# Deep transcranial ultrasound stimulation using personalized acoustic metamaterials improves treatment-resistant depression in humans

David Attali, Thomas Tiennot, Thomas J Manuel, Maxime Daniel, Alexandre Houdouin, Philippe Annic, Alexandre Dizeux, Alexandre Haroche, Ghita Dadi, Adèle Henensal, et al.

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## To cite this version:

David Attali, Thomas Tiennot, Thomas J Manuel, Maxime Daniel, Alexandre Houdouin, et al. Deep transcranial ultrasound stimulation using personalized acoustic metamaterials improves treatment-resistant depression in humans. Brain Stimulation, 2025, 18 (3), pp.1004 - 1014. 10.1016/j.brs.2025.04.018. hal-05335780

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# Deep transcranial ultrasound stimulation using personalized acoustic metamaterials improves treatment-resistant depression in humans

David Attali<sup>a,b,c,1</sup> ID, Thomas Tiennot<sup>a,1</sup>, Thomas J. Manuel<sup>a</sup>, Maxime Daniel<sup>a</sup>, Alexandre Houdouin<sup>a</sup>, Philippe Annic<sup>a</sup>, Alexandre Dizeux<sup>a</sup>, Alexandre Haroche<sup>b,d</sup>, Ghita Dadi<sup>b</sup>, Adèle Henensal<sup>d</sup>, Mylène Moyal<sup>d ID</sup>, Alice Le Berre<sup>d,e</sup>, Cécile Paolillo<sup>b,g</sup>, Sylvain Charron<sup>d,e</sup>, Clément Debacker<sup>d,e ID</sup>, Maliesse Lui<sup>d,e</sup>, Sabrina Lekcir<sup>f</sup>, Rosella Mancusi<sup>f ID</sup>, Thierry Gallarda<sup>b</sup>, Tarek Sharshar<sup>c,h</sup>, Khaoussou Sylla<sup>f</sup>, Catherine Oppenheim<sup>d,e</sup>, Arnaud Cachia<sup>d,g</sup>, Mickael Tanter<sup>a</sup>, Jean-Francois Aubry<sup>a,1,* ID</sup>, Marion Plaze<sup>b,d,1</sup>

## ARTICLE INFO

### Keywords:

Treatment-resistant depression
Transcranial ultrasound stimulation
Focused ultrasound neuromodulation
Subcallosal cingulate
Tractography
Personalized acoustic metalens

## ABSTRACT

**Background:** Neuromodulation of deep brain regions has shown promise for treatment-resistant depression (TRD). However, it currently requires neurosurgical electrode implantation, posing significant risks and limiting widespread use while TRD affects around 100 million people worldwide. Low-intensity transcranial ultrasound stimulation (TUS) could allow precise and non-invasive deep neuromodulation, provided that the challenge of the defocusing effects of the skull is tackled.

**Objective/hypothesis:** Here, we present the development of a portable and neuronavigated TUS prototype based on the use of patient-specific metamaterials (metalens) that correct for skull-induced aberrations. We then present the first application of metalens-based Transcranial Ultrasound Stimulation (mTUS) in TRD. The primary objective was to assess the safety and efficacy of mTUS targeting on individual level specific white matter tracts of the subcallosal cingulate involved in TRD.

**Methods:** The safety and precision of this device was addressed through a series of numerical simulations and experimental measurements on ex vivo human skulls. Five participants with TRD were included in this open-label study (ClinicalTrials.gov identifier: NCT06085950) and underwent an intensive 5-day course of mTUS with a total of 25 sessions of 5 min each.

**Results:** No serious adverse events occurred during the study. By day 5 of treatment, depression severity was reduced by an average of 60.9 % (range: [30 %–83.9 %]), and four out of five patients qualified as responders, with two of them in remission.

**Conclusions:** This study provides first-in-human evidence of the potential of mTUS as a precise, safe and effective non-invasive neuromodulation technique for neuropsychiatric disorders involving deep brain regions, offering a safer and more accessible alternative to invasive approaches.

<footnote><sup>a</sup> Institute Physics for Medicine Paris, Inserm U1273, ESPCI Paris, PSL University, CNRS UMR 8063, 75015, Paris, France</footnote>

<footnote><sup>b</sup> S17-18 Adult Psychiatry Department, GHU Paris Psychiatrie & Neurosciences, Site Sainte-Anne, 75014, Paris, France</footnote>

<footnote><sup>c</sup> Anesthesia and Intensive Care Department, GHU Paris Psychiatrie & Neurosciences, Pôle Neuro, Sainte-Anne Hospital, 75014, Paris, France</footnote>

<footnote><sup>d</sup> Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, IMA-brain Team, 75014, Paris, France</footnote>

<footnote><sup>e</sup> Department of Neuroradiology, GHU Paris Psychiatrie & Neurosciences, Site Sainte-Anne, 75014, Paris, France</footnote>

<footnote><sup>f</sup> Clinical Research and Innovation Department, GHU Paris Psychiatrie & Neurosciences, Site Sainte-Anne, 75014, Paris, France</footnote>

<footnote><sup>g</sup> Université Paris Cité, LaPsyDÉ, CNRS, F-75005, Paris, France</footnote>

<footnote><sup>h</sup> Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, 75014 Paris, France</footnote>

<footnote>* Corresponding author.
E-mail address: jean-francois.aubry@espci.fr (J.-F. Aubry).</footnote>

<footnote n="1">¹ These authors contributed equally.</footnote>
# 1. Introduction

The last decade has witnessed a dramatic increase in the impact of neuropsychiatric disorders, with anxiety and depressive disorders showing the two greatest rises in burden worldwide among all medical conditions [1]. Psychotropic drugs are standard treatment for neuropsychiatric disorders, but their therapeutic effects have an onset delay of several weeks, and 20–60 % of patients with mental disorders are drug resistant [2]. Drug resistance leads to a substantial increase in morbidity and in healthcare burden and costs, up to ten times higher than for non-resistant patients [3,4]. Neuromodulation of deep brain regions is increasingly recognized as a promising approach for the treatment of neuropsychiatric disorders with, to date, Deep Brain Stimulation (DBS) being the only technique able to precisely target these deep-seated brain areas at an individual level [5–11]. Notably, DBS of the subcallosal cingulate (SCC) has been shown to provide a robust clinical response in patients with treatment-resistant depression (TRD) [12]. Nevertheless, DBS requires an invasive neurosurgical procedure which entails bleeding or infection risks [13]. As a result, DBS is limited to a small number of patients with the most resistant and severe forms of mental disorders. This limitation is in conflict with the alarming indicators of TRD, with an incidence of 100 million worldwide, a high mortality and the leading cause of loss of healthy life based on international epidemiological estimates [14]. There is therefore a crucial need for the development of precise, safe, fast-acting and easy-to-deploy non-invasive techniques to neuromodulate deep areas involved in neuropsychiatric disorders.

A leading candidate for such non-invasive deep neuromodulation is Transcranial Ultrasound Stimulation (TUS), which uses low-intensity focused ultrasound to induce mechanical effects including bulk compression, radiation pressure particle displacement, and acoustic streaming [15,16]. TUS has been shown effective in modulating neural circuits *in vitro* [17,18], in small animals [19–22] and in non-human primates [23–27]. Clinical translation of TUS into humans, however, remains limited by three main challenges: precision, safety and portability. Precision is undermined by distortions induced by the variable thickness and heterogeneity of the human skull [28] which defocuses ultrasound more than in other species [29], potentially preventing accurate targeting or causing focal shift and attenuation due to destructive interference [30–32]. To this end, ultrasonic arrays based on high piezoelectric element counts have been introduced to adjust the time delays on each individual ultrasonic element and compensate for the defocusing [33,34], such as the InSightec Exablate Neuro, FDA-approved for applications at high intensity to induce irreversible lesions (e.g. for thalamotomy in essential tremor [35]). Nevertheless, the large-scale application in neuromodulation with multi-element systems are constrained by their large physical footprint (over 1.2 tons), high channel count, and reliance on a magnetic resonance imaging (MRI) environments for real-time monitoring and targeting. Recently, more compact multi-element ultrasonic systems have been introduced for neuromodulation to offer steering capability [36,37] or aberration correction [38], and the ability to be used outside an MRI environment. Despite this progress, achieving efficient and safe TUS in patients remains challenging. Indeed, focused ultrasound presents potential mechanical risks associated with acoustic cavitation (the growth and collapse of pre-existing microbubbles under the influence of an ultrasonic field), and potential thermal risks associated with excessive energy deposition that can cause irreversible thermal ablation [39]. In contrast to other brain neuromodulation techniques used in medicine, there are currently no established safety guidelines for the newly emerging TUS.

In this context, we developed a portable clinical TUS device based on personalized acoustic metamaterials, metalens-based TUS (mTUS), which allows adaptive skull aberration corrections [32,40]. The profile of the metalens is designed to counteract the patient-specific skull deformation [41] and to reproduce the wavefront that would be generated by a multi-element array. It enables precise focusing by

emitting a complex distorted wave upstream of the skull, so that the phase shifts induced by the skull restore a spherical wave that converges towards the intended target. The metalens additionally addresses the second challenge, i.e. portability, as it is integrated into a simple, lightweight, portable ultrasound system. We then conceived a patient-specific treatment planning pipeline for both personalized metalens design and personalized MRI tractography-based targeting. Ultrasound-specific biophysical risks were assessed using a series of calibrated measurements in open water and through *ex vivo* skulls.

Here, we report the feasibility, safety, tolerability, and preliminary efficacy from an open-label trial on five TRD patients treated with mTUS.

# 2. Methods

## 2.1. Open-label trial design

The StimulUS study, a monocentric open-label pilot trial, was approved by a French Ethical Committee (ID-RCB number: 2022-A00178-35) and registered in the U.S. Clinical Trials registry (NCT06085950 [42]). All patients gave written informed consent to participate in this study. This study was carried out at Hôpital Sainte-Anne (S17-18 adult psychiatry department, GHU Paris Psychiatrie et Neurosciences, Université Paris Cité, Paris, France).

