Thalamic functional connectivity on 7-Tesla magnetic resonance imaging and its relation to motor signs in early-stage Parkinson’s disease
Original Article

Thalamic functional connectivity on 7-Tesla magnetic resonance imaging and its relation to motor signs in early-stage Parkinson’s disease

Xiaoyu Wang1,2, Yongqin Xiong2, Jianxing Hu2, Fengzhu Li3, Caohui Duan2, Haoxuan Lu2, Dong Zhang2, Jiayu Huang2, Xiangbing Bian2, Song Wang2, Miao Wang3, Xi Yin3, Zhongbao Gao3, Xin Lou1,2

1School of Medicine, Nankai University, Tianjin, China; 2Department of Radiology, Chinese PLA General Hospital, Beijing, China; 3Department of Neurology, the Second Medical Center & National Clinical Research Center for Geriatric Disease, Chinese PLA General Hospital, Beijing, China

Contributions: (I) Conception and design: X Wang; (II) Administrative support: X Lou, Z Gao; (III) Provision of study materials or patients: All authors; (IV) Collection and assembly of data: All authors; (V) Data analysis and interpretation: All authors; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: Xin Lou, MD, PhD. School of Medicine, Nankai University, 94 Weijin Road, Tianjin 300071, China; Department of Radiology, Chinese PLA General Hospital, 28 Fuxing Road, Beijing 100853, China. Email: louxin@301hospital.com.cn; Zhongbao Gao, MD. Department of Neurology, the Second Medical Center & National Clinical Research Center for Geriatric Disease, Chinese PLA General Hospital, 28 Fuxing Road, Beijing 100853, China. Email: gaozb301@163.com.

Background: It is well known that dysfunction of thalamocortical circuity generates the motor signs that lead to distinct disease processes and prognoses in Parkinson’s disease (PD). This study aimed to leverage ultrahigh-field magnetic resonance imaging (MRI) to identify the connectivity alterations of thalamocortical circuity and clarify their relation to motor signs in early PD.

Methods: Patients with early-stage PD (n=55) and healthy controls (HCs, n=56) were recruited from March 2022 to July 2023. All participants underwent 7-Tesla MRI scans as the baseline. Sign scores were calculated from the Movement Disorder Society Unified Parkinson’s Disease Rating Scale III. Significant differences in the functional connectivity between the thalamus subregions and cortex between the PD and HC groups were discovered. The association between altered thalamic functional connectivity and sign scores was evaluated using Spearman or Pearson correlation analysis with false discovery rate (FDR) correction.

Results: Compared to the HCs, the patients with early-stage PD exhibited a decreased functional connectivity between thalamic subregions (primary motor, sensory, occipital, premotor, and parietal thalamus regions) and the cortex [voxel-level P<0.001, cluster-level Pfamily-wise error (FWE) <0.05]. Further exploration of the connection pattern within thalamic subregions showed that the connection strength between the primary motor and sensory (t=2.055; P=0.042), sensory and occipital (t=2.173; P=0.032), and occipital and parietal (t=2.365; P=0.020) regions were reduced. Importantly, motor signs in early-stage PD were associated with the alterations of functional connectivity pattern between the parietal thalamus and left dorsolateral part of the superior frontal gyrus (r=–0.272; PFDR =0.049) and the right thalamus (r=–0.267; PFDR =0.048) .

Conclusions: These findings support the use of ultrahigh-field MRI for examining the thalamic subregions and clarifying their involvement in the neural mechanisms of various motor signs in early-stage PD.

Keywords: Parkinson’s disease (PD); ultrahigh field; magnetic resonance imaging (MRI); thalamus; motor sign

Submitted Jul 22, 2024. Accepted for publication Nov 14, 2024. Published online Dec 18, 2024.

doi: 10.21037/qims-24-1498

Introduction

Parkinson’s disease (PD) is a progressive neurodegenerative disease characterized by resting tremor, bradykinesia, rigidity, and postural balance disorder (1). Generally, the expression and predominance of each classic clinical sign vary from patient to patient. Studies have shown that different motor features in PD can be used to monitor therapeutic responses and to assess the processes and prognoses of diseases (2,3). Moreover, the neuropathological hallmark of PD is the depletion of nigrostriatal dopaminergic system; however, it primarily reflects the terminal stages of the disease but not the motor and non-motor impairments in early-stage PD (4). Therefore, exploring quantitative imaging markers for different motor signs of early-stage PD is crucial.

