The Claustrum is Involved in Cognitive Processes Related to the Classical Conditioning of Eyelid Responses in Behaving Rabbits
Bibliographic record
Abstract
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.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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".