Cargando…

Neurophysiological Markers of Premotor–Motor Network Plasticity Predict Motor Performance in Young and Older Adults

Aging is commonly associated with a decline in motor control and neural plasticity. Tuning cortico–cortical interactions between premotor and motor areas is essential for controlling fine manual movements. However, whether plasticity in premotor–motor circuits predicts hand motor abilities in young...

Descripción completa

Detalles Bibliográficos
Autores principales: Turrini, Sonia, Bevacqua, Naomi, Cataneo, Antonio, Chiappini, Emilio, Fiori, Francesca, Battaglia, Simone, Romei, Vincenzo, Avenanti, Alessio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10216324/
https://www.ncbi.nlm.nih.gov/pubmed/37239135
http://dx.doi.org/10.3390/biomedicines11051464
_version_ 1785048271005155328
author Turrini, Sonia
Bevacqua, Naomi
Cataneo, Antonio
Chiappini, Emilio
Fiori, Francesca
Battaglia, Simone
Romei, Vincenzo
Avenanti, Alessio
author_facet Turrini, Sonia
Bevacqua, Naomi
Cataneo, Antonio
Chiappini, Emilio
Fiori, Francesca
Battaglia, Simone
Romei, Vincenzo
Avenanti, Alessio
author_sort Turrini, Sonia
collection PubMed
description Aging is commonly associated with a decline in motor control and neural plasticity. Tuning cortico–cortical interactions between premotor and motor areas is essential for controlling fine manual movements. However, whether plasticity in premotor–motor circuits predicts hand motor abilities in young and elderly humans remains unclear. Here, we administered transcranial magnetic stimulation (TMS) over the ventral premotor cortex (PMv) and primary motor cortex (M1) using the cortico–cortical paired-associative stimulation (ccPAS) protocol to manipulate the strength of PMv-to-M1 connectivity in 14 young and 14 elderly healthy adults. We assessed changes in motor-evoked potentials (MEPs) during ccPAS as an index of PMv-M1 network plasticity. We tested whether the magnitude of MEP changes might predict interindividual differences in performance in two motor tasks that rely on premotor-motor circuits, i.e., the nine-hole pegboard test and a choice reaction task. Results show lower motor performance and decreased PMv-M1 network plasticity in elderly adults. Critically, the slope of MEP changes during ccPAS accurately predicted performance at the two tasks across age groups, with larger slopes (i.e., MEP increase) predicting better motor performance at baseline in both young and elderly participants. These findings suggest that physiological indices of PMv-M1 plasticity could provide a neurophysiological marker of fine motor control across age-groups.
format Online
Article
Text
id pubmed-10216324
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-102163242023-05-27 Neurophysiological Markers of Premotor–Motor Network Plasticity Predict Motor Performance in Young and Older Adults Turrini, Sonia Bevacqua, Naomi Cataneo, Antonio Chiappini, Emilio Fiori, Francesca Battaglia, Simone Romei, Vincenzo Avenanti, Alessio Biomedicines Article Aging is commonly associated with a decline in motor control and neural plasticity. Tuning cortico–cortical interactions between premotor and motor areas is essential for controlling fine manual movements. However, whether plasticity in premotor–motor circuits predicts hand motor abilities in young and elderly humans remains unclear. Here, we administered transcranial magnetic stimulation (TMS) over the ventral premotor cortex (PMv) and primary motor cortex (M1) using the cortico–cortical paired-associative stimulation (ccPAS) protocol to manipulate the strength of PMv-to-M1 connectivity in 14 young and 14 elderly healthy adults. We assessed changes in motor-evoked potentials (MEPs) during ccPAS as an index of PMv-M1 network plasticity. We tested whether the magnitude of MEP changes might predict interindividual differences in performance in two motor tasks that rely on premotor-motor circuits, i.e., the nine-hole pegboard test and a choice reaction task. Results show lower motor performance and decreased PMv-M1 network plasticity in elderly adults. Critically, the slope of MEP changes during ccPAS accurately predicted performance at the two tasks across age groups, with larger slopes (i.e., MEP increase) predicting better motor performance at baseline in both young and elderly participants. These findings suggest that physiological indices of PMv-M1 plasticity could provide a neurophysiological marker of fine motor control across age-groups. MDPI 2023-05-17 /pmc/articles/PMC10216324/ /pubmed/37239135 http://dx.doi.org/10.3390/biomedicines11051464 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Turrini, Sonia
Bevacqua, Naomi
Cataneo, Antonio
Chiappini, Emilio
Fiori, Francesca
Battaglia, Simone
Romei, Vincenzo
Avenanti, Alessio
Neurophysiological Markers of Premotor–Motor Network Plasticity Predict Motor Performance in Young and Older Adults
title Neurophysiological Markers of Premotor–Motor Network Plasticity Predict Motor Performance in Young and Older Adults
title_full Neurophysiological Markers of Premotor–Motor Network Plasticity Predict Motor Performance in Young and Older Adults
title_fullStr Neurophysiological Markers of Premotor–Motor Network Plasticity Predict Motor Performance in Young and Older Adults
title_full_unstemmed Neurophysiological Markers of Premotor–Motor Network Plasticity Predict Motor Performance in Young and Older Adults
title_short Neurophysiological Markers of Premotor–Motor Network Plasticity Predict Motor Performance in Young and Older Adults
title_sort neurophysiological markers of premotor–motor network plasticity predict motor performance in young and older adults
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10216324/
https://www.ncbi.nlm.nih.gov/pubmed/37239135
http://dx.doi.org/10.3390/biomedicines11051464
work_keys_str_mv AT turrinisonia neurophysiologicalmarkersofpremotormotornetworkplasticitypredictmotorperformanceinyoungandolderadults
AT bevacquanaomi neurophysiologicalmarkersofpremotormotornetworkplasticitypredictmotorperformanceinyoungandolderadults
AT cataneoantonio neurophysiologicalmarkersofpremotormotornetworkplasticitypredictmotorperformanceinyoungandolderadults
AT chiappiniemilio neurophysiologicalmarkersofpremotormotornetworkplasticitypredictmotorperformanceinyoungandolderadults
AT fiorifrancesca neurophysiologicalmarkersofpremotormotornetworkplasticitypredictmotorperformanceinyoungandolderadults
AT battagliasimone neurophysiologicalmarkersofpremotormotornetworkplasticitypredictmotorperformanceinyoungandolderadults
AT romeivincenzo neurophysiologicalmarkersofpremotormotornetworkplasticitypredictmotorperformanceinyoungandolderadults
AT avenantialessio neurophysiologicalmarkersofpremotormotornetworkplasticitypredictmotorperformanceinyoungandolderadults