The thalamus, considered an important hub in thalamocortical circuity, is a comprehensive relay node for transmitting diverse information (5). Many studies have examined the thalamus to investigate how basal ganglia-thalamocortical circuits are affected in PD in order to generate deeper insights into the underlying mechanism and pathophysiology of the disease (6-8). Bu et al. found that differences in the functional connectivity density of the bilateral premotor thalamus could differentiate between the PD subtypes of tremor dominant (TD) and postural instability and gait difficulty (PIGD) (6). A prospective longitudinal study reported that alterations in bilateral thalamus morphology could predict conversion to freezing of gait in patients with PD (8). Over the years, the thalamus has also become a target area for surgical treatments in PD (9). Deep brain stimulation (DBS) and magnetic resonance imaging (MRI)-guided focused ultrasound (MRgFUS) targeting the thalamus can effectively improve motor signs in patients with PD (10,11). These recent studies have confirmed the role of the thalamus in modulating the cortical activity associated with motor signs, disease progression, and surgical efficacy in PD.

Clinical MRI studies, including those using a conventional clinical field of 1.5 and 3 Tesla (T), have reported several measures of changes in the functional connectivity between various substructures of the thalamus and various cortical regions in PD (12-15). However, these conventional clinical fields currently lack the sensitivity and specificity of scope required to fully characterize elements of thalamic subregions (16). Therefore, their related connections and changes have not been examined with sufficient thoroughness to contextualize the changes associated with PD. Ultrahigh-field MRI scanners, especially the 7-T types, when combined with bold-oxygenation-level-dependent (BOLD) functional MRI (fMRI), provides a powerful tool for investigating the alterations in functional connectivity in small thalamic subregions (17,18). This research approach has gradually gained recognition in its ability to reveal the pathogenesis of nervous system diseases, such as schizophrenia, trigeminal neuralgia, and major depressive disorder (16,17,19).

We hypothesized that alterations in thalamic functional connectivity as detected by ultrahigh-field BOLD fMRI between patients with PD and healthy controls (HCs) could provide new evidence for understanding the different motor signs of PD. To test our hypothesis, in this study, we (I) applied a voxel-based analysis to the functional neuroimaging data to identify a differential connectivity pattern between the thalamic subregion and cortex, (II) analyzed the thalamic subregion characteristics based on a region of interest (ROI)-wise approach to further clarify this connectivity pattern, and (III) applied Pearson or Spearman correlation analysis to characterize its signatures for motor signs. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-24-1498/rc).

Methods

Ethical considerations

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) and was approved by the Chinese PLA General Hospital Ethics Committee (No. S2022-572-01). Informed consent was obtained from all individual participants. The ethical approval included construction of a comprehensive assessment system for neurodegenerative diseases based on multimodal imaging. The same ethical approval number applies to in multiple related studies due to the broad scope of the approval.

Participants

The protocol of this study was registered in the ClinicalTrials.gov database (NCT06449404). A total of 145 patients with PD were initially recruited for this study from March 2022 to July 2023. Two neurologists assessed each patient’s clinical state and diagnosed PD according to the Movement Disorder Society (MDS) Clinical Diagnostic Criteria (20). Early-stage PD is defined as Hoehn and Yahr Scale (H-Y) score between 1 and 2.5 (3). The inclusion and exclusion criteria for early-stage PD are shown in Figure 1. Finally, we included 55 patients with right-handed PD, and 56 age- and gender-matched right-handed HCs were recruited from the community for analysis.

Figure 1 Flowchart of study participants with early-stage PD. PD, Parkinson’s disease; MRI, magnetic resonance imaging; MR, magnetic resonance.

