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Record W2034313429 · doi:10.1093/brain/aws373

Motor cortex and gait in mild cognitive impairment: a magnetic resonance spectroscopy and volumetric imaging study

2013· article· en· W2034313429 on OpenAlexafffund
Cédric Annweiler, Olivier Beauchet, Robert Bartha, Jennie Wells, Michael Borrie, Vladimir Hachinski, Manuel Montero‐Odasso

Bibliographic record

VenueBrain · 2013
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsParkwood InstituteSt Joseph's Health CareLawson Health Research InstituteWestern University
FundersSchulich School of Medicine and DentistrySchulich School of Medicine and Dentistry, Western University
KeywordsCreatinePrimary motor cortexGaitPhysical medicine and rehabilitationDementiaPsychologyPremotor cortexMedicineMotor cortexMagnetic resonance imagingCognitionNeuroscienceInternal medicineAnatomyRadiology

Abstract

fetched live from OpenAlex

Gait disorders are common in the course of dementia, even at the stage of mild cognitive impairment, owing to probable changes in higher levels of motor control. Since motor control message is ultimately supported in the brain by the primary motor cortex and since cortical lesions are frequent in the dementia process, we hypothesized that impairments of the primary motor cortex may explain the early gait disorders observed in mild cognitive impairment. Our purpose was to determine whether the neurochemistry of the primary motor cortex measured with proton magnetic resonance spectroscopy, and its volume, were associated with gait performance while single and dual-tasking in mild cognitive impairment. Twenty community dwellers with mild cognitive impairment, aged 76 years (11) [median (interquartile range)] (30% female) from the 'Gait and Brain Study' were included in this analysis. Gait velocity and stride time variability were measured while single (i.e. walking alone) and dual tasking (i.e. walking while counting backwards by seven) using an electronic walkway (GAITRite System). Ratios of N-acetyl aspartate to creatine and choline to creatine and cortical volume were calculated in the primary motor cortex. Participants were categorized according to median N-acetyl aspartate to creatine and choline to creatine ratios. Age, gender, body mass index, cognition, education level and subcortical vascular burden were used as potential confounders. Participants with low N-acetyl aspartate to creatine (n = 10) had higher (worse) stride time variability while dual tasking than those with high N-acetyl aspartate to creatine (P = 0.007). Those with high choline to creatine had slower (worse) gait velocity while single (P = 0.015) and dual tasking (P = 0.002). Low N-acetyl aspartate to creatine was associated with increased stride time variability while dual tasking (adjusted β = 5.51, P = 0.031). High choline to creatine was associated with slower gait velocity while single (adjusted β = -26.56, P = 0.009) and dual tasking (adjusted β = -41.92, P = 0.022). Cortical volume correlated with faster gait velocity while single (P = 0.029) and dual tasking (P = 0.037), and with decreased stride time variability while single tasking (P = 0.034). Finally, the probability of exhibiting abnormal metabolite ratios in the primary motor cortex was 63% higher among participants with major gait disturbances in dual task. Those with compromised gait velocity in dual task had a 2.05-fold greater risk of having a smaller cortical volume. In conclusion, the neurochemistry and volume of the primary motor cortex were associated with gait performance while single and dual tasking. Stride time variability was mainly sensitive to neuronal function (N-acetyl aspartate to creatine), whereas gait velocity was more affected by inflammatory damage (choline to creatine) and volumetric changes. These findings may contribute to a better understanding of the higher risks of mobility decline and falls in subjects with mild cognitive impairment.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
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 head0.015
GPT teacher head0.254
Teacher spread0.239 · 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 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

Citations110
Published2013
Admission routes2
Has abstractyes

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