## 2.2. Participants

Participants were required to have a diagnosis of major depressive episode (MDE) as part of major depressive disorder (MDD) as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) [43]. The episode had to be severe, defined as Hamilton Depression Rating Scale higher than 20 (HDRS-17 > 20), and drug-resistant, defined as resistant to at least two antidepressant trials of adequate doses and durations [44]. Antidepressant treatment was required to have been unchanged for at least 4 weeks prior to inclusion and was maintained at least until the end of the follow up of the study. Participants were required to be between 18 and 75 years old. Non-inclusion criteria were: psychiatric history, including bipolar disorder; neurological history, including epilepsy and intracerebral calcifications; history of substance use disorder other than tobacco; contraindication to brain MRI; compulsory psychiatric care; protected adults, people under legal protection; pregnant or breastfeeding women; women of childbearing age without a negative pregnancy test and not using contraception.

## 2.3. MRI data acquisition

MRI data were acquired at the brain imaging facility of the GHU Paris Psychiatrie & Neurosciences with a 3-T MRI (Vantage Galan 3T/XGO; Canon Medical Systems) and a 32-channel head coil. Anatomical T1-weighted MPRAGE sequences, fluid-attenuated inversion recovery (FLAIR) sequences, T2*-weighted imaging, diffusion tensor imaging (DTI), and resting-state functional (rs-fMRI) data were acquired at the inclusion visit and the week after the 5-day mTUS protocol. T1, FLAIR and T2* data were compared before and after treatment to assess the safety of mTUS. T1 and DTI data were used for personalized targeting. Rs-fMRI was used to assess changes in connectivity after mTUS. MRI sequence parameters are detailed in the Supplementary Material.

## 2.4. mTUS device

We developed a portable clinical TUS device based on personalized acoustic metamaterials (Fig. 1a-b). mTUS was delivered using a spherical transducer (center frequency of 500 kHz, radius of curvature of 10 cm, aperture diameter of 10 cm, Serial Number 13474-1002, Imasonic, Voray-sur-l'Ognon, France) connected to dedicated driving electronics
<figure><img src="image_4.png" /><figcaption>Fig. 1. Metalens-based transcranial ultrasound stimulation (mTUS).</figcaption></figure>

a. Adaptive techniques for ultrasonic transcranial focusing. Single-element ultrasound transducers emit a spherical wave distorted by the skull, which may lead to an inability to focus the energy at a given point in the brain. Multi-element devices, deforming the ultrasound field upstream of the skull to regain its spherical shape behind the skull, are the gold standard for compensating for skull-induced aberrations. Personalized metalenses, designed for a given patient and target, apply this principle to single-element transducers which are cheaper, smaller, and simpler to use. b. Photography of the mTUS prototype, calibrated for safety, tested for precision, and approved for human use in a pilot study by the French ANSM and an independent ethics committee. c. Personalized metalenses are designed through an automated pipeline. Step 1: acquisition of skull CT images (upper row), brain anatomical T1 MRI (middle row) and a tractogram reconstructed from diffusion MRI sequences (lower row). d. Step 2: definition of the personalized target as the intersect of three left subcallosal cingulate (SCC) white matter tracts: the forceps minor (FM), the uncinate fasciculus (UF) and the cingulum bundle (CB). e. Step 3: design of the personalized metalens for wave front shaping. After defining the transducer position, a “backward” numerical simulation is performed from the target to the modeled transducer. Time offsets are used to design the metamaterial with variable thickness (Δwidth). A “forward” simulation then estimates the precision of the metalens. f. Step 4: 3D printing of a mold to produce the metalens. Steps 3 requires 1h and step 4 requires 6 h per metalens. g. The position and orientation of the metalens relative to the patient are loaded into a modified neuronavigator. Participants undergo an intensive mTUS course: five 5-min sessions per day for 5 days, with an overall duty cycle of 1.8 % to inhibit SCC.

(custom-made prototype developed with Image Guided Therapy, Pessac, France) operating at 500 kHz. The free field (in water) lateral and axial dimensions of the –3 dB oval-shaped acoustic beam cross-sections were 2.9 and 18 mm, respectively. The transducer was mounted in a custom 3D-printed housing which included mounting clips to hold the personalized metalens. Coupling to the patient's scalp was achieved using a degassed water-filled silicone membrane and with additional medical acoustic gel (colorless contact gel, Drexco Medical, Crosne, France) on the membrane and on the skin. An optical neuronavigator (Visor2, ANT Neuro, Hengelo, The Netherlands) was used for targeting, allowing the clinician to overlay the metalens-corrected acoustic focus on the target area displayed on the pre-treatment T1 MR images. We calibrated the

neuronavigator for the acoustic focus to be displayed on the screen to match the focal position of the transducer (as detailed in the Supplementary Material). The mean ± SD measured error was 0.09 ± 0.07 mm. A non-invasive head support system ensured that participants' heads remained immobile during the sessions.

The electronics were programmed to deliver ramped pulses with a 5 % duty cycle (pulse duration of 4.5 ms including ramp duration of 0.75 ms, pulse repetition interval of 71 ms, pulse repetition frequency of 14 Hz), repeated in a pulse train (pulse train duration of 5 s, pulse train repetition interval of 15 s, pulse train repetition frequency of 0.07 Hz, pulse train duty cycle of 33 %), resulting in an overall duty cycle of 1.8 % (Fig. 1g), according to the ITRUSST reporting terminology [45]. A low
duty cycle associated with inhibitory stimulation [46] was used since depression is associated with SCC hyperactivity [47,48]. The sonication patterns were inspired by previous studies [49,50] and optimized to ensure thermal safety. The 5-s pattern was repeated 20 times for a total treatment time of 5 min. Ramping was applied to each pulse to avoid auditory cofound [51], as described in Ref. [52]. After each mTUS session, participants were asked if they heard any particular sounds during the session. The total electric power administered was the same for each subject, which resulted in different ultrasound exposures at the target due to varied skull losses, estimated using numerical simulations. Pulsed ultrasound was applied for 5 min, 5 times per day for 5 days with a minimum delay of 1 h between two sessions.

Ultrasound-specific biophysical risks of ultrasound device were assessed using a series of calibrated measurements in open water and through *ex vivo* skulls, detailed in the Supplementary Material. In summary, the prototype exposures are consistent with an $MI < 1.9$, a $TIC < 2$ and a maximum thermal rise < 2 °C. The electromagnetic compatibility and electrical safety of the instrument have been certified by an independent laboratory (Laboratoire Central des Industries Electriques, Fontenay-Aux-Roses, France). Aspects of standards IEC 60601-1-2: 2014 and IEC 60601-1: 2012 were used. No CE or FDA marking was sought for this device, and so some tests related only to commercial products and thus not necessary for performing clinical studies were not performed. However, all key safety elements relating to radiation emission, electrostatic discharge, RF electromagnetic fields, leakage current, dielectric strength test of solid insulating materials with safety function, excessive temperatures in the equipment and proximity fields from RF wireless communications have been tested and found compliant. The complete ultrasound device (Fig. 1b), including electronics, transducer, acoustic metalens, neuronavigator, chair and head support system, obtained the French National Agency for Medicinal Products (ANSM) authorization for use in a pilot open-label trial.

## 2.5. Personalized acoustic metalenses

In order to achieve the accuracy required for targeting, the aberrations caused by the human skull must be corrected [53]. Here, the thickness of the metalens placed in front of a simple transducer was adjusted to induce the same wavefront that would be produced by a multi-element array (Fig. 1a), as detailed below. As described by Maimbourg et al. [41], the variable thickness of the metalenses was computed for a given skull and target to shape the ultrasound field in front of the skull so that the skull-induced aberrations were restored to a spherical and therefore focused wave [41]. Their design is based on simulation, using skull speed of sound and density maps derived from CT scans, as described in Marsac et al. [54]. A cranial CT scan was acquired for each subject and registered to the T1 MR images using rigid transformation with Elastix software [55]. CT acquisition parameters are detailed in the Supplementary Material.

Numerical simulations were performed using the GPU-accelerated k-Wave Toolbox [56] code on a Titan RTX graphics card (NVIDIA, Santa Clara, CA, USA) and Matlab 2019b (Mathworks, Natick, MA, USA). The skull properties used in the simulations were derived from the CT scans as described by Maimbourg et al. [57]. Simulations were performed at a resolution of 0.3 mm (λ/10) with a CFL ratio of 0.1.

Robustness of metalens precision was assessed on *ex vivo* skulls prior to the clinical trial, on patients' CT scans throughout the clinical trial, and according to transducer positioning deviations, as detailed in the Supplementary Material.

## 2.6. Treatment planning pipeline

A patient-specific treatment planning pipeline was developed for both personalized metalens design and personalized MRI tractography-based targeting (Fig. 1c-f). The DTI sequences were computed into a full tractogram using MRTrix [58] and the methodology detailed in the B.A.

T.M.A.N. pipeline [59]. The first step of the pipeline was the overlay of skull computed tomography (CT), brain MRI and tractogram (Fig. 1c). Patient-specific targets were defined using tractograms from the crossing in the left SCC of the forceps minor, the cingulum bundle and the uncinate fasciculus (Fig. 1d), as in invasive DBS where a correlation between antidepressant efficacy and stimulation engagement in these specific white matter fiber bundles has been demonstrated [12,60–62]. The initial transducer position was determined so that the ultrasound beam passes through the forehead, avoiding sensitive structures (the eyes) and air (the sinuses). The distortions induced by the skull bone were estimated by simulating the propagation of an acoustic wave originating from the target and propagating towards the transducer position (Fig. 1e) using CT-derived skull acoustic property maps. The phase shifts induced by the skull at each simulation grid point on the surface of the transducer were then calculated, as was the thickness of the metamaterial required to compensate for them (1h process). Then, a silicone with known acoustic properties was cast between a hemispherical mold and the personalized 3D-printed counter-mold (6h process) generated by the automated pipeline (Fig. 1f). Finally, the position and orientation of the metalens relative to the patient were loaded into the neuronavigator for the intensive 5-day mTUS course (Fig. 1g).

This treatment pipeline also provided each participant with an estimate of the spatial position of the maximum pressure in the brain, and the acoustic intensity at target. To quantify the spatial correction provided by the metalens, these two values were estimated for two conditions: (i) without correction of skull-induced aberrations (i.e., without the metalens), and (ii) with the metalens.

## 2.7. Clinical assessment

Participants were assessed at 10 visits: at baseline, after the last session of each of the 5 days of mTUS treatment (described below as day 1–5), and then weekly for 4 weeks after the week of treatment (described below as week 2–5). At each visit, the severity of depression was assessed using clinical and self-report assessments: the Montgomery-Åsberg Depression Rating Scale [63] (MADRS), the 17- and 6-item Hamilton Depression Rating Scale [64] (HDRS) and the Quick Inventory of Depressive Symptomatology-Self Report [65] (QIDS-SR).