Clinical assessment

Basic demographic data including age, gender, and years of education were collected. Among patients with PD, the data also included years of disease duration and the levodopa equivalent daily dose (LEDD). The MDS Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) was used to evaluate the disease severity of PD, which consists of part I (nonmotor daily living experience), part II (motor daily living experience), part III (motor examinations), and part IV (motor complications). We also calculated the sign scores of MDS-UPDRS III items that represented four major motor signs in early-stage PD (21): bradykinesia, rigidity, tremor, and axial signs. Additionally, gait scores were further calculated in a subanalysis. The method employed for calculating motor signs is available in the Supplementary file (Appendix 1). The Mini-Mental State Examination (MMSE) was applied to evaluate cognitive function. The normal MMSE scores in this study were used the cutoff points as follows (22): illiterate, >17; literate to a grade school level, >20; and literate to a level of junior high school or higher education, >23.

MRI acquisition

The experiment was performed on a whole-body 7-T scanner (MAGNETOM Terra, Siemens Healthineers, Erlangen, Germany) equipped with an 8-channel transmit and 32-channel receive coil. A resting-state fMRI (rsfMRI) scan was performed with echo-planar imaging (EPI) as follows: voxel =1.8×1.8×1.8 mm3, repetition time (TR) =2,000 msec, echo time (TE) =24 msec, flip angle =90°, field of view (FOV) =216 mm × 216 mm, matrix =120×120, slice thickness =1.8 mm, and interleaved slices =80. Each functional run produced 240 volumes.

MRI data preprocessing

Data Processing and Analysis for Brain Imaging (DPABI) software (http://www.rfmri.org/dpabi) was used to preprocess the rsfMRI data, including motion correction, removal of the top 10 time points, slice timing, normalization to Montreal Neurological Institute (MNI) space, nuisance regression, detrending, smoothing with a 4-mm full width at half maximum (FWHM), and band-pass filtering (0.008–0.08 Hz).

Calculation of functional connectivity

Functional connectivity was defined as the correlation of time series between brain regions as measured by the Pearson correlation coefficient and reflected the temporal coherence between brain regions. DPABI software was used to build functional connectivity. The ROI was defined as the brain regions outlined in the Oxford thalamic connectivity atlas (23). This atlas is generated using diffusion-based structural connectivity in white matter between the thalamus and cortex, which segments the thalamus into seven subregions, with >25% probability of connection to seven exclusive cortical areas, respectively. Therefore, many voxels within a subregion can still have anatomical connections to other brain regions (23), which also applies to functional connectivity. Seed-based analysis was carried out using each thalamic subregion as a seed, and a whole brain connectivity map (z values) to each seed was calculated. ROI-wise analyses were calculated on seven regions to obtain the connection strength within the thalamic subregions.

Statistical analysis

Statistical analyses and plots were performed using SPSS 26 (http://www.spss.com/) software (IBM Corp., Armonk, NY, USA) and GraphPad Prism version 9 (https://www.graphpad.com/) software (GraphPad Software, Boston, MA, USA), respectively. The Shapiro-Wilk test was used to check normality of the data distribution. The two-sample independent t-test was used to analyze the continuous variables (e.g., age, years of education), while the χ2 test was used to analyze the dichotomous variables (e.g., sex).

Statistical Parametric Mapping software (SPM12; Wellcome Centre for Human Neuroimaging, London, UK) was used for statistical analysis of the MRI data. A whole-brain voxel-wise-dependent t-test was used to identify significant alterations in functional connectivity between the early-stage PD and HC group [voxel P<0.001 and cluster P<0.05, with family-wise error (FWE) correction]. Age, sex, and education were entered as covariates. Significant clusters of thalamic connectivity were reported based on the Automated Anatomical Labeling (AAL) atlas (24) to identify anatomical regions. Subsequently, the significant values of brain regions were extracted. Spearman or Pearson correlation analysis was used to evaluate the relationship between thalamic functional connectivity and clinical scores. The results of correlation analysis were corrected by the false discovery rate (FDR) to ensure accuracy. The significance threshold was set at a two-tailed P value <0.05.

