Jonathan P Mathias1, Gergely I Barsi2, Mark van de Ruit1, Michael J Grey3. 1. School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Life Sciences, University of Birmingham, UK. 2. Center for Sensory-Motor Interaction (SMI), Department of Health Science and Technology, Aalborg University, Denmark. 3. School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Life Sciences, University of Birmingham, UK; Department of Neuroscience and Pharmacology, Panum Institute, University of Copenhagen, Copenhagen, Denmark. Electronic address: m.j.grey@bham.ac.uk.
Abstract
BACKGROUND: Transcranial magnetic stimulation is frequently used to construct stimulus response (SR) curves in studies of motor learning and rehabilitation. A drawback of the established method is the time required for data acquisition, which is frequently greater than a participant's ability to maintain attention. The technique is therefore difficult to use in the clinical setting. OBJECTIVE: To reduce the time of curve acquisition by determining the minimum acquisition time and number of stimuli required to acquire an SR curve. METHODS: SR curves were acquired from first dorsal interosseous (FDI) and abductor digiti minimi (ADM) at 6 interstimulus intervals (ISI) between 1.4 and 4 s in 12 participants. To determine if low-frequency rTMS might affect the SR curve, MEP amplitudes were monitored before and after 3 min of 1 Hz rTMS delivered at 120% of resting motor threshold in 12 participants. Finally, SR curves were acquired from FDI, ADM and Biceps Brachii (BB) in 12 participants, and the minimum number of stimuli was calculated using a sequential MEP elimination process. RESULTS: There were no significant differences between curves acquired with 1.4 s ISI and any other ISI. Low frequency rTMS did not significantly depress MEP amplitude (P = 0.87). On average, 61 ± 18 (FDI), 60 ± 16 (ADM) and 59 ± 16 (BB) MEPs were needed to construct a representative SR curve. CONCLUSIONS: This study demonstrates that reliable SR curves may be acquired in less than 2 min. At this rate, SR curves become a clinically feasible method for assessing corticospinal excitability in research and rehabilitation settings.
BACKGROUND: Transcranial magnetic stimulation is frequently used to construct stimulus response (SR) curves in studies of motor learning and rehabilitation. A drawback of the established method is the time required for data acquisition, which is frequently greater than a participant's ability to maintain attention. The technique is therefore difficult to use in the clinical setting. OBJECTIVE: To reduce the time of curve acquisition by determining the minimum acquisition time and number of stimuli required to acquire an SR curve. METHODS: SR curves were acquired from first dorsal interosseous (FDI) and abductor digiti minimi (ADM) at 6 interstimulus intervals (ISI) between 1.4 and 4 s in 12 participants. To determine if low-frequency rTMS might affect the SR curve, MEP amplitudes were monitored before and after 3 min of 1 Hz rTMS delivered at 120% of resting motor threshold in 12 participants. Finally, SR curves were acquired from FDI, ADM and Biceps Brachii (BB) in 12 participants, and the minimum number of stimuli was calculated using a sequential MEP elimination process. RESULTS: There were no significant differences between curves acquired with 1.4 s ISI and any other ISI. Low frequency rTMS did not significantly depress MEP amplitude (P = 0.87). On average, 61 ± 18 (FDI), 60 ± 16 (ADM) and 59 ± 16 (BB) MEPs were needed to construct a representative SR curve. CONCLUSIONS: This study demonstrates that reliable SR curves may be acquired in less than 2 min. At this rate, SR curves become a clinically feasible method for assessing corticospinal excitability in research and rehabilitation settings.
Authors: Prisca R Bauer; Annika A de Goede; William M Stern; Adam D Pawley; Fahmida A Chowdhury; Robert M Helling; Romain Bouet; Stiliyan N Kalitzin; Gerhard H Visser; Sanjay M Sisodiya; John C Rothwell; Mark P Richardson; Michel J A M van Putten; Josemir W Sander Journal: Brain Date: 2018-02-01 Impact factor: 13.501
Authors: Elisabetta Peri; Emilia Ambrosini; Vera Maria Colombo; Mark van de Ruit; Michael J Grey; Marco Monticone; Giorgio Ferriero; Alessandra Pedrocchi; Giancarlo Ferrigno; Simona Ferrante Journal: PLoS One Date: 2017-09-14 Impact factor: 3.240