Movement and Action Representation TMS-EEG Lab

Combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) is widely used to probe cortical excitability at the network level, but technical challenges have prevented its application to investigate local excitability of the stimulated area. A recent study revealed immediate TMS-evoked potentials (i-TEPs) after primary motor cortex (M1) stimulation, suggesting that it may represent a local response. Here, we aimed at testing if this activity is physiological in nature and what it represents.

We analyzed a TMS-EEG dataset from 28 healthy participants recorded at 9.6 kHz including two M1 stimulation conditions with opposite biphasic current directions. We localized the brain sources of i-TEPs, calculated the immediate TMS-related power (i-TRP) to distinguish between two oscillatory components that may contribute to i-TEPs, and investigated the relationship between i-TRP and motor-evoked potentials (MEPs). In an additional recording, we stimulated a control site evoking a muscular response to understand the contribution of the TMS-related muscle artifact.

Results confirmed i-TEPs with similar characteristics as previously described. The i-TRP revealed strong activity in two ranges 600-800 Hz and 100-200 Hz; The former was positively associated with MEPs amplitude for both current direction conditions. Moreover, i-TEPs were localized in the precentral gyrus of the stimulated hemisphere and the muscular response generated by the control stimulation site differed from i-TEPs and i-TRP.

These findings provide first evidence on the physiological nature of i-TEPs and i-TRP following M1 stimulation and that i-TRP represents a direct measure of excitability of the stimulated cortex.

In studies combining transcranial magnetic stimulation and electroencephalography (TMS-EEG), two artifacts appear instantly after the TMS pulse, i.e., the TMS-pulse Artifact and the Decay Artifact, and limit the possibility to measure immediate cortical excitability responses. High-frequency sampling rates in EEG recordings have shown promise in reducing artifact duration, allowing more rapid signal recovery, which is crucial for developing biomarkers for neuropsychiatric conditions. However, the features of early TMS-induced artifacts for sampling rates above 5000 Hz are still unclear. Here, we explored the duration of TMS artifacts in the first milliseconds after TMS to understand how they can be further reduced in future studies. We recorded from a phantom head model and from a simple electrical circuit with a sampling rate of 4800 Hz, 9600 Hz, and 19200 Hz and at three TMS intensities (40%, 70%, 100% of maximum stimulator output) in two commercial stimulators. Results showed an initial sharp TMS-pulse Artifact lasting less than 1 ms and decreasing in duration at higher sampling rates. However, the signal was back to baseline at about 2-3 ms due to the presence of a decay artifact that was evident even in optimal conditions of low impedance and mostly dependent on stimulation intensity. These results highlight the need to develop efficient ways to eliminate the decay artifact in order to measure immediate TMS responses.

Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs) represent an innovative measure for examining brain connectivity and developing biomarkers of psychiatric conditions. Minimizing TEP variability across studies and participants, which may stem from methodological choices, is therefore vital. By combining classic peak analysis and microstate investigation, we tested how TMS pulse waveform and current direction may affect cortico-cortical circuit engagement when targeting the primary motor cortex (M1). We aim to disentangle whether changing these parameters affects the degree of activation of the same neural circuitry or may lead to changes in the pathways through which the induced activation spreads. Thirty-two healthy participants underwent a TMS-EEG experiment in which the pulse waveform (monophasic, biphasic) and current direction (posterior-anterior, anterior-posterior, latero-medial) were manipulated. We assessed the latency and amplitude of M1-TEP components and employed microstate analyses to test differences in topographies. Results revealed that TMS parameters strongly influenced M1-TEP components’ amplitude but had a weaker role over their latencies. Microstate analysis showed that the current direction in monophasic stimulations changed the pattern of evoked microstates at the early TEP latencies, as well as their duration and global field power. This study shows that the current direction of monophasic pulses may modulate cortical sources contributing to TEP signals, activating neural populations and cortico-cortical paths more selectively. Biphasic stimulation reduces the variability associated with current direction and may be better suited when TMS targeting is blind to anatomical information.

The distinction between acting jointly and acting side-by-side permeates our daily lives and is crucial for understanding the evolution and development of human sociality. While acting in parallel involves agents pursuing individual goals, acting jointly requires them to share a collective goal. We used dual EEG to investigate neural dynamics underlying these action types. We recorded event-related potentials (ERPs) from 20 dyads while they had to transport an object in a video game, either jointly or in parallel. Conditions were matched for task execution complexity, confirmed by equal success rates. Results revealed a distinctive pattern swap in ERPs during action preparation. Early preparation showed significantly higher amplitude during joint versus parallel action. This pattern reversed in late preparation, with significantly reduced ERP amplitude in joint compared to parallel action. Notably, decreased late ERPs correlated with higher RT variability in partners but not participants' own RT variability. This dynamic swap suggests different cognitive processes operate at distinct stages of action preparation. Sharing a collective goal may impose cognitive costs (reflected in higher early ERPs), but this is offset by facilitated late action preparation (as shown by reduced late ERPs), likely due to the enhanced predictability of partners' actions.

Neural variability, traditionally viewed as a barrier to consistent outcomes across all areas of neuroscience, is increasingly recognized as a critical element of brain function. This manuscript explores the idea that neural variability and neural noise, rather than being detrimental, is essential for enhancing adaptability and robustness in neural systems. By capturing this variability through indices that accurately represent an individual neural state through detailed brain activity recordings and advanced analytical techniques, brain research and more specifically non-invasive brain stimulation protocols can be optimized for individual brain states, thereby improving outcomes. The manuscript emphasizes the importance of capturing individual neural variability for developing more precise and effective neurostimulation/neuromodulation protocols. It also explores the roles of neural variability and noise in relation to excitability, plasticity, and homeostatic regulation, proposing a framework change for understanding NIBS effects on brain function and behaviour. This approach signifies a shift from minimizing neural variability to leveraging it strategically, offering new insights for research and clinical applications.