Results

Demographic information and clinical characteristics

The group of 55 patients with early-stage PD who underwent 7-T MRI scan had a mean age of 61.98±1.02 years and a mean disease duration of 4.50±0.39 years. Among the patients, 27 patients were female, and 28 patients were male. The mean value of the H-Y score was 1.75±0.94 which was an appropriate stage for early-stage PD. Other demographic and clinical characteristics of early-stage patients with PD and HCs are shown in Table 1. There were no significant differences between the two groups (Table 1) in terms of age, sex, or years of education (all P values >0.05).

Table 1

Demographic and clinical characteristics of the included participants with early-stage PD and the HC groups

Variable Early PD (n=55) HC (n=56) t/χ2 value P value
Age (years) 61.98±1.02 64.48±0.79 −1.950 0.054
Sex (male/female) 28/27 21/35 2.023 0.155
Education (years) 11.46±0.67 12.73±0.42 −1.627 0.107
Disease duration (years) 4.50±0.39 – – –
MMSE 26.20±0.53 – – –
H-Y stage 1.75±0.94 – – –
LEDD (mg/day) 475.45±29.78 – – –
MDS-UPDRS
   I 7.84±0.60 – – –
   II 9.15±0.72 – – –
   III 25.78±1.44 – – –
   IV 0.84±0.23 – – –
   Total 43.60±2.34 – – –
Sign scores – – –
   Tremor 3.82±3.50 – – –
   Axial signs
    Axial1 6.09±3.87 – – –
    Axial2 4.80±3.14 – – –
    Gait 1.29±0.98 – – –
   Rigidity 6.29±3.29 – – –
   Bradykinesia 9.56±5.73 – – –

Data are presented as the mean ± standard deviation or number. PD, Parkinson’s disease; HC, healthy control; MMSE, Mini-Mental State Examination; H-Y stage, Hoehn and Yahr stage; LEDD, levodopa-equivalent daily dose; MDS-UPDRS, Movement Disorder Society Unified-Parkinson Disease Rating Scale; Axial1, with gait score; Axial2, without gait score.

Brain functional connectivity alterations between thalamic subregions and the cortex in the early-stage PD and HC groups

We compared the early-stage PD and HC groups in terms of the alteration in functional connectivity between the thalamic subregions and cortex. Five subregions of the thalamus showed significant differences in the functional connectivity between two groups, including the primary motor thalamus, sensory thalamus, occipital thalamus, premotor thalamus, and posterior parietal thalamus (Table 2 and Figure 2). The other subregions showed no significant difference between the two groups.

Table 2

Voxel-based analysis of thalamic functional connectivity in the early-stage PD and HC groups (HC group > PD group)

