The Cumulative Therapeutic Effect of Acupuncture Treatment in Patients with Migraine without Aura: Evidence from Dynamic Alterations of Intrinsic Brain Activity and Effective Connectivity Analysis

We explored the dynamic alterations of intrinsic brain activity and effective connectivity after acupuncture treatment to investigate the underlying neurological mechanism of acupuncture treatment in patients with migraine without aura (MwoA). The fMRI scans were separately obtained at baseline, after the rst and after the 12th acupuncture sessions in 40 patients with MwoA. Compared with HCs, patients with MwoA showed mostly decreased dynamic amplitude of low-frequency uctuation (dALFF) variability in regions with differences. After acupuncture treatment, the decreased dALFF variability of the rostral ventromedial medulla (RVM), the superior lobe of left cerebellum (Cerebelum_Crus1_L), and the right precuneus (PCUN.R) progressively recovered. The RVM revealed gradually increased dynamic effective connectivity (DEC) variability outow to the right middle frontal gyrus, the left insula, the right precentral gyrus, and the right supramarginal gyrus, and enhanced DEC variability from the right fusiform gyrus inow to RVM. Furthermore, the increased DEC variability were found from Cerebelum_Crus1_L outow to the left middle occipital gyrus and the left precentral gyrus, from PCUN.R outow to the right thalamus. These dALFF variabilities were positive correlated with frequency of migraine attack and negative correlated with disease duration, dynamic GCA coecients were positive correlated with Migraine-Specic Quality of Life Questionnaire score, negative correlated with frequency of migraine attack and visual analog scale score postacupuncture treatment. Our results provide insight into dynamic alterations from the perspective of dynamic local brain activity and effective connectivity for the understanding mechanisms of cumulative therapeutic effect of acupuncture in patients with MwoA. signicant negative correlations with the SD value of the dynamic GCA coecient from PCUN.R to THA.R (p < 0.001, r = -0.544; p < 0.001, r = -0.691 respectively), and were signicantly positive correlated with MSQ score (p < 0.001, r = -0.568; p < 0.001, r = -0.675; p < 0.001, r = -0.566 respectively) (see Fig. S4). No other signicant linear correlation was observed. Cerebelum_Crus1_L, PCUN.R recovered acupuncture coecients migraine pre- acupuncture of local


