Abstract

The agonist–antagonist myoneural interface (AMI) is an amputation surgery that preserves sensorimotor signaling mechanisms of the central-peripheral nervous systems. Our first neuroimaging study investigating AMI subjects conducted by Srinivasan et al. (2020) focused on task-based neural signatures, and showed evidence of proprioceptive feedback to the central nervous system. The study of resting state neural activity helps non-invasively characterize the neural patterns that prime task response. In this study on resting state functional magnetic resonance imaging in AMI subjects, we compared functional connectivity in patients with transtibial AMI (n = 12) and traditional (n = 7) amputations (TA). To test our hypothesis that we would find significant neurophysiological differences between AMI and TA subjects, we performed a whole-brain exploratory analysis to identify a seed region; namely, we conducted ANOVA, followed by t-test statistics to locate a seed in the salience network. Then, we implemented a seed-based connectivity analysis to gather cluster-level inferences contrasting our subject groups. We show evidence supporting our hypothesis that the AMI surgery induces functional network reorganization resulting in a neural configuration that significantly differs from the neural configuration after TA surgery. AMI subjects show significantly less coupling with regions functionally dedicated to selecting where to focus attention when it comes to salient stimuli. Our findings provide researchers and clinicians with a critical mechanistic understanding of the effect of AMI amputation on brain networks at rest, which has promising implications for improved neurorehabilitation and prosthetic control.

Details

Title
Resting state neurophysiology of agonist–antagonist myoneural interface in persons with transtibial amputation
Author
Chicos, Laura A. 1 ; Rangaprakash, D. 2 ; Srinivasan, Shriya S. 3 ; Gutierrez-Arango, Samantha 1 ; Song, Hyungeun 4 ; Barry, Robert L. 5 ; Herr, Hugh M. 6 

 Massachusetts Institute of Technology, Biomechatronics Group, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Massachusetts Institute of Technology, K. Lisa Yang Center for Bionics, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) 
 Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, USA (GRID:grid.32224.35) (ISNI:0000 0004 0386 9924); Harvard Medical School, Department of Radiology, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X) 
 Harvard–MA Institute of Technology Division of Health Sciences and Technology, Cambridge, USA (GRID:grid.413735.7) (ISNI:0000 0004 0475 2760); Harvard University, John A. Paulson School of Engineering and Applied Sciences, Allston, USA (GRID:grid.38142.3c) (ISNI:0000 0004 1936 754X) 
 Massachusetts Institute of Technology, Biomechatronics Group, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Massachusetts Institute of Technology, K. Lisa Yang Center for Bionics, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Harvard–MA Institute of Technology Division of Health Sciences and Technology, Cambridge, USA (GRID:grid.413735.7) (ISNI:0000 0004 0475 2760) 
 Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, USA (GRID:grid.32224.35) (ISNI:0000 0004 0386 9924); Harvard Medical School, Department of Radiology, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); Harvard–MA Institute of Technology Division of Health Sciences and Technology, Cambridge, USA (GRID:grid.413735.7) (ISNI:0000 0004 0475 2760) 
 Massachusetts Institute of Technology, Biomechatronics Group, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Massachusetts Institute of Technology, K. Lisa Yang Center for Bionics, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Massachusetts Institute of Technology, McGovern Institute for Brain Research, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) 
Pages
13456
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3066605419
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.