Distance-related functional reorganization predicts motor outcome in stroke patients

Distance-related functional reorganization predicts motor outcome in stroke patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Distance-related functional reorganization predicts motor outcome in stroke patients Wenjun Hong, Zaixing Liu, Xin Zhang, Ming Li, Zhixuan Yu, Yuxin Wang, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3916957/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Jun, 2024 Read the published version in BMC Medicine → Version 1 posted You are reading this latest preprint version Abstract Background Analyzing distance-dependent functional connectivity density (FCD) yield valuable insights into patterns of brain activity. Nevertheless, whether alterations of FCD in chronic stroke patients are associated with the anatomical distance between brain regions remains unclear. This study aimed to explore the distance-related functional reorganization in chronic stroke patients following left and right hemisphere subcortical lesions, and its relationship with clinical assessments. Methods In this study, we used resting-state fMRI to calculate distance-dependent (i.e., short- and long-range) FCD in 25 left subcortical stroke (LSS) patients, 22 right subcortical stroke (RSS) patients, and 39 well-matched healthy controls (HCs). Then, we compared FCD differences among the three groups and assessed the correlation between FCD alterations and paralyzed motor function using linear regression analysis. Results Our findings demonstrated that the left inferior frontal gyrus (IFG) displayed distance-independent FCD changes, while the bilateral supplementary motor area (SMA), cerebellum, and left middle occipital gyrus exhibited distance-dependent FCD alterations in two patient subgroups compared with HCs. Furthermore, we observed a positive correlation between increased FCD in the bilateral SMA and the motor function of lower limbs, and a negative correlation between increased FCD in the left IFG and the motor function of both upper and lower limbs across all stroke patients. These associations were validated by using a longitudinal dataset. Conclusions The FCD in the cerebral and cerebellar cortices shows distance-related changes in chronic stroke patients with motor dysfunction, which may serve as potential biomarkers for predicting motor outcomes after stroke. These findings enhance our comprehension of the neurobiological mechanisms driving chronic stroke. Trial registration All data for the present study were obtained from a research trial registered with the ClinicalTrials.gov database (NCT05648552, registered 05 December 2022). Neurology Stroke Distance Functional Connectivity Density Motor Function Resting-state fMRI Biomarker Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background During the chronic stroke stage, survivors continue to undergo a dynamic process of functional reorganization associated with post-stroke recovery [ 1 , 2 ]. Resting-state fMRI (rs-fMRI) has emerged as a promising avenue to explore brain functional integration and separation after stroke [ 3 ]. Our prior rs-fMRI studies found decreased functional connectivity (FC) between hippocampal subfields and left postcentral gyrus (PosCG) as well as right middle occipital gyrus (MOG) [ 4 ], between cerebellum posterior lobe and left precentral gyrus (PreCG), inferior frontal gyrus (IFG) as well as middle temporal gyrus [ 5 ], and increased FC from the ipsilesional M1 to the ipsilesional occipital lobes [ 6 ] in chronic stroke patients compared with healthy controls (HCs). However, the FC analysis needs a predefined selection of regions of interest, which is a challenging issue in neuroimaging. To overcome this limitation, a data-driven analysis called functional connectivity density (FCD) mapping was proposed, treating each voxel as a seed and calculating the number of connections it holds with other voxels, thereby indirectly elucidating the spatial distribution and importance of brain regions within the whole brain [ 7 ]. Thus, the FCD provides an unbiased search of functional connectome abnormalities within the whole brain without prior hypothesis [ 8 ]. This method has been used to detect functional reorganization patterns across diverse diseases, such as stroke [ 2 , 9 , 10 ], depression [ 11 ], and Parkinson’s disease [ 12 ]. Increasing evidence has indicated that the FC between brain regions is closely associated with their anatomical locations [ 13 , 14 ]. Recent studies divided the FCD into short-range FCD (sFCD) and long-range FCD (lFCD) based on a distance criterion [ 15 ], representing functional specialization and integration of brain networks, respectively [ 16 ]. This approach has identified distance-dependent