Introduction
Migraine is a prevalent primary headache disorder characterized by recurrent headache attacks, nausea or vomiting, and sensitivity to sound or light [Headache Classi cation Committee of the International Headache Society (IHS), 2018]. There are two major types of migraine: migraine without aura (MwoA) and migraine with aura, MwoA is the most common type of migraine, patients with migraine usually have frequent, severe, and disabling headache attacks, which causes the enormous individual and social burden (Leonardi et al. 2005). Migraine is typically treated by various pharmacological or non-pharmacological therapies to relieve pain or prevent migraine attacks, but these methods have limited e cacy and multiple adverse effects, such as weight gain, fatigue, sleep disturbance, gastrointestinal reaction, and medication overuse (Diener et al. 2015). Acupuncture as one of the treatment modalities of Traditional Chinese Medicine (TCM) in china and is widely used as a complementary and alternative treatment to prevent migraine attacks and to relieve pain during a migraine, the long-term prophylactic effect of acupuncture for migraine is recognized (Xu et al. 2020; Zhao et al. 2017), however, the mechanism of cumulative effect of acupuncture treatment is currently unclear.
Recently, neuroimaging have provided signi cant new insights to explore the central mechanism of the effects of acupuncture on migraine (Chang et al. 2021; L. Liu et al. 2021). Several fMRI studies have indicated that verum and sham acupuncture have different modulation effects on amplitude of low-frequency uctuation (ALFF) in the rostral ventromedial medulla (RVM)/trigeminocervical complex (TCC) of migraine patients (Li, Zeng, et al. 2017). Verum acupuncture elicited a more widespread and remarkable cerebral response, including the pain matrix, lateral pain system, medial pain system, default mode network, and cognitive components of pain processing compared to sham acupuncture (Zhao et al. 2014), Verum acupuncture also could normalize the abnormal network connectivity in the visual, default mode, sensorimotor, and frontal-parietal networks (Tu et al. 2020). Furthermore, it was demonstrated that acupuncture treatment could increased right frontoparietal network functional connectivity (Li, Lan, et al. 2017), and the connectivity of DMN had been normalized after acupuncture intervention (Zou et al. 2019). Nevertheless, these studies have been limited to compare the effect of acupuncture at pre-and post-treatment and not explored the continuous effects of acupuncture in different periods of treatment. Our previous studies demonstrated that acupuncture could improve the dysfunction of cerebellum, and activate brain regions involved in modulation of pain and emotion in patients with MwoA by the regional homogeneity (ReHo) analysis method (S. Liu et al. 2021). However, most of the studies above have focused on the static characterizations or traditional unidirectional functional connectivity (FC) of brain. Brain activity is inherently dynamic (Bassett & Sporns 2017), Recently, a number of studies have proposed that brain activity was dynamically changed over time, so dynamic ALFF was an effective tool to explore brain dynamic activity in healthy people , the time-varying brain activity characterized by dynamic ALFF may underline the disruption of brain activity in various mental disorders (Fu et al. 2018), such as schizophrenia (Yang et al. 2019). Meanwhile, granger causality analysis (GCA) is a fMRI-based directed connectivity to assess causality between different brain regions, which can provide richer information for connectivity analysis than unidirectional FC (Huang et al. 2021;Wei et al. 2020). To date, the dynamic characteristics of ALFF and GCA have rarely been investigated the effect of acupuncture treatment in migraine patients.
In the present study, patients with MwoA received 6 weeks of standard acupuncture treatment, and the fMRI scans were performed at baseline, after the rst and 12th acupuncture sessions. Utilizing dynamic ALFF analysis method, we rst explored the differences in dynamic ALFF variability between patients with MwoA and HCs at baseline. And then, the brain regions with intergroup differences were de ned as the region of interests (ROI). Dynamic ALFF and GCA analysis method were employed to explore the standard deviation (SD) value of the dALFF and GCA variability of different time periods after acupuncture treatments. Finally, correlation analysis were performed to investigate the associations between the values of dALFF and GCA variability and clinical variables. In this study, we hypothesized that (1) there would be several differences in dynamic ALFF at baseline inter-group comparison, (2) the dALFF and GCA variability may be alter during the different periods of acupuncture treatment, (3)  International Classi cation of Headache Disorders, 3rd edition" 2018). Inclusion criteria required that all patients: 1) were 18-65 years old and right-handed; 2) had two to eight times of migraine attacks during the past month; 3) had at least six months of migraine history; and 4) had no prophylactic headache medications during the past month, had no psychoactive or vasoactive agents during the last three months. The exclusion criteria included the following: 1) suffered from other type of primary or secondary headache; 2) had a history of head trauma or brain tumor; 3) had any other neurological or psychiatric disorder; 4) were pregnancy or breast-feeding; 5) had MRI or acupuncture contraindications.

Study design
The total observation period for Patients with MwoA of this study was ten weeks. Weeks 1 to 4 served as a baseline phase,and all patients had recorded headache diaries at baseline. Weeks 5-10 served as an intervention phase. During this period, patients with MwoA standard acupuncture treatment. All the patients maintained a headache diary during the study period. FMRI scans were administered before and immediately after the rst and 12th acupuncture sessions for patients with MwoA (all fMRI were scanned within 1 h before and after acupuncture). All patients with MwoA had been migraine-free for at least 72h at the time of the fMRI scans.
HCs group only received the baseline MRI scan (see Fig. 1).

