MétaCan
Menu
Back to cohort

Developmental and Interventional Plasticity of Motor Maps after Perinatal Stroke

2021· article· en· W3164193197 on OpenAlexaff
Sarah Y. Zhang, Matthew S. Jeffers, Diane C. Lagace, Adam Kirton, Gergely Silasi

Bibliographic record

VenueJournal of Neuroscience · 2021
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsOntario Brain InstituteAlberta Children's HospitalUniversity of CalgaryOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsForelimbNeuroplasticityNeuroscienceOptogeneticsPhysical medicine and rehabilitationStroke (engine)Motor skillMedicinePsychology

Abstract

fetched live from OpenAlex

Within the perinatal stroke field, there is a need to establish preclinical models where putative biomarkers for motor function can be examined. In a mouse model of perinatal stroke, we evaluated motor map size and movement latency following optogenetic cortical stimulation against three factors of post-stroke biomarker utility: (1) correlation to chronic impairment on a behavioral test battery; (2) amenability to change using a skilled motor training paradigm; and (3) ability to distinguish individuals with potential to respond well to training. Thy1-ChR2-YFP mice received a photothrombotic stroke at postnatal day 7 and were evaluated on a battery of motor tests between days 59 and 70. Following a cranial window implant, mice underwent longitudinal optogenetic motor mapping both before and after 3 weeks of skilled forelimb training. Map size and movement latency of both hemispheres were positively correlated with impaired spontaneous forelimb use, whereas only ipsilesional hemisphere map size was correlated with performance in skilled reaching. Map size and movement latency did not show groupwise changes with training; however, mice with the smallest pretraining map sizes and worst impairments demonstrated the greatest expansion of map size in response to skilled forelimb training. Overall, motor map size showed utility as a potential biomarker for impairment and training-induced modulation in specific individuals. Future assessment of the predictive capacity of post-stroke motor representations for behavioral outcome in animal models opens the possibility of dissecting how plasticity mechanisms contribute to recovery following perinatal stroke. SIGNIFICANCE STATEMENT We investigated the utility of two cortical motor representation measures (motor map size and movement onset latency) as potential biomarkers for post-stroke motor recovery in a mouse model of perinatal stroke. Both motor map size and movement latency were associated with functional recovery after perinatal stroke, with map size showing an additional association between training responsiveness and severity of impairment. Overall, both motor map size and movement onset latency show potential as neurophysiological correlates of recovery. As such, future studies of perinatal stroke rehabilitation and neuromodulation should include these measures to help explain neurophysiological changes that might be occurring in response to treatment.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.046
GPT teacher head0.311
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of NeuroscienceSame topicPhotoreceptor and optogenetics researchFrench-language works237,207