Skip to main content
NCBI home page
Acta Neuropathologica Communications logoLink to Acta Neuropathologica Communications
. 2026 Jun 11;14:169. doi: 10.1186/s40478-026-02344-5

Low-intensity transcranial ultrasound stimulation suppresses abnormal neural oscillations in the motor cortex by stimulating STN in α-synucleinA53T mice

Qianqian Wang 1,2, Shuxun Dong 1,2, Zhe Zhao 3, Zhenfang Ma 4, Xiaoli Li 5,6, Jiaqing Yan 7, Yi Yuan 1,2,✉
PMCID: PMC13480255  PMID: 42277970

Abstract

Previous studies have shown that low-intensity transcranial ultrasound stimulation (TUS) of the subthalamic nucleus (STN) in mice with Parkinson’s disease (PD) effectively suppresses pathological discharge activities in motor cortex. However, how TUS modulates the neural activity of the STN-motor cortex circuits, and the long-term effects of suppressing abnormal neural oscillations in α-synucleinA53T (α-syn) mice remain unclear. Here, we conducted STN-targeted ultrasound in α-syn mice, and examined the treatment efficacy via behavior test and electrophysiology in vivo. Alterations in neural activity patterns were specifically assessed in α-syn mice during pre- and post-therapeutic interventions. We found that TUS targeted at STN significantly (1) ameliorated abnormal neural activity in the STN, (2) reduced the neural correlation between STN and motor cortex, and (3) improved locomotor capability in α-syn mice. Thus, our results demonstrated that STN-targeted TUS rebalanced the neural activity in STN-motor cortex circuit, which was causally linked to the improvement of motor function in α-syn transgenic mice.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40478-026-02344-5.

Keywords: Transcranial ultrasound stimulation, Parkinson’s disease, Subthalamic nucleus, Motor cortex, Neural oscillation

Introduction

Parkinson's disease (PD) is a common neurodegenerative disease with clinical symptoms such as abnormal neural oscillations, impaired motor function, resting tremors, and bradykinesia [13, 32, 33]. Pathological neural oscillations in the subthalamic nucleus (STN) are the most obvious electrophysiological features of PD, highly related to the severity of motor symptoms [15, 44].

Motor dysfunction in PD arises from disturbances within the cortico-basal ganglia motor network [35, 43]. The cortex represents movement through specific activation patterns of neuronal groups. There are tight fiber projections between the motor cortex and basal ganglia, in which STN is an important component [1, 29]. Notably, many key studies have shown that bradykinesia in patients with PD is related to abnormal neural oscillations in the STN-motor cortex circuit [4, 8, 18].

Low-intensity transcranial ultrasound stimulation (TUS) is a new brain stimulation technology with advantages such as noninvasiveness, high spatial resolution, and high stimulation depth [5, 27, 28]. Previous studies have shown that TUS improves motor function in models of PD [38], and preliminary findings suggest a potential neuroprotective effect, providing evidence for delaying PD progression [46]. In our previous study, we conducted STN-targeted ultrasound stimulation in mouse model of PD, which demonstrated that the TUS effectively suppressed neural oscillations in the motor cortex [38]. However, until now, it was unclear how STN-targeted TUS modulates the STN-motor cortex circuit.

In previous studies, the missense mutation (A53T) in α-synuclein was discovered in familial hereditary PD [31]. Mice overexpressing α-synuclein exhibit Parkinsonism-like motor deficits [16, 40]. Elucidating the modulatory effects of TUS on abnormal neural oscillations within the STN-motor cortex circuit, as well as the mechanisms underlying improved motor behavior, requires an assessment of neural activity in the STN and the motor cortex of freely moving animals [21, 24, 30].

Thus, to address these questions, we performed simultaneous recordings in α-synuclein mice during freely moving tasks before and after TUS, and analyzed local field activity in STN along with neocortical spikes. We observed sustained effects of the STN-targeted TUS on the suppression of abnormal neural oscillations in mice with PD, along with the evidence of suppression in pathological neural activity, and the alleviation of movement disorders.

Methods

Animals and groups

In our experiments, 42 wild type (WT) mice (C57BL/6, equal numbers of male and female, 2-month-old, Beijing Vital River Laboratory Animal Technology Co., Ltd., China) and 132 B6-Tg mice (α-synucleinA53T [α-syn], equal numbers of males and females, 10-month-old, Beijing HFK Biotechnology Co., Ltd., China) were used. The α-syn mice exhibited prominent α-synuclein-positive signals in substantia nigra pars compacta (SNpc) (Fig. S1). All α-syn mice used in experiments as a PD mouse model showed a marked decline in motor function at 7 months of age and exhibited progressive deterioration with advancing age [14].

The experiments were divided into two parts: one with a single-day TUS and the other with a consecutive 7-day TUS. There are four groups (WT group, α-syn group, α-syn + TUS group, and α-syn + Sham group) in each part. In this experiment, the WT and α-syn groups were subjected only to the same anesthetic regimen and procedural duration as the α-syn + TUS group, without application of the ultrasound equipment, the α-syn + Sham group underwent procedures identical to those of the α-syn + TUS group, with the sole exception that the ultrasound device was not turned on. Each group had 8 animals in the first part and 10 animals in the second part. All experimental procedures complied with the animal ethics requirements of Yanshan University. All mice were housed in standard cages with a 12-h light/dark cycle and provided with water and food.

Experimental procedures

The bregma is used as the reference point for defining stereotaxic coordinates in the anterior–posterior (AP), medial–lateral (ML), and dorsal–ventral (DV) axes. We implanted a single-channel tungsten wire electrode (impedance < 500 kΩ) in the STN (AP: -1.8 mm, ML: -1.5 mm, DV: -4.5 mm) and a multi-channel nickel–chromium microwire electrode (35 μm in diameter, 150 μm inter-wire spacing, impedance < 1 MΩ, 15 channels, Bio-Signal Technologies, China) in motor cortex (M1) (AP: 1.5 mm, ML: 1.5 mm, DV: -0.7 mm). The implantation sites of the electrodes are shown in Fig. S2. After implantation, dental cement was applied to the electrodes and skull to secure the electrode and protect the wound.

