Cognitive Improvement Via Left Angular Gyrus-Navigated Repetitive Transcranial Magnetic Stimulation Inducing the Neuroplasticity of Thalamic System in Alzheimer’s Disease Spectrum Patients

Zhiyuan Yang Nanjing Drum Tower Hospital: Nanjing University Medical School A liated Nanjing Drum Tower Hospital Xiaoning Sheng Nanjing Drum Tower Hospital: Nanjing University Medical School A liated Nanjing Drum Tower Hospital Ruomeng Qin Nanjing Drum Tower Hospital: Nanjing University Medical School A liated Nanjing Drum Tower Hospital Haifeng Chen Nanjing Drum Tower Hospital: Nanjing University Medical School A liated Nanjing Drum Tower Hospital Pengfei Shao Nanjing Drum Tower Hospital: Nanjing University Medical School A liated Nanjing Drum Tower Hospital Hengheng Xu Nanjing Drum Tower Hospital: Nanjing University Medical School A liated Nanjing Drum Tower Hospital Weina Yao Nanjing University of Traditional Chinese Medicine: Nanjing University of Chinese Medicine Hui Zhao Nanjing Drum Tower Hospital: Nanjing University Medical School A liated Nanjing Drum Tower Hospital Yun Xu Nanjing Drum Tower Hospital: Nanjing University Medical School A liated Nanjing Drum Tower Hospital Feng Bai (  baifeng515@126.com ) Nanjing Drum Tower Hospital: Nanjing University Medical School A liated Nanjing Drum Tower Hospital


Participants
The current study was approved by the Ethics Committee of Nanjing Drum Tower Hospital, and written informed consent was obtained from all patients before entering the study. Twenty-six patients, admitted to the Neurology Department in Drum Tower Hospital of Medical School, Nanjing University, were screened for the current study. Two patients were excluded because of excessive head movement during MRI scanning and two patients were excluded because of loss of imaging data. These participants were composed of MCI and AD patients. The AD, in the presence of AD pathology as supported by cerebrospinal uid or other imaging biomarker, was diagnosed based on the National Institute of Neurological and Communicative Disorders and Stroke and the AD and Related Disorders Association (NINCDSADRDA) and the Diagnostic and Statistical Manual of Mental Disorders IV criteria (DSM-IV) guidelines [20]. The MCI patients included in this study were diagnosed according to the recommendations of Petersen and described as follows [21]: (1) memory complaint con rmed by the subject and/or an informant; (2) objective cognitive performance documented by an auditory verbal learning test-delayed recall (AVLT-DR) scores below or equal to 1.5 SD of education-and age-adjusted norms; (3) clinical dementia rating (CDR) score = 0.5; (4) the scores for the Mini-Mental State Examination (MMSE) ≥ 24; and (5) not su cient to dementia according to NINCDS-ADRDA and DSM-IV. Exclusion criteria included brain tumors, epilepsy, Parkinson's disease, serve anxiety and depression, thyroid dysfunction or other neurological or psychiatric disorders which can cause memory loss. Participants were excluded if the MRI scans evidenced signi cant vascular pathology or micro bleeds, or head motion artefacts that affect T1w3d quality and segmentation. Four patients were excluded for these reasons.

Experiment design and Neuro-navigated rTMS
In the rst visit, patients underwent a complete clinical investigation, including medical history and neurological examination, a neuropsychiatric evaluation, brain MRI scanning, and an extensive neuropsychological assessment exploring all cognitive domains. The region, which exhibited signi cant functional connectivity differences among healthy controls, MCI and AD participants, calculated by our team was located at the left angular gyrus (MNI: -45, -67, 38). The region was calculated by seed-based functional connectivity analysis using the left hippocampus as a seed. All the patients were stimulated the angular gyrus by the Neuro-navigated rTMS for four weeks. rTMS was applied daily at the same 5 times per week. Neuropsychological measurement and brain MRI scanning were performed again after four weeks rTMS treatment. Details of the study design are summarized in Fig. 1. rTMS was delivered using a commercially available magnetic stimulator (CCY-IV model; YIRUIDE Inc., Wuhan, China) with a 70-mm gure eight coil and an electromyography device. Each stimulation session consisted of forty circulations of 2 second delivered at 20 Hz spaced-out by 28 s of no stimulation, for a grand total of 1600 stimulations. During the rTMS treatment, the coil was set on the angular gyrus was constantly motored using a navigation system, which was anatomically referred by individual T1-weighed MRI volumes. The treatments lasted about 20 minutes. Intensity of stimulation was set at 100% of the resting motor threshold (RMT), de ned as the lowest intensity producing MEPs of > 50 µV in at least ve out of 10 trials in the relaxed rst dorsal interosseous (FDI) muscle of the right hand. RMT was assessed over the optimal stimulus site to elicit MEPs in the right FDI, which was considered motor spot. For each patient, a source estimation on pre-processed TMS data was run at the beginning of each treatment session to con rm the correct anatomical targeting for rTMS.

