Cortically Mediated Muscle Responses to Balance Perturbations Increase with Perturbation Magnitude in Older Adults with and without Parkinson's Disease.
The 5 matches · all tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
- [1] § Materials and Methods › Model parameter identification ↔ fitResidualSRM_CoM.m, the whole file · a weak match · score 0.83 · upper bounds, initial guess, MaxFunEvals, TolFun, TolX, fmincon
- [2] § Materials and Methods › Model parameter identification ↔ fitResidualSRM_eeg.m, the whole file · a weak match · score 0.83 · upper bounds, initial guess, MaxFunEvals, TolFun, TolX, fmincon
- [3] § Materials and Methods › Goodness of fit ↔ rsqr_uncentered.m, the whole file · a weak match · score 0.59 · uncentered correlation coefficient, regress, square, reconstructions
- [4] § Materials and Methods › Model parameter identification ↔ modelIPI.m, the whole file · a weak match · score 0.58 · squared error, penalizes, minimize, fmincon, optimizations, weighted
- [5] § Results › Correlations to clinical measures ↔ plotExemplarSRMFits.m, the whole file · a weak match · score 0.57 · MDS UPDRS III, PD duration
Paper
Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC
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The authors' code
MATLAB · 43 lines · 1.5 KB · no license · 1 match
- function [xBraking, eBraking, fitsBraking] = fitResidualSRM_CoM(e,atime,predictors,subjID,magnitude,LB,UB)
- % fit residuals using beta power.
- % load optimization options. these include overall cost function options as
- % well as direct options for the Matlab optimizer.
- optimizationParameters = loadOptimizationParameters();
- options = optimoptions('fmincon',...
- 'display',optimizationParameters.display,...
- 'TolX',optimizationParameters.TolX,...
- 'TolFun',optimizationParameters.TolFun,...
- 'MaxFunEvals',optimizationParameters.MaxFunEvals...
- );
- %Initial guess is midpoint of lower and upper bounds (LB and UB, respectively)
- X0 = (UB-LB)/2;
- gainFlag = [true true true false];
- if (strcmp(subjID,'HOA19') & magnitude == 7.5)
- X0(end) = 0.200; %manually set ctx CoM delay
- UB(end) = 0.250;
- end
- fixBurstGain = true;
- if fixBurstGain
- burstGain = max(e(1,atime>0.150&atime<0.600))/max(predictors(1,:));
- [X0(1),UB(1)] = deal(max(min(burstGain,15),0));
- LB(1) = 0.9 * X0(1);
- end
- [X,FVAL,EXITFLAG] = fmincon(@(X) jigsawPassthrough(X,predictors,gainFlag,atime,e,optimizationParameters),X0,[],[],[],[],LB,UB,[],options);
- xBraking = X;
- eBraking = assembleChannel(predictors,X(gainFlag),X(~gainFlag),atime);
- fitParameters = modelIPI('X',X,'eRecon',eBraking,'e',e,'optimizationParameters',optimizationParameters,'gainWeight',double(gainFlag));
- fitsBraking(1) = fitParameters.r2;
- fitsBraking(2) = fitParameters.r2u;
- fitsBraking(isnan(fitsBraking)) = 0;
- end % fit residusls w/ coM
fitResidualSRM_CoM.m at commit 0e0b94b, no license · at the source
Overview
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, Georgia 30322
- Department of Physical Therapy, College of Health Sciences and Professions, Ohio University, Athens, Ohio 45701
- Department of Biomedical Sciences, University of Padova, Padua 35131, Italy
- Division of Physical Therapy, Department of Rehabilitation Medicine, Emory University, Atlanta, Georgia 30322
- Department of Neurology, Emory University, Atlanta, Georgia 30322
- Department of Biomedical Informatics, Emory University, Atlanta, Georgia 30322
Abstract
We lack a mechanistic understanding of how cortical contributions to balance control change in aging and Parkinson's disease (PD). Balance is governed by brainstem circuits, with higher-order centers like the cortex or basal ganglia becoming engaged as challenge increases or balance health declines. We previously showed that parallel sensorimotor feedback loops engaging brainstem and cortical circuitry contribute to muscle activity for balance control in young adults (YAs). Here, we analyze data from male and female older adults (OAs) with and without PD, decomposing perturbation-evoked tibialis anterior and medial gastrocnemius muscle activity into hierarchical components based on latencies of feedback control loops. We found that balance-correcting muscle activity followed a stereotypical waveform of long-latency responses (LLRs): LLR1 began ∼120 ms and LLR2 occurred ∼210 ms, respectively, consistent with subcortical and cortical feedback latencies. Both LLRs increased with balance challenge and could be explained by center of mass kinematics. Perturbation-evoked antagonist muscle activity consisted of destabilizing and stabilizing components categorized based on whether they resist the kinematic errors that drive their activation. The destabilizing component occurred at ∼180 ms and was negatively correlated with clinical measures of balance ability in the OA but not PD group. Exploratory comparisons showed OA and PD groups had larger LLR2s at lower challenge levels than YAs, consistent with greater cortical engagement during balance with aging. These findings demonstrate that a neuromechanical model can decompose perturbation-evoked muscle activity into hierarchical components related to clinical balance ability and identify mechanistic changes in the neural control of balance without direct brain measurements.
Reproduced under the paper's license (CC BY), from the paper cited above.
Repository
Its files are read in the Code ↔ Paper reader above, with 5 matches between paragraphs and lines of code.
