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Record W2129941909 · doi:10.12688/f1000research.6966.2

Hippocampal development and the dissociation of cognitive-spatial mapping from motor performance

2015· preprint· en· W2129941909 on OpenAlexaff
Bryan D. Devan, Christopher Magalis, Robert J. McDonald

Bibliographic record

VenueF1000Research · 2015
Typepreprint
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsMorris water navigation taskCognitive psychologyPsychologyNeuroscienceDissociation (chemistry)CognitionHippocampal formationSpatial learningSpatial memoryMotor learningWorking memory

Abstract

fetched live from OpenAlex

The publication of a recent article in F1000Research has led to discussion of, and correspondence on a broader issue that has a long history in the fields of neuroscience and psychology. Namely, is it possible to separate the cognitive components of performance, in this case spatial behavior, from the motoric demands of a task? Early psychological experiments attempted such a dissociation by studying a form of spatial maze learning where initially rats were allowed to explore a complex maze, termed "latent learning," before reinforcement was introduced. Those rats afforded the latent learning experience solved the task faster than those that were not, implying that cognitive map learning during exploration aided in the performance of the task once a motivational component was introduced. This form of latent learning was interpreted as successfully demonstrating that an exploratory cognitive map component was acquired irrespective of performing a learned spatial response under deprivation/motivational conditions. The neural substrate for cognitive learning was hypothesized to depend on place cells within the hippocampus. Subsequent behavioral studies attempted to directly eliminate the motor component of spatial learning by allowing rats to passively view the distal environment before performing any motor response using a task that is widely considered to be hippocampal-dependent. Latent learning in the water maze, using a passive placement procedure has met with mixed results. One constraint on viewing cues before performing a learned swimming response to a hidden goal has been the act of dynamically viewing distal cues while moving through a part of the environment where an optimal learned spatial escape response would be observed. We briefly review these past findings obtained with adult animals to the recent efforts of establishing a "behavioral topology" separating cognitive-spatial learning from tasks differing in motoric demands in an attempt to define when cognitive-spatial behavior emerges during development.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.369
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.227
GPT teacher head0.360
Teacher spread0.133 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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