There is a pressing need to develop precise and effective methods of non-invasive brain stimulation, both as tools to investigate neurophysiology and as potential therapeutic modalities for circuitopathies such as Parkinson’s disease. Low-intensity transcranial ultrasound (TUS) is a promising noninvasive brain stimulation technique actively being studied for its ability to reversibly modulate mammalian brain activity (Fomenko et al., 2018; Naor et al., 2016; Tyler et al., 2008). By focusing the propagation of acoustic waves through the skull, a higher degree of spatial specificity and deeper targeting can be achieved over other noninvasive stimulation methods such as transcranial magnetic stimulation (TMS) and transcranial direct-current stimulation (Fomenko and Lozano, 2019; Pasquinelli et al., 2019).

Proof-of-concept studies using TUS on healthy human volunteers have elicited a broad range of suppressive and inhibitory effects on cortical and subcortical target areas, although it remains unknown how varying the sonication parameters (i.e.: sonication duration, duty cycle, frequency) affects the magnitude and direction of neural activity within human brain circuits (Ai et al., 2018; Lee et al., 2016b; Legon et al., 2014; Sanguinetti et al., 2014). To date, published human experiments have demonstrated electrophysiological suppression of sensory-evoked potentials, task performance alteration, modulation of cortical oscillatory dynamics, and corresponding activation on fMRI (Lee et al., 2016a; Legon et al., 2014; Mueller et al., 2014). Self-reported outcomes induced by TUS have included mood improvement (Hameroff et al., 2013), phosphene detection (Lee et al., 2016b; Schimek et al., 2020), and tactile limb sensations (Lee et al., 2015; Lee et al., 2016a), when frontal, somatosensory, and occipital cortices were targeted, respectively. However, each study examined only a single set of stimulation parameters, and it is not known whether human neural circuits are more sensitive to titration of a particular parameter, nor whether a dose-response effect exists. Furthermore, studies reported heterogeneous effects of TUS on targets such as the motor cortex, with some studies showing suppression of motor-evoked potentials (MEPs) (Legon et al., 2018a), and others demonstrating increased cortical excitability after prolonged sonication (Gibson et al., 2018).

Here, we describe the first double-blinded study examining the effects of systematically varying sonication parameters of TUS applied to the primary motor cortex (M1) of healthy human participants (Figure 1). We tested the M1 because measurement of MEPs from TMS provides an objective and readily quantifiable measure of M1 excitability. Using a combined TMS-TUS stimulation approach (Legon et al., 2018a), we hypothesize that some parameters have a linear suppressive dose-response effect, and others may be less important. We then examine the effects of TUS on several intracortical circuits using paired-pulse TMS. Finally, we study the effects of applying TUS to M1 in a visuo-motor behavioral task, to determine whether sonication alone can affect higher order synaptically connected circuits involved in motor initiation and execution.

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To our knowledge, our experiment represents the first systematic investigation of low-intensity ultrasound parameters on human cortical activity. We found a dose-response effect of prolonging the sonication duration on the suppression of TMS-induced MEPs, up to a maximum duration of 0.5 s, and show that a lower duty cycle (10%) has the greatest efficacy in suppressing motor cortex potentials. Similar studies with large animals appear to be in line with our data. A recent systematic examination of TUS parameters in sheep showed that low duty cycles (<10%) and long sonication durations (~1 min) yielded suppressive effects on sensory-evoked potentials, while high duty cycles (>30%) and short sonication durations (<500 ms) were excitatory on the motor cortex (Yoon et al., 2019) However, unlike our study, suppressive parameters were only applied to the sensory cortex, and the excitatory parameters to the motor cortex, and the animals were de anesthetized during the experiment.

Interestingly, our initial results show that although a particular combination of parameters can robustly suppress TMS-elicited cortical activity when applied in a sham-controlled block design (Figure 4), some parameters such as PRF when randomized and varied individually do not have the same robust effect, whereas others such as sonication duration do (Figure 5C–D). To address this discrepancy, we conducted follow-up experiments (Figure 5—figure supplement 1) in which we delivered three distinct parameter sets in blocked, and interleaved fashion. We found that sonication at 10% DC consistently results in suppression regardless of experimental design, whereas 30% DC only results in suppression when applied in blocked fashion. A duty cycle of 50% did not show any difference compared to sham regardless of experimental design. In contrast, we observed that sonication at three different pulse repetition frequencies (200, 500, and 1000 Hz) applied in a blocked design resulted in reduced cortical excitability compared to sham, whereas interleaving these parameters yielded no significant difference. These results held whether duty cycle was fixed, or whether the DC was adjusted to maintain an equal burst duration.

