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Real TMS of motor cortex results in cortical responses significantly different from realistic sham. These differences very likely reflect to a significant extent direct activation of neurons, rather than sensory evoked activity.

A recent study by Conde, Tomasevic et al. (2019) [1] puts a spotlight on the subtleties of experimental design and analysis of studies involving TMS-evoked EEG potentials (TEPs), specifically focusing on the challenge of disentangling genuine cortical responses to TMS from those resulting from concomitant sensory activation. This is a relevant topic that the TMSeEEG community has previously identified [2] and addressed with different strategies [3e6]. Based on the similarity of the evoked EEG responses they obtained in real TMS at different sites and in sham conditions (auditory and somatosensory scalp stimulation), the authors of [1] inferred that TEPs can be significantly contaminated by the effects of concurrent, non-transcranial stimulation.We acknowledge this is a valuable reminder to the TMS-EEG community; however, we contend that another fundamental implication of the work by Conde, Tomasevic and colleagues [1] -only incidentally mentioned at the end of their discussion e is that the evoked responses they obtain from both real TMS and sham conditions are substantially different from the TEPs reported in many of the previous studies (see, for example [7e11]). This discrepancy offers a timely opportunity to focus on the issue of the reproducibility of TEPs across laboratories and, most important, can encourage a constructive debate within the whole TMSeEEG community towards the optimization of shared procedures to obtain genuine responses to TMS.In this vein, Fig. 1 directly compares the TEPs reported in Ref.[1] with others previously published in different studies taken as a reference by Conde, Tomasevic and colleagues [1].The inspection of Fig. 1 clearly shows that it is possible to effectively trigger high-amplitude, sharply rising early (<50 ms) components and overall TEP wave-shapes that are specific for the angle and site of stimulation and that are very different from those obtained in Ref. [1]. This simple comparison highlights a general problem of reproducibility and offers an excellent opportunity to discuss two critical steps in TMSeEEG data acquisition: (i) maximising the impact of TMS on the cortex, and (ii) minimizing EEG confounding factors due to sensory co-stimulation.Regarding the impact of TMS on the cortex, it is very likely that the authors of [1] were not as effective as other investigators for the following reasons. First, they applied TMS with a maximum electric field (E-field) intensity between 70 and 90 V/m according to their estimation, assuming a priori that this would have warranted effective cortical activation based on a previous work [12]. However, in Ref. [1] the authors adopted a small coil (outer winding diameter: 45 mm) which, compared to the larger ones (outer winding

The theory of communication through coherence predicts that effective connectivity between nodes in a distributed oscillating neuronal network depends on their instantaneous excitability state and phase synchronicity (Fries, 2005). Here, we tested this prediction by using state-dependent millisecond-resolved real-time electroencephalography-triggered dual-coil transcranial magnetic stimulation (EEG-TMS) (Zrenner et al., 2018) to target the EEG-negative (high-excitability state) versus EEG-positive peak (low-excitability state) of the sensorimotor-rhythm in the left (conditioning) and right (test) motor cortex (M1) of 16 healthy human subjects (9 female, 7 male). Effective connectivity was tested by short-interval interhemispheric inhibition (SIHI); that is, the inhibitory effect of the conditioning TMS pulse given 10-12 ms before the test pulse on the test motor-evoked potential. We compared the four possible combinations of excitability states (negative peak, positive peak) and phase relations (in-phase, out-of-phase) of the-rhythm in the conditioning and test M1 and a random phase condition. Strongest SIHI was found when the two M1 were in phase for the high-excitability state (negative peak of the-rhythm), whereas the weakest SIHI occurred when they were out of phase and the conditioning M1 was in the low-excitability state (positive peak). Phase synchronicity contributed significantly to SIHI variation, with stronger SIHI in the in-phase than out-ofphase conditions. These findings are in exact accord with the predictions of the theory of communication through coherence. They open a translational route for highly effective modification of brain connections by repetitive stimulation at instants in time when nodes in the network are phase synchronized and excitable.

Key points Oscillatory brain activity coordinates the response of cortical neurons to synaptic inputs in a phase‐dependent manner. Larger motor‐evoked responses are obtained in a hand muscle when transcranial magnetic stimulation (TMS) is synchronized to the phase of the sensorimotor μ‐rhythm. In this study we further showed that TMS applied at the negative vs. positive peak of the μ‐rhythm is associated with higher absolute amplitude of the evoked EEG potential at 100 ms after stimulation. This demonstrates that cortical responses are sensitive to excitability fluctuation with brain oscillations Our results indicate that brain state‐dependent stimulation is a new useful technique for the investigation of stimulus‐related cortical dynamics. Abstract Oscillatory brain activity coordinates the response of cortical neurons to synaptic inputs in a phase‐dependent manner. Transcranial magnetic stimulation (TMS) of the human primary motor cortex elicits larger motor‐evoked potentials (MEPs) when applied at the negative vs. positive peak of the sensorimotor μ‐rhythm recorded with EEG, demonstrating that this phase represents a state of higher excitability of the cortico‐spinal system. Here, we investigated the influence of the phase of the μ‐rhythm on cortical responses to TMS as measured by EEG. We tested different stimulation intensities above and below resting motor threshold (RMT), and a realistic sham TMS condition. TMS at 110% RMT applied at the negative vs. positive peak of the μ‐rhythm was associated with higher absolute amplitudes of TMS‐evoked potentials at 70 ms (P70) and 100 ms (N100). Enhancement of the N100 was confirmed with negative peak‐triggered 90% RMT TMS, while phase of the μ‐rhythm did not influence evoked responses elicited by sham TMS. These findings extend the idea that TMS applied at the negative vs. positive peak of the endogenous μ‐oscillation recruits a larger portion of neurons as a function of stimulation intensity. This further corroborates that brain oscillations determine fluctuations in cortical excitability and establishes phase‐triggered EEG‐TMS as a sensitive tool to investigate the effects of brain oscillations on stimulus‐related cortical dynamics.

