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Record W4322617774 · doi:10.7554/elife.78729

Sensory input-dependent gain modulation of the optokinetic nystagmus by mid-infrared stimulation in pigeons

2023· article· en· W4322617774 on OpenAlexfundno aff
Tong Xiao, Kaijie Wu, Peiliang Wang, Yali Ding, Xiao Yang, Chao Chang, Yan Yang

Bibliographic record

VenueeLife · 2023
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsnot available
FundersYork University
KeywordsNeuroscienceOptokinetic reflexPretectal areaSensory systemStimulationPsychologyNeuromodulationPremovement neuronal activityBiologyEye movementMidbrainCentral nervous system

Abstract

fetched live from OpenAlex

Neuromodulation serves as a cornerstone for brain sciences and clinical applications. Recent reports suggest that mid-infrared stimulation (MIRS) causes non-thermal modulation of brain functions. Current understanding of its mechanism hampers the routine application of MIRS. Here, we examine how MIRS influences the sensorimotor transformation in awaking-behaving pigeons, from neuronal signals to behavior. We applied MIRS and electrical stimulation (ES) to the pretectal nucleus lentiformis mesencephali (nLM), an essential retinorecipient structure in the pretectum, and examined their influences on the optokinetic nystagmus, a visually guided eye movement. We found MIRS altered eye movements by modulating a specific gain depending on the strength of visual inputs, in a manner different than the effect of ES. Simultaneous extracellular recordings and stimulation showed that MIRS could either excite and inhibit the neuronal activity in the same pretectal neuron depending on its ongoing sensory responsiveness levels in awake-behaving animals. Computational simulations suggest that MIRS modulates the resonance of a carbonyl group of the potassium channel, critical to the action potential generation, altering neuronal responses to sensory inputs and as a consequence, guiding behavior. Our findings suggest that MIRS could be a promising approach toward modulating neuronal functions for brain research and treating neurological diseases.

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)0.001
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 score0.119
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.050
GPT teacher head0.322
Teacher spread0.272 · 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

Citations48
Published2023
Admission routes1
Has abstractyes

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