Acupuncture treatment
In our study, the patients with MwoA were performed 12 sessions of acupuncture (twice a week, nished in 6 weeks), and every session lasted for 20 minutes. Acupoints were selected according to the standardized acupuncture protocol: Baihui (DU20), Taiyang (EX-HN5), bilateral Fengchi (GB20), Shuaigu (GB8), Xuanlu (GB5), Toulinqi (GB15), Hegu(LI4), and Taichong (LR3) (Zhao et al. 2017). Two licensed acupuncturists (Wang B and Liu S) were responsible for all the acupuncture treatments. Sterile disposable acupuncture needles of 25-40 mm in length and 0.25 mm in diameter were inserted to achieve the sensation of deqi. Electrical stimulation was applied bilaterally at GB20 and GB8 at a frequency of 2Hz and intensity ranging from 0.1 to 1.0mA until the patient felt bearable. All participants agreed not to take any conventional medication for migraine during the study period. In cases of severe pain, ibuprofen (as 300 mg extended-release capsules) was allowed as a rescue medication.

Clinical assessments
During the four weeks before the rst fMRI scans and after all the acupuncture sessions, the frequency of migraine attack (days/month), VAS (0-10 scale, 10 being the most intense imaginable pain), Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS) and MSQ were assessed. Adverse events associated with acupuncture, including bleeding, subcutaneous bleeding, severe pain, fainting and local infection, were recorded at each treatment.
Data acquisition MR scans were acquired on a 3.0-T MRI scanner (uMR780 Platform, United Imaging Medical Systems, Shanghai, China) with an 12channel exible head coil at the Shuguang Hospital MRI Center. The rest fMRI images were obtained axially by a multislice gradientecho echo-planar imaging (EPI) sequence and the parameters were as following: repetition time (TR)=2000 ms, echo time (TE)=30 ms, ip angle=90°, eld of view=240×240mm 2 , matrix=64×64, 33 contiguous slices with 3.5 mm slice thickness, 240 time points. Structural images were acquired by a three-dimensional turbo fast echo (3D-TFE) sequence with voxel size of 1mm 3 , and the parameters were as following: TR=7.2ms, TE=3.1ms, slice thickness, 1.0mm, ip angle=10°, eld of view=256×256mm 2 , matrix=256×256, 176 slices without interslice gap. A cushion was placed into the coil to x the head and reduce motion.The participants were instructed to keep still with eyes close, to relax but not to fall asleep, and to try not to think about anything.
Data preprocessing FMRI data preprocessing was performed by DPABI software (http://www.rfmri.org/) in MATLAB. The preprocessing course consisted of the following steps: 1) the rst 10 images were discarded and the remained 230 images were used for data analysis; 2) slice timing correction; 3) head motion correction (the translation or rotation motion in any given data did not exceed 2.0mm or 2.0°); 4) The coregistered functional images were spatially normalized to the Montreal Neurological Institute (MNI) space and resampled to 3-mm cubic voxels; 5) linear trend removal was performed to reduce the effect of low-frequency drifts; 6) nuisance covariates regression (the white matter signal, the cerebrospinal uid signal and 24 head motion parameters; 7) lintemporal band-pass ltering at a frequency band of 0.01-0.08 Hz. After these head motion controls, eleven of the subjects (three HCs and eight patients with MwoA) were excluded.

Dynamic ALFF analysis
The dynamic ALFFfor each participant was performed by DynamicBC (v2.2 www.restfmri.net/forum/DynamicBC) toolbox. Speci cally, a temporal rectangular window was rstly chosen. Then, the ALFF values in each window were calculated. Window length was an important parameter in resting-state dynamics computation. The 'rule of thumb' of sliding-window length is that the minimum window length should be no less than 1/fmin, fmin=0.01 Hz. Here, a window length of 50 TR was considered as the optimal parameter to maintain the balance between capturing a rapidly shifting dynamic relationship and obtaining reliable estimates of the correlations between regions (Cui et al. 2020; Li et al. 2019), The sliding window was systematically shifted with a step size of 5 ve TR (10 s) to calculate the dALFF of each participant. The preprocessed data of each individual were segmented into 37 windows, and the ALFF map was obtained for each sliding window. Subsequently, we measured the variance of these maps using standard deviation (SD) to evaluate the temporal variability of dALFF across 37 windows. The dALFF variability of each voxel was further transformed into a zscore by subtracting the mean and dividing by the SD of global values. Finally, the mean normalized dALFF maps were spatially smoothed using an isotropic Gaussian kernel of 8 mm full-width at half-maximum.

