M1-P15 as a cortical marker for transcallosal inhibition: A preregistered TMS-EEG study

Abstract

In a recently published study combining transcranial magnetic stimulation and electroencephalography (TMS-EEG), an early component of TMS-evoked potentials (TEPs), i.e., M1-P15, was proposed as a measure of transcallosal inhibition between motor cortices. Given that early TEPs are known to be highly variable, further evidence is needed before M1-P15 can be considered a reliable index of effective connectivity. Here, we conceived a new preregistered TMS-EEG study with two aims. The first aim was validating the M1-P15 as a cortical index of transcallosal inhibition by replicating previous findings on its relationship with the ipsilateral silent period (iSP) and with performance in bimanual coordination. The second aim was inducing a task-dependent modulation of transcallosal inhibition. A new sample of 32 healthy right-handed participants underwent behavioral motor tasks and TMS-EEG recording, in which left and right M1 were stimulated both during bimanual tasks and during an iSP paradigm. Hypotheses and methods were preregistered before data collection. Results show a replication of our previous findings on the positive relationship between M1-P15 amplitude and the iSP normalized area. Differently, the relationship between M1-P15 latency and bimanual coordination was not confirmed. Finally, M1-P15 amplitude was modulated by the characteristics of the bimanual task the participants were performing, and not by the contralateral hand activity during the iSP paradigm. In sum, the present results corroborate our previous findings in validating the M1-P15 as a cortical marker of transcallosal inhibition and provide novel evidence of its task-dependent modulation. Importantly, we demonstrate the feasibility of preregistration in the TMS-EEG field to increase methodological rigor and transparency.

Effects of transcranial magnetic stimulation (TMS) current direction and pulse waveform on cortico‐cortical connectivity: A registered report TMS‐EEG study

“…It has to be noted that our ICC estimation does not take measurement error into account. (b) Positive significant relationship between M1‐P15 amplitude and normalized iSP area, recorded in the experimental condition replicating the parameters exploited in our previous studies on this TEP component (Bortoletto et al, 2021; Zazio et al, 2022).…”

“…the first point after iSP onset at which the level of EMG activity returned to the mean EMG signal); and the normalized iSP area, calculated using the following formula: [(area of the rectangle defined as mean EMG × iSP duration) − (area underneath the iSP)]. Then, the normalized iSP area was defined as the ratio between the iSP area and the area underneath EMG from −150 to 50 ms preceding TMS and multiplied by 100 (for a similar procedure, see Bortoletto et al, 2021; Zazio et al, 2022). Simple linear regression was used to test if the normalized iSP predicted M1‐P15 amplitude.…”

“…At the beginning of the experiment, a thin layer of foam was placed under the TMS coil to reduce sensory stimulation associated with TMS, and white noise was played through noise‐cancelling earphones (Biabani et al, 2019). The volume of the white noise was individually adjusted to mask the TMS click but avoid hearing discomfort, as done in previous studies by our group (Bortoletto et al, 2021; Zazio et al, 2022). Throughout the experiment, the TMS coil was held by a trained experimenter and adjusted according to the information provided by the neuronavigation system.…”

“…TEP preprocessing followed a pipeline that is currently used for TMS‐EEG data in our lab, adapted from our previous studies targeting M1‐P15 (Bortoletto et al, 2021; Zazio et al, 2022). The pipeline has been implemented in MATLAB R2020b (The MathWorks, Natick, MA, USA) with custom scripts combining EEGLAB v.2020.0 (Delorme & Makeig, 2004) and FieldTrip v.20190905 functions (Oostenveld et al, 2011) and two analysis methods, namely, the source‐estimate‐utilizing noise‐discarding (SOUND) algorithm (Mutanen et al, 2018) and the signal‐space projection and source‐informed reconstruction (SSP‐SIR) algorithm (Mutanen et al, 2016).…”

“…F4 and FC4), we measured its amplitude and latency in each experimental condition as the peak in the window between 7 and 25 ms. Finally, the presence of M1‐P15 was visually assessed (for a similar procedure, see Bortoletto et al, 2021; Zazio et al, 2022).…”