Ultrasound experimental setup

The TUS system (Fig. S3A) and ultrasound parameters were the same as those used in our previously published paper [38]. A transducer (V301-SU, Olympus, USA) with the nominal element size of 1 inch was employed for the TUS procedure. The collimator was fabricated from UV-curable resin and filled with an ultrasound coupling gel composed of purified water, glycerol, carbomer, and propylene glycol (Medical Ultrasonic Coupling, Cofoe Medical Technology Co., Ltd., China). The TUS was applied to the skull with the scalp divided. The stimulation target was the left STN, consistent with the STN recording site. The fundamental frequency, pulsed repetition frequency, duty cycle, and stimulation duration were 500 kHz, 1 kHz, 5%, and 50 ms, respectively, with a total stimulation time of 30 min per TUS session. The maximum sound pressure was 0.39 MPa, with a corresponding Isppa of 5.1 W/cm2 and Ispta of 255 mW/cm2. According to previous literature [23], we calculated the temperature rise (ΔT) induced by ultrasound stimulation in brain tissue as approximately ΔT = 0.02℃ (Calculation of temperature change in supplementary material). To ensure accurate area-specific stimulation, mice received TUS under anesthesia with 0.6% isoflurane, while oxygen was delivered at a flow rate of 0.5 L/min. To target the STN, the head of each mouse was secured using a mouse adapter to ensure stable positioning during stimulation. A rotating digital stereotactic instrument (69100, RWD Life Science Co., Ltd., Shenzhen, China) was used to assist TUS operations to ensure positioning accuracy, and the cannula was positioned 1.5 mm lateral and 4.5 mm posterior to bregma. The ultrasound emitted through the collimator was angled at 30° relative to the vertical direction to align the acoustic focus with the stereotactic coordinates of the STN (Fig. S4A). The dimensions of the collimated acoustic beam within the brain are shown in Fig. S4B-C, which were generated from three-dimensional acoustic simulations performed in COMSOL Multiphysics (Burlington, MA, USA); detailed simulation procedures are provided in the supplementary materials. In the first part of the experiment, behavioral testing was conducted on Day0 (Pre), and we performed TUS once for 30 min prior to the behavior test on Day1 (Fig. S3B). In the second part of the experiment, we performed TUS for 30 min on consecutive 7 days and behavior tests at baseline (Day0, Pre) and on Days 7 and 14 (Fig. S3B). The behavioral assessments (open field test and rotarod test) were performed 2 h after TUS to allow the mice to recover.

Open field test

An open-field experiment was conducted to evaluate the effect of TUS on the locomotor ability of α-syn mice (Fig. S3C). 2 h after TUS, the mice were placed in a square open-field arena for 10 min to adapt to the environment. An overhead camera recorded the movement trajectory for 5 min, while local field potential (LFP) and spike signals were recorded simultaneously.

Rotarod test

Prior to the experiment and after TUS, rotarod test was conducted to evaluate the effect of TUS on the locomotor ability of α-syn mice (Fig. S3B). Each mouse was trained for 5 min to remain on the rotarod, followed by a 2 min rest period before starting the test. The rotation speed of the rod was set at 24 r/min, and the recording time was 300 s. Each mouse was tested five times with a 30 min interval between each test, and the average performance was calculated.

Data acquisition

LFP and spike signals were recorded for 5 min during each open field test using a multi-channel data acquisition system (Apollo, Bio-Signal Technologies, China). The sampling rate was 30 kHz for spikes, and 1 kHz for LFP.

LFP preprocessing

We performed band-pass filtering (4–100 Hz) and removed power frequency (50 Hz) interference caused by the equipment used for the LFP signals.

Power spectrum analysis and phase amplitude coupling (PAC)

The Welch algorithm was used to analyze the power spectrum of the LFP [10] and calculate the power in the theta (4–12 Hz) and beta (13–30 Hz) frequency bands, the window length was set to 2 s, with a window overlap of 1 s (50% overlap). We use PAC to observe the coupling relationship between the low-frequency phase and high-frequency amplitude of LFP. We use the phase locking value algorithm to calculate the phase-amplitude coupling [39] with a spectrum resolution of 1 Hz. The formula is as follows:

graphic file with name d33e478.gif

Among them, N represents the size of the signal, Inline graphic represents the phase of the low-frequency signal, and Inline graphic represents the phase of the amplitude of the high-frequency signal modulated by the low-frequency signal. We calculate the PAC index of theta frequency band and beta frequency band respectively, and use data to quantitatively analyze the changes in PAC strength between the two frequency bands.

Connection relationship of LFP between STN and M1

The Pearson correlation coefficient (PCC) was used to evaluate the correlation of LFP between the STN and M1. First, MATLAB software was used to analyze the PCC of LFP in the two brain regions [37]. The r is commonly used to represent the PCC of the sample. The formula is as follows:

graphic file with name d33e502.gif

Among them, n represents the length of the sample, Inline graphic and Inline graphic represent the means of the two signals, respectively. The r value is between -1 and + 1, where r = -1 represents a perfect negative linear correlation and r =  + 1 indicates a perfect positive linear correlation. For the LFP of each channel of M1, the r value between it and the LFP of STN was calculated respectively, and the mean value was calculated to obtain the r value of the two brain regions.

The unit peak value was used to calculate the normalized cross-correlation of the LFP of the STN and M1. The analysis lags range from -2 s to 2 s, and the mean value is taken to obtain the normalized cross-correlation value of the two brain regions.

Spike analysis

When analyzing the spikes, we first used a high-pass filter (> 300 Hz) to extract spikes from the raw data. Principal component analysis and the K-Means algorithm were then employed (Blackrock Offline Spike Sorter (BOSS) software, version 1.2.0, Blackrock, USA) to classify the spikes and distinguish pyramidal neurons from interneurons [36]. Specifically, spikes were manually sorted in the three-dimensional parameter space of the BOSS software, and pyramidal neurons and interneurons were differentiated based on spike duration and firing rates. Pyramidal neurons displayed a spike duration of 0.86 ± 0.17 ms with relatively low firing rates (< 10 Hz), while interneurons showed a spike duration of 0.43 ± 0.27 ms and higher firing rates (~ 8–45 Hz) [2, 25, 45].