Dynamic effective connectivity analysis
In this study, we performedseed-baseddynamic Granger causality analysis (GCA) by the DynamicBC toolbox to detect the dynamic effective connectivity (DEC). The time series of the each ROI based on dALFF results was de ned as the seed time series X, and the time course of voxels within the whole brain was de ned as Y. A bivariate coe cient GCA to investigate the Granger causal in uence between the per ROI and each voxel of the whole brain. A positive coe cient indicates that activity in region X exerts a positive in uence on activity in region Y, whereas a negative coe cient indicated that the activity of region X exerted a negative in uence on the activity of region Y. The dynamic GCA was estimated using the sliding window approach above, the time series of each participant was also divided into 37 windows. Thus, For each subject, the averaged time course of GCA coe cient of each ROI was extracted across 37 windows and concatenated to form a 2 × W × N matrix (where W denotes the number of windows and N denotes the number of ROIs).
The DEC variability for each ROI was assessed with the SD of the averaged time course of GCA coe cient across 37 windows. Finally, the dynamic GCA coe cient maps for all subjects were then converted to z-scores by Fisher z-transformation.

Statistical analyses
Demographic characteristics were evaluated between MwoA and HCs. Differences of two groups in age and education level were analyzed with two-sample t test; χ2 test was used for analyzing the difference of gender in two groups. Two-sample t -tests or Mann-Whitney U test was used to compare differences in the clinical variables between the two time points. P < 0.05 existed statistical difference.
Two-sample t-tests were performed to compare dALFF variability maps between MwoA at baseline and HCs within a gray matter mask with age, gender, education and head motion as covariates. The resultant T-maps were corrected for multiple comparisons using the Gaussian random eld (GRF) theory (voxel p<0.001, cluster p<0.05, two tailed).
To nd the differences effect of acupuncture during the different periods of treatment, we rst performed repeated-measures one-way ANOVA to investigate the dALFF variability among the different periods. The SD value of each brain region with signi cant difference between groups was extracted for statistical analysis in SPSS version 25.0 (SPSS, Inc., Chicago, IL, United States), and post hoc t-tests were performed to detect differences of dALFF variability among two periods (false discovery rate corrected, P < 0.05).
For group level analyses on DEC of the ROIs, the SD values of Zx→y and Zy→x dynamic GCA coe cient maps were calculated for each group. These maps were entered into repeated-measures one-way ANOVA to determine the difference among the different periods with age, sex, and education level included as covariates. Multiple comparison correction was performed based on Gaussian random eld theory (GRF, voxelwise p < 0.001, cluster-wise p < 0.05, two-tailed). Post hoc t-tests were performed to detect the differences in DEC variability between two periods (false discovery rate corrected, P < 0.05).
Finally, the SD value of the dALFF variability and DEC variability in regions with signi cant differences in each MwoA individual were extracted, Based on these regions, Pearson/Spearman correlation was analyzed to probe the relation of alterations in dALFF variability/DEC variability to the clinical data of MwoA. The signi cance was set at a threshold of p < 0.05 using Bonferroni correction.

Validation analyses
To validate the main ndings of dALFF variability and DEC variability obtained from sliding-window length of 50 TR, we carried out auxiliary analyses with different sliding window lengths(30 and 80 TR).

Demographic and clinical characteristics at baseline
The demographic information and clinical characteristics of all the participants are presented in Table 1. There were no statistical difference in age (p = 0.408), education level (p = 0.313), and gender (p = 0.490) between patients with MwoA and HCs. The disease duration of the MwoA patients group was 16.21±12.56 years, the frequency of migraine attack was 5.14±1.53 days, and the VAS score was 7.81±1.39 (see Table 1).  Gaussian Random Field theory correction, voxel P value < 0.001, cluster P value < 0.05; All abbreviations are de ned in the Abbreviations section.

