Evidence map›Paper›PMID 39287879›Full record

ArticleGeroScience2025

Age-related breakdown in networks of inter-muscular coordination.

Sergi Garcia-Retortillo, Óscar Abenza, Fidanka Vasileva, Natàlia Balagué, Robert Hristovski, Andrew Wells, Jason Fanning, Jeff Kattula, Plamen Ch Ivanov

Abstract read
In one paragraph

Article in GeroScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
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  3. Observational
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  5. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Sergi Garcia-RetortilloDepartment of Health and Exercise Science, Wake Forest University, Winston-Salem, NC, 27190, USA.ORCID 0000-0002-4867-1589
Óscar AbenzaComplex Systems in Sport, INEFC University of Barcelona, 08038, Barcelona, Spain.ORCID 0000-0003-4735-1855
Fidanka VasilevaUniversity School of Health and Sport, University of Girona, Girona, Spain.ORCID 0000-0002-0057-9329
Natàlia BalaguéComplex Systems in Sport, INEFC University of Barcelona, 08038, Barcelona, Spain.ORCID 0000-0001-5076-9166
Robert HristovskiComplex Systems in Sport, INEFC University of Barcelona, 08038, Barcelona, Spain.ORCID 0000-0001-6805-2833
Andrew WellsDepartment of Health and Exercise Science, Wake Forest University, Winston-Salem, NC, 27190, USA.
Jason FanningDepartment of Health and Exercise Science, Wake Forest University, Winston-Salem, NC, 27190, USA.ORCID 0000-0002-5527-1698
Jeff KattulaDepartment of Health and Exercise Science, Wake Forest University, Winston-Salem, NC, 27190, USA.ORCID 0000-0003-2009-2443
Plamen Ch IvanovKeck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, 02215, USA. plamen@buphy.bu.edu.ORCID 0000-0001-7629-762X

Funding

Translational Science Center, Wake Forest University ID0576--590006-U05244United States - Israel Binational Science Foundation BSF Grant 2020020
6 · The paper itself

Abstract

Assessing inter-muscular coordination in older adults is crucial, as it directly impacts an individual's ability for independent functioning, injury prevention, and active engagement in daily activities. However, the precise mechanisms by which distinct muscle fiber types synchronize their activity across muscles to generate coordinated movements in older adults remain unknown. Our objective is to investigate how distinct muscle groups dynamically synchronize with each other in young and older adults during exercise. Thirty-five young adults and nine older adults performed one bodyweight squat set until exhaustion. Simultaneous surface electromyography (sEMG) recordings were taken from the left and right vastus lateralis, and left and right erector spinae. To quantify inter-muscular coordination, we first obtained ten time series of sEMG band power for each muscle, representing the dynamics of different muscle fiber types. Next, we calculated the bivariate equal-time Pearson's cross-correlation for each pair of sEMG band power time series across all leg and back muscles. The main results show (i) an overall reduction in the degree of inter-muscular coordination, and (ii) increased stratification of the inter-muscular network in older adults compared to young adults. These findings suggest that as individuals age, the global inter-muscular network becomes less flexible and adaptable, hindering its ability to reorganize effectively in response to fatigue or other stimuli. This network approach opens new avenues for developing novel network-based markers to characterize multilevel inter-muscular interactions, which can help target functional deficits and potentially reduce the risk of falls and neuro-muscular injuries in older adults.

Indexed as

AgingExerciseMuscle, SkeletalAdultAgedElectromyographyFemaleHumansMaleYoung AdultAgingComplex systemsInter-muscular coordinationMuscle fibersNetwork physiologySkeletal muscles

Identifiers

PMID39287879
PMCPMC11978574

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.