FCD alterations in neuropsychiatric disorders. For instance, a schizophrenia study revealed a significant interaction between genotype and diagnosis in the sFCD but not in the lFCD [ 17 ]. Another study found altered lFCD, but not altered sFCD, in the frontoparietal areas in children with attention-deficit/hyperactivity disorder [ 18 ]. The bipolar disorder patients showed a positive correlation between increased sFCD in the left fusiform gyrus and depressive episodes and a negative correlation between decreased lFCD in the left angular gyrus and depressive severity [ 19 ]. The major depressive patients displayed significantly negative correlations between decreased sFCD in the left PreCG/PosCG and depressive severity, which were not observed in the lFCD [ 20 ]. However, previous FCD studies in stroke have not accounted for the effect of distance on functional reorganization, and it still remains unclear whether the FCD shows distance-dependent alterations in chronic stroke patients. The present study aimed to explore whether the functional organization in cerebral and cerebellar cortices correlates with the spatial distances between brain regions in chronic stroke patients following left and right hemisphere subcortical lesions using the FCD approach. Based on the prior reports on stroke [ 4 – 6 , 21 ], we hypothesized that chronic stroke patients with unilateral subcortical lesions would show distance-dependent FCD changes in motor and non-motor brain regions, such as sensorimotor cortex, frontoparietal cortex, and cerebellum, which would correlate with the motor function of the patients and might serve as potential biomarkers to predict motor outcome after stroke. Methods Participants A cohort of sixty-four patients who had suffered from a unilateral chronic stroke and forty-one HCs were initially recruited from the Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University and local community. The study was structured into two components: a cross-sectional investigation involving fifty-four patients and all HCs, and a longitudinal experiment with ten patients. The inclusion criteria for stroke patients were as follows: (1) confirmation of first-episode, unilateral, subcortical stroke using CT or MRI; (2) age > 18 years; (3) right-handedness prior to the stroke event; (4) stroke duration > three months; and (5) normal or corrected-to-normal hearing and vision. Patients were excluded if they met any of the following conditions: (1) contraindication for MRI; (2) coexistence of neuropsychiatric disorders other than stroke, including but not limited to anxiety disorders, major depressive disorders, schizophrenia, and bipolar disorder; (3) unstable medical conditions, such as severe atrial fibrillation; (4) prior exposure to transcranial electromagnetic and ultrasound stimulation; and (5) a history of tobacco, alcohol, or other drug addiction. The unilateral stroke patient cohort in cross-sectional dataset was further subdivided into two subgroups based on the location of the subcortical lesion: left subcortical stroke (LSS) and right subcortical stroke (RSS) groups. As for the inclusion criteria for the HCs group, participants were required to satisfy the following conditions: (1) closely matched age and educational levels with the stroke patient cohort, and (2) right-handedness. Exclusion criteria for the HCs group entailed the presence of (1) noticeable physical or neuropsychiatric disorders and (2) a history of tobacco, alcohol, or other drug addiction. Following the exclusion of nine participants due to incomplete MRI scans (three LSS patients, two RSS patients, and two HCs) and the presence of excessive head motion (two LSS patients, as elaborated in the Data preprocessing), a final cohort of twenty-five LSS patients, twenty-two RSS patients, and thirty-nine HCs constituted the cross-sectional dataset for subsequent analysis. A post-hoc power analysis was calculated for a one-way analysis of covariance (ANCOVA) using the G*Power tool. With an effect size of 0.5, α set at 0.05, a total sample size of 86 participants, and three groups under consideration, the power (1 - β ) stood at 0.95. Moreover, the sample size in the current study was also similar to those reported in the previous studies investigating functional reorganization after stroke [ 22 , 23 ]. For the longitudinal dataset, seven patients were included in the subsequent analysis because three patients failed to complete the second MRI scans. Behavioral instruments Before MRI scanning, each stroke patient underwent evaluations of motor performance and activities of daily living (ADL) utilizing the Fugl-Meyer Assessment (FMA) and the Chinese version of Modified Barthel Index (MBI-C), respectively. For non-acute stroke patients, achieving