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Functional brain changes in the elderly for the perception of hand movements: A greater impairment occurs in proprioception than touch

2020· article· en· W3036076246 on OpenAlexaff
Caroline Landelle, Jean‐Luc Anton, Bruno Nazarian, Julien Sein, Ali Gharbi, Olivier Félician, Anne Kavounoudias

Bibliographic record

VenueNeuroImage · 2020
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersCentre National de la Recherche ScientifiqueAgence Nationale de la Recherche
KeywordsProprioceptionPsychologyIllusionSomatosensory systemPerceptionNeurosciencePrecuneusTactile perceptionPhysical medicine and rehabilitationSensationAudiologyCognitionMedicine

Abstract

fetched live from OpenAlex

Unlike age-related brain changes linked to motor activity, neural alterations related to self-motion perception remain unknown. Using fMRI data, we investigated age-related changes in the central processing of somatosensory information by inducing illusions of right-hand rotations with specific proprioceptive and tactile stimulation. Functional connectivity during resting-state (rs-FC) was also compared between younger and older participants. Results showed common sensorimotor activations in younger and older adults during proprioceptive and tactile illusions, but less deactivation in various right frontal regions and the precuneus were found in the elderly. Older participants exhibited a less-lateralized pattern of activity across the primary sensorimotor cortices (SM1) in the proprioceptive condition only. This alteration of the interhemispheric balance correlated with declining individual performance in illusion velocity perception from a proprioceptive, but not a tactile, origin. By combining task-related data, rs-FC and behavioral performance, this study provided consistent results showing that hand movement perception was altered in the elderly, with a more pronounced deterioration of the proprioceptive system, likely due to the breakdown of inhibitory processes with aging. Nevertheless, older people could benefit from an increase in internetwork connectivity to overcome this kinesthetic decline.

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 score0.002
Threshold uncertainty score0.005

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.077
GPT teacher head0.311
Teacher spread0.234 · 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

Citations30
Published2020
Admission routes1
Has abstractyes

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