Statistical analysis

Results are expressed as mean ± standard error of the mean (SEM). When analyzing pre- and post-data, we first conducted a normality test (Lilliefors test) and a test for homogeneity of variances (Bartlett's test). If both conditions were met, one-way ANOVA was used for statistical analysis. If not, the Kruskal–Wallis test was applied. For Pre, Day7, and Day14 data, we used the repeated measures ANOVA method. When Mauchly’s test of sphericity was significant, Greenhouse–Geisser correction was applied to adjust the p value. Finally, Tukey’s Honestly Significant Difference procedure was used for multiple comparisons. And effect sizes (eta-squared, η2) were calculated. P-value of 0.05 was considered statistically significant.

Results

TUS can improve movement and weaken abnormal neural oscillations in STN and M1 of α-syn mice

We first analyzed how TUS modulates neural oscillations in the STN and motor cortex and their relationship in α-syn mice. In the open field test, we found that the length of movement trajectories of α-syn mice increased after 30 min of TUS (Fig. 1A). Quantitative analysis showed that the movement distance (Fig. 1B, Pre 515.5 ± 45.5 cm vs. Day1 635.8 ± 44.3 cm in the α-syn + TUS group; Mean ± SEM, Pα-syn+TUS = 0.027, η2 = 0.27. N = 8 per group, Kruskal–Wallis test) and movement time (Fig. 1C, Pre 58.5 ± 4.3 s vs. Day1 73.3 ± 4.1 s in the α-syn + TUS group; Mean ± SEM, Pα-syn+TUS = 0.021, η2 = 0.31. N = 8 per group, Kruskal–Wallis test) increased to approximately 1.23 and 1.25 times, respectively, in the α-syn + TUS group. In addition, we evaluated the motor abilities of the different groups of mice using the rotarod test and found that the residence time of α-syn mice after TUS was significantly enhanced compared to that before TUS in the α-syn + TUS group (Fig. 1D, Pre 21.3 ± 2.0 s vs. Day1 31.2 ± 2.6 s in the α-syn + TUS group; Mean ± SEM, Pα-syn+TUS = 0.015, η2 = 0.34. N = 8 per group, Kruskal–Wallis test). The open field test and rotarod test results indicated that the TUS-targeted STN improved the motor abilities of α-syn mice. In contrast, no significant changes in motor behavior were observed in the other groups (Fig. S5A, C, and E). Next, we analyzed neural oscillations in the STN and M1 before and after TUS. Figure 1E and S5B, D, and F show representative 1-min LFP recordings and time–frequency spectrogram from each group. We found that the power of the theta and beta frequency bands in the STN and M1 decreased significantly after TUS in the α-syn + TUS group (Fig. 1F, Pre 60,657.0 ± 8788.8 μV2/Hz vs. Day1 20,716.6 ± 3864.2 μV2/Hz in the α-syn + TUS group; Mean ± SEM, Pα-syn+TUS = 0.0023, η2 = 0.59. Figure 1G, Pre 3342.4 ± 401.6 μV2/Hz vs. Day1 1692.6 ± 187.2 μV2/Hz in the α-syn + TUS group; Mean ± SEM, Pα-syn+TUS = 0.0021, η2 = 0.59. Figure 1H, Pre 108,914.0 ± 11,212.3 μV2/Hz vs. Day1 36,926.0 ± 6872.6 μV2/Hz in the α-syn + TUS group; Mean ± SEM, Pα-syn+TUS = 0.0011, η2 = 0.68. Figure 1I, Pre 6385.0 ± 542.5 μV2/Hz vs. Day1 2130.2 ± 256.4 μV2/Hz in the α-syn + TUS group; Mean ± SEM, Pα-syn+TUS = 0.00077, η2 = 0.73. N = 8 per group, Kruskal–Wallis test), whereas no similar phenomenon was observed in the other three groups. We also find significant negative linear correlations between the behavioral test’s parameters and the LFP power in theta and beta frequency bands in STN and M1 (Fig. S6). Furthermore, we plotted the movement speed of a typical mouse corresponding to the 60-s LFP shown in Fig. 1E. We observed that when the movement speed changed rapidly, the peak value and power of the corresponding LFP and time–frequency diagram did not change significantly. Conversely, when the peak and power of the LFP and time–frequency diagrams changed significantly, the movement speed of the mice remained relatively constant. These results suggest that the increase in LFP amplitude and power intensity is not caused by the movement of the mice. We also found that the LFP of the STN and M1 of α-syn mice were highly correlated (0.66 ± 0.033) during the impaired motor state. However, it is worth noting that the correlation was significantly reduced (0.25 ± 0.028) after TUS in the α-syn + TUS group (Fig. 1J, K, Mean ± SEM, Fig. 1J: Pα-syn+TUS = 0.00068, η2 = 0.73. N = 8 per group, Kruskal–Wallis test). These results indicate that the TUS of the STN attenuated abnormal neural oscillations in the STN and M1 and weakened their correlation, which may explain the improvement in motor behavior.

Fig. 1.

Fig. 1

Open in a new tab

TUS modulates neural oscillations in the STN and motor cortex and their relationship in α-syn mice. A Movement paths taken in the open-field test before and after ultrasound stimulation from one typical mouse in the α-syn + TUS group. B Total movement distance in all groups. C Total movement time in all groups. D Residence time in the rotarod tests in all groups. E The LFP and its corresponding time–frequency diagram, and movement speed from a typical mouse in the α-syn + TUS group. F–G Power of theta and beta frequencies from STN before and after TUS in all groups. H, I Power of theta and beta frequencies from M1 before and after TUS in all groups. J PCC of LFP between STN and M1 before and after TUS in all groups. K the correlation of LFP between STN and M1 before and after TUS in the α-syn + TUS group. (Mean ± SEM, *P < 0.05, **P < 0.01, ***P < 0.001, N = 8 in each group, Kruskal–Wallis test)