The unintended effects of mTUS were collected each day of treatment, before the first session and after each of the 5 daily mTUS sessions, using an adapted version of the TMSens_Q, a consensus-based questionnaire designed to collect unintended effects of TMS [66]. This scale consists of 20 items that rate the most common sensations or involuntary effects of TMS on a scale of 0–4 (none/mild/moderate/marked/strong). A last item, a free-form question about other sensations or unexpected effects, is included in this scale. This scale has been modified to replace the item "Coil pressure" with "Transducer pressure". Cognitive side effects were screened from neuropsychological assessments, conducted the week before and the week after the 5-day mTUS course, including an evaluation of processing speed (D2 test of attention [67]), sustained attention (D2 test of attention), cognitive flexibility (trail making test [68]), verbal fluency (category fluency task [69]), anterograde memory (16-item Grober & Buschke test [70]), working memory (WAIS-IV, digit span [71]) and inhibition (Stroop test [72]).

Serious adverse events were screened at each study visit using the CTCAE V5.0 [73]. Finally, a follow-up MRI scan was performed the week after treatment and analyzed by the neuroradiological team to detect any post-treatment signal changes.

## 2.8. Statistical analysis

Statistical analyses were performed using R software version 4.3.2 [74]. The primary outcome of the open-label trial was the change in Montgomery-Åsberg Depression Rating Scale (MADRS) score from baseline to the endpoint at day 5. Hypothesis testing of MADRS decrease was performed using a one-sided Wilcoxon signed-rank permutation
test. The non-parametric permutation test was chosen to account for the small sample size. Response was defined as a 50 % reduction in MADRS score, and remission was defined as a MADRS score ≤10. Total MADRS, 17- and 6-item HDRS and QIDS-SR scores at each visit were used as secondary measures of change in depression severity. Data are presented as mean change ±SD and intervals. The methodology of the functional connectivity analyses is detailed in the Supplementary Material.

# 3. Results

## 3.1. Participant characteristics

Five participants were included. Table 1 summarizes the participants' demographic characteristics and drug treatment history. Patients' ages ranged from 23 to 75 years. The duration of the current depressive episode ranged from 18 to 109 months, and the mean ±SD initial severity of depression, as assessed with the MADRS score, was 37.2 ± 6.9 (range: [31-48]).

## 3.2. Accuracy of metalens-TUS

The personalized SCC targets were deeply located, at a mean ± SD depth of 67.1 ± 7.6 mm from the skin (range: [54.5–74.8]). The mean ± SD offset of the maximum pressure in the brain would have been 5.0 ± 4.3 mm (range: [1.6–12.3]) without correction (i.e., without the metalens), and was significantly improved (W = 15, p = 0.031) to 1.3 ± 0.4 mm (range: [1.0–1.8]) with the personalized metalens (Fig. 2a-b). The mean ± SD derated spatial peak time average intensity (I<sub>SPTA</sub>) at the target for the five participants would have been 91.7 ± 20.3 mW/cm² (range: [64.7–119.7]) without correction and was significantly increased (+101 %, W = 15, p = 0.031) to 184.4 ± 74.0 mW/cm² (range: [103.6–291.9]) with the metalens (Fig. 2c). Robustness of metalens precision was furthermore assessed on ex vivo skulls prior to the clinical trial and on patients' CT scans throughout the clinical trial, as detailed in the Supplementary Material.

## 3.3. Safety and tolerance

The mTUS protocol consisted of five 5-min sessions a day over 5 days (Fig. 3a). All patients completed the 25 mTUS sessions. No serious adverse events occurred during this study and post-treatment MRI scans showed no signal changes in the brain. None of the patients reported any sensation or pain on the scalp during or after the sessions. They did not

<caption>**Table 1**</caption>

Characteristics of participants included in the open-label trial. Group values are reported in mean ± SD, unless otherwise stated.

<table><thead><tr><th rowspan="2"></th><th colspan="5">Participant</th><th rowspan="2">Group</th></tr><tr><th>#1</th><th>#2</th><th>#3</th><th>#4</th><th>#5</th></tr></thead><tbody><tr><td>Age (year)</td><td>23</td><td>38</td><td>59</td><td>75</td><td>58</td><td>50.6 ± 20.3</td></tr><tr><td>Sex</td><td>F</td><td>M</td><td>M</td><td>M</td><td>F</td><td>Female:2 (40 %)</td></tr><tr><td>Illness duration (years)</td><td>5.6</td><td>2.8</td><td>1.5</td><td>9.6</td><td>4.9</td><td>4.9 ± 3.1</td></tr><tr><td>Current episode duration (months)</td><td>38</td><td>29</td><td>18</td><td>109</td><td>29</td><td>44.6 ± 36.7</td></tr><tr><td>Number of past episodes</td><td>1</td><td>1</td><td>0</td><td>1</td><td>8</td><td>2.2 ± 3.3</td></tr><tr><td>Adequate antidepressant trials (current episode)</td><td>4<sup>a</sup></td><td>2</td><td>5</td><td>2</td><td>3</td><td>3.2 ± 1.3</td></tr><tr><td>Adequate augmentation trials (current episode)</td><td>1</td><td>1</td><td>1</td><td>0</td><td>1</td><td>0.8 ± 0.4</td></tr><tr><td>Maudsley Staging Method score</td><td>10</td><td>9</td><td>10</td><td>8</td><td>10</td><td>9.4 ± 0.9</td></tr><tr><td>Baseline MADRS</td><td>33</td><td>34</td><td>40</td><td>48</td><td>31</td><td>37.2 ± 6.9</td></tr><tr><td>Baseline QIDS-SR</td><td>13</td><td>14</td><td>20</td><td>23</td><td>13</td><td>16.6 ± 4.6</td></tr><tr><td>Baseline HDRS-17</td><td>24</td><td>23</td><td>27</td><td>33</td><td>22</td><td>25.8 ± 4.4</td></tr><tr><td>Baseline HDRS-6</td><td>16</td><td>13</td><td>14</td><td>19</td><td>15</td><td>15.4 ± 2.3</td></tr></tbody></table>

hear any sound and could thus not distinguish between periods of ultrasound emission and free intervals.

Of the 20 items on the tolerance questionnaire completed after each of the 25 mTUS sessions (a total of 125 records for the 5 patients), 8 unintended effects were reported (Suppl. Fig. 1 and Suppl. Fig. 2): sleepiness was reported after 31/125 sessions, anxiety/nervousness after 3/125 sessions, tinnitus after 2/125 sessions, fatigue after 2/125 sessions, and tingling (in the right arm), burning or heat (in the right arm), euphoria, and transducer pressure after 1/125 sessions. These unintended effects were transient, as they were absent the day after they occurred and during follow-up visits in all cases.

Suppl. Table 1

## 3.4. Efficacy

The primary outcome of the preliminary clinical study was the change in MADRS between the baseline and the fifth day of treatment. There was a significant change in MADRS at day 5, with a mean reduction of 60.9 % (range: [30 %–83.9 %], paired one-sided Wilcoxon signed-rank test = 15, p = 0.031), from a mean ± SD score of 37.2 ± 6.9 (range: [31–48]) at baseline to 14.8 ± 8.6 (range: [5–28]) after the final mTUS session at day 5 (Fig. 3c). At the end of the treatment week (on day 5), four out of five patients qualified as responders (≥50 % decrease in the MADRS), with two of these responders in full remission (MADRS ≤10). At the 4-week follow-up visit, there was a persistent 22.4 % (range: [0 %–47.5 %]) reduction on the MADRS across all five patients (Fig. 3d) but no participants met the response criteria. Equivalent results were found for the secondary efficacy outcomes (change in scores on the 6-item HDRS, 17-item HDRS, and QIDS-SR, see Suppl. Table 2 for group and individual data).

## 3.5. Neuropsychological outcomes

Following treatment, neuropsychological performance demonstrated improvement or stability in the domains of processing speed, sustained attention, cognitive flexibility, verbal fluency, anterograde memory, working memory and inhibition (Fig. 3b). Individual neuropsychological data is reported in Suppl. Table 1.

## 3.6. Changes in functional connectivity

An exploratory analysis was performed on all subjects to estimate changes in functional connectivity of the stimulated left SCC by comparing resting state functional MRI (fMRI) sequences before and after the 5-day treatment. Two significant clusters involved in the SCC long-range connectivity network in depression were identified: a left dorsolateral prefrontal cortex (DLPFC) region (MNI coordinates [−28 48 28], see Suppl. Fig. 3 and Suppl. Table 3), with an increased connectivity after treatment, and the right hippocampal and parahippocampal region (MNI coordinates [−42–8 30]), with a decreased connectivity after treatment. Three other significant clusters were identified, in the left postcentral gyrus, the left supplementary motor area, and close to the left primary motor cortex (Suppl. Table 3).

# 4. Discussion

In this study, we report the development and performance of a portable metalens-based TUS technology that enables safe, precise and non-invasive deep brain neuromodulation for TRD. Although preliminary, our findings indicate that precise ultrasound neuromodulation of the crossing of the forceps minor, the cingulum bundle and the unicate fasciculus [60] within the SCC led to a significant reduction in depressive symptoms over a span of 5 days among five patients with TRD, with no serious adverse events. The primary endpoint, the percentage reduction in MADRS score after a 5-day course of mTUS, demonstrated a significant mean reduction of 60.9 % (range: [30 %–

<footnote>a Including a course of esketamine.</footnote>
<figure><img src="image_5.png" /><figcaption>b</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>c</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>d</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>**Fig. 2.** Metalens spatial precision contribution in treatment-resistant depression.</figcaption></figure>

a. Quasi-sagittal (rotated to be in the plane of the metalens) and axial sections of co-registered brain MRI, skull CT and delivered acoustic intensity at target (white cross) for subject #2. b-c. Without metalens, the stimulation is associated with a significantly increased offsets in targeting (b., p = 0.031), and with significantly lower acoustic intensity at target (c., p = 0.031). Boxplots start at the first quartile and end at the third. The inner line represents the median. d. The target was individually defined as the crossing of three left SCC white matter tracts involved in TRD: the forceps minor (FM), the uncinate fasciculus (UF) and the cingulum bundle (CB). The white matter fibers recruited, that overlap the acoustic focus, for subject #2 are shown with the personalized metalens and without it (i.e. if it hadn't been used). Right: the simulated acoustic intensity field is superimposed on the intersect of the SCC white matter tracts.