Cluster ID Brain region Hemisphere Cluster size
(voxels)		 Peak MNI coordinate (mm) Peak-level
t value		 Voxel-level P Cluster-level PFWE
x y z
Subregion 1 (connection to primary motor region) <0.001 <0.05*
   1 REC L 133 −10 26 −14 5.067
   2 TPOsup R 556 60 10 −8 5.518
   3 LING L 386 −14 −52 2 5.561
   4 TPOsup L 69 -50 12 −14 4.839
   5 LING R 107 20 −72 0 4.559
   6 THA L 80 −16 −18 0 4.233
   7 ROL L 127 −46 −12 16 4.519
   8 STG L 84 −56 −40 22 4.594
   9 STG R 26 42 −34 16 4.387
   10 MOG R 78 48 −68 26 4.551
Subregion 2 (connection to sensory region) – –
   1 TPOsup R 300 54 10 −14 5.992
   2 REC L 74 −12 28 −18 4.403
   3 LING L 595 −14 −54 0 5.561
   4 ROL L 284 −44 −16 16 4.920
   5 ORBsupmed L 76 −4 66 −2 4.890
   6 THA L 93 −22 −28 6 5.036
   7 IFGoperc L 101 −38 14 20 4.895
   8 MTG L 7 −44 −42 10 4.982
   9 DCG R 110 8 22 32 4.358
   10 DCG L 52 −12 −36 50 4.177
   11 SMA R 119 6 10 56 4.547
Subregion 3 (connection to occipital region) – –
   1 STG R 1181 64 −18 −4 5.779
   2 TPOsup L 14 −18 10 −32 5.217
   3 PHG R 111 28 −16 −24 5.269
   4 STG L 852 −52 −14 10 5.727
   5 SFGmed L 52 −2 70 8 4.328
   6 SPG R 17 10 −82 48 5.324
   7 DCG L 130 −12 −36 46 4.790
   8 SPG R 100 16 −56 70 4.599
   9 PCUN L 62 −12 −58 66 4.250
Subregion 5 (connection to premotor region) – –
   1 ORBsupmed L 29 −8 66 −4 4.135
   2 LING L 39 −14 −52 2 4.026
   3 ROL L 70 −48 −10 14 4.282
Subregion 6 (connection to posterior region) – –
   1 STG R 1054 60 −32 18 5.412
   2 HIP R 59 28 −16 −22 4.761
   3 STG L 949 −58 −2 −10 5.240
   4 SFGdor L 109 −18 62 28 4.705
   5 THA R 47 12 −16 −2 5.259
   6 IFGtriang R 80 54 32 14 4.548
   7 DCG R 27 2 16 30 3.985
   8 DCG L 111 −14 −36 46 4.658
   9 SMA L 20 −10 −4 48 4.349
   10 DCG R 75 14 −34 46 4.735
   11 PreCG L 80 −38 −26 58 3.893

*, the voxel-level threshold was P<0.001, with cluster-level PFWE <0.05. The brain regions are reported based on the Automated Anatomical Labeling atlas: DCG, median cingulate and paracingulate gyri; HIP, hippocampus; IFGoperc, inferior frontal gyrus, opercular part; IFGtriang, inferior frontal gyrus, triangular part; LING, lingual gyrus; MOG, middle occipital gyrus; MTG, middle temporal gyrus; ORBsupmed, superior frontal gyrus, medial orbital; PCUN, precuneus; PHG, parahippocampal gyrus; PreCG, precentral gyrus; REC, gyrus rectus; ROL, rolandic operculum; SFGdor, superior frontal gyrus, dorsolateral; SFGmed, superior frontal gyrus, medial; SMA, supplementary motor area; SPG, superior parietal gyrus; STG, superior temporal gyrus; THA, thalamus; TPOsup, temporal pole: superior temporal gyrus. PD, Parkinson’s disease; HC, healthy control; MNI, Montreal Neurological Institute; FWE, family-wise error.

Figure 2 Voxel-based analysis for thalamic functional connectivity in the early-stage PD and HC groups. Five subregions of the thalamus showed significant differences in the functional connectivity, with decreased activity in patients with early-stage PD compared to HCs. The color bar represents the t value. PD, Parkinson’s disease; HC, healthy control.

With primary motor thalamus as the seed region, there was a reduction in functional connectivity to the cortex, including the left rectus, bilateral temporal pole, bilateral lingual gyrus (LING), left thalamus, left rolandic operculum, bilateral superior temporal gyrus (STG), and right middle occipital gyrus (voxel-level P<0.001, cluster-level PFWE <0.05).

With the sensory thalamus as the seed region, there was a decreased functional connectivity between the cortex and right temporal pole (TPOsup.R), left rectus, left LING, left rolandic operculum, left medial orbital part of the superior frontal gyrus (ORBsupmed.L), left thalamus, left opercular part of the inferior frontal gyrus (IFGoperc.L), left middle temporal gyrus, bilateral median cingulate and paracingulate gyri (DCG), and right supplementary motor area (SMA) (voxel-level P<0.001, cluster-level PFWE <0.05).

With the occipital thalamus as the seed region, there was a decrease in functional connectivity between the cortex and bilateral STG, left temporal pole (TPOsup.L), right parahippocampal gyrus, left medial part of superior frontal gyrus, right superior parietal gyrus, left DCG, and left precuneus (voxel-level P<0.001, cluster-level PFWE <0.05).