a score of 9 (sensitivity: 80.39%, specificity: 70%) up to 10 (sensitivity: 97.62%, specificity: 89.66%) on the FMA Upper Extremity (FMA-UE) scale indicates a higher likelihood of experiencing clinical improvement in disability [ 24 ]. Furthermore, the FMA Lower Extremity (FMA-LE) scale demonstrates commendable sensitivity (0.87) and specificity (0.81) in differentiating levels of lower extremity function among chronic stroke survivors [ 25 ]. The MBI-C measures the ADL of stroke survivors and can be categorized into functional performance and physiological needs. Notably, the MBI-C exhibits comparable validity and reliability to the original version at the item level, with kappa statistics ranging from 0.63 to 1.00 [ 26 ]. It is noteworthy that seven patients in the longitudinal dataset underwent two identical behavioral assessments with an averaged interval of twenty days, during which the patients received routine rehabilitation treatments, such as physical and/or occupational therapy. MRI data acquisition All MRI data were acquired at a 3.0 T MRI scanner (Philips Healthcare, Netherlands). Resting-state fMRI was scanned using an echo-planar imaging (EPI) sequence with the following parameters: repetition time (TR) = 2000 ms, echo time (TE) = 30 ms, matrix = 64 × 64, slice thickness = 4 mm, field of view = 192 mm × 192 mm, voxel size = 3 mm × 3 mm × 4 mm, flip angle = 90°, 38 axial slices, 230 volumes, and scan time = 8 min 08 s. Furthermore, three-dimensional high-resolution T1-weighted images were obtained using a three-dimensional fast field-echo sequence with the following parameters: TR = 9.9 ms, TE = 4.6 ms, matrix = 256 × 256, slice thickness = 1 mm, field of view = 256 mm × 256 mm, 192 sagittal slices, voxel size = 1 mm × 1 mm × 1 mm, flip angle = 8°, and scan time = 6 min 47 s. Additionally, T2-weighted images were collected using a MultiVane sequence with the following parameters: TR = 4,000 ms, TE = 91 ms, matrix = 230 × 230, slice thickness = 5 mm, field of view = 230 mm × 230 mm, 30 axial slices, voxel size = 1 mm × 1 mm× 5 mm, flip angle = 90°, and scan time = 1 min 4 s. Notably, seven patients in the longitudinal dataset underwent two MRI scans with an averaged interval of twenty days. Lesion overlap analysis Using MRIcron software ( https://www.nitrc.org/projects/mricron ), two physicians, who were blinded to the clinical data, determined the lesion outline on T2-weighted images for each stroke patient. Then, the lesion masks of all stroke patients were normalized to the MNI space based on the EPI template. Finally, all the normalized lesion masks were summed to generate a lesion overlap map within each patient subgroup. The group-level lesion overlap map and the precise lesion locations for each patient are displayed in Fig. 1 and Supplementary Materials ( Supplementary Fig. 1 ), respectively. [Insert Fig. 1 here] Data preprocessing Resting-state fMRI data were preprocessed using the Advanced Data Processing Assistant for Resting-State fMRI (DPARSF) software ( http://rfmri.org/DPARSF ) [ 27 ]. The preprocessing procedure included the following steps: (1) removal of the first 10 volumes; (2) slice-timing correction; (3) head motion correction, with the exclusion of two LSS patients who exhibited excessive motion exceeding 2.5 mm of translation or greater than 2.5 degrees of rotation in any direction; (4) regression of the linear trend, white matter and cerebrospinal fluid signals, and the 24 head motion parameters [ 28 ]; (5) spatial normalization using a diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL) method, and resampled every 3 mm; (6) spatial smoothing with a full width at a half maximum (FWHM) = 6 mm, and (7) temporal bandpass filtering (0.01–0.1 Hz). Distance-dependent FCD analysis To explore the effect of distance on functional connections, the three-dimensional anatomical distance between every pair of voxels ( i and j ) was approximated using the Euclidean distance: $${D}_{ij}= \sqrt{{({x}_{i}-{x}_{j})}^{2}+{({y}_{i}-{y}_{j})}^{2}+{({z}_{i}-{z}_{j})}^{2}}$$ where (x i , y i , z i ) and (x j , y j , z j ) are stereotaxic coordinates for voxels i and j , respectively, in the MNI space. The FCD of a voxel indicates the average strength of its functional connection with all other voxels. The functional connections of each voxel were classified as either short- or long-range based on a distance criterion of 12 mm [ 13 , 29 ]. To improve normality, the FCD maps were converted to z -values using Fisher’s r -to- z transformation. Here, the FCD was calculated using the absolute weighted value of the functional connection. Finally, each subject yielded three z -maps representing global, long-range, and short-range FCD (gFCD/lFCD/sFCD). Statistical analyses Statistical