TUS attenuates PAC in STN and M1 of α-syn mice

PAC is the coupling degree index between the low-frequency phase and the high-frequency amplitude of LFP. Previous studies have shown that PAC and single-neuron discharge are key indicators for the detection and treatment of PD [11, 25]. Next, we analyzed the PAC strength of the LFP in different groups. We found that, in the α-syn + TUS group, the PAC of the theta-beta frequency band of STN decreased significantly (Fig. 2A), and the PAC strength after TUS (Fig. 2B, Pre 0.073 ± 0.0031 vs. Day1 0.06 ± 0.0033 in the α-syn + TUS group; Mean ± SEM, Pα-syn+TUS = 0.016, η2 = 0.35. N = 8 per group, Kruskal–Wallis test) dropped to approximately 82% of that before TUS in the α-syn + TUS group. We also found a similar situation in M1 (Fig. 2C), and the PAC strength after TUS (Fig. 2D, Pre 0.071 ± 0.0033 vs. Day1 0.058 ± 0.0035 in the α-syn + TUS group; Mean ± SEM, Pα-syn+TUS = 0.021, η2 = 0.31. N = 8 per group, Kruskal–Wallis test) dropped to approximately 81% of that before TUS, which is almost the same as STN. We also observed that the PAC strength of the theta-beta frequency bands did not change significantly in the WT group (Fig. S7), α-syn group (Fig. S8), and α-syn + Sham group (Fig. S9).

Fig. 2.

Fig. 2

Open in a new tab

TUS modulates the PAC strength of LFP and the spikes of neurons in α-syn mice. A The PAC in STN from one typical mouse before and after TUS in the α-syn + TUS group. B The PAC strength of the theta and beta frequency bands in STN before and after TUS in all groups. C The PAC in M1 from one typical mouse before and after TUS in the α-syn + TUS group. D The PAC strength of theta-beta frequency band in M1 before and after TUS in all groups. E Auto correlogram and shape example of pyramidal neurons. F The firing rate of pyramidal neurons before and after TUS in M1 in in all groups. G Auto correlogram and shape example of interneurons. H The firing rate of interneurons before and after TUS in M1 in all groups. (Mean ± SEM, *P < 0.05, **P < 0.01, N = 8 in each group, Kruskal–Wallis test)

TUS attenuates the firing rate of M1 neurons in α-syn mice

Finally, we counted the firing rates of pyramidal neurons and interneurons in the motor cortex of the different groups. It is worth noting that the firing rate of pyramidal neurons in Day1 is much lower than that in pre-TUS in the α-syn + TUS group (Fig. 2F, Pre 10.1 ± 0.74 Hz vs. Day1 5.9 ± 0.60 Hz in the α-syn + TUS group; Mean ± SEM, Pα-syn+TUS = 0.0063, η2 = 0.46. N = 8 per group, Kruskal–Wallis test). We also found that, like the pyramidal neurons, the number of units sorted as interneurons in the four groups remained unchanged (Fig. S10). The firing rate of interneurons also decreased significantly in the α-syn + TUS group (Fig. 2H, Pre 25.9 ± 2.6 Hz vs. Day1 17.4 ± 1.6 Hz in the α-syn + TUS group; Mean ± SEM, Pα-syn+TUS = 0.036, η2 = 0.24. N = 8 per group, Kruskal–Wallis test). These results indicate that TUS of the STN can ameliorate theta-beta PAC in the STN and M1 and slow down the activity of pyramidal neurons and interneurons in the motor cortex of α-syn mice, which may ameliorate the motor impairments in α-syn mice.

The sustained amelioration of PD-related motor impairments in α-syn mice after TUS up to day 14

Supported by the above significant and effective results, we further studied the sustained effects of the STN TUS on ameliorating the PD-related motor impairments in α-syn mice. In the α-syn + TUS group, TUS was performed on the STN of α-syn mice for 7 days, and the motor abilities and corresponding neural activity of mice in all groups were evaluated. In the open field test, we found that the motor abilities of α-syn mice in the α-syn + TUS group was significantly improved on the 7th day after TUS and had a sustained effect on the 14th day (Fig. 3A). The movement distances on the 7th and 14th days increased to ~ 1.78 and ~ 1.66 times (Fig. 3B, Pre 525.8 ± 39.8 cm vs. Day7 939.7 ± 71.2 cm vs. Day14 876.2 ± 61.0 cm in the α-syn + TUS group; Mean ± SEM, Pre&Day7: Pα-syn+TUS = 0.0012, Pre&Day14: Pα-syn+TUS = 0.0052, η2 = 0.63. N = 10 per group, repeated measures ANOVA with Post-hoc comparisons), respectively, after TUS in the α-syn + TUS group. Additionally, movement duration on the 7th and 14th days (Fig. 3C, Pre 59.8 ± 6.4 s vs. Day7 106.6 ± 7.5 s vs. Day14 96.8 ± 7.2 s in the α-syn + TUS group; Mean ± SEM, Pre&Day7: Pα-syn+TUS = 0.0069, Pre&Day14: Pα-syn+TUS = 0.0096, η2 = 0.51. N = 10 per group, repeated measures ANOVA with Post-hoc comparisons), increased to ~ 1.78 times and ~ 1.62 times, respectively. In the rotarod test, we found that after 7 days of TUS, the residence time of α-syn mice on the 7th and 14th days was significantly higher than before TUS (Fig. 3D, Pre 22.3 ± 1.6 s vs. Day7 36.5 ± 2.7 s vs. Day14 33.9 ± 3.1 s in the α-syn + TUS group; Mean ± SEM, Pre&Day7: Pα-syn+TUS = 0.011, Pre&Day14: Pα-syn+TUS = 0.015, n.s.: no significance, η2 = 0.48. N = 10 per group, repeated measures ANOVA with Post-hoc comparisons). We also found that TUS significantly attenuated the abnormal elevation of α-synuclein expression of SNpc in α-syn + TUS group (Fig. S11). Our results showed that motor behavior in the other three groups did not change significantly on the 7th and 14th days (Fig. S12). These findings indicate that ultrasound stimulation can improve the motor deficits in α-syn mice, and this improvement is sustained over time.

Fig. 3.

