Abstract
Movement-evoked fields to passive movements and corticokinematic coherence between limb kinematics and magnetoencephalographic signals can both be used to quantify the degree of cortical processing of proprioceptive afference. We examined in 20 young healthy volunteers whether processing of proprioceptive afference in the primary sensorimotor cortex is modulated by attention directed to the proprioceptive stimulation of the right index finger using a pneumatic-movement actuator to evoke continuous 3-Hz movement for 12 min. The participant attended either to a visual (detected change of fixation cross colour) or movement (detected missing movements) events. The attentional task alternated every 3-min. Coherence was computed between index-finger acceleration and magnetoencephalographic signals, and sustained-movement-evoked fields were averaged with respect to the movement onsets every 333ms. Attention to the proprioceptive stimulation supressed the sensorimotor beta power (by ~12%), enhanced movement-evoked field amplitude (by ~16%) and reduced corticokinematic coherence strength (by ~9%) with respect to the visual task. Coherence peaked at the primary sensorimotor cortex contralateral to the proprioceptive stimulation. Our results indicated that early processing of proprioceptive afference in the primary sensorimotor cortex is modulated by inter-modal directed attention in healthy individuals. Therefore, possible attentional effects on corticokinematic coherence and movement-evoked fields should be considered when using them to study cortical proprioception in conditions introducing attentional variation.
Highlights
IntroductionCortical processing of proprioceptive afference (i.e., from the “movement sensors,” for review see (Proske & Gandevia, 2012) to the primary sensorimotor (SM1) cortex can be examined using precise computer controlled movement actuators, that is, proprioceptive stimulators, in magnetoencephalography (MEG; Alary et al, 2002; Lange et al, 2001; Piitulainen et al, 2015), electroencephalography (EEG; Desmedt & Ozaki, 1991; Mima et al, 1996; Piitulainen et al, 2020) or functional magnetic resonance imaging (MRI; Nurmi et al, 2018; Weiller et al, 1996)
We examined whether processing of proprioceptive afference is modulated by inter-modal directed attention using an MEG-compatible movement actuator to stimulate the proprioceptors of the hand, and Corticokinematic coherence (CKC) and movement-evoked field (MEF) to quantify the consequent proprioceptive processing in the SM1 cortex
Our results indicated that the cortical processing of proprioceptive afference was significantly modulated by the change in the degree of attention to the proprioceptive stimulus, accompanied with significant attentional modulation observed in the SM1 cortex beta power
Summary
Cortical processing of proprioceptive afference (i.e., from the “movement sensors,” for review see (Proske & Gandevia, 2012) to the primary sensorimotor (SM1) cortex can be examined using precise computer controlled movement actuators, that is, proprioceptive stimulators, in magnetoencephalography (MEG; Alary et al, 2002; Lange et al, 2001; Piitulainen et al, 2015), electroencephalography (EEG; Desmedt & Ozaki, 1991; Mima et al, 1996; Piitulainen et al, 2020) or functional magnetic resonance imaging (MRI; Nurmi et al, 2018; Weiller et al, 1996). Corticokinematic coherence (CKC) can be used to quantify the coupling between oscillatory cortical activity measured with electrophysiological recordings (MEG or EEG) and limb kinematics Coherence is correlation in the frequency domain between two signals, and CKC peaks at the movement frequency and its harmonics, and primarily reflects proprioceptive processing in the SM1 cortex (Bourguignon et al, 2015; Piitulainen et al, 2013b). The strength of CKC quantifies the degree of cortical proprioceptive processing and has shown to be associated with motor performance (Piitulainen, Seipäjärvi, et al, 2018b). CKC is a potential clinical tool to detect, examine and follow deficits in cortical proprioceptive processing, for example, in newborn using EEG (Smeds et al, 2017) or in motor impairments such as Friedreich ataxia using MEG (Marty et al, 2019)
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