<figure><img src="image_9.png" /><figcaption>b</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>c</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>d</figcaption></figure>

<figure><img src="image_12.png" /></figure>

**Fig. 3.** Preliminary results for mTUS tolerance and efficacy in treatment-resistant depression. a. Design of the open-label trial. b. mTUS cognitive tolerance was assessed by means of neuropsychological tests performed before and after the 5-day treatment. Neuropsychological data are available for 4 subjects. Group data are presented as z-scores adjusted for age and education. A higher z-score corresponds to better performance. c-d. Changes in MADRS depression scores during treatment week (c.) and follow-up (d.). Error bars representing standard error of mean are shown. MADRS scores decreased, from a mean ± SD score of 37.2 ± 6.9 at baseline to 14.8 ± 8.6 at day 5 (–60.2 %, p = 0.031). Response (MADRS ≤50 % of initial score) and remission (MADRS ≤10) were achieved in 4/5 and 2/5 patients at day 5, respectively.
83.9 %]). Furthermore, the response and remission rates reached 80 % (4 out of 5 patients) and 40 % (2 out of 5 patients), respectively, after the 5-day treatment period. Although these results are based on a small number of patients and an open design, they appear promising, particularly in terms of speed of efficacy. Indeed, a recent large-scale open-label study of two treatments currently indicated for TRD, ECT and esketamine, reported response rates of 55.4 % and 41.2 %, respectively, but with longer treatment time (3 weeks of treatment) [75]. Conventional drug approaches are less effective and have a longer onset of action in TRD, as demonstrated in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial [76]. After failure of the first two treatment steps in the STAR*D trial, the response rates for the third and fourth courses were 16.8 % and 16.3 %, and the onsets of action were 6.4 weeks and 8.3 weeks, respectively. Of note, in addition to behavioral changes, our SCC-mTUS also yielded functional brain changes. Exploratory analysis evidenced a modification of SCC connectivity with both the right hippocampus and left dorsolateral prefrontal cortex (DLPFC) at the group level, two regions widely involved in TRD [77,78]. Interestingly, the left DLPFC region identified here is close (Euclidean distance of 11 mm) to the most widely used repetitive transcranial magnetic stimulation (rTMS) target in the treatment of TRD [79], a region identified and selected for its intrinsic functional connectivity to the SCC [80].

The mechanism of ultrasound neuromodulation is still not fully understood but is primarily due to mechanical [81] rather than thermal effects [16]. It has been shown that focused ultrasound was able to excite cultured murine neurons through a mechanical mechanism mediated by specific calcium-selective mechanosensitive ion channels and that the activation of these channels results in a progressive build-up of calcium, which then produces a burst firing response [82]. In addition to neurons, ultrasound modulation of calcium activity has been reported in cultured murine glial cells, endothelial cells and pericytes [83].

The precision of transcranial ultrasound refocusing is key for clinical translation. When high-intensity focused ultrasound is used to induce an irreversible lesion, the devices include a correction for skull-induced aberrations with multi-element transducers [35,84]. Without correction, there would be no guarantee that the lesion would be at the intended location, and the risk would not be acceptable. The risk-benefit ratio for ultrasound neuromodulation is lower and the excitement surrounding promising preclinical results [23,25,85] led to a growing number of human applications that neglect the impact of the skull [15, 37,51,86–109]. Nevertheless, the human skull is thicker and more heterogeneous than that of species such as rodents and non-human primates studied preclinically [29], and it defocuses ultrasound waves. Recently, Rezai et al. [110] and Bancel et al. [111] took advantage of a high intensity 1024-element clinical array with skull aberration correction developed for thalamotomy [112] and operated the device at its lowest energy bound to explore the feasibility of deep brain transcranial ultrasound stimulation on addiction and essential tremor patients, respectively. The 1024-element device offers state-of-the-art transcranial refocusing capabilities, but is oversized for neuromodulation since these devices are not portable, are embedded in an MRI machine, and have cumbersome multichannel electronics to adjust time delays to compensate for the effect of the skull. The personalized metamaterials introduced here offer high precision and are suitable for neuromodulation. The metalens approach is based on the general principle of acoustic holography [113]. A hologram stores the phase and/or the amplitude of a desired wavefront [114] and reconstructs the wavefront by interference when the hologram is illuminated by a coherent source. In acoustics, the phase and the amplitude of the hologram can be stored electronically and emitted by multielement phased arrays [115–117]. However, the number and the size of the elements is limited by the electronics and the paving of the array [118], which constrains the degrees of freedom and the spatial spectral content of the phase and amplitude screen. Acoustic lenses with a varying thickness have thus been introduced to store the phase [119] and the amplitude [120] of the

wavefront. The resolution of multi-element arrays is limited by the size of the individual elements, typically several wavelengths [121]. The resolution of acoustic lenses depends on their design. The resolution of the 3D printers used to fabricate acoustic lenses is typically as low as 300 µm [40] to 250 µm [122] corresponding to one fifth of the wavelength in Ref. [40] and to one twelfth of the wavelength in Ref. [122]. The ability to control the wavefront with sub-wavelength details is a singularity of metamaterials and such high-resolution lenses are called metasurfaces [122]. In this open-label trial, the mold used to cast the metalenses was 3D printed with a resolution of one fifth of the wavelength. The mean absolute 3D offset with these metalenses was 1.3 mm, compared to 5.0 mm with no correction. Without correction, the shifts in peak pressure were associated with a lower acoustic intensity at the predefined target, on average half that with the metalens. Although the positioning of the metalens relies on the precision of the neuronavigator, there is tolerance for transducer steering or misalignment, as previously demonstrated [41] and further explored here through numerical simulations of lateral positioning errors up to 2 mm (detailed in the Supplementary Material). These results confirm that the metalens prototype is appropriate for clinical use, with a total calculation time and manufacturing process of a few hours, millimetric precision, and good usability. Each patient and each targeting require a unique personalized metalens. Compared to multi-element systems, which are more flexible for users but more expensive and bulkier, the scalability of mTUS will depend on the manufacturing and logistics solutions offered by the company who will license the intellectual property of the metalens approach.

High precision TUS has the potential to offer unique advantages to the field of neurostimulation in neuropsychiatry. Electroconvulsive therapy (ECT) [123,124] is the most efficient treatment for TRD but causes adverse cognitive effects such as retrograde amnesia [125] and is not widely available due to the required general anesthesia. Compared to current non-invasive techniques (TMS and transcranial direct current stimulation, tDCS) which are limited to shallow targets, mTUS allows stimulation of deep brain regions, hubs of altered connectivity networks in psychiatric disorders [126–128], with unprecedented spatial resolution. Compared to invasive DBS, mTUS avoids the risks associated with neurosurgical procedures such as infection and hemorrhagic risks [13, 129,130]. Invasive DBS is thus restricted to a small number of patients suffering from the most resistant and severe forms of mental disorders: a recent review of DBS in TRD [5] reported a total of 432 patients treated in randomized controlled trials (n = 239) and open-label studies (n = 193) since the first proof of concept in 2005 [131]. The unintended effects reported here, mostly fatigue, were transient and not severe. In particular, patients did not experience any discomfort or pain at the site of stimulation during the sessions and no participants withdrew from the study. Moreover, the patients did not report hearing any sound nor experiencing any discomfort that could be attributed to ultrasound exposure, with the inability to distinguish between emission periods and pauses. Hence, the development of randomized placebo-controlled studies of TUS with robust double-blinding will be facilitated.

Other TUS protocols have been proposed, highlighting the therapeutic potential of ultrasound neuromodulation for TRD. In particular, Oh et al. conducted a randomized sham-controlled trial on drug-naïve or drug-resistant depression, targeting the same superficial cortical region as in rTMS, the left DLPFC [132]. As superficial targeting is less sensitive to skull-induced shifting of the acoustic focus, Oh et al. team used a device that did not correct for skull-induced aberrations and reported a 41 % decrease in depressive intensity after two weeks of treatment in the active group. Riis et al. targeted the same deep region as in this study, the SCC, with a multi-element system to correct for skull aberrations, in a double-blind, randomized, sham-controlled, crossover trial. Although no significant differences were found in the crossover statistical analyses, they report a mean reduction in depression severity of 55 % after a single TUS session [133]. Another TUS device based on a multi-element technology used for electronic steering (and not for skull-induced
aberration correction) has recently been tested for deep neuro-
modulation in epilepsy [37] and blood-brain barrier opening [36]
outside of an MRI environment. Finally, transcranial temporal interfer-
ence stimulation (tTIS), another emerging non-invasive deep neuro-
modulation technique, has recently been proposed to target SCC in
depression [134]. tTIS uses high-frequency (>1 kHz) alternating electric
fields applied through multiple scalp electrodes and interfering within
the brain to create a low-frequency envelope that can selectively stim-
ulate deep brain structures [135]. However, this technique is associated
with lower focality compared to mTUS and requires large computational
resources to account for the inter-individual variability of electric fields
[136].

Nevertheless, mTUS would benefit from further improvements. First, patients underwent a CT scan and a brain MRI prior to treatment. The use of magnetic resonance bone imaging [137–139] could advantageously overcome the need for CT scans. Second, the depression severity shows a continuous decrease over the 5 days of treatment without reaching a floor, in favor of a stimulation dose escalation. Patients follow-up demonstrated a progressive worsening of depression after the 5-day mTUS course, suggesting the potential benefit of consolidation sessions, similarly to those conducted with ECT and esketamine [140, 141]. Another limitation is the lack of direct monitoring of the stimulated region during sessions; functional MRI during sessions would highlight the online effect of ultrasound neuromodulation [133]. Finally, the preliminary data presented here are from an open-label, uncontrolled trial in a small number of patients. The clinical efficacy of mTUS in TRD needs to be confirmed in larger cohorts with double-blinded randomized controlled trials.

Overall, mTUS could open new avenues in neuroscience and medi-
cine. Non-invasive deep brain neuromodulation paves the way for (i)
causal inference of deep brain regions in neuroscience, as TMS has done
for superficial cortical structures, the role of deep brain regions being
until now only studied using correlational approaches with functional
MRI, electroencephalography or magnetoencephalography; (ii) a pre-
liminary step for personalized targeting with invasive DBS by testing the
efficacy of non-invasive stimulation of one or more deep brain targets
prior to neurosurgery; and (iii) non-invasive deep brain stimulation in
drug-resistant neuropsychiatric disorders for which invasive DBS has
been shown to be effective - such as for obsessive-compulsive disorder,
addiction, eating disorders, and Tourette syndrome - with the potential
for widespread dissemination.