Fig. 3

Open in a new tab

The sustained effect of TUS of the STN in ameliorating the PD-related motor impairments in α-syn mice. A Movement paths taken in the open-field test before TUS and on the 7th and 14th days from one typical mouse in the α-syn + TUS group. B Total movement distance in all groups. C Total movement time in all groups. (D) Residence time in the rotarod tests before TUS and on the 7th and 14th days in all groups. E, F Power of theta and beta frequencies from STN before TUS and on the 7th and 14th days in all groups. G, H Power of theta and beta frequencies from M1 before TUS and on the 7th and 14th days in all groups. I, J The firing rate of pyramidal neurons and interneurons before TUS in M1 and on the 7th and 14th days in all groups. K The PAC in STN from one typical mouse before TUS and on the 7th and 14th days in the α-syn + TUS group. L The PAC strength of the theta-beta frequency band in STN before TUS and on the 7th and 14th days in all groups. M The PAC in M1 from one typical mouse before TUS and on the 7th and14th days in the α-syn + TUS group. N The PAC strength of the theta-beta frequency band in M1 before TUS and on the 7th and 14th days in all groups. (Mean ± SEM, *P < 0.05, **P < 0.01, ***P < 0.001, n.s.: no significance, N = 10 in each group, repeated measures ANOVA with Post-hoc comparisons)

Next, we analyzed the changes in LFP and spikes in the different groups. We noticed that the power of the theta and beta frequency bands in the STN and M1 was significantly reduced on the 7th and 14th days in the α-syn + TUS group, whereas there was no similar phenomenon in the other three groups (Fig. 3E, Pre 65,034.6 ± 6381.4 μV2/Hz vs. Day7 19,504.7 ± 2678.0 μV2/Hz vs. Day14 25,893.3 ± 4096.3 μV2/Hz in the α-syn + TUS group; Mean ± SEM, Pre&Day7: Pα-syn+TUS = 0.00052, Pre&Day14: Pα-syn+TUS = 0.0019, η2 = 0.74. Figure 3F, Pre 4482.0 ± 388.9 μV2/Hz vs. Day7 2087.9 ± 226.1 μV2/Hz vs. Day14 2582.5 ± 291.6 μV2/Hz in the α-syn + TUS group; Mean ± SEM, Pre&Day7: Pα-syn+TUS = 0.00078, Pre&Day14: Pα-syn+TUS = 0.012, η2 = 0.63. Figure 3G, Pre 115,891.1 ± 10,432.0 μV2/Hz vs. Day7 41,747.7 ± 4629.3 μV2/Hz vs. Day14 51,066.3 ± 4690.8 μV2/Hz in the α-syn + TUS group; Mean ± SEM, Pre&Day7: Pα-syn+TUS = 0.00025, Pre&Day14: Pα-syn+TUS = 0.00012, η2 = 0.81. Figure 3H, Pre 7187.9 ± 886.5 μV2/Hz vs. Day7 3511.1 ± 496.4 μV2/Hz vs. Day14 4308.9 ± 578.6 μV2/Hz in the α-syn + TUS group; Mean ± SEM, Pre&Day7: Pα-syn+TUS = 0.0036, Pre&Day14: Pα-syn+TUS = 0.018, η2 = 0.56. N = 10 per group, repeated measures ANOVA with Post-hoc comparisons). We also found that, in the α-syn + TUS group, the firing rate of pyramidal neurons in M1 decreased to ~ 48% and ~ 62.3% on 7th day and 14th day (Fig. 3I, Pre 10.6 ± 1.1 vs. Day7 5.1 ± 0.56 Hz vs. Day14 6.6 ± 0.77 Hz in the α-syn + TUS group; Mean ± SEM, Pre&Day7: Pα-syn+TUS = 0.0017, Pre&Day14: Pα-syn+TUS = 0.039, η2 = 0.58. N = 10 per group, repeated measures ANOVA with Post-hoc comparisons), respectively; the firing rate of interneurons dropped to ~ 65% and ~ 80% on 7th day and 14th day, respectively (Fig. 3J, Pre 28.9 ± 2.0 Hz vs. Day7 18.8 ± 2.1 Hz vs. Day14 23.1 ± 1.3 Hz in the α-syn + TUS group; Mean ± SEM, Pre&Day7: Pα-syn+TUS = 0.024, Pre&Day14: Pα-syn+TUS = 0.043, η2 = 0.41. N = 10 per group, repeated measures ANOVA with Post-hoc comparisons).

Finally, we analyzed the theta-beta PAC in the STN and M1. The results of the different groups are shown in Fig. 3K, 3M, S13, S14, and S15. We noted a significant decrease in the PAC strength on the 7th and 14th days only in the α-syn + TUS group. The results of quantitative calculations showed that the theta-beta PAC strength in both STN and M1 is weakened on the 7th and 14th days, with values dropped to ~ 62% and ~ 67% in STN and ~ 60% and ~ 71% in M1 on the 7th and 14th day, respectively (Fig. 3L, Pre 0.078 ± 0.0057 vs. Day7 0.048 ± 0.0019 vs. Day14 0.053 ± 0.0029 in the α-syn + TUS group; Mean ± SEM, Fig. 3L, Pre&Day7: Pα-syn+TUS = 0.0073, Pre&Day14: Pα-syn+TUS = 0.016, η2 = 0.60. Figure 3N, Pre 0.072 ± 0.0045 vs. Day7 0.044 ± 0.0027 vs. Day14 0.051 ± 0.0031 in the α-syn + TUS group; Mean ± SEM, Pre&Day7: Pα-syn+TUS = 0.0049, Pre&Day14: Pα-syn+TUS = 0.017, η2 = 0.60. N = 10 per group, repeated measures ANOVA with Post-hoc comparisons). These results indicate that 7 days of TUS of the STN can improve performance of motor behavior and corresponding neural oscillations in α-syn mice. When tested 7 days after the TUS treatment, the improvement effect was still maintained, which means that TUS has a good sustained effect in attenuating the abnormal neural oscillations of the STN and M1 in PD, and improving behavior.