MRI scanning
All participants were examined on a Philips 3.0-T scanner (Philips Medical Systems). The examination protocol included the highresolution T1-weighted turbo gradient echo sequence (repetition time [

Neuropsychological Measurement
To evaluate the behavioral effects of the rTMS treatment, we employed a standardized neuropsychological test protocol, including global cognitive assessments and multiple cognitive domain examinations. We also completed the Clinical Dementia Rating Scale (CDRS) to assess the degree of cognitive impairment of the participants. Global cognitive function was evaluated by Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment Beijing (MoCA-BJ). The raw test scores were converted to Z-scores, which Loading [MathJax]/jax/output/CommonHTML/jax.js were used to calculate the compound cognitive index. Episodic memory was calculated as the mean of the Z-scores from Auditory Verbal Learning Test-delayed recall (AVLT-DR) scores and the Wechsler Memory Scale-Visual Reproduction-delayed recall (VR-DR). Information processing speed was calculated as the average Z-scores of the Trail Making Test-A (TMT-A) and the Stroop Color and Word Tests A and B (Stroop A and B). The language function consisted of the Boston Naming Test and Category Verbal Fluency test. Executive function is a compound score of the average Z-scores of the Digit Span Test-backward, Trail Making Test-A (TMT-B) and Stroop Color and Word Tests C (Stroop C). Visuospatial function is a compound score that includes the mean of the Z-scores of the Clock Drawing Test and Visual Reproduction-copy test.

Multimodal magnetic resonance image preprocessing
In recent years, more and more neuroimaging studies suggested that white matter alterations may be an important pathophysiological feature and a potential target of AD [22]. However, whether patterns of white matter change in different ber tracts are different and what happens to the white matter after the intervention are still largely unknown [13]. We decided to use AFQ, applying deterministic tractography approach, to reconstruct whole-brain white matter and analyze point-wise diffusion parameters in speci c ber tracts. AFQ can not only trace the ber tracts associated with the thalamus, but also analyze the important tracts in the brain, such as corticospinal tract, cingulate fasciculus, uncinate fasciculus, and arch fasciculus and so on to provide a comprehensive detection for whole-brain [23]. However, the changes in the microstructure of the white matter tracts are not necessarily consistent with alterations in the brain's complex networks [24] and it is better to combine multi-modality data to detect complex network changes in AD patients then a single modality [25,26]. It is effective to quantify the complex brain network topology by graph theory using rs-fMRI to build functional network [27,28]. As a result, we combined DTI and rs-fMRI to better explore thalamus and related network alteration after treatment.
For diffusion images, the data preprocessing was carried out by FSL 5.0.9 software (Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford; https://www.fmrib.ox.ac.uk/fsl/). The preprocessing included the following steps: DICOM-to NIfTI format conversion, registering DWI images (b = 1000 s/mm2) to the non-DWI image (B0), eddy current and head motion correction, and then nonbrain tissue exclusion. After preprocessing, using DTIFIT command of FSL to obtain the whole brain images of diffusion metrics, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (DA) and radial diffusivity (RD), Speci c calculation indexes are as follows: (λ 2 + λ 3 ) /2, λ 1 , λ 2 ,λ 3 re ect the three dispersion directions of water molecules [13]. λ 1 travels in or against the direction of the ber bundle of the voxel, which called axial direction and λ 2 , λ 3 , corresponds to the direction perpendicular to the axis, which called radial direction.
For rs-fMRI images, the data were preprocessed by GRETNA, a graph theoretical network analysis toolbox for imaging connectomes [29].
During the preprocessing, the rst 10 volumes for signal were removed to reach a steady state, leaving 220 functional volumes for each participant. The remaining functional volumes were corrected for acquisition time delay between slices (slice timing) and head motion between volumes (realignment). Then, these functional data were normalized to the T1 segmentation individually and spatially smoothed with a Gaussian kernel (full width at half-maximum of 4 mm). We regressing out covariates (white matter, cerebral spinal uid, global signals, and head-motion pro les) by multiple regression analysis to avoid noise signals. Other steps in preprocessing consisting of temporally linear detrending, temporal band-pass ltering (0.01-0.1 Hz), and scrubbing to reduce the effects of head motion on rs-fMRI data. The network construction was based on a voxel or region of interest approach. The Human Brainnetome Atlas was used to parcellate the brain into 246 regions. All network analyses were performed using GRETNA.