Funding

This work was supported and funded by the Focused Ultrasound Foundation (Charlottesville, VA, USA). The work performed in this publication was performed with the support of the Inserm Technology Research Accelerator (Inserm ART) in Biomedical Ultrasound (Paris, France) and with financial support from Inserm to the booster program NeuroTechnologies (Paris, France).

CRediT authorship contribution statement

**David Attali:** Writing – review & editing, Writing – original draft, Visualization, Software, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization. **Thomas Tiennot:** Writing – review & editing, Writing – original draft, Software, Methodology, Formal analysis, Data curation, Conceptualization. **Thomas J. Manuel:** Writing – review & editing, Writing – original draft. **Maxime Daniel:** Writing – review & editing. **Alexandre Houdouin:** Writing – review & editing, Resources. **Philippe Annie:** Writing – review & editing, Resources. **Alexandre Dizeux:** Writing – review & editing, Visualization. **Alexandre Haroche:** Writing – review & editing, Investigation. **Ghita Dadi:** Writing – review & editing, Investigation. **Adèle Henensal:** Writing – review & editing, Formal analysis. **Mylène Moyal:** Writing – review & editing. **Alice Le Berre:** Writing – review & editing,

Methodology. **Cécile Paolillo:** Writing – review & editing, Investiga-
tion. **Sylvain Charron:** Writing – review & editing, Methodology.
**Clément Debacker:** Writing – review & editing, Methodology. **Maliesse
Lui:** Writing – review & editing, Methodology. **Sabrina Lekcir:** Writing
– review & editing, Project administration. **Rosella Mancusi:** Writing –
review & editing, Formal analysis. **Thierry Gallarda:** Writing – review
& editing. **Tarek Sharshar:** Writing – review & editing. **Khaoussou
Sylla:** Writing – review & editing, Project administration. **Catherine
Oppenheim:** Writing – review & editing, Supervision, Methodology.
**Arnaud Cachia:** Writing – review & editing, Supervision, Methodology.
**Mickael Tanter:** Writing – review & editing, Supervision, Resources,
Methodology, Funding acquisition, Conceptualization. **Jean-Francois
Aubry:** Writing – review & editing, Writing – original draft, Supervision,
Methodology, Funding acquisition, Formal analysis, Conceptualization.
**Marion Plaze:** Writing – review & editing, Writing – original draft,
Supervision, Methodology, Investigation, Funding acquisition, Formal
analysis, Conceptualization.

Declaration of competing interest

MP has been invited to scientific meetings, consulted and served as a speaker, and received compensation from Janssen. TT, JFA and MT hold patents related to the technology described in this study. After the study was completed, TT, JFA and MT co-founded SonoMind, a startup company related to the technology described in this study and hold shares. After the study was completed, TJM became a consultant for Nudge, a company developing transcranial ultrasound stimulation. The remaining authors declare no competing interests and no financial relationships with commercial interests.

Acknowledgements

We thank the patients for the trust and commitment that enabled this
first clinical study. We thank all the nursing and administrative staff who
devoted time and effort to the success of this research project.

The clinical trial was supported by the Groupe Hospitalier Uni-
versitaire Paris Psychiatrie et Neurosciences and its Delegation for
Clinical Research and Innovation as the sponsor; we thank Charlène Le
Garrec, Stéphane Geyssens, Didier André, Mamoudou Lah, Aurélien
Delas and Marin Chapelle.

We thank ANT Neuro (Berlin, Germany), Deymed (Cahors, France), Image Guided Therapy (Pessac, France), Imasonic (Voray-sur-l'Ognon, France), and SQI (Meylan, France) for their support throughout the development of the mTUS device.

Finally, we thank the reviewers for their significant contribution to
improve this work.

**Appendix A. Supplementary data**

Supplementary data to this article can be found online at https://doi.
org/10.1016/j.brs.2025.04.018.

References

[1] Ferrari AJ, Santomauro DF, Aali A, Abate YH, Abbafati C, Abbastabar H, et al. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 2024;403:2133–61. https://doi.org/10.1016/S0140-6736(24)00757-8.

[2] Howes OD, Thase ME, Pillinger T. Treatment resistance in psychiatry: state of the art and new directions. Mol Psychiatry 2022;27:58–72. https://doi.org/10.1038/s41380-021-01200-3.

[3] Crown WH, Finkelstein S, Berndt ER, Ling D, Poret AW, Rush AJ, et al. The impact of treatment-resistant depression on health care utilization and costs. J Clin Psychiatry 2002;63:963–71. https://doi.org/10.4088/jcp.v63n1102.

[4] Kennedy JL, Altar CA, Taylor DL, Degtiar I, Hornberger JC. The social and economic burden of treatment-resistant schizophrenia: a systematic literature
review. Int Clin Psychopharmacol 2014;29:63–76. https://doi.org/10.1097/YIC.0b013e32836508e6.

[5] Johnson KA, Okun MS, Scangos KW, Mayberg HS, de Hemptinne C. Deep brain stimulation for refractory major depressive disorder: a comprehensive review. Mol Psychiatry 2024. https://doi.org/10.1038/s41380-023-02394-4.

[6] Wu H, Hariz M, Visser-Vandewalle V, Zrinzo L, Coenen VA, Sheth SA, et al. Deep brain stimulation for refractory obsessive-compulsive disorder (OCD): emerging or established therapy? Mol Psychiatry 2021;26:60–5. https://doi.org/10.1038/s41380-020-00933-x.

[7] Corripio I, Roldán A, Sarró S, McKenna PJ, Alonso-Solís A, Rabella M, et al. Deep brain stimulation in treatment resistant schizophrenia: a pilot randomized cross-over clinical trial. EBiomedicine 2020;51. https://doi.org/10.1016/j.ebiom.2019.11.029.

[8] Karaszewska D, Cleintuar P, Oudijn M, Lok A, van Elburg A, Denys D, et al. Efficacy and safety of deep brain stimulation for treatment-refractory anorexia nervosa: a systematic review and meta-analysis. Transl Psychiatry 2022;12:1–7. https://doi.org/10.1038/s41398-022-02102-w.

[9] Shivacharan RS, Rolle CE, Barbosa DAN, Cunningham TN, Feng A, Johnson ND, et al. Pilot study of responsive nucleus accumbens deep brain stimulation for loss-of-control eating. Nat Med 2022;28:1791–6. https://doi.org/10.1038/s41591-022-01941-w.

[10] Schiff ND, Giacino JT, Butson CR, Choi EY, Baker JL, O'Sullivan KP, et al. Thalamic deep brain stimulation in traumatic brain injury: a phase 1, randomized feasibility study. Nat Med 2023;29:3162–74. https://doi.org/10.1038/s41591-023-02638-4.

[11] Hollunder B, Ostrem JL, Sahin IA, Rajamani N, Oxenford S, Butenko K, et al. Mapping dysfunctional circuits in the frontal cortex using deep brain stimulation. Nat Neurosci 2024;27:573–86. https://doi.org/10.1038/s41593-024-01570-1.

[12] Alagapan S, Choi KS, Heisig S, Riva-Posse P, Crowell A, Tiruvadi V, et al. Cingulate dynamics track depression recovery with deep brain stimulation. Nature 2023;622:130–8. https://doi.org/10.1038/s41586-023-06541-3.

[13] Berlim MT, McGirr A, Van den Eynde F, Fleck MPA, Giacobbe P. Effectiveness and acceptability of deep brain stimulation (DBS) of the subgenual cingulate cortex for treatment-resistant depression: a systematic review and exploratory meta-analysis. J Affect Disord 2014;159:31–8. https://doi.org/10.1016/j.jad.2014.02.016.

[14] McIntyre RS, Alsuwaidan M, Baune BT, Berk M, Demyttenaere K, Goldberg JF, et al. Treatment-resistant depression: definition, prevalence, detection, management, and investigational interventions. World Psychiatry 2023;22: 394–412. https://doi.org/10.1002/wps.21120.

[15] Lee W, Kim H-C, Jung Y, Chung YA, Song I-U, Lee J-H, et al. Transcranial focused ultrasound stimulation of human primary visual cortex. Sci Rep 2016;6:34026. https://doi.org/10.1038/srep34026.

[16] Constans C, Mateo P, Tanter M, Aubry J-F. Potential impact of thermal effects during ultrasonic neurostimulation: retrospective numerical estimation of temperature elevation in seven rodent setups. Phys Med Biol 2018;63:025003. https://doi.org/10.1088/1361-6560/aaa15c.

[17] Tufail Y, Matyushov A, Baldwin N, Tauchmann ML, Georges J, Yoshihiro A, et al. Transcranial pulsed ultrasound stimulates Intact brain circuits. Neuron 2010;66: 681–94. https://doi.org/10.1016/j.neuron.2010.05.008.

[18] Suarez-Castellanos IM, Dossi E, Vion-Bailly J, Salette L, Chapelon J-Y, Carpentier A, et al. Spatio-temporal characterization of causal electrophysiological activity stimulated by single pulse focused ultrasound: an ex vivo study on hippocampal brain slices. J Neural Eng 2021;18:026022. https:// doi.org/10.1088/1741-2552/abdfb1.

[19] Tufail Y, Yoshihiro A, Pati S, Li MM, Tyler WJ. Ultrasonic neuromodulation by brain stimulation with transcranial ultrasound. Nat Protocols 2011;6:1453–70. https://doi.org/10.1038/nprot.2011.371.

[20] Younan Y, Deffieux T, Larrat B, Fink M, Tanter M, Aubry J-F. Influence of the pressure field distribution in transcranial ultrasonic neurostimulation: influence of pressure distribution in transcranial ultrasonic neurostimulation. Med Phys 2013;40:082902. https://doi.org/10.1118/1.4812423.

[21] King RL, Brown JR, Newsome WT, Pauly KB. Effective Parameters for Ultrasound-Induced In Vivo Neurostimulation. Ultrasound in Medicine & Biology 2AD:39: 312–331. https://doi.org/10.1016/j.ultrasmedbio.2012.09.009.

[22] Estrada H, Robin J, Özbek A, Chen Z, Marowsky A, Zhou Q, et al. High-resolution fluorescence-guided transcranial ultrasound mapping in the live mouse brain. Sci Adv 2021;7:eabi5464. https://doi.org/10.1126/sciadv.abi5464.