Discussion

PD is one of the most common neurodegenerative diseases. However, there is still a lack of efficient treatment options. Low-intensity TUS with high spatial resolution, high penetration intensity, and noninvasive advantages is expected to become a promising technology that can effectively suppress the motor dysfunction of PD. Our previous research found that TUS-targeted STN could ameliorate abnormal discharges of the M1 [38]. This study provides further in-depth research based on our previous work [38] by analyzing changes in the neural oscillations of the STN and M1. The correlation of activity explains previous findings from the perspective of neural oscillations and suggests that TUS may improve motor behavior and modulate corresponding neural activity in M1 by regulating neural oscillations in the STN. Furthermore, we explored the persistence of TUS effects. We found that the ameliorative effect on abnormal neural oscillations in the STN and M1, as well as the improvement in motor behavior, lasted for 7 days after the end of TUS. This study provides a foundation for the use of ultrasound stimulation in the clinical treatment of PD.

What is the mechanism through which ultrasound stimulation modulates neural oscillations in the STN? Previous studies have shown that mechanical vibrations generated by ultrasound, as a mechanical wave, can gate mechanosensitive ion channels in the neuronal cell membrane and participate in neuromodulation [41, 47]. Studies have shown that voltage-gated calcium ion channels and calcium-activated potassium channels are considered to be key factors in determining the action potential of STN neurons [17]. In addition, mechanosensitive potassium channels such as TREK1 and TRAAK have been shown to be modulated by ultrasound [22]. Ultrasound can affect calcium ion firing by regulating calcium ion mechanosensitive ion channels and, in combination with other calcium- and voltage-gated channels, affect the firing of neurons [41]. Therefore, we speculate that TUS may act on mechanosensitive ion channels in the STN to alter potassium conductance and intracellular calcium dynamics, thereby modulating the firing patterns and oscillatory activity of STN neurons. And it is known that changes in the firing rhythm of a large number of neurons cause changes in network activity. Therefore, TUS may regulate neural oscillations in the STN by acting on these targets, alleviating abnormal neural oscillatory activity related to motor deficits in PD model mice, restoring coordinated neuronal activity, and maintaining normal neural oscillations.

Previous studies have confirmed that STN-DBS reduces the synchrony of oscillatory activity between the STN and the motor cortex, which is the key to improving PD symptoms [12, 19, 25]. Our results show that TUS of the STN can suppress abnormal neural oscillations in the STN and M1 and significantly reduce the PCC of M1 and STN. Therefore, TUS’s ability to reduce the synchrony of neural oscillations between the STN and motor cortex is a key factor in improving motor behavior in PD.

Previous studies have shown that beta-gamma PAC is a promising electrophysiological biomarker of motor status in PD and can be detected in the motor cortex [8, 9]. In our previous study, significant changes in beta-gamma PAC were also found in the motor cortex of an 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mouse model, and ultrasound stimulation reduced beta-gamma PAC in MPTP mice [38]. In this study, we found that theta-beta PAC significantly increased in the motor cortex of α-synucleinA53T PD model mice, and TUS ameliorated this PAC increase. It is well known that after MPTP acts on animal bodies, it primarily causes necrosis and a deficiency of dopaminergic neurons, leading to severe degeneration of the substantia nigra and striatum, which results in movement disorder symptoms [7]. However, α-synuclein is a soluble, small protein mainly expressed near the presynaptic and perinuclear areas of the central nervous system [26], and is critically involved in presynaptic neurotransmitter release [34]. Previous studies have demonstrated that PAC is closely associated with synaptic activity [3]. Therefore, we speculate that abnormal synaptic activity may exist within the STN of α-syn mice, thereby further contributing to abnormal PAC in STN LFPs. Following TUS of STN, the abnormal synaptic activity may be partially alleviated, consequently alleviating the abnormal enhancement of PAC between the LFP of the motor cortex and STN in different frequency bands.

The safety of TUS is crucial for its application in neuromodulation. We used the same ultrasound parameters to stimulate the STN of mice, and histological analysis after 7 days revealed no any tissue damage in the STN or adjacent brain regions (Fig. S16). This finding aligns with previous studies suggesting that properly calibrated TUS does not induce tissue damage [42]. Careful selection of ultrasound parameters ensures minimal thermal and mechanical effects, reducing potential cavitation risks. While our results confirm the short-term safety of TUS, further studies are needed to assess its long-term effects and optimize stimulation protocols for broader clinical applications.

Recently, studies have been conducted on the long-term effects of deep brain stimulation of the subthalamic nucleus (STN-DBS) [6, 20]. The persistence of the treatment effect is a key indicator for evaluating the effects of PD treatment. We continued to evaluate the motor abilities and neural oscillations of the STN and motor cortex of α-syn mice 7 and 14 days after the end of the 7-day of TUS. The results showed that the ameliorative effect of ultrasound on motor deficits in PD model mice was maintained for 14 days. But the TUS treatment effect gradually weakens over time, suggesting that the therapeutic effect has a certain time dependence (Fig. S17). This result suggests that in clinical translations, continuous or repeated TUS interventions may be necessary to maintain long-term therapeutic effects. This study provides a foundation for the consolidation of therapeutic effects and is helpful for the promotion of TUS in the clinical treatment of PD. The limitations include the mechanism of this persistence, whether the maintenance time is longer, and whether it is selective for the ultrasound parameters. We plan to conduct in-depth research in our future to address these questions.

Conclusion

In summary, ultrasound stimulation can ameliorate abnormal neural activity in the STN, thereby suppressing abnormal neural activity in the M1 and improving motor behavior by regulating the correlation between the STN and M1 in α-syn mice. The improvement in motor function, as well as the amelioration of abnormal neural oscillations in the STN and M1 in α-syn mice, persisted for at least 14 days after consecutive 7-day TUS treatment.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1 (3.3MB, docx)

Acknowledgements

Not applicable.

Abbreviations

α-syn

α-SynucleinA53T

LFP

Local field potential

M1

Motor cortex

MPTP

1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine

PAC

Phase amplitude coupling

PCC

Pearson correlation coefficient

PD

Parkinson’s disease

STN

Subthalamic nucleus

STN-DBS

Deep brain stimulation of the subthalamic nucleus

TUS

Transcranial ultrasound stimulation

Author contributions

Qianqian Wang: Conceptualization, Methodology, Software, Data curation, Writing-original draft. Shuxun Dong: Data curation, Writing-original draft. Zhe Zhao: Data curation, Writing-original draft. Zhenfang Ma: Data curation, Writing-original draft. Xiaoli Li: Writing-original draft. Jiaqing Yan: Conceptualization, Writing-review & editing, Yi Yuan: Supervision, Conceptualization, Methodology, Writing-review & editing.