Automated ber quanti cation procedure
We identi ed 20 major tracts in whole brain and further quanti ed the diffusion metrics along the tract trajectory by applying the AFQ package. This is a description of AFQ steps in this result: (1) Fiber Tract Identi cation First, 3D T1-weighted images were co-registered into the b0 image for each participant based on FSL, and poorly aligned images were excluded by visual evaluation. Second, using deterministic tractography and a fourth-order Runge-Kutta path integration method [30] to perform whole-brain tractography with thresholds of turning angle < 30° and FA > 0.2. The tracking procedure generates a database of √ ( ) ( ) ( ) √ ( ) ( ) candidate bers in the whole-brain, which can be broken down into anatomically de ned bundles; Third, based on the waypoint ROI procedure described in Wakana et al [31], ber tract is segmented. In this procedure, if they pass through two waypoints de ned by ROI of AFQ, bers are assigned to a speci c ber group. Fourth, by comparing each candidate ber to ber tract probability maps, the ber tract re nement is accomplished. Each ber conforms to the shape of the tracts de ned by the ber tract probability maps (2) Fiber Tract Cleaning.
Due to the noise in the data, areas with complex ber orientation and ambiguous stopping criteria, a few bers may differ from the rest of the ber group. The bers were resampled to 100 equidistant nodes rstly and the ber tract core is calculated as the mean of each bers x, y, z coordinates at each node. The spread of bers in 3-dimensional space is calculated by computing the covariance between each ber's x, y, z coordinates at 100 nodes. Thus, each node on the tract is represented as a mean coordinate, m, and a 3 by 3 covariance matrix, S. Then we can calculate its Mahalanobis distance D m (x). The speci c formula is as follows: corresponds to the probability that a given point belongs to the distribution. Abnormal bers are removed if bers deviate substantially from the average position. (

3) Fiber Tract Quanti cation
The ber group is clipped to the central portion that spans between the two de ning ROIs and each ber was resampled to 100 equally spaced nodes. The properties such as DA, FA, MD and RD at each ber node are summarized by a weighted average of the diffusion properties. This probability is calculated based on the ber's Mahalanobis distance from the ber tract core.
The identi ed 20 WM tracts in the whole brain are listed in supplementary Table 1. It did not succeed in identifying 20 white matter tracts per participant because of the strict criteria applied by AFQ in the identi cation of white matter tracts. We excluded 3 ber tracts, right arcuate fasciculus (AF) and the bilateral cingulum hippocampus (CH) which largely unidenti ed. Only the remaining 17 ber tracts would be analyzed in further study. The thresholds were set at a p < 0.05.

Network parameter analysis
Graph theoretical analysis was performed on the interregional connectivity matrix by using GRETNA. The weight network properties were calculated under the threshold set by network sparsity with a range of 0.05-0.5 step size of 0.05. GRTNA was used to calculate the global network metrics including global e ciency, global clustering coe cient (Cp), characteristic path length (Lp), and nodal network metrics including node degree centrality (DC), nodal global e ciency (Ne) and nodal shortest path (Nlp). The calculating formula and descriptions of these topological properties for a network G with N nodes and V edges are as follows [32]: 1. Characteristic Lp at the level of network is an indicator of overall network connectedness and quanti es the parallel information propagation ability, which can be calculated as Lp(G) = L ij is the characteristic Lp between nodes i and j. 2. Eg is de ned as the inverse of the harmonic mean of shortest path between each pair of nodes within the network, which effectively measures the information communication capacity of the whole network and is calculated as the shortest Lp between node i and j in the network. 3. Cp at the network level represents the degree of local cliquishness or interconnectedness within the network. It can be calculated as Cp(G) = 4. Node degree centrality is number of links connected to a node. It can be represented as DC = ∑ j ∈ N d ij 5. Nodal Lp (Nlp) quanti es the mean distance or routing e ciency between one node and all the other nodes in the network, which calculated as: Lp (i) = 1 N − 1 ∑ i ≠ j ∉ G dij, d ij is the shortest Lp between node i and j in the network.
. Nodal e ciency means the e ciency of parallel information transfer of one node in the network. It can be calculated as: dij , dij is the shortest Lp between node i and j in the network.