In summary, our findings suggest that when delivered in blocked fashion, longer sonication durations, lower duty cycles, and all three PRFs tested yield effective suppression of TMS-elicited MEPs. The trend toward greater suppression with increasing blocked PRF agree with recent literature, where higher PRF (1500 Hz) in combination with low duty cycles were found to be more effective than lower PRF (300 Hz) in neuromodulation of mouse motor cortex in vivo (King et al., 2013) and in vitro (Manuel et al., 2020). Furthermore, recent large animal studies reveal a bidirectional neuromodulation effects of varying TUS parameters (Yoon et al., 2019). As such, interleaving different parameters in short succession may lead to spillover effects, due to the random order of parameter delivery. From animal studies where randomized delivery of TUS parameters was studied, non-linear effects were found, possibly related to non-linear piezoelectric accumulation across the neural membrane capacity under the Neuronal Bilayer Sonophore model (Kim et al., 2014; Plaksin et al., 2014). In addition, excitatory or inhibitory changes in short-term plasticity may occur with repeated TUS stimulation, similar to those observed with repeated magnetic (Watanabe et al., 2014) and electrical stimulation (Udupa et al., 2016). These are currently under study in our laboratory and in emerging reports on LITUS short-term plasticity in animal models (Yu et al., 2019).

To test whether a progressive accumulation of inhibition might be responsible for the observed difference in results between the blocked and interleaved study designs, we performed a post-hoc analysis of our blocked experiments, stratifying by trial number across all participants (Figure 5—figure supplement 2). Within each parameter condition, we did not detect a significant difference between the magnitude of early and late trials and conclude that there is no temporal accumulation of MEP-suppressive effects over blocks of 15 trials, corresponding to a block length of approximately 90 s. Instead, the suppression appears to be instantaneous, with effective parameters increasing the likelihood of generating a lower TMS-elicited MEP, but not potentiating the effect of a subsequent stimulation. Notably, our blocked design features a 20 s pause between each set of 15 replicate stimulations, whereas interleaved delivery of random parameters involves an uninterrupted session of 60 stimulations. We speculate that this 20-s rest period may lead to a resetting of cortical excitability to a more TUS-sensitive state. The lack of resetting could play a role in our observation of less robust effects when certain parameters are randomized in succession.

Possibly because of these longer term effects and the heterogeneity of experimental methods and sonication parameters used between human studies, conflicting reports have emerged. For instance, Legon et al., 2018a applied simultaneous 500 kHz TUS and TMS to the M1 of healthy human subjects to examine effects on the MEP, intracortical excitability, and reaction time (Legon et al., 2018b). TUS was found to attenuate TMS-evoked MEP amplitude, reduce ICF, but with no effect on intracortical inhibition, and improve reaction time. However, another study by Gibson found that application of continuous sonication for 2 min to M1 increased subsequent TMS-induced corticospinal excitability compared to baseline (Gibson et al., 2018). Notably, both studies were single-blinded, used a single set of sonication parameters and used a blocked study design to examine sham and active TUS conditions. The study by Gibson also used an unfocused imaging transducer operating at high fundamental frequencies (2.32 MHz), decreasing the likelihood that the acoustic energy reached the brain due to the lower transmission coefficient of the skull at this frequency range (Mueller et al., 2017). Since Gibson’s study measured motor cortical excitability only after ultrasound was applied for several minutes, the potential neuromodulatory mechanisms may have opposing effects on excitability compared to the on-line TUS-TMS paradigm studied herein, and in Legon’s experiments (Gibson et al., 2018; Legon et al., 2018b).