There was also decreased functional connectivity between the premotor thalamus and the ORBsupmed, LING, and rolandic operculum in the left hemisphere.

With the posterior parietal thalamus as the seed region, there was decreased functional connectivity between the cortex and the bilateral STG, right hippocampus, left dorsolateral part of the superior frontal gyrus (SFGdor.L), right thalamus, right triangular part of the inferior frontal gyrus, bilateral DCG, left SMA, and left precentral gyrus (voxel-level P<0.001, cluster-level PFWE <0.05).

Brain functional connectivity alterations within thalamic subregions in the early-stage PD and HC groups

To observe the alterations of the functional connectivity within thalamic subregions, we further conducted ROI-wise analysis (Figure 3). There were significant differences between the PD and HC groups in terms of functional connectivity between the primary motor and sensory thalamus (t=2.055; P=0.042), sensory and occipital thalamus (t=2.173; P=0.032), and occipital and parietal thalamus (t=2.365, P=0.020) (Figure 3). There were no significant differences in the functional connectivity between the target regions including the prefrontal thalamus, premotor thalamus, and temporal thalamus and the other six thalamic subregions, respectively (P>0.05). These results of ROI-wise analysis are shown in Table S1.

Figure 3 ROI-based analysis of thalamic functional connectivity in the early-stage PD and HC groups. (A) The Oxford thalamic connectivity atlas. (B-G) Comparison of the target thalamic subregion with other regions. *, P<0.05. ROI, region of interest; PD, Parkinson’s disease; HC, healthy control.

Correlations between brain functional changes and clinical scores

Spearman or Pearson correlation analysis was conducted to investigate the relationship between functional connectivity in the related brain regions and clinical scores (Figure 4). The results revealed that the connectivity between the parietal thalamus and right thalamus and between the parietal thalamus and SFGdor.L were negatively correlated with rigidity (r=–0.272; PFDR =0.049) score and gait score (r=–0.267; PFDR =0.048), respectively. Other results of correlation analysis did not pass FDR correction and are shown in Table S2.

Figure 4 The significant results for relationships between thalamic functional connectivity and the clinical scores in the early-stage PD group after FDR correction. (A) The correlation of the functional connectivity between ParietalTH and SFGdor.L with gait score in the early-stage PD group. (B) The correlation of functional connectivity between the ParietalTH and THA.R with rigidity score in early-stage PD. ParietalTH, parietal thalamus; SFGdor.L, left dorsolateral part of the superior frontal gyrus; THA.R, right thalamus; PD, Parkinson’s disease; FDR, false discovery rate.

Discussion

This is the first study to use ultrahigh-field MRI to investigate the alterations in thalamic functional connectivity associated with different motor signs in early-stage PD. We identified a decreased connectivity pattern between the thalamic subregion and other brain regions in patients with PD as compared to HCs. Additionally, this decreased connectivity pattern was also confirmed among various thalamic subregions, including between the primary motor and sensory regions, sensory and occipital regions, and occipital and parietal regions. Finally, these alterations in functional connectivity pattern between the parietal thalamus and SFGdor.L and the right thalamus were related to motor signs in early-stage PD.

Thus far, the majority of studies in patients with PD have investigated the thalamus as a whole despite the differential connectivity and function of its subregions (25,26). In our study, we used ultrahigh-field imaging with voxel-based analysis to detect a pattern of reduced connectivity between five seeded thalamic subregions, including the primary motor thalamus, sensory thalamus, occipital thalamus, premotor thalamus, and posterior parietal thalamus, and relevant brain regions. The voxel-level analysis of thalamic subregions in previous 3-T MR studies has not been conducted to a sufficient extent (6,26). The sensitivity of BOLD fMRI is expected to increase super-linear enhancement with field strength (27), and a previous study indicated that ultrahigh-field 7-T BOLD fMRI may require a smaller sample size than may 3 T for exploring smaller regions within the thalamus (17). Therefore, we have good reason to believe that the results we detected are stable and reliable, as the sample in this study included 111 participants (55 in the PD group and 56 in the HC group).