Statistical analyses
To examine the point-wise difference of white matter tracts between baseline and post-treatment, we sorted DTI metrics (FA, MD, DA, and RD) of 100 nodes along each white matter tract calculated by AFQ in all patients. Then, paired T test was used to detect the differences in the DTI metrics of each ber tract. Paired T tests were performed in Gretna's nodal metric comparison toolkit and false discovery rate (FDR) was applied to determine the signi cance for p-values (p < 0.05). Within each ber, we only chose more than or equal to three adjacent nodes corrected by FDR to further analyze [26]. Differences of whole-network and nodal properties in functional network between pretherapy and post-treatment was performed in Gretna toolbox using paired samples T test and FDR corrected p < 0.05.
Baseline and post-treatment cognitive assessment were compared using paired-samples T test in SPSS software (Version 22). We divided the participants into the AD group and MCI group. We would conduct data analysis from the perspective of the whole participant, AD group and MCI group respectively. In order to investigate possible relationships between alteration of white matter ber and cognition change, we tested correlations using the Spearmen coe cient (two-tailed) between the altered diffusion metrics and cognitive change (calculated by using post-treatment data minus the baseline data). The thresholds were set at a p < 0.05.

Cognitive function improvement by neuro-navigated rTMS
Participant characteristics and neuropsychological evaluations were shown in Table 1. Compared with the baseline, general cognition (i.e., MOCA-BJ), episodic memory (i.e., AVLT-DR and VR-DR) and language function (i.e., BNT) showed the signi cant improvement after four-week neuro-navigated rTMS treatment among all participants. However, no difference between the baseline and post-treatment was observed in information processing speed and executive function in these subjects (p > 0.05).

Table1
Baseline demographic and neuropsychological data After dividing all participants into AD and MCI, we respectively analyzed cognitive function in these two groups (Table 1 and Figure 2) We found that the cognitive improvement was occurred in general cognition (i.e., MOCA-BJ), episodic memory (i.e., AVLT-DR and VR-DR) Loading [MathJax]/jax/output/CommonHTML/jax.js and language function (i.e., BNT) among MCI group (p < 0.05). In addition, although there are some differences in neuropsychological tests, there also exist some very similar improvement on general cognition (i.e., MOCA-BJ) and language function (i.e., BNT) in AD group (p < 0.05).

Point-wise differences of white matter tracts between baseline and posttreatment
Group point-wise differences of white matter tract were determined by mean diffusion metrics (FA, MD, AD, and RD) and only more than or equal to three adjacent nodes were reported within each ber. The major tracts we studied were bilateral thalamic radiation, which regions of interests are based on the coronal plane at the anterior edge of pons to delineate thalamus and internal capsule [31]. We also analyzed other ber tracts successfully tracked as described above. The following were the details (Figure 3).

Function network topology properties change in thalamus after treatment
The region of functional network was based on the Human Brainnetome Atlas and the brain aera representing the thalamus were selected [33]. Thalamus was divided into medial pre-frontal thalamus, pre-motor thalamus, sensory thalamus, rostral temporal thalamus, posterior parietal thalamus, occipital thalamus, caudal temporal thalamus and lateral pre-frontal thalamus [33]. Our study shows signi cant alterations in the degree centrality (DC), nodal e ciency (Ne) and nodal shortest path (Nlp) in patients with MCI. In MCI group, the DC and Ne of right medial pre-frontal thalamus, right posterior parietal thalamus, right occipital thalamus and right lateral pre-frontal thalamus were decreased after treatment. The Ne of caudal temporal thalamus was also decreased in MCI. In the meanwhile, the Nlp of right posterior parietal thalamus, right occipital thalamus and right lateral pre-frontal thalamus was increased after treatment (Figure4, p<0.05, FDR corrected). We didn't nd similar changes in AD patients. In the meanwhile, we analyzed brain regions associated with remaining altered two tracts--left Cingulum Cingulate and left uncinate fasciculus. The brain regions of the analysis were de ned according to the starting and ending points of the ber tracking [31]. The network properties of these brain regions did not change signi cantly after intervention.