Clinical Outcomes
After 12 sessions of acupuncture treatment, the frequency of migraine attack and the VAS score were signi cantly lower than those at baseline (p < 0.001). The SAS scores, SDS scores and MSQ scores (restrictive, preventive, and emotional functional subscales) were signi cant improved (p < 0.001) (see Table 3). All abbreviations are de ned in the Abbreviations section.

Dynamic ALFF analysis during the different periods of treatment in patients with MwoA
The seven differential brain regions in dynamic ALFF analysis above were extracted as the ROIs. According to repeated-measures oneway ANOVA tests, we found that the dALFF variability were signi cant different in RVM, Cerebelum_Crus1_L, and PCUN.R. Post hoc tests revealed that the dALFF variability of patients with MwoA increased signi cantly in the RVM after the rst acupuncture session compared with at baseline, after all sessions of acupuncture compared with at baseline and after the rst acupuncture session. The dALFF variability of the Cerebelum_Crus1_L and PCUN.R after all sessions of acupuncture was signi cantly increased compared with after the rst acupuncture session. There were no statistical differences in the dALFF variability within the other ROIs (see Fig. 2).

Seed-based dynamic GCA analysis during the different periods of treatment in patients with MwoA
The bivariate RVM-to-whole-brain dynamic GCA showed that DEC variability from RVM out ow to the right Middle frontal gyrus (MFG.R), the left Insula (INS.L), the right Precentral gyrus (PreCG.R), and the right Supramarginal gyrus (SMG.R) were signi cantly enhanced in repeated-measures one-way ANOVA tests (see Table 4). Post hoc tests revealed that the DEC variability from RVM out ow to INS.L and PreCG.R after the rst acupuncture session were enhanced compared with at baseline. The DEC variability from RVM out ow to MFG.R, INS.L, PreCG.R, and SMG.R were signi cantly enhanced after all sessions of acupuncture compared with at baseline and after the rst acupuncture session. Next, whole-brain-to-RVM dynamic GCA showed that the DEC variability from the right Fusiform gyrus (FFG.R) in ow to RVM was signi cantly enhanced. Post hoc tests revealed that the DEC variability from FFG.R to RVM after all sessions of acupuncture was signi cantly increased compared with after the rst acupuncture session (see Fig. 3). Furthermore, the bivariate Cerebelum_Crus1_L-to-whole-brain dynamic GCA showed that DEC variability from Cerebelum_Crus1_L out ow to the left Middle occipital gyrus (MOG.L) and the left Precentral gyrus (PreCG.L) (see Table 4) were signi cantly enhanced. Post hoc tests indicated that the DEC variability after all sessions of acupuncture signi cantly enhanced compared with at baseline and after the rst acupuncture session, while there was no signi cant difference in DEC variability after the rst acupuncture session compared with at baseline (see Fig. 4). In addition, we also observed that the bivariate PCUN.R-to-whole-brain dynamic GCA displayed signi cantly enhanced DEC variability from PCUN.R out ow to the right Thalamus (THA.R) (see Table 4), and post hoc tests indicated that the DEC variability after the rst acupuncture session was enhanced compared with at baseline, after all sessions of acupuncture compared with at baseline and after the rst acupuncture session (see Fig. 5). There were no statistical difference in DEC variability in the remained ROIs. Gaussian Random Field theory correction, voxel P value < 0.001, cluster P value < 0.05; Correlation between dALFF variability, DEC variability and clinical variables at baseline and after acupuncture treatment The SD value of the dALFF variability in RVM within patients with MwoA were signi cantly positive correlated with frequency of migraine attack and negative correlated with disease duration at baseline ( p < 0.001, r = 0.597; p = 0.033, r = -0.338 respectively). The frequency of migraine attack was also signi cantly positive correlated with the SD value of the dALFF variability in Cerebelum_Crus1_L ( p = 0.049, r = 0.314) (see Fig. S1). The SD value of the dynamic GCA coe cient between MFG.R, INS.L, PreCG.R, and SMG.R, and FFG.R with RVM were signi cantly positive correlated with MSQ score, negative correlated with frequency of migraine attack and VAS score (see Fig. S2 and Table 5) during the different periods of treatment. In addition, there were signi cant negative correlations between the SD value of the dynamic GCA coe cient from Cerebelum_Crus1_L to MOG.L and PreCG.L with VAS score (p = 0.006, r = -0.360; p = 0.009, r = -0.340 respectively), and also was signi cant negative correlations between the from Cerebelum_Crus1_L to PreCG.L with frequency of migraine attack (p = 0.002, r = -0.397) (see Fig. S3). Moreover, the VAS score and frequency of migraine attack were signi cant negative correlations with the SD value of the dynamic GCA coe cient from PCUN.R to THA.R (p < 0.001, r = -0.544; p < 0.001, r = -0.691 respectively), and were signi cantly positive correlated with MSQ score (p < 0.001, r = -0.568; p < 0.001, r = -0.675; p < 0.001, r = -0.566 respectively) (see Fig. S4). No other signi cant linear correlation was observed.

