference may not necessarily reflect the status of object-recognition memory. Next, we assessed rats’ performance on the mDNMS task and NOP test following surgical lesions made to either the hippocampus (HPC) or perirhinal cortex (PRh)—two brain areas implicated in object-recognition memory. Neither HPC nor PRh lesions failed to disrupt performance on the mDNMS task, but rats with PRh lesions failed to display a novelty preference on the NOP test. The discrepancy in the PRh rats’ performance on both tasks further adds to concerns regarding the internal validity of the NOP test, such that a lack of novelty preference is not necessarily indicative of an object-recognition memory impairment. The final experiment focused on refining the mDNMS task to include an additional behavioural measure—latency to make a choice. We incorporated a Go/No-go procedure and found that latency to make a choice provided a more sensitive measure of object-recognition memory than choice-accuracy on the test. Collectively, these findings confirmed the utility of the mDNMS task as a means to gauge object-recognition memory in rats. The results also highlight the limitations of the NOP test, and raise concerns regarding the internal validity of it as a means to measure object-recognition abilities in rats.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.123
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.111
GPT teacher head0.343
Teacher spread0.232 · 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 teacher head, 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

Citations0
Published2020
Admission routes1
Has abstractyes

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