The changed diffusion metrics, theoretical parameter and behavioral signi cance
Based on the multi-modal analysis in Figure 3 and Figure 4, we further analyzed the correlation between the diffusion metrics, theoretical parameter and cognition respectively (Figure5): (i) Post-wise differences correlation: It should be noted that the improved white matter integrity of right Thalamic Radiation were observed after four-week neuro-navigated rTMS treatment. Among MCI group, the increased white matter integrity of posterior portion of the right Thalamic Radiation's (nodes 88-94) correlated positively with the improved episodic memory (r = 0.585, p = 0.028) and improved language function (r = 0.663, p = 0.007) (ii) Theoretical parameter correlation: previous studies demonstrated that compared to healthy control, AD patients showed higher degree centrality and nodal e ciency in thalamus [34]. We thought that network attributes of the thalamus were improved after the intervention. In order to better describe this improvement, we took the negative number of these attributes for correlation analysis. After the conversion, we found signi cantly positive correlation between transformed Ne of right posterior parietal thalamus (r = 0.543, p = 0.030), right lateral pre-frontal thalamus (r = 0.497, p = 0.050) and the improved episodic memory among MCI group. In addition, we also found similar positive correlation between DC (r = 0.577, p = 0.021), Ne (r = 0.674, p = 0.004) of right posterior parietal thalamus, Ne (r = 0.726, p = 0.001) of right occipital thalamus and the language function (the score of BNT test ) among MCI group. The improved Nlp of right posterior parietal thalamus (r = 0.806, p < 0.001), right occipital thalamus (r = -0.824, p < 0.001) was positively correlated with the score of BNT test.

Discussion
Our study was the rst to use neuro-navigated rTMS targeting left angular gyrus to improve cognitive impairments in AD spectrum patients. And, we rstly demonstrated the changes in ber associated with thalamus after neuro-navigated rTMS treatment in AD spectrum patients. We investigated function network alteration in patients from a multimodal perspective and found a signi cant bene cial effect of rTMS targeting angular gyrus on improving episodic memory and language function. Furthermore, signi cant improvement was observed in microstructural integrity of right anterior thalamic radiation. Network topology properties in thalamus, such as nodal e ciency and degree centrality, were also changed at the function network level. This investigative approach may lead to a better understanding of cognitive improvement via neuro-navigated rTMS inducing the neuroplasticity of thalamic system in AD spectrum patients.

The selection and importance of stimulation target
In previous studies, rTMS intervention tends to stimulate the brain area traditionally associated with brain function such as dorsolateral prefrontal cortex (DLPFC) [35], inferior frontal gyrus(IFG)[36], parietal lobe and temporal lobe [37] and so on. These conventional interventions are often localized through body surface markers and brain region system such as electroephalogram 10-20 system. These positioning methods are not accurate enough, easy to occur error and other side-effects[38].Although they have a partial intervention effect, it's too crude to further explore the mechanism behind the study. As technology develops, neuro-navigated rTMS has signi cant advantages, such as more accurate location determination by using structural and functional neuroimaging and choosing target according to speci c study purpose [39]. In this study, our team calculated the region which is the most extraordinary different among healthy controls, MCI and AD patients using functional connectivity analysis based on the left hippocampus and located it to the left angular gyrus in our other large sample (these data were not listed in this study). Our intervention target was identi ed precisely and individually by neuro-navigated system. Previous researchers have used this precise navigation technique to target region of interest, such as, Koch et al. treated AD patients with rTMS in the precuneus region (MNI : 0,-65,37) and found their AVLT-DR scores improved signi cantly [39]; Ilona Eliasova performed intervention in the right inferior frontal gyrus (MNI : 48, 21, 3) in AD and MCI patients and resulted that TMT-A and TMT-B scores was improved after treatment [40].
The improvement of memory function by rTMS is consistent with previous studies, that angular gyrus, and its connectivity with the hippocampus, are involved in different degrees of memory function [41]. Recent models of long-term memory showed that the left angular gyrus played a critical role in episodic retrieval and recollection [42][43][44]. Inhibitory TMS of the angular gyrus impaired retrieval of episodic memory [45,46], and supported encoding in experience memory [47]. Moreover, memory encoding is an important target of rTMS to improve episodic memory [48]. These results lead us to propose a hypothesis that navigated rTMS targeting angular gyrus improve episodic memory by in uencing memory encoding and left angular gyrus-navigated rTMS may be an effective treatment to improve memory in AD patients.