Validation Results
To verify the stability of our main results, other window sizes were included, such as 30 TRs and 80 TRs. The analysis of dynamic ALFF analysis and dynamic DEC analysis using different sliding-window lengths supported our main results (see Fig. S5-S8).

Discussion
In this study, we applied the dALFF analysis to assess the abnormal of variability between in patients with MwoA and HCs. And the changes of dALFF and GCA variability in the follow-up phase after acupuncture treatments were found. These alterations were associated with clinical variables. The results could be summarized as follows: (1) most of the differential brain regions of dALFF variability were decreased compared with HCs at baseline, included RVM, Cerebelum_Crus1_L, and PCUN.R etc.
(2) the decreased dALFF variability of brain regions of RVM, Cerebelum_Crus1_L, and PCUN.R progressively recovered and the DEC was variability gradually increased after acupuncture treatment. (3) these dALFF variabilities were positively correlated positively with the frequency of migraine attacks and negatively with the disease duration at baseline, and the dynamic GCA coe cients were positively correlated positively with MSQ scores, and negatively with the frequency of migraine attacks and VAS scores after postacupuncture treatment.
Overall, our ndings proved that the cumulative therapeutic effects of acupuncture treatment in patients with MwoA were related with the changes of the dynamic local brain activity and effective connectivity.
We rstly found an decreased dALFF variability at the brain region of RVM in patients with migraine without aura. The ALFF has been proven to be an effective and reliable parameter for evaluating local intrinsic brain activity ( . These results be able to intuitively explain the cumulative therapeutic effect of acupuncture treatment. It was also shown that the cumulative therapeutic effects of acupuncture treatment in migraine could be regarded as the consequence of interactions between pain modulation and cortical networks, which might provide an objective reference of treatment in migraine. Moreover, these DEC variabilities of Cerebelum_Crus1_L, and PCUN.R to-whole-brain were correlated with frequency of migraine attack, disease duration, and MSQ scores after postacupuncture treatment, which suggested that these brain regions might be the target areas for acupuncture recovering migraine without aura. Our study has several potential limitations. First, there was no follow-up in the control group, which made it impossible to evaluate the interaction between the groups and time. However, all patients with MwoA performed a series of fMRI scans at three time points, which enabled to get the longitudinal evidence of cumulative therapeutic effect in acupuncture treatments. Second, the optimal sliding window length to obtain dynamic changes in brain activity remains unclear. We selected 50 TRs as the window length based on previous studies and validated our results by using different sliding window lengths and demonstrated that our ndings were stable and not in uenced by this factor. Third, the small sample size may have weakened the liability of our results and they should be proved by the study with a big sample size in the future.. Fourth, multimodal brain imaging (i.e. diffusion tensor imaging) was useful for studying anatomical connectivity of patients with MwoA after acupuncture treatments, and it could be employed in experiments in the future.

Conclusion
In conclusion, this prospective longitudinal study showed that the cumulative therapeutic effect of acupuncture in Patients with MwoA manifested as the impaired brain regions of local brain activity progressively recovered and enhanced effective connectivity with other brain regions gradually from the perspective of dynamic local brain activity and effective connectivity, which could help enhance our understanding of the mechanism of acupuncture for migraine.

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