In this study, we interestingly observed a pattern of reduced thalamic interconnectivity based on the ROI-wise level. No differences in thalamic interconnectivity were detected in the connectivity pattern between the thalamus and cortex at the voxel-level between the PD and HC groups. This discrepancy may be due to the different analytic approaches. The role of the thalamus and its subregions in PD have received considerable attention in clinical practice. A previous study suggested that levodopa could improve different the motor signs in PD through decreasing the functional connectivity of specific thalamic subregions (28). The functional connectivity patterns of thalamic subregions provide crucial information for distinguishing between patients with mild cognitive impairment and those with different motor subtypes of PD (6,7). However, the results of functional connectivity patterns noted in the abovementioned study differ from those in our study. These discrepancies may be due to several factors, including the variable impact on thalamic nuclei in the patients with PD, different combinations of PD, individual variations, and the use of different analytical methods. Nevertheless, the thalamic interconnectivity differences we detected using ultrahigh-field imaging provide additional data for clarifying the neural mechanisms of PD.

The thalamocortical connectivity reductions identified between PD and HC using voxel-based analysis prompted us to further explore their role in PD motor signs. Our observation that SFG was specifically affected in patients with PD with gait deficit is a new finding. Gait deficits are among the most debilitating signs of PD and often indicate that patients are at an increased risk of falls and have worsening disease severity (29). The relationship between the brain region in SFG and gait deficit could be interpreted as a reduction in the functional connectivity between the parietal thalamus and SFG being associated with higher gait scores. First, previous studies have demonstrated that the SFG plays an important role in the regulation of response inhibition (30,31). Specifically, the SFG has been shown to play a crucial role in the control of impulsive responses by regulating the inhibitory process (32). Considering these data together, we hypothesized that the decreased functional connectivity in SFG in patients with PD compared to HCs with higher gait scores may reflect the close relationship between dysfunction in the inhibitory control of the SFG and the severity of gait deficit. Second, another study demonstrated that SFG plays a crucial role in in integrating visual information with higher motor and cognitive functions (33). More recently, it was reported that severity of gait impairment and freezing was correlated with visual abnormalities (34). Thus, it has been proposed that a series of cortical connections from visual areas to motor areas underly the sensory guidance of movement (35). Therefore, we speculate that the SFG integrates visual information to guide gait control in patients with PD; however, this needs to be further confirmed with longitudinal data.

There are certain limitations to this study which should be acknowledged. One of the limitations is the use of Oxford thalamic connectivity atlas, as the use of other atlases might have led to different results. Although, the Oxford thalamic connectivity atlas is the primary atlas used in studies of thalamic subregions (17), examining other atlases is also essential. Another issue is the lack of longitudinal data. As we employed a case–control design, the functional changes identified in our study caused by the progression of disease should be further confirmed and longitudinal follow-up conducted in future research.

Conclusions

Through use of ultrahigh-field BOLD fMRI, we found a reduced functional connectivity pattern of the thalamocortical circuit between the PD and HC groups. Additionally, the functional connectivity pattern between the parietal thalamus and SFGdor.L and the right thalamus in early-stage PD were related to gait and rigidity scores, respectively. Our results provide new insights into neural mechanisms underlying the pathophysiology of early-stage PD.

Acknowledgments

Funding: This research was supported by National Natural Science Foundation of China (Nos. 82151309 and 82327803 to X.L., and No. 82302146 to Y.X.).

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-24-1498/rc

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-1498/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) and was approved by the Chinese PLA General Hospital Ethics Committee (No. S2022-572-01). Informed consent was obtained from all individual participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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Cite this article as: Wang X, Xiong Y, Hu J, Li F, Duan C, Lu H, Zhang D, Huang J, Bian X, Wang S, Wang M, Yin X, Gao Z, Lou X. Thalamic functional connectivity on 7-Tesla magnetic resonance imaging and its relation to motor signs in early-stage Parkinson’s disease. Quant Imaging Med Surg 2025;15(1):623-635. doi: 10.21037/qims-24-1498

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