analyses were conducted using the Statistical Package for Social Sciences (SPSS) version 21 for Windows to compare the demographic characteristics and clinical assessments between LSS, RSS, and HCs in the cross-sectional dataset, and between pre- and post-observations in the longitudinal dataset. In the cross-sectional dataset, we first performed ANCOVA analysis to compare differences in FCD values among the three groups, controlling for age, gender, education, and head motion as covariates (with Gaussian Random Field (GRF) correction, voxel-level P < 0.01, and cluster-level P < 0.05, two-tailed). Then, post-hoc two-sample t -tests were conducted to explore differences between all paired groups. Moreover, a linear regression analysis was employed to assess the relationship between the FCD values and the scores on clinical assessments (FMA-UE, FMA-LE, and MBI-C scales) while controlling for age, gender, education, head motion, and lesion volume in the cross-sectional dataset. This regression analysis was conducted separately for the LSS, RSS, and total patients, with false discovery rate (FDR) correction ( P < 0.05). Validation analysis Considering the relatively small sample size of each group in the current study, we performed three distinct validations as follows: (1) we recalculated the lFCD and sFCD using alternative distance thresholds of 6 mm and 18 mm, respectively; (2) we carried out a leave-one-out cross-validation (LOOCV) methodology [ 30 ]. Specifically, one stroke patient was left out of the sample, and the ANCOVA analysis was performed on permuted datasets (i.e., 24 LSS vs. 22 RSS vs. 39 HC or 25 LSS vs. 21 RSS vs. 39 HC). The LOOCV resulted in a total of 47 F maps, which were then used to compute voxel-wise reproducibility by calculating the number of a voxel that exhibited significant differences among the three groups across 47 ANCOVA tests; and (3) we validated the associations between FCD values and clinical assessments in the longitudinal dataset. Results Demographic characteristics and clinical assessment For the cross-sectional dataset, 9 participants were excluded due to incomplete MRI scans for personal reasons (3 LSS patients, 2 RSS patients, and 2 HCs) and excessive head motion (2 LSS patients). The final analysis included 25 LSS patients, 22 RSS patients, and 39 HCs. These groups were well-matched in age, gender, education level, head motion, and handedness ( P > 0.05). For the longitudinal dataset, 3 patients were excluded from the analysis due to incomplete the second session of MRI scans for personal reasons. The detailed demographic characteristics and clinical assessments for both stroke patients and HCs are presented in Table 1 . Table 1 Demographics and clinical details of the participants. Cross-sectional dataset Longitudinal dataset LSS group ( n = 25) RSS group ( n = 22) HCs group ( n = 39) F/t /χ 2 value P value ( n = 7) Age (years) 57.72 ± 10.68 54.55 ± 9.15 57.90 ± 8.50 1.01 0.37 a 52.43 ± 6.53 Gender (male: female, n ) 22 : 3 19 : 3 35 : 4 0.16 0.92 b 6 : 1 Education (years) 10.40 ± 2.77 9.86 ± 2.75 9.92 ± 3.40 0.24 0.79 a 11.29 ± 3.09 Hand dominance right-side right-side right-sided - - right-sided Duration of illness (months) 13.47 ± 10.32 14.02 ± 10.62 - -0.18 0.86 a 14.86 ± 12.62 Lesion volume (ml) 2.58 ± 1.92 3.39 ± 3.59 - -0.97 0.34 a 3.92 ± 4.68 (pre) 3.70 ± 4.86 (post) Head motion (mm) 0.17 ± 0.18 0.14 ± 0.08 0.13 ± 0.11 0.82 0.44 a 0.11 ± 0.04 (pre) 0.12 ± 0.05 (post) FMA-UE 44.40 ± 19.18 46.59 ± 17.44 - -0.41 0.69 a 31.43 ± 9.54 (pre) 36.14 ± 10.89 (post) FMA-LE 27.96 ± 5.41 27.68 ± 6.82 - 0.16 0.88 a 29.29 ± 3.73 (pre) 31.00 ± 2.94 (post) MBI-C 79.20 ± 22.17 87.73 ± 14.41 - -1.58 0.12 a 72.86 ± 5.31 (pre) 76.57 ± 5.32 (post) Note: a ANOVA for three groups and Independent t -test for two groups in cross-sectional study, b Chi-square test in cross-sectional study. LSS, left subcortical stroke; RSS, right subcortical stroke; HCs, healthy controls; FMA-UE, Fugl-Meyer Assessment of upper extremity; FMA-LE, Fugl-Meyer Assessment of lower extremity; MBI-C, the Chinese version of Modified Barthel Index. [Insert Table 1 here] Disrupted distance-related FCD in the stroke groups Figure 2 A displays the mean FCD maps for each group. At the whole-brain level, the LSS group exhibited significantly higher mean values of gFCD ( P = 0.001, Cohen's d = 0.89), lFCD ( P = 0.001, Cohen's d = 0.89), and sFCD ( P = 0.002, Cohen's d = 0.83) compared to the HCs ( Supplementary Fig. 2 ). However, no significant differences in the three FCD values were found between other paired groups ( P > 0.05). At the voxel level, the ANCOVA analysis showed significant group differences in the left IFG and bilateral supplementary motor gyrus (SMA) for both gFCD and lFCD (Table 2 and Fig. 2 