Neuronal activity in the brain reflects an excitation–inhibition balance that is regulated predominantly by glutamatergic and GABAergic neurotransmission, and often disturbed in neuropsychiatric disorders. Here, we tested the effects of a single oral dose of two anti-glutamatergic drugs (dextromethorphan, an NMDA receptor antagonist; perampanel, an AMPA receptor antagonist) and an L-type voltage-gated calcium channel blocker (nimodipine) on transcranial magnetic stimulation (TMS)-evoked electroencephalographic (EEG) potentials (TEPs) and TMS-induced oscillations (TIOs) in 16 healthy adults in a pseudorandomized, double-blinded, placebo-controlled crossover design. Single-pulse TMS was delivered to the hand area of left primary motor cortex. Dextromethorphan increased the amplitude of the N45 TEP, while it had no effect on TIOs. Perampanel reduced the amplitude of the P60 TEP in the non-stimulated hemisphere, and increased TIOs in the beta-frequency band in the stimulated sensorimotor cortex, and in the alpha-frequency band in midline parietal channels. Nimodipine and placebo had no effect on TEPs and TIOs. The TEP results extend previous pharmaco-TMS-EEG studies by demonstrating that the N45 is regulated by a balance of GABAAergic inhibition and NMDA receptor-mediated glutamatergic excitation. In contrast, AMPA receptor-mediated glutamatergic neurotransmission contributes to propagated activity reflected in the P60 potential and midline parietal induced oscillations. This pharmacological characterization of TMS-EEG responses will be informative for interpreting TMS-EEG abnormalities in neuropsychiatric disorders with pathological excitation–inhibition balance.

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Measuring the brain's response to transcranial magnetic stimulation (TMS) with electroencephalography (EEG) offers unique insights into the cortical circuits activated following stimulation, particularly in non-motor regions where less is known about TMS physiology. However, the mechanisms underlying TMS-evoked EEG potentials (TEPs) remain largely unknown. We assessed TEP sensitivity to changes in excitatory neurotransmission mediated by n-methyl-d-aspartate (NMDA) receptors following stimulation of non-motor regions. In fourteen male volunteers, resting EEG and TEPs from prefrontal (PFC) and parietal (PAR) cortex were measured before and after administration of either dextromethorphan (NMDA receptor antagonist) or placebo across two sessions in a doubleblinded pseudo-randomised crossover design. At baseline, there were amplitude differences between PFC and PAR TEPs across a wide time range (15-250 ms), however the signals were correlated after ~80 ms, suggesting early peaks reflect site-specific activity, whereas late peaks reflect activity patterns less dependent on the stimulated sites. Early TEP peaks were not reliably altered following dextromethorphan compared to placebo, although findings were less clear for later peaks, and low frequency resting oscillations were reduced in power. Our findings suggest that early TEP peaks (<80 ms) from PFC and PAR reflect stimulation site specific activity that is largely insensitive to changes in NMDA receptor-mediated neurotransmission.Transcranial magnetic stimulation (TMS) is a brain stimulation method capable of non-invasively activating cortical neurons across the scalp in humans via electromagnetic induction 1 . A single TMS pulse evokes a series of time-locked peaks and troughs in electroencephalographic (EEG) recordings of brain activity 2 , which are commonly known as TMS-evoked EEG potentials (TEPs). TEPs are reliable within and between sessions 3-5 , are sensitive to changes in TMS parameters such as intensity 4 and pulse shape 6 , and differ depending on the cortical site stimulated 4,7 . In addition, TEPs are sensitive to changes in cortical properties resulting from differing brain states, plasticity-inducing brain stimulation paradigms, and brain disorders 8 . As such, TMS-EEG is emerging as a powerful method for investigating cortical dynamics in health and disease.Despite the recent uptake of TMS-EEG within the brain stimulation field, it remains largely unclear what physiological properties underlie the size, shape and distribution of TEPs, thereby limiting their interpretability. Current hypotheses suggest that TEPs primarily reflect fluctuations in cortical excitability resulting from excitatory and inhibitory neurotransmission at the site of stimulation, as well as the propagation of activation through www.nature.com/scientificreports www.nature.com/scientificreports/ PFC (15-45 ms) 60 [18-133] 73 [40-103] 0.93 [0.81-0.99] 0.135 PFC (95-125 ms) 80 [24-129] 59 [20-110] 0.88 [0.68-0.99] 0.077 PFC (175-205 ms) 80 [37-123] 51 [21-122] 0.84 [0.69-0.99] 0....