Since the piezoelectric element within our ultrasound transducer emits a slightly audible buzzing tone when activated, also reported in other human TUS-TMS studies (Legon et al., 2018b), we implemented a novel method of delivering a masking audio stimulus to reduce potential auditory confounding effects. This is particularly salient because our sham conditions were randomly interleaved with active TUS delivery in order to reduce the effects of time-related fluctuations of cortical excitability and to blind the experimenter (Huber et al., 2013). Recent literature demonstrating potential auditory confounding in rodent TUS cortical neuromodulation (Guo et al., 2018; Niu et al., 2018; Sato et al., 2018), highlight the importance of strategies aimed at prevent conscious or unconscious auditory contamination in ultrasound neuromodulation experiments. Human TMS studies have shown that pairing TMS with an audible stimulus, especially human speech, can lead to increases in cortical excitability. For instance, TMS to the M1 hand area, concomitant with different auditory stimuli Flöel et al., 2003 have shown that pure tonal sounds do not alter the magnitude of MEP, while language perception significantly increases motor excitability. In agreement, studies examining TMS motor response of the leg (Liuzzi et al., 2008) and tongue (Fadiga et al., 2002) show a motor facilitation with semantic speech stimuli, but not with audible tonal sounds or noise. In our study, we did not find facilitation, but rather decreased excitability with application of TUS to the hand area of M1, while controlling for audible tones in all delivered conditions including sham. Furthermore, our audible masking tone was played for the same 0.5 s duration for every experimental condition, including the sham, relative to the TMS pulse, and we therefore expect that any TMS-acoustic pairing would be controlled for.

A recent report examining masked and unmasked delivery of TUS conditions highlights the electrophysiological basis of potential auditory confounds in human single-transducer TUS experiments (Braun et al., 2020). In particular, this report shows that an audio-masked TUS sonication and audio-masked sham evoke identical auditory ERP's, whereas TUS alone without a mask evokes a significantly different ERP, and moreover can also be reliably differentiated from sham by participants (Braun et al., 2020). This report appears to corroborate our strategy and highlights the importance of controlling for auditory confounds in future human ultrasound neuromodulation studies.

The results from our paired-pulse experiments suggest that TUS potentiates short-interval intracortical inhibition (SICI). Previous pharmacological and physiological investigations have shown that SICI is a marker of GABA_A-receptor-mediated inhibition and may reflect activity of inhibitory interneurons (Stagg et al., 2011; Udupa et al., 2010). Our finding may suggest that cortical interneurons in layers II/III which are well-encompassed within the acoustic focus (Figure 2B) may be preferentially sensitive to ultrasound applied for long durations and a short duty cycle and confer an overall suppressive effect by increasing GABA_A activity. Indeed, emerging electrophysiology work in animal models is suggesting that sensitivity to low-intensity TUS is mediated not only by parameter selection but also that excitatory and inhibitory neurons have different sensitivities to sonication (Yu et al., 2019). One possible mechanobiological explanation for the cell-type selective effects of ultrasound is the neuronal intramembrane cavitation excitation (NICE) model. Predictive modeling studies within the NICE framework, corroborated with animal electrophysiological studies are suggesting that inhibitory cortical neurons are hypersensitive to discontinuous pulsed bursts of TUS (Plaksin et al., 2014; Plaksin et al., 2016). The T-type voltage-gated calcium channels within these neurons predispose to accumulation of electrical charge between short bursts of ultrasound, predisposing to inhibitory neural activation during low duty-cycle sonication (Plaksin et al., 2016; Plaksin et al., 2014).

In Legon’s study, TUS was found to attenuate ICF but did not affect intracortical inhibition (Legon et al., 2018b). Several methodological differences from our study should be noted, such as time-locking the ultrasound to begin 100 ms prior to the conditioning stimulus, whereas our sonication was time-locked to 490 ms prior to the first TMS pulse. Since sonication duration is a key parameter of TMS-mediated EMG suppression according to our findings, the earlier onset of TUS in our experiment relative to the CS and TS pulses might have potentiated greater GABA_A-mediated inhibition, despite the total sonication time being the same. In addition, we randomized the TS-alone condition with the paired pulse conditions in our experiment, whereas (Legon et al., 2018b) compared to a baseline MEP conducted in a temporally discrete block, potentially introducing variability inherent in MEP fluctuations over time (Ellaway et al., 1998).

The cortical silent period, thought to be a marker of GABA_B activity (Tremblay et al., 2013; Ziemann et al., 2015), did not significantly change with application of TUS in our experiments. Likewise, we did not observe an effect of TUS on LICI, another TMS marker of GABA_B-ergic inhibition (Premoli et al., 2014). Reports using voltage-clamp and in-vivo experiments are beginning to show that TUS has preferential effects on certain ion channel currents (Kubanek et al., 2016; Yu et al., 2019), and our results may suggest that the ligand-gated ionotropic GABA_A channel may be such a mechanosensitive substrate.