Neuromechanics-Lab/HOA_PD_SRM
0e0b94baa0d23d4514724d78040999dff2f98a75, 18 November 2025Availability: 1 check, the latest on 28 September 2026: the link answers
- 28 September 2026: the link answers
46 files
- CreateEEGDataTable.m, MATLAB, 72 lines
- EpochEEG.m, MATLAB, 30 lines
- HOA_PD_AIC_Analysis.m, MATLAB, 92 lines
- HOA_PD_ConcatinateEEGand
EMGDataTables.m , MATLAB, 53 lines - HOA_PD_SRM.m, MATLAB, 465 lines
- HOA_PD_SRM_Analysis.m, MATLAB, 463 lines
- HOA_PD_SRM_AntagComp_AUC
_Analysis.m , MATLAB, 78 lines - HOA_PD_SRM_CompareReconA
ccuracies.m , MATLAB, 48 lines - HOA_PD_SRM_HandFit.m, MATLAB, 272 lines
- HOA_PD_calculateCoMExcur
sion.m , MATLAB, 41 lines - HYA_SRM_ctxAUC.m, MATLAB, 170 lines
- InterpolateAndNormalizeE
EG.m , MATLAB, 96 lines - ModifyEegEvents.m, MATLAB, 78 lines
- Plot_Ag_Antag_EMG.m, MATLAB, 87 lines
- Plot_SRM_Recons.m, MATLAB, 266 lines
- Plot_SRM_methods_fig.m, MATLAB, 73 lines
- Stats_For_OA_PD_Manuscri
pt.R , R, 2,714 lines - Stats_For_OA_PD_Manuscri
pt_reviewerRequests.R , R, 1,213 lines - Stats_YA_HOA_PD_SRM_AUC_
allGroups.R , R, 304 lines - assembleChannel.m, MATLAB, 3 lines
- assembleChannelComponent
s.m , MATLAB, 14 lines - assembleTwoChannels.m, MATLAB, 10 lines
- calculateExemplarSRMFits
.m , MATLAB, 49 lines - calculateSRMFits.m, MATLAB, 78 lines
- channelDelay.m, MATLAB, 3 lines
- fitBrakingSRM.m, MATLAB, 46 lines
- fitDestabilizingSRM.m, MATLAB, 55 lines
- fitResidualSRM_CoM.m, MATLAB, 43 lines, 1 match
- fitResidualSRM_eeg.m, MATLAB, 38 lines, 1 match
- fitTotalDualSRM_CoM.m, MATLAB, 74 lines
- fitTotalDualSRM_eeg.m, MATLAB, 53 lines
- fitTotalSRM.m, MATLAB, 58 lines
- fitTraditionalSRM.m, MATLAB, 66 lines
- fitTraditionalSRM_DualSR
M.m , MATLAB, 141 lines - fitTraditionalSRM_eeg.m, MATLAB, 45 lines
- jigsawPassthrough.m, MATLAB, 11 lines
- jigsawTwoChannelPassthro
ugh.m , MATLAB, 15 lines - loadOptimizationParamete
rs.m , MATLAB, 10 lines - makeDelayFigure.m, MATLAB, 12 lines
- modelIPI.m, MATLAB, 49 lines, 1 match
- names.m, MATLAB, 3 lines
- plotExemplarSRMFits.m, MATLAB, 98 lines, 1 match
- rsqr.m, MATLAB, 57 lines
- rsqr_uncentered.m, MATLAB, 30 lines, 1 match
- stictionTemplate.m, MATLAB, 58 lines
- threshold.m, MATLAB, 3 lines
Code accessibility
The custom code used for neuromechanical modeling, figure generation, and statistical analysis is freely available on GitHub via https://
Reproduced under the paper's license (CC BY), from the paper cited above.
Tracing map
Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.
What the map holds:
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- 46 scripts, each with its path and the digest of its content;
- 5 matches between paragraphs of the paper and lines of the code (method lexical-v1);
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Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.
Data
No dataset and no data link were found in the paper.
Versions
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Version 1, 28 September 2026: the first record
Recorded: type, language, journal, volume, issue, pages, dates, 7 authors, 5 keywords, 12 MeSH terms, 3 funders, 64 references.
Cite
This paper
Boebinger, S. E., Payne, A. M., Xiao, J., Martino, G., Borich, M. R., Lucas McKay, J., & Ting, L. H. (2026). Cortically Mediated Muscle Responses to Balance Perturbations Increase with Perturbation Magnitude in Older Adults with and without Parkinson's Disease. eNeuro, 13(4), ENEURO.0423-25.2026. https://
BibTeX
@article{boebinger2026co
author = {Boebinger, Scott E and Payne, Aiden M and Xiao, Jifei and Martino, Giovanni and Borich, Michael R and Lucas McKay, J and Ting, Lena H},
title = {{Cortically Mediated Muscle Responses to Balance Perturbations Increase with Perturbation Magnitude in Older Adults with and without Parkinson's Disease}},
journal = {eNeuro},
year = {2026},
month = apr,
volume = {13},
number = {4},
pages = {ENEURO.0423--25.2026},
publisher = {Society for Neuroscience},
issn = {2373-2822},
doi = {10.1523/
url = {https://
pmid = {41871956},
pmcid = {PMC13064419}
}
RIS
TY - JOUR
AU - Boebinger, Scott E
AU - Payne, Aiden M
AU - Xiao, Jifei
AU - Martino, Giovanni
AU - Borich, Michael R
AU - Lucas McKay, J
AU - Ting, Lena H
TI - Cortically Mediated Muscle Responses to Balance Perturbations Increase with Perturbation Magnitude in Older Adults with and without Parkinson's Disease
T2 - eNeuro
J2 - eNeuro
PY - 2026
DA - 2026/
VL - 13
IS - 4
SP - ENEURO.0423
EP - 25.2026
SN - 2373-2822
PB - Society for Neuroscience
DO - 10.1523/
UR - https://
LA - en
ER -
CSL-JSON
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"container-title": "eNeuro",
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