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Non-invasive electroencephalography in awake cats: Feasibility and application to sensory processing in chronic pain

2024· article· en· W4401750913 on OpenAlexafffund
Aliénor Delsart, Aude Castel, Guillaume Dumas, Colombe Otis, Mathieu Lachance, Maude Barbeau-Grégoire, Bertrand Lussier, Franck Péron, Marc Hébert, Nicolas Lapointe, Maxim Moreau, Johanne Martel‐Pelletier, Jean‐Pierre Pelletier, Éric Troncy

Bibliographic record

VenueJournal of Neuroscience Methods · 2024
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Pharmacology and Anesthesia
Canadian institutionsCanadian Hemophilia SocietyUniversité LavalUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of CanadaInstitut de Valorisation des DonnéesFonds de recherche du QuébecCanada Foundation for InnovationCanadian Institute for Advanced ResearchMorris Animal Foundation
KeywordsElectroencephalographySomatosensory systemChronic painCATSSensory systemOsteoarthritisMedicineNeurosciencePsychologyAnesthesiaPathologyInternal medicine

Abstract

fetched live from OpenAlex

Feline osteoarthritis (OA) leads to chronic pain and somatosensory sensitisation. In humans, sensory exposure can modulate chronic pain. Recently, electroencephalography (EEG) revealed a specific brain signature to human OA. However, EEG pain characterisation or its modulation does not exist in OA cats, and all EEG were conducted in sedated cats, using intradermal electrodes, which could alter sensory (pain) perception. Cats ( n =11) affected by OA were assessed using ten gold-plated surface electrodes. Sensory stimuli were presented in random orders: response to mechanical temporal summation, grapefruit scent and mono-chromatic wavelengths (500 nm-blue, 525 nm-green and 627 nm-red light). The recorded EEG was processed to identify event-related potentials (ERP) and to perform spectral analysis (z-score). The procedure was well-tolerated. The ERPs were reported for both mechanical (F3, C3, Cz, P3, Pz) and olfactory stimuli (Cz, Pz). The main limitation was motion artifacts. Spectral analysis revealed a significant interaction between the power of EEG frequency bands and light wavelengths ( p <0.001). All wavelengths considered, alpha band proportion was higher than that of delta and gamma bands ( p <0.044), while the latter was lower than the beta band ( p <0.016). Compared to green and red, exposure to blue light elicited distinct changes in EEG power over time ( p <0.001). This is the first demonstration of EEG feasibility in conscious cats with surface electrodes recording brain activity while exposing them to sensory stimulations. The identification of ERPs and spectral patterns opens new avenues for investigating feline chronic pain and its potential modulation through sensory interventions. • Electroencephalography (EEG), using surface electrodes, allowed non-invasive recording of brain activity in conscious cats. • Event-related potentials following mechanical and olfactory stimulations were identified in awake cats using EEG. • Visual stimulations correlated with EEG spectral signatures, showed distinct patterns across different light wavelengths. • This method allows to study brain activity in animals affected by chronic pain and its modulation with sensory stimulation.

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)0.005
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.918
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.089
GPT teacher head0.449
Teacher spread0.360 · 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

Citations5
Published2024
Admission routes2
Has abstractyes

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