Funding

This work was supported by the National Natural Science Foundation of China (62273291), International Science and Technology Cooperation Project of Hebei Province (25297701D).

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

All experimental procedures complied with the animal ethics requirements of Yanshan University.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  • 1.Arber S, Costa RM (2022) Networking brainstem and basal ganglia circuits for movement. Nat Rev Neurosci 23:342–360 [DOI] [PubMed] [Google Scholar]
  • 2.Barthó P, Hirase H, Monconduit L, Zugaro M, Harris KD, Buzsáki G (2004) Characterization of neocortical principal cells and interneurons by network interactions and extracellular features. J Neurophysiol 92:600–608 [DOI] [PubMed] [Google Scholar]
  • 3.Bergmann TO, Born J (2018) Phase-amplitude coupling: a general mechanism for memory processing and synaptic plasticity? Neuron 97:10–13 [DOI] [PubMed] [Google Scholar]
  • 4.Burciu RG, Vaillancourt DE (2018) Imaging of motor cortex physiology in Parkinson’s disease. Mov Disord 33:1688–1699 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Bystritsky A, Korb AS, Douglas PK, Cohen MS, Melega WP, Mulgaonkar AP et al (2011) A review of low-intensity focused ultrasound pulsation. Brain Stimul 4:125–136 [DOI] [PubMed] [Google Scholar]
  • 6.Cavallieri F, Campanini I, Gessani A, Budriesi C, Fioravanti V, Di Rauso G et al (2023) Long-term effects of bilateral subthalamic nucleus deep brain stimulation on gait disorders in Parkinson’s disease: a clinical-instrumental study. J Neurol 270:4342–4353 [DOI] [PubMed] [Google Scholar]
  • 7.Dauer W, Przedborski S (2003) Parkinson’s disease: mechanisms and models. Neuron 39:889–909 [DOI] [PubMed] [Google Scholar]
  • 8.De Hemptinne C, Ryapolova-Webb ES, Air EL, Garcia PA, Miller KJ, Ojemann JG et al (2013) Exaggerated phase-amplitude coupling in the primary motor cortex in Parkinson disease. Proc Natl Acad Sci USA 110:4780–4785 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.De Hemptinne C, Swann NC, Ostrem JL, Ryapolova-Webb ES, San Luciano M, Galifianakis NB et al (2015) Therapeutic deep brain stimulation reduces cortical phase-amplitude coupling in Parkinson’s disease. Nat Neurosci 18:779–786 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.De Stefano P, Carboni M, Marquis R, Spinelli L, Seeck M, Vulliemoz S (2022) Increased delta power as a scalp marker of epileptic activity: a simultaneous scalp and intracranial electroencephalography study. Eur J Neurol 29:26–35 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Devergnas A, Caiola M, Pittard D, Wichmann T (2019) Cortical phase–amplitude coupling in a progressive model of Parkinsonism in nonhuman primates. Cereb Cortex 29(1):167–177 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Eusebio A, Thevathasan W, Doyle Gaynor L, Pogosyan A, Bye E, Foltynie T et al (2011) Deep brain stimulation can suppress pathological synchronisation in parkinsonian patients. J Neurol Neurosurg Psychiatry 82:569–573 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Fahn S (2011) Classification of movement disorders. Mov Disord 26:947–957 [DOI] [PubMed] [Google Scholar]
  • 14.Gao N, Quan X, Chen W, Li W, Liu P, Feng J et al (2008) Establishment of α-Synuclein transgenic mouse model of Parkinson’s disease. Chin J Comp Med 18:28–36 [Google Scholar]
  • 15.Gatev P, Darbin O, Wichmann T (2006) Oscillations in the basal ganglia under normal conditions and in movement disorders. Mov Disord 21:1566–1577 [DOI] [PubMed] [Google Scholar]
  • 16.Giasson BI, Duda JE, Quinn SM, Zhang B, Trojanowski JQ, Lee VM (2002) Neuronal alpha-synucleinopathy with severe movement disorder in mice expressing A53T human alpha-synuclein. Neuron 34:521–533 [DOI] [PubMed] [Google Scholar]
  • 17.Hallworth NE, Wilson CJ, Bevan MD (2003) Apamin-sensitive small conductance calcium-activated potassium channels, through their selective coupling to voltage-gated calcium channels, are critical determinants of the precision, pace, and pattern of action potential generation in rat subthalamic nucleus neurons in vitro. J Neurosci 23:7525–7542 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Hamani C, Saint-Cyr JA, Fraser J, Kaplitt M, Lozano AM (2004) The subthalamic nucleus in the context of movement disorders. Brain J Neurol 127:4–20 [DOI] [PubMed] [Google Scholar]
  • 19.Hammond C, Bergman H, Brown P (2007) Pathological synchronization in Parkinson’s disease: networks, models and treatments. Trends Neurosci 30:357–364 [DOI] [PubMed] [Google Scholar]
  • 20.Jahanshahi M, Leimbach F, Rawji V (2022) Short and long-term cognitive effects of subthalamic deep brain stimulation in Parkinson’s disease and identification of relevant factors. J Parkinsons Dis 12:2191–2209 [DOI] [PubMed] [Google Scholar]
  • 21.Johnson LA, Xu W, Baker KB, Zhang J, Vitek JL (2015) Modulation of motor cortex neuronal activity and motor behavior during subthalamic nucleus stimulation in the normal primate. J Neurophysiology 113:2549–2554 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Kubanek J, Shi J, Marsh J, Chen D, Deng C, Cui J (2016) Ultrasound modulates ion channel currents. Sci Rep 6:24170 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Lee W, Kim H, Jung Y, Song IU, Chung YA, Yoo SS (2015) Image-guided transcranial focused ultrasound stimulates human primary somatosensory cortex. Sci Rep 5:8743 [DOI] [PMC free article] [PubMed]