Similar to prior reports of M1 TUS in humans (Gibson et al., 2018; Legon et al., 2018b), we were unable to evoke motor potentials or EMG activities by application of TUS alone to the motor cortex. Interestingly, studies in small rodents consistently show EMG activity and frank motor contractions of hindlimbs (Gulick et al., 2017), whiskers (Mehić et al., 2014), and tail (Yoo et al., 2013) contralateral to the sonicated motor cortex, as well as inducing eye movements and pupillary dilatation (Kamimura et al., 2016). Although the majority of these studies were done under complete or partial anesthesia, recent studies with awake, freely moving rats have also found that TUS alone can also trigger truncal and limb movements (Lee et al., 2018). Applying a similar paradigm to larger animals such as sheep failed to trigger visible motor contractions with TUS alone, although time-locked and parameter-dependent EMG activity in the corresponding hindlimbs was seen (Lee et al., 2016c; Yoon et al., 2019). In the even larger human brain, we speculate that the narrow acoustic focus of a single transducer targets a small proportion of the entire motor cortex and either recruits insufficient cortical neurons to trigger a contraction, or preferentially recruits an inhibitory ensemble of interneurons thereby having the opposite effect. Moreover, recent studies with deafened rodents (Guo et al., 2018; Sato et al., 2018) have challenged the notion that low-intensity TUS can directly mediate small animal motor cortical activation, instead proposing that an indirect auditory mechanism, or a peripherally mediated startle response due may be involved. The narrow ellipsoid-shaped acoustic focus may also explain why we observed an increase in the stimulator output required to generate a 1 mV MEP (Figure 7A) and reduction in resting MEP amplitude, but found no change in the active motor threshold or active MEP amplitude (Figure 6), given the active condition is likely associated with larger area of activation in the motor cortex.

Data used for this study are included in the manuscript and supporting files. Files for 3D printing the stimulating devices and custom MATLAB scripts used for stimulation have been deposited into a cited GitHub repository.

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Author details

1. Anton Fomenko

   Krembil Research Institute, University Health Network, Toronto, Canada

   Contribution

   Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing

   Contributed equally with

   Kai-Hsiang Stanley Chen

   For correspondence

   anton.fomenko@uhnresearch.ca

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4131-6784

2. Kai-Hsiang Stanley Chen

   1. Krembil Research Institute, University Health Network, Toronto, Canada
   2. Department of Neurology, National Taiwan University Hospital Hsin-Chu Branch, Hsin-Chu, Taiwan

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Writing - review and editing

   Contributed equally with

   Anton Fomenko

   Competing interests

   No competing interests declared

3. Jean-François Nankoo

   Krembil Research Institute, University Health Network, Toronto, Canada

   Contribution

   Conceptualization, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

4. James Saravanamuttu

   Krembil Research Institute, University Health Network, Toronto, Canada

   Contribution

   Data curation, Formal analysis, Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

5. Yanqiu Wang

   Krembil Research Institute, University Health Network, Toronto, Canada

   Contribution

   Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

6. Mazen El-Baba

   Krembil Research Institute, University Health Network, Toronto, Canada

   Contribution

   Software, Visualization

   Competing interests

   No competing interests declared

7. Xue Xia

   Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada

   Contribution

   Investigation

   Competing interests

   No competing interests declared

8. Shakthi Sanjana Seerala

   Sunnybrook Research Institute, Toronto, Canada

   Contribution

   Resources, Investigation

   Competing interests

   No competing interests declared

9. Kullervo Hynynen

   Sunnybrook Research Institute, Toronto, Canada

   Contribution

   Resources, Writing - review and editing

   Competing interests

   No competing interests declared

10. Andres M Lozano

    1. Krembil Research Institute, University Health Network, Toronto, Canada
    2. Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University of Toronto, Toronto, Canada

    Contribution

    Conceptualization, Supervision, Writing - review and editing

    For correspondence

    lozano@uhnresearch.ca

    Competing interests

    No competing interests declared

11. Robert Chen

    1. Krembil Research Institute, University Health Network, Toronto, Canada
    2. Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada

    Contribution

    Conceptualization, Supervision, Writing - review and editing

    For correspondence

    robert.chen@uhn.ca

    Competing interests

    No competing interests declared

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