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Record W3083100064 · doi:10.1093/cercor/bhaa225

The Claustrum is Involved in Cognitive Processes Related to the Classical Conditioning of Eyelid Responses in Behaving Rabbits

2020· article· en· W3083100064 on OpenAlexaff
M Mar Reus-García, Raudel Sánchez‐Campusano, Julia Ledderose, Godwin Dogbevia, Mario Treviño, Mazahir T. Hasan, Agnès Gruart, José M. Delgado‐García

Bibliographic record

VenueCerebral Cortex · 2020
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsUniversity of Ottawa
FundersMax-Planck-GesellschaftFritz Thyssen Stiftung
KeywordsClaustrumEyelidCognitionNeurosciencePsychologyClassical conditioningCognitive psychologyConditioningCognitive scienceMedicineMathematicsOphthalmology

Abstract

fetched live from OpenAlex

It is assumed that the claustrum (CL) is involved in sensorimotor integration and cognitive processes. We recorded the firing activity of identified CL neurons during classical eyeblink conditioning in rabbits, using a delay paradigm in which a tone was presented as conditioned stimulus (CS), followed by a corneal air puff as unconditioned stimulus (US). Neurons were identified by their activation from motor (MC), cingulate (CC), and medial prefrontal (mPFC) cortices. CL neurons were rarely activated by single stimuli of any modality. In contrast, their firing was significantly modulated during the first sessions of paired CS/US presentations, but not in well-trained animals. Neuron firing rates did not correlate with the kinematics of conditioned responses (CRs). CL local field potentials (LFPs) changed their spectral power across learning and presented well-differentiated CL-mPFC/CL-MC network dynamics, as shown by crossfrequency spectral measurements. CL electrical stimulation did not evoke eyelid responses, even in trained animals. Silencing of synaptic transmission of CL neurons by the vINSIST method delayed the acquisition of CRs but did not affect their presentation rate. The CL plays an important role in the acquisition of associative learning, mostly in relation to the novelty of CS/US association, but not in the expression of CRs.

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)0.000
metaresearch head score (Gemma)0.005
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 score0.009
Threshold uncertainty score0.550

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.103
GPT teacher head0.335
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

Citations54
Published2020
Admission routes1
Has abstractyes

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