The underlying mechanism and intervention opportunity of cognitive improvement
Thalamus is traditionally considered as a transmission center, responsible for transmission of sensory and motor inputs to the cerebral cortex, however, recent studies had shown that thalamus also play an important role in memory function [49,50]. It is consistent with our results that after four-week rTMS intervention, patient's memory improved along with changes in the thalamus. Previous study showed that the white matter integrity of anterior thalamic radiation was damaged in AD spectrum patients [51][52][53]. These studies indicated that the anterior thalamic radiation may serve as an important marker of AD diagnose. Our results showed that the FA value of right anterior thalamic radiation increased in MCI group after rTMS treatment. This demonstrated that these white matter ber bundles may have been remodeled due to the rTMS intervention, and the improvement of episodic memory and language scale score was positively correlated with the degree of such reconstruction. These ndings provide a new underlying mechanism of how rTMS improves cognition.
In addition, to explain the therapeutic mechanism of rTMS from the perspective of white matter integrity, functional network change can't be ignored. It's worth noting that the potential effect of rTMS spread from directly targeted areas to anatomically areas, which provides an opportunity to apply rTMS at one point of neural circuit [54]. And, previous graph theoretical analysis in functional network showed that AD patients had higher degree centrality and nodal e ciency in thalamus [34]. These ndings were consistent to our results. By shifting the thalamus FC graph pattern to that of healthy control, rTMS improved MCI's episodic memory and language function. Our correlation analysis also con rmed that the greater the alteration, the better the patient's memory and language function. Interestingly, we also found changes in other ber tracts, with either an increase or a decrease in the integrity of white matter tracts, which may be the result of natural physiological processes and need furthered investigated. We found these white matter and functional changes primarily in the MCI population suggested that rTMS has a good effect in the early stages of cognitive impairment. Our ndings were consistent with previous studies about the curative effect of rTMS in which patients with mild AD showed better cognitive improvement than those with moderate AD through combined rTMS and cognitive training intervention [55,56]. In late AD, irreversible damage has occurred, including excessive Aβ accumulation, neuronal damage, death, and destruction of the blood-brain barrier [57]. At this stage, drugs or other interventions are di cult to play a good therapeutic effect.
Our study showed that after four-week rTMS intervention targeting angular gyrus, memory and language function in both MCI and AD patients had been improved. White matter integrity of right anterior thalamic radiation is reconstructed and functional network topology properties was re ned in thalamus. These alterations play a key role in cognitive improvement. The causal relationship between these changes will be the focus of future research.

Methodological issues Limitations and prospects
There are several limitations of our study needs improved. Firstly, these observations in our study were made in a relatively small sample and lacked a sham group due to the relatively complex experimental design. Further investigation through large prospective studies is necessary. Secondly, depending on the strict requirements for ber tracking, the ber tracts like bilateral cingulum hippocampus tracts were not traceable in some subjects, led to lack into these important ber tracts, however, all of our subjects' target bers associated with thalamus were reconstructed successfully, which lends con dence in further study.

Conclusion
In support of the growing evidence for an intervention strategy of AD spectrum patients, this study provided neuroimaging evidence that the cognitive improvement via left angular gyrus-navigated rTMS inducing the neuroplasticity of thalamic system, especially in the early disease process at the stage of MCI. These ndings may open novel avenues for better understanding the effects of rTMS in improving episodic memory and language function in AD spectrum patients.  Figure 1 Study and experiment design All patients (n=26) were stimulated the angular gyrus (MNI: -45, -67, 38). by the Neuro-navigated rTMS for four weeks. rTMS was applied at 20 Hz ve times a week, using a neuron avigation system to ensure that the same spot was constantly stimulated across sessions.  Behavioral result All participants showed improvement in general cognition, episodic memory and language function. MCI' s general cognition, episodic memory and language function improved and AD's general cognition, and language function were also improved.   Alterations in thalamic-related functional network properties In MCI group, Nodal shortest path length of right posterior parietal thalamus, occipital thalamus and lateral pre-frontal thalamus was improved. (FDR correction, p < 0.05). Nodal e ciency of right medial pre-frontal thalamus, posterior parietal thalamus, occipital thalamus, caudal temporal thalamus, lateral pre-frontal thalamus was decreased. (FDR correction, p < 0.05). Degree centrality in right medial pre-frontal thalamus, posterior parietal thalamus, occipital thalamus and lateral pre-frontal thalamus was decreased (FDR correction, p < 0.05).

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