[23] Folloni D, Verhagen L, Mars RB, Fouragnan E, Constans C, Aubry J-F, et al. Manipulation of subcortical and deep cortical activity in the primate brain using transcranial focused ultrasound stimulation. Neuron 2019. https://doi.org/ 10.1016/j.neuron.2019.01.019.

[24] Verhagen L, Gallea C, Folloni D, Constans C, Jensen DE, Ahnine H, et al. Offline impact of transcranial focused ultrasound on cortical activation in primates. Elife 2019;8:e40541. https://doi.org/10.7554/eLife.40541.

[25] Fouragnan EF, Chau BKH, Folloni D, Kolling N, Verhagen L, Klein-Flügge M, et al. The macaque anterior cingulate cortex translates counterfactual choice value into actual behavioral change. Nat Neurosci 2019;22:797–808. https://doi.org/ 10.1038/s41593-019-0375-6.

[26] Boroujeni KB, Sigona MK, Treuting RL, Manuel TJ, Caskey CF, Womelsdorf T. Anterior cingulate cortex causally supports flexible learning under motivationally challenging and cognitively demanding conditions. PLoS Biol 2022;20:e3001785. https://doi.org/10.1371/journal.pbio.3001785.

[27] Webb TD, Wilson MG, Odéen H, Kubanek J. Sustained modulation of primate deep brain circuits with focused ultrasonic waves. Brain Stimul 2023;16:798–805. https://doi.org/10.1016/j.brs.2023.04.012.

[28] Fry FJ, Barger JE. Acoustical properties of the human skull. J Acoust Soc Am 1978;63:1576–90.

[29] Lillie EM, Urban JE, Lynch SK, Weaver AA, Stitzel JD. Evaluation of skull cortical thickness changes with age and sex from computed tomography scans. J Bone Miner Res 2016;31:299–307. https://doi.org/10.1002/jbmz.2613.

[30] Gimeno LA, Martin E, Wright O, Treeby BE. Experimental assessment of skull aberration and transmission loss at 270 kHz for focused ultrasound stimulation of the primary visual cortex. 2019 IEEE international ultrasonics symposium (IUS). 2019. p. 556–9. https://doi.org/10.1109/ULTSYM.2019.8926097.

[31] Bancel T, Houdouin A, Annic P, Rachmilevitch I, Shapira Y, Tanter M, et al. Comparison between ray-tracing and full-wave simulation for transcranial ultrasound focusing on a clinical system using the transfer matrix formalism. IEEE Trans Ultrason Ferroelectrics Freq Control 2021;68:2554–65.

[32] Tanter M, Thomas J-L, Fink M. Focusing and steering through absorbing and aberrating layers: application to ultrasonic propagation through the skull. J Acoust Soc Am 1998;103:2403–10. https://doi.org/10.1121/1.422759.

[33] Clement GT, Hynynen K. A non-invasive method for focusing ultrasound through the human skull. Phys Med Biol 2002;47:1219–36. https://doi.org/10.1088/ 0031-9155/47/8/301.

[34] Aubry JF, Tanter M, Pernot M, Thomas JL, Fink M. Experimental demonstration of noninvasive transskull adaptive focusing based on prior computed tomography scans. J Acoust Soc Am 2003;113:84–93.

[35] Elias W Jeffrey, Nir Lipsman, Ondo William G, Ghanouni Pejman, Kim Young G, Lee Wonhee, et al. A randomized trial of focused ultrasound thalamotomy for essential tremor. N Engl J Med 2016;375:730–9. https://doi.org/10.1056/ NEJMoa1600159.

[36] Chen K-T, Chai W-Y, Lin Y-J, Lin C-J, Chen P-Y, Tsai H-C, et al. Neuronavigation-guided focused ultrasound for transcranial blood-brain barrier opening and immunostimulation in brain tumors. Sci Adv 2021;7:eabd0772. https://doi.org/ 10.1126/sciadv.abd0772.

[37] Lee C-C, Chou C-C, Hsiao F-J, Chen Y-H, Lin C-F, Chen C-J, et al. Pilot study of focused ultrasound for drug-resistant epilepsy. Epilepsia 2022;63:162–75. https://doi.org/10.1111/epi.17105.

[38] Riis T, Feldman D, Losser A, Mickey B, Kubanek J. Device for multifocal delivery of ultrasound into deep brain regions in humans. IEEE Trans Biomed Eng 2024; 71:660–8. https://doi.org/10.1109/TBME.2023.3319387.

[39] Miller D, Smith N, Bailey M, Czarnota G, Hynynen K, Makin I. Overview of therapeutic ultrasound applications and safety considerations. J Ultrasound Med 2012;31:623–34.

[40] Maimbourg G, Houdouin A, Deffieux T, Tanter M, Aubry J-F. 3D-printed adaptive acoustic lens as a disruptive technology for transcranial ultrasound therapy using single-element transducers. Phys Med Biol 2018;63:025026. https://doi.org/ 10.1088/1361-6560/aaa037.

[41] Maimbourg G, Houdouin A, Deffieux T, Tanter M, Aubry J-F. Steering capabilities of an acoustic lens for transcranial therapy: numerical and experimental studies. IEEE (Inst Electr Electron Eng) Trans Biomed Eng 2020;67:27–37. https://doi. org/10.1109/TBME.2019.2907556.

[42] Centre Hospitalier Sainte-Anne. Transcranial ultrasonic stimulation in treatment-resistant depression : an open-label pilot trial. n.d.

[43] American Psychiatric Association. Diagnostic and statistical manual of mental disorders: dsm-5. 5th Revised edition. Washington, D.C: American Psychiatric Association Publishing; 2013.

[44] Souery D, Papakostas GI, Trivedi MH. Treatment-resistant depression. J Clin Psychiatry 2006;67(Suppl 6):16–22.

[45] Martin E, Aubry J-F, Schafer M, Verhagen L, Treeby B, Pauly KB. ITRUSST consensus on standardised reporting for transcranial ultrasound stimulation. Brain Stimul 2024;17:607–15. https://doi.org/10.1016/j.brs.2024.04.013.

[46] Kim H-C, Lee W, Kunes J, Yoon K, Lee JE, Foley L, et al. Transcranial focused ultrasound modulates cortical and thalamic motor activity in awake sheep. Sci Rep 2021;11:19274. https://doi.org/10.1038/s41598-021-98920-x.

[47] Drevets WC, Savitz J, Trimble M. The subgenual anterior cingulate cortex in mood disorders. CNS Spectr 2008;13:663–81.

[48] Greicius MD, Flores BH, Menon V, Glover GH, Solvason HB, Kenna H, et al. Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol Psychiatry 2007;62:429–37. https://doi.org/10.1016/j.biopsych.2006.09.020.

[49] Yoo S-S, Bystritsky A, Lee J-H, Zhang Y, Fischer K, Min B-K, et al. Focused ultrasound modulates region-specific brain activity. NeuroImage 6AD:56: 1267–1275. https://doi.org/10.1016/j.neuroimage.2011.02.058.

[50] Pouget P, Frey S, Ahnine H, Attali D, Claron J, Constans C, et al. Neuronavigated repetitive transcranial ultrasound stimulation induces long-lasting and reversible effects on oculomotor performance in non-human primates. Front Physiol 2020; 11. https://doi.org/10.3389/fphys.2020.01042.

[51] Braun V, Blackmore J, Cleveland RO, Butler CR. Transcranial ultrasound stimulation in humans is associated with an auditory confound that can be effectively masked. Brain Stimul 2020;13:1527–34. https://doi.org/10.1016/j. brs.2020.08.014.

[52] Deffieux T, Younan Y, Wattiez N, Tanter M, Pouget P, Aubry J-F. Low-intensity focused ultrasound modulates monkey visuomotor behavior. Curr Biol 2013;23: 2430–3.

[53] Fry FJ, Ades HW, Fry WJ. Production of reversible changes in the central nervous system by ultrasound. Science 1958;127:83–4. https://doi.org/10.1126/ science.127.3289.83.

[54] Marsac L, Chauvet D, La Greca R, Boch A-L, Chaumoitre K, Tanter M, et al. Ex vivo optimisation of a heterogeneous speed of sound model of the human skull for
non-invasive transcranial focused ultrasound at 1 MHz. Int J Hyperthermia 2017; 33:635-45. https://doi.org/10.1080/02656736.2017.1295322.

[55] Klein S, Staring M, Murphy K, Viergever MA, Plum JPW. Elastix: a toolbox for intensity-based medical image registration. IEEE Trans Med Imag 2010;29: 196-205. https://doi.org/10.1109/TMI.2009.2035616.

[56] Treeby BE, Cox BT. k-Wave: MATLAB toolbox for the simulation and reconstruction of photoacoustic wave fields. JBO 2010;15:021314. https://doi.org/10.1117/1.3360308.

[57] Maimbourg G, Guilbert J, Bancel T, Houdouin A, Raybaud G, Tanter M, et al. Computationally efficient transcranial ultrasonic focusing: taking advantage of the high correlation length of the human skull. IEEE Trans Ultrason Electromagnics Freq Control 2020;67:1993–2002. https://doi.org/10.1109/TUFFC.2020.2993718.

[58] Tournier J-D, Smith R, Raffelt D, Tabbara R, Dhollander T, Pietsch M, et al. MRtrix3: a fast, flexible and open software framework for medical image processing and visualisation. Neuroimage 2019;202:116137. https://doi.org/10.1016/j.neuroimage.2019.116137.

[59] Tahedl M. B.A.T.M.A.N.: basic and advanced tractography with MRtrix for all neurophiles. https://doi.org/10.17605/OSF.IO/FKYHT; 2017.

[60] Riva-Posse P, Choi KS, Holtzheimer PE, Crowell AL, Garlow SJ, Rajendra JK, et al. A connectomic approach for subcallosal cingulate deep brain stimulation surgery: prospective targeting in treatment-resistant depression. Mol Psychiatr 2018;23: 843–9. https://doi.org/10.1038/mp.2017.59.

[61] Gutman DA, Holtzheimer PE, Behrens TEJ, Johansen-Berg H, Mayberg HS. A tractography analysis of two deep brain stimulation white matter targets for depression. Biol Psychiatry 2009;65:276–82. https://doi.org/10.1016/j.biopsych.2008.09.021.

