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Record W3106580826 · doi:10.1101/2020.11.30.404525

Freely behaving mice can brake and turn during optogenetic stimulation of the Mesencephalic Locomotor Region

2020· preprint· en· W3106580826 on OpenAlexafffund
Cornelis Immanuel van der Zouwen, Joël Boutin, Maxime Fougère, Aurélie Flaive, Mélanie Vivancos, Alessandro Santuz, Turgay Akay, Philippe Sarret, Dimitri Ryczko

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsDalhousie UniversityCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
FundersFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsOptogeneticsNeuroscienceChannelrhodopsinStimulationPhotostimulationGlutamatergicMicrostimulationNeuromodulationBiologyGlutamate receptor

Abstract

fetched live from OpenAlex

A bstract Background Stimulation of the Mesencephalic Locomotor Region ( MLR ) is increasingly considered as a target to improve locomotor function in Parkinson’s disease, spinal cord injury and stroke. A key function of the MLR is to control the speed of forward symmetrical locomotor movements. However, the ability of freely moving mammals to integrate environmental cues to brake and turn during MLR stimulation is poorly documented. Objective/hypothesis We investigated whether freely behaving mice could brake or turn based on environmental cues during MLR stimulation. Methods We stimulated the cuneiform nucleus in mice expressing channelrhodopsin in Vglut2-positive neurons in a Cre-dependent manner (Vglut2-ChR2-EYFP) using optogenetics. We detected locomotor movements using deep learning. We used patch-clamp recordings to validate the functional expression of channelrhodopsin and neuroanatomy to visualize the stimulation sites. Results Optogenetic stimulation of the MLR evoked locomotion and increasing laser power increased locomotor speed. Gait diagram and limb kinematics were similar during spontaneous and optogenetic-evoked locomotion. Mice could brake and make sharp turns (∼90⁰) when approaching a corner during MLR stimulation in an open-field arena. The speed during the turn was scaled with the speed before the turn, and with the turn angle. In a reporter mouse, many Vglut2-ZsGreen neurons were immunopositive for glutamate in the MLR. Patch-clamp recordings in Vglut2-ChR2-EYFP mice show that blue light evoked short latency spiking in MLR neurons. Conclusion MLR glutamatergic neurons are a relevant target to improve locomotor activity without impeding the ability to brake and turn when approaching an obstacle, thus ensuring smooth and adaptable navigation. H ighlights - Mice brake and turn when approaching the arena’s corner during MLR-evoked locomotion - Speed decrease is scaled to speed before the turn during MLR-evoked locomotion - Turn angle is scaled to turn speed during MLR-evoked locomotion - Gait and limb kinematics are similar during spontaneous and MLR-evoked locomotion

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 categoriesMeta-epidemiology (narrow)
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 score0.230
Threshold uncertainty score1.000

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 science0.0010.001
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 head0.037
GPT teacher head0.257
Teacher spread0.219 · 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.

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

Citations7
Published2020
Admission routes2
Has abstractyes

Explore more

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