Steady-state evoked potentials distinguish brain mechanisms of self-paced versus synchronization finger tapping

Abstract

Sensorimotor synchronization (SMS) requires aligning motor actions to external events and represents a core part of both musical and dance performances. In the current study, to isolate the brain mechanisms involved in synchronizing finger tapping with a musical beat, we compared SMS to pure self-paced finger tapping and listen-only conditions at different tempi. We analyzed EEG data using frequency domain steady-state evoked potentials (SSEPs) to identify sustained electrophysiological brain activity during repetitive tasks. Behavioral results revealed different timing modes between SMS and self-paced finger tapping, associated with distinct scalp topographies, thus suggesting different underlying brain sources. After subtraction of the listen-only brain activity, SMS was compared to self-paced finger tapping. Resulting source estimations showed stronger activation of the left inferior frontal gyrus during SMS, and stronger activation of the bilateral inferior parietal lobule during self-paced finger tapping. These results point to the left inferior frontal gyrus as a pivot for perception-action coupling. We discuss our findings in the context of the ongoing debate about SSEPs interpretation given the variety of brain events contributing to SSEPs and similar EEG frequency responses.

Spontaneous and stimulus-driven rhythmic behaviors in ADHD adults and controls

“…Thus, the key distinction between spontaneous tapping and synchronization is whether they are guided by an internal or external pace. This is also reflected in the differential neural engagement of components within the 'temporal hub' in these two types of behaviors (Bichsel et al, 2018;Chauvigné et al, 2014;De Pretto et al, 2018). Supporting a dissociation between neural mechanisms that are critical for self-paced and synchronization tapping, lesions and brain-stimulation studies have shown that the cerebellum and premotor cortex are important for auditory-motor synchronization, but their impairment does not affect generation of self-paced rhythms (Kornysheva & Schubotz, 2011;Schwartze et al, 2016).…”

Neural entrainment facilitates duplets: Frequency-tagging differentiates musicians and non-musicians when they tap to the beat

“…Higher-order oscillations in EEG/MEG recordings reflect the integration of exogenous (bottom-up) and endogenous (top-down) processes underlying the perception and prediction of the beat and its metrical grouping (Nozaradan et al, 2011;Fujioka, Zendel & Ross, 2010;Stupacher et al, 2016;Celma-Miralles, de Menezes & Toro, 2016). In fact, neural entrainment is not just a reflection of the physical signal (Pretto, Deiber & James, 2018) but involves the selection and enhancement of relevant frequencies of the signal, such as the beat of complex syncopated rhythms (Nozaradan, Peretz & Keller, 2016;Tal et al, 2017), the periodic pulses of naturalistic musical excerpts (Tierney & Kraus 2015), and the syntactic levels of linguistic phrases (Ding et al, 2017).…”

Which factors modulate spontaneous motor tempo? A systematic review of the literature

“…In some studies listed in Table 3 , authors report that participants have no musical training. Note that some studies mix musicians and non-musicians in their samples (e.g., Michaelis et al, 2014 ; De Pretto et al, 2018 ). However, three studies reported in Table 4 show an effect of music expertise (Drake et al, 2000 ; Slater et al, 2018 ; Hammerschmidt et al, 2021 ).…”

“…Regarding the age, participants are from 18 to 45 years old ( Table 1 ). Despite the fact that the age range is representative of healthy young adults, the range of SMT values varies in five studies about manual responses from 333 to 1,100 ms (Michaelis et al, 2014 ; De Pretto et al, 2018 ; McPherson et al, 2018 ; Zhao et al, 2020 ). Regarding the sex repartition, only two studies recruit an equal number of women and men (Michaelis et al, 2014 ; De Pretto et al, 2018 ); the others recruit either more women or more men.…”

“…Despite the fact that the age range is representative of healthy young adults, the range of SMT values varies in five studies about manual responses from 333 to 1,100 ms (Michaelis et al, 2014 ; De Pretto et al, 2018 ; McPherson et al, 2018 ; Zhao et al, 2020 ). Regarding the sex repartition, only two studies recruit an equal number of women and men (Michaelis et al, 2014 ; De Pretto et al, 2018 ); the others recruit either more women or more men. As reported in Table 4 , the effect of sex on SMT has not been extensively studied, given that only one study addresses this question and reports no significant results (Suzuki and Ando, 2018 ).…”