[62] Riva-Posse P, Choi KS, Holtzheimer PE, McIntyre CC, Gross RE, Chaturvedi A, et al. Defining critical white matter pathways mediating successful subcallosal cingulate deep brain stimulation for treatment-resistant depression. Biol Psychiatry 2014;76:963–9. https://doi.org/10.1016/j.biopsych.2014.03.029.

[63] Montgomery SA, Asberg M. A new depression scale designed to be sensitive to change. Br J Psychiatry 1979;134:382–9.

[64] Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatr 1960;23: 56–62.

[65] Rush AJ, Trivedi MH, Ibrahim HM, Carmody TJ, Arnow B, Klein DN, et al. The 16-Item Quick Inventory of Depressive Symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression. Biol Psychiatry 2003;54:573–83.

[66] Giustiani A, Vallesi A, Oliveri M, Tarantino V, Ambrosini E, Bortoloetto M, et al. A questionnaire to collect unintended effects of transcranial magnetic stimulation: a consensus based approach. Clin Neurophysiol 2022;141:101–8. https://doi.org/10.1016/j.clinphys.2022.06.008.

[67] Brickenkamp R, Zilmer E. d2 test of attention. Seattle, Washington: Hogrefe & Huber Publishers; 1998.

[68] Spreen O, Strauss E. A compendium of neuropsychological tests: administration, norms, and comments. USA: Oxford University Press; 1998.

[69] Lezak MD. Neuropsychological assessment. USA: Oxford University Press; 1995.

[70] Grober E, Buschke H. Genuine memory deficits in dementia. Dev Neuropsychol 1987;3:13–36. https://doi.org/10.1080/87565648709540361.

[71] Wechsler D. Wechsler adult intelligence scale. fourth ed. San Antonio, TX: Pearson; 2008.

[72] Stroop JR. Studies of interference in serial verbal reactions. J Exp Psychol 1935; 18:643–62. https://doi.org/10.1037/h0054651.

[73] Common Terminology Criteria for Adverse Events (CTCAE) n.d. https://ctep.cancer.gov/protocoldevelopment/electronic_applications/docs/CTCAE_v5_Quick_Requerence_8.5x11.pdf.

[74] R Core Team. R: a language and environment for statistical computing. 2021.

[75] Anand A, Mathew SJ, Sanacora G, Murrough JW, Goes FS, Wang JN, et al. Ketamine versus ECT for nonpsychotic treatment-resistant major depression. N Engl J Med 2023;388:2315–25. https://doi.org/10.1056/NEJMoa2302399.

[76] Rush AJ, Trivedi MH, Wisniewski SR, Nierenberg AA, Stewart JW, Warden D, et al. Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. Aust J Pharm 2006;163:1905–17. https://doi.org/10.1176/ajp.2006.163.11.1905.

[77] Milne AMB, MacQueen GM, Hall GBC. Abnormal hippocampal activation in patients with extensive history of major depression: an fMRI study. Journal of Psychiatry and Neuroscience 2012;37:28–36. https://doi.org/10.1503/jpn.110004.

[78] Pizzagalli DA, Roberts AC. Prefrontal cortex and depression. Neuropsychopharmacol 2022;47:225–46. https://doi.org/10.1038/s41386-021-01101-7.

[79] Blumberger DM, Maller JJ, Thomson L, Mulsant BH, Rajji TK, Maher M, et al. Unilateral and bilateral MRI-targeted repetitive transcranial magnetic stimulation for treatment-resistant depression: a randomized controlled study. J Psychiatry Neurosci 2016;41:E58–66. https://doi.org/10.1503/jpn.150265.

[80] Fox MD, Buckner RL, White MP, Greicius MD, Pascual-Leone A. Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate. Biol Psychiatry 2012;72: 595–603. https://doi.org/10.1016/j.biopsych.2012.04.028.

[81] O'Reilly MA. Exploiting the mechanical effects of ultrasound for noninvasive therapy. Science 2024;385:eadp7206. https://doi.org/10.1126/science.adp7206.

[82] Yoo S, Mittelstein DR, Hurt RC, Lacroix J, Shapiro MG. Focused ultrasound excites cortical neurons via mechanosensitive calcium accumulation and ion channel amplification. Nat Commun 2022;13:493. https://doi.org/10.1038/s41467-022-28040-1.

[83] Newman M, Rasiah PK, Kusunose J, Rex TS, Mahadevan-Jansen A, Hardenburger J, et al. Ultrasound modulates calcium activity in cultured neurons, glial cells, endothelial cells and pericytes. Ultrasound Med Biol 2024;50:341–51. https://doi.org/10.1016/j.ultrasmedbio.2023.11.004.

[84] Chang WS, Jung HH, Zadicario E, Rachmivitch I, Tlusty T, Vitek S, et al. Factors associated with successful magnetic resonance-guided focused ultrasound treatment: efficiency of acoustic energy delivery through the skull. J Neurosurg 2016;124:411–6. https://doi.org/10.3171/2015.3.JNS142592.

[85] Deffieux T, Younan Y, Wattiez N, Tanter M, Pouget P, Aubry J-F. Low-intensity focused ultrasound modulates monkey visuomotor behavior. Curr Biol 2013;23: 2430–3. https://doi.org/10.1016/j.cub.2013.10.029.

[86] Legon W, Sato TF, Opitz A, Mueller J, Barbour A, Williams A, et al. Transcranial focused ultrasound modulates the activity of primary somatosensory cortex in humans. Nat Neurosci 2014;17:322–9. https://doi.org/10.1038/nn.3620.

[87] Mueller J, Legon W, Opitz A, Sato TF, Tyler WJ. Transcranial focused ultrasound modulates intrinsic and evoked EEG dynamics. Brain Stimul 2014;7:900–8. https://doi.org/10.1016/j.brs.2014.08.008.

[88] Lee W, Kim H, Jung Y, Song I-U, Chung YA, Yoo S-S. Image-guided transcranial focused ultrasound stimulates human primary somatosensory cortex. Sci Rep 2015;5:8743. https://doi.org/10.1038/srep08743.

[89] Monti MM, Schnakers C, Korb AS, Bystritsky A, Vespa PM. Non-invasive ultrasonic thalamic stimulation in disorders of consciousness after severe brain injury: a first-in-man report. Brain Stimul: Basic, Translational, and Clinical Research in Neuromodulation 2016;9:940–1. https://doi.org/10.1016/j.brs.2016.07.008.

[90] Ai L, Mueller JK, Grant A, Eryaman Y, Legon W. Transcranial focused ultrasound for BOLD fMRI signal modulation in humans. Annu Int Conf IEEE Eng Med Biol Soc 2016;2016:1758–61. https://doi.org/10.1109/EMBC.2016.7591057.

[91] Lee W, Chung YA, Jung Y, Song I-U, Yoo S-S. Simultaneous acoustic stimulation of human primary and secondary somatosensory cortices using transcranial focused ultrasound. BMC Neurosci 2016;17:68. https://doi.org/10.1186/s12868-016-0303-6.

[92] Legon W, Ai L, Bansal P, Mueller JK. Neuromodulation with single-element transcranial focused ultrasound in human thalamus. Hum Brain Mapp 2018;39: 1995–2006. https://doi.org/10.1002/hbm.23981.

[93] Legon W, Bansal P, Tyshynsky R, Ai L, Mueller JK. Transcranial focused ultrasound neuromodulation of the human primary motor cortex. Sci Rep 2018;8: 10007. https://doi.org/10.1038/s41598-018-28320-1.

[94] Ai L, Bansal P, Mueller JK, Legon W. Effects of transcranial focused ultrasound on human primary motor cortex using 7T fMRI: a pilot study. BMC Neurosci 2018; 19. https://doi.org/10.1186/s12868-018-0456-6.

[95] Badran BW, Caulfield KA, Stomberg-Firestone S, Summers PM, Dowdle LT, Savoca M, et al. Sonication of the anterior thalamus with MRI-Guided transcranial focused ultrasound (tFUS) alters pain thresholds in healthy adults: a double-blind, sham-controlled study. Brain Stimul 2020;13:1805–12. https://doi.org/10.1016/j.brs.2020.10.007.

[96] Brinker ST, Preiswerk F, White PJ, Mariano TY, McDannold NJ, Bubrick EJ. Focused ultrasound platform for investigating therapeutic neuromodulation across the human Hippocampus. Ultrasound Med Biol 2020;46:1270–4. https://doi.org/10.1016/j.ultrasmedbio.2020.01.007.

[97] Fomenko A, Chen K-HS, Nankoo J-F, Saravanamuttu J, Wang Y, El-Baba M, et al. Systematic examination of low-intensity ultrasound parameters on human motor cortex excitability and behavior. Elife 2020;9:e54497. https://doi.org/10.7554/ eLife.54497.

[98] Yu K, Liu C, Niu X, He B. Transcranial focused ultrasound neuromodulation of voluntary movement-related cortical activity in humans. IEEE Trans Biomed Eng 2021;68:1923–31. https://doi.org/10.1109/TBME.2020.3030892.

[99] Lambert J, Mouraux A. Transcranial focused ultrasonic stimulation to modulate the human primary somatosensory cortex. 2020 IEEE international ultrasonics symposium (IUS). 2020. p. 1–4. https://doi.org/10.1109/ IUS46767.2020.9251668.

[100] Cain JA, Visagan S, Johnson MA, Crone J, Blades R, Spivak NM, et al. Real time and delayed effects of subcortical low intensity focused ultrasound. Sci Rep 2021; 11:6100. https://doi.org/10.1038/s41598-021-85504-y.

[101] Heimbuch IS, Fan TK, Wu AD, Faas GC, Charles AC, Iacoboni M. Ultrasound stimulation of the motor cortex during tonic muscle contraction. PLoS One 2022; 17:e0267268. https://doi.org/10.1371/journal.pone.0267268.

[102] Jeong H, Im JJ, Park J-S, Na SH, Lee W, Yoo S-S, et al. A pilot clinical study of low-intensity transcranial focused ultrasound in Alzheimer's disease. Ultrasonography 2021;40:512–9. https://doi.org/10.14366/usg.20138.

[103] Liu C, Yu K, Niu X, He B. Transcranial focused ultrasound enhances sensory discrimination capability through somatosensory cortical excitation. Ultrasound Med Biol 2021;47:1356–66. https://doi.org/10.1016/j.ultrasmedbio.2021.01.025.