  • 24.Li M, Zhou M, Wen P, Wang Q, Yang Y, Xiao H et al (2016) The network of causal interactions for beta oscillations in the pedunculopontine nucleus, primary motor cortex, and subthalamic nucleus of walking parkinsonian rats. Exp Neurol 282:27–36 [DOI] [PubMed] [Google Scholar]
  • 25.Li Q, Ke Y, Chan DC, Qian ZM, Yung KK, Ko H et al (2012) Therapeutic deep brain stimulation in Parkinsonian rats directly influences motor cortex. Neuron 76:1030–1041 [DOI] [PubMed] [Google Scholar]
  • 26.Lim KL, Ng CH (2009) Genetic models of Parkinson disease. Biochem Biophys Acta 1792:604–615 [DOI] [PubMed] [Google Scholar]
  • 27.Lin YT, Chen KT, Hsu CC, Liu HL, Jiang YT, Ho CW et al (2025) Stimulation of dorsal root ganglion with low-intensity focused ultrasound ameliorates pain responses through the GABA inhibitory pathway. Life Sci 361:123323 [DOI] [PubMed] [Google Scholar]
  • 28.Meng Y, Hynynen K, Lipsman N (2021) Applications of focused ultrasound in the brain: from thermoablation to drug delivery. Nat Rev Neurol 17:7–22 [DOI] [PubMed] [Google Scholar]
  • 29.Obeso JA, Rodríguez-Oroz MC, Benitez-Temino B, Blesa FJ, Guridi J, Marin C et al (2008) Functional organization of the basal ganglia: therapeutic implications for Parkinson’s disease. Mov Disord 23(Suppl 3):S548-559 [DOI] [PubMed] [Google Scholar]
  • 30.Oza CS, Brocker DT, Behrend CE, Grill WM (2018) Patterned low-frequency deep brain stimulation induces motor deficits and modulates cortex-basal ganglia neural activity in healthy rats. J Neurophysiol 120:2410–2422 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Polymeropoulos MH, Lavedan C, Leroy E, Ide SE, Dehejia A, Dutra A et al (1997) Mutation in the alpha-synuclein gene identified in families with Parkinson’s disease. Science (New York, NY) 276:2045–2047 [DOI] [PubMed] [Google Scholar]
  • 32.Qiu R, Sun W, Su Y, Sun Z, Fan K, Liang Y et al (2024) Irisin's emerging role in Parkinson's disease research: A review from molecular mechanisms to therapeutic prospects. Life Sci 357:123088 [DOI] [PubMed] [Google Scholar]
  • 33.Seppi K, Weintraub D, Coelho M, Perez-Lloret S, Fox SH, Katzenschlager R et al (2011) The movement disorder society evidence-based medicine review update: treatments for the non-motor symptoms of Parkinson's disease. Mov Disord 26 Suppl 3:S42–80 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Sharma M, Burré J (2023) α-Synuclein in synaptic function and dysfunction. Trends Neurosci 46:153–166 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Sun S, Wang X, Shi X, Fang H, Sun Y, Li M et al (2023) Neural pathway connectivity and discharge changes between M1 and STN in hemiparkinsonian rats. Brain Res Bull 196:1–19 [DOI] [PubMed] [Google Scholar]
  • 36.Wang X, Yan J, Zhang H, Yuan Y (2021) Ultrasonic thalamic stimulation modulates neural activity of thalamus and motor cortex in the mouse. J Neural Eng. 10.1088/1741-2552/ac409f [DOI] [PubMed] [Google Scholar]
  • 37.Wang X, Zhang Y, Zhang K, Yuan Y (2021) Influence of behavioral state on the neuromodulatory effect of low-intensity transcranial ultrasound stimulation on hippocampal CA1 in mouse. Neuroimage 241:118441 [DOI] [PubMed]
  • 38.Wang Z, Yan J, Wang X, Yuan Y, Li X (2020) Transcranial ultrasound stimulation directly influences the cortical excitability of the motor cortex in Parkinsonian mice. Mov Disord 35:693–698 [DOI] [PubMed] [Google Scholar]
  • 39.Xie Z, Yan J, Dong S, Ji H, Yuan Y (2022) Phase-locked closed-loop ultrasound stimulation modulates theta and gamma rhythms in the mouse hippocampus. Front Neurosci 16:994570 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Xu J, Ao YL, Huang C, Song X, Zhang G, Cui W et al (2022) Harmol promotes α-synuclein degradation and improves motor impairment in Parkinson's models via regulating autophagy-lysosome pathway. NPJ Parkinsons Dis 8:100 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Yoo S, Mittelstein DR, Hurt RC, Lacroix J, Shapiro MG (2022) Focused ultrasound excites cortical neurons via mechanosensitive calcium accumulation and ion channel amplification. Nat Commun 13:493 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Yoo SS, Bystritsky A, Lee JH, Zhang Y, Fischer K, Min BK et al (2011) Focused ultrasound modulates region-specific brain activity. Neuroimage 56:1267–1275 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Yu Y, Escobar Sanabria D, Wang J, Hendrix CM, Zhang J, Nebeck SD et al (2021) Parkinsonism alters beta burst dynamics across the basal ganglia-motor cortical network. J Neurosci 41:2274–2286 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Zavala B, Zaghloul K, Brown P (2015) The subthalamic nucleus, oscillations, and conflict. Mov Disord 30:328–338 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Zhang L, Chen G, Niu R, Wei W, Ma X, Xu J et al (2012) Hippocampal theta-driving cells revealed by Granger causality. Hippocampus 22:1781–1793 [DOI] [PubMed] [Google Scholar]
  • 46.Zhou H, Niu L, Meng L, Lin Z, Zou J, Xia X et al (2019) Noninvasive ultrasound deep brain stimulation for the treatment of Parkinson’s disease model mouse. Research (Washington, DC) 2019:1748489 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Zhu J, Xian Q, Hou X, Wong KF, Zhu T, Chen Z et al (2023) The mechanosensitive ion channel Piezo1 contributes to ultrasound neuromodulation. Proc Natl Acad Sci U S A 120:e2300291120 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1 (3.3MB, docx)

Data Availability Statement

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Articles from Acta Neuropathologica Communications are provided here courtesy of BMC

RESOURCES