[104] Stern JM, Spivak NM, Becerra SA, Kuhn TP, Korb AS, Kronemyer D, et al. Safety of focused ultrasound neuromodulation in humans with temporal lobe epilepsy. Brain Stimul: Basic, Translational, and Clinical Research in Neuromodulation 2021;14:1022–31. https://doi.org/10.1016/j.brs.2021.06.003.

[105] Xia X, Fomenko A, Nankoo J-F, Zeng K, Wang Y, Zhang J, et al. Time course of the effects of low-intensity transcranial ultrasound on the excitability of ipsilateral and contralateral human primary motor cortex. Neuroimage 2021;243:118557. https://doi.org/10.1016/j.neuroimage.2021.118557.

[106] Zeng K, Darmani G, Fomenko A, Xia X, Tran S, Nankoo J-F, et al. Induction of human motor cortex plasticity by theta burst transcranial ultrasound stimulation. Ann Neurol 2022;91:238–52. https://doi.org/10.1002/ana.26294.
[107] Zhang Y, Ren L, Liu K, Tong S, Yuan T-F, Sun J. Transcranial ultrasound stimulation of the human motor cortex. *iScience* 2021;24:103429. https://doi.org/10.1016/j.isci.2021.103429.

[108] Johnstone A, Nandi T, Martin E, Bestmann S, Stagg C, Treeby B. A range of pulses commonly used for human transcranial ultrasound stimulation are clearly audible. *Brain Stimul* 2021;14:1353–5. https://doi.org/10.1016/j.brs.2021.08.015.

[109] Cain JA, Spivak NM, Coetzee JP, Crone JS, Johnson MA, Lutkenhoff ES, et al. Ultrasonic thalamic stimulation in chronic disorders of consciousness. *Brain Stimul* 2021;14:301–3. https://doi.org/10.1016/j.brs.2021.01.008.

[110] Mahoney JJ, Haut MW, Carpenter J, Ranjan M, Thompson-Lake DGY, Marton JL, et al. Low-intensity focused ultrasound targeting the nucleus accumbens as a potential treatment for substance use disorder: safety and feasibility clinical trial. *Front Psychiatry* 2023;14:1211566. https://doi.org/10.3389/fpsyt.2023.1211566.

[111] Bancel T, Béranger B, Daniel M, Didier M, Santin M, Rachmilevitch I, et al. Sustained reduction of Essential Tremor with low-power non-thermal transcranial focused ultrasound stimulations in humans. *Brain Stimul: Basic, Translational, and Clinical Research in Neuromodulation* 2024. https://doi.org/10.1016/j.brs.2024.05.003. 0.

[112] Elias WJ, Huss D, Voss T, Loomba J, Khaled M, Zadicario E, et al. A pilot study of focused ultrasound thalamotomy for essential tremor. *N Engl J Med* 2013;369: 640–8. https://doi.org/10.1056/NEJMoa1300962.

[113] Burstow R, Andrés D, Jiménez N, Camarena F, Thanou M, Pouliopoulos AN. Acoustic holography in biomedical applications. *Phys Med Biol* 2025;70:06TR01. https://doi.org/10.1088/1361-6560/adb89a.

[114] Gabor D. A new microscopic principle. *Nature* 1948;161:777–8. https://doi.org/10.1038/161777a0.

[115] Marzo A, Seah SA, Drinkwater BW, Sahoo DR, Long B, Subramanian S. Holographic acoustic elements for manipulation of levitated objects. *Nat Commun* 2015;6:8661. https://doi.org/10.1038/ncomms9661.

[116] Hertzberg Y, Navon G. Bypassing absorbing objects in focused ultrasound using computer generated holographic technique. *Med Phys* 2011;38:6407–15. https://doi.org/10.1118/1.3651464.

[117] Drinkwater BW, Wilcox PD. Ultrasonic arrays for non-destructive evaluation: a review. *NDT E Int* 2006;39:525–41. https://doi.org/10.1016/j.ndteint.2006.03.006.

[118] Rosnitskiy PB, Vysokanov BA, Gavrilov LR, Sapozhnikov OA, Khokhlova VA. Method for designing multielement fully populated random phased arrays for ultrasound surgery applications. *IEEE Trans Ultrason Ferroelectr Freq Control* 2018;65:630–7. https://doi.org/10.1109/TUFFC.2018.2800160.

[119] Melde K, Mark AG, Qiu T, Fischer P. Holograms for acoustics. *Nature* 2016;537: 518–22. https://doi.org/10.1038/nature19755.

[120] Brown MD, Cox BT, Treeby BE. Stackable acoustic holograms. *Appl Phys Lett* 2020;116:261901. https://doi.org/10.1063/5.0009829.

[121] Pernot M, Aubry JF, Tanter M, Thomas JL, Fink M. High power transcranial beam steering for ultrasonic brain therapy. *Phys Med Biol* 2003;48:2577–89. https://doi.org/10.1088/0031-9155/48/16/301.

[122] Hu Z, Yang Y, Xu L, Jing Y, Chen H. Airy-beam-enabled binary acoustic metasurfaces for underwater ultrasound-beam manipulation. *Phys Rev Appl* 2022;18:024070. https://doi.org/10.1103/PhysRevApplied.18.024070.

[123] Fink M, Taylor MA. Electroconvulsive therapy: evidence and challenges. *JAMA* 2007;298:330–2.

[124] UK Ect Review Group. Efficacy and safety of electroconvulsive therapy in depressive disorders: a systematic review and meta-analysis. *Lancet* 2003;361: 799–808.

[125] Lisanby SH, Maddox JH, Prudic J, Devanand D, Sackeim HA. The effects of electroconvulsive therapy on memory of autobiographical and public events. *Arch Gen Psychiatry* 2000;57:581–90.

[126] Siddiqi SH, Khosravani S, Rolston JD, Fox MD. The future of brain circuit-targeted therapeutics. *Neuropsychopharmacol* 2024;49:179–88. https://doi.org/10.1038/s41386-023-01670-9.

[127] Khan S, Gramfort A, Shetty NR, Kitzbichler MG, Ganesan S, Moran JM, et al. Local and long-range functional connectivity is reduced in concert in autism spectrum disorders. *Proc Natl Acad Sci* 2013;110:3107–12. https://doi.org/10.1073/pnas.1214533110.

[128] Xia M, Womer FY, Chang M, Zhu Y, Zhou Q, Edmiston EK, et al. Shared and distinct functional architectures of brain networks across psychiatric disorders. *Schizophr Bull* 2019;45:450–63. https://doi.org/10.1093/schbul/sby046.

[129] Sillay KA, Larson PS, Starr PA. Deep brain stimulator hardware-related infections: incidence and management in a large series. *Neurosurgery* 2008;62:360–6. https://doi.org/10.1227/01.neu.0000316002.03765.33. discussion 366-367.

[130] Zrinzo L, Foltynie T, Limousin P, Hariz MI. Reducing hemorrhagic complications in functional neurosurgery: a large case series and systematic literature review. *J Neurosurg* 2012;116:84–94. https://doi.org/10.3171/2011.8.JNS101407.

[131] Mayberg HS, Lozano AM, Voon V, McNeely HE, Seminowicz D, Hamani C, et al. Deep brain stimulation for treatment-resistant depression. *Neuron* 2005;45: 651–60. https://doi.org/10.1016/j.neuron.2005.02.014.

[132] Oh J, Ryu JS, Kim J, Kim S, Jeong HS, Kim KR, et al. Effect of low-intensity transcranial focused ultrasound stimulation in patients with major depressive disorder: a randomized, double-blind, sham-controlled clinical trial. *Psychiatry Investig* 2024;21:885–96. https://doi.org/10.30773/pi.2024.09.029.

[133] Riis TS, Feldman DA, Kwon SS, Vonesh LC, Koppelmans V, Brown JR, et al. Noninvasive modulation of the subcallosal cingulate and depression with focused ultrasonic waves. *Biol Psychiatry* 2024;S0006-3223(24):1662-7. https://doi.org/10.1016/j.biopsych.2024.09.029.

[134] Demchenko I, Rampersad S, Datta A, Horn A, Churchill NW, Kennedy SH, et al. Target engagement of the subgenual anterior cingulate cortex with transcranial temporal interference stimulation in major depressive disorder: a protocol for a randomized sham-controlled trial. *Front Neurosci* 2024;18. https://doi.org/10.3389/finns.2024.1390250.

[135] Grossman N, Bono D, Dedic N, Kodandaramiaiah SB, Rudenko A, Suk H-J, et al. Noninvasive deep brain stimulation via temporally interfering electric fields. *Cell* 2017;169:1029–1041.e16. https://doi.org/10.1016/j.cell.2017.05.024.

[136] von Conta J, Kasten FH, Curčić-Blake B, Aleman A, Thielscher A, Herrmann CS. Interindividual variability of electric fields during transcranial temporal interference stimulation (tTIS). *Sci Rep* 2021;11:20357. https://doi.org/10.1038/s41598-021-99749-0.

[137] Miller GW, Eames M, Snell J, Aubry J-F. Ultrashort echo-time MRI versus CT for skull aberration correction in MR-guided transcranial focused ultrasound: in vitro comparison on human calvaria. *Med Phys* 2015;42:2223–33. https://doi.org/10.1118/1.4916656.

[138] Manuel TJ, Bancel T, Tiernot T, Didier M, Santin M, Daniel M, et al. Ultra-short time-echo based ray tracing for transcranial focused ultrasound aberration correction in human calvaria. *Phys Med Biol* 2024. https://doi.org/10.1088/1361-6560/ad4f44.

[139] Leung SA, Moore D, Gilbo Y, Snell J, Webb TD, Meyer CH, et al. Comparison between MR and CT imaging used to correct for skull-induced phase aberrations during transcranial focused ultrasound. *Sci Rep* 2022;12:13407. https://doi.org/10.1038/s41598-022-17319-4.

[140] Elias A, Phutane VH, Clarke S, Prudic J. Electroconvulsive therapy in the continuation and maintenance treatment of depression: systematic review and meta-analyses. Aust N Z J Psychiatry 2018;52:415–24. https://doi.org/10.1177/0004867417743343.

[141] Ej D, Mh T, A J, H L, Y Z, X L, et al. Efficacy of esketamine nasal spray plus oral antidepressant treatment for relapse prevention in patients with treatment-resistant depression: a randomized clinical trial. *JAMA Psychiatry* 2019;76. https://doi.org/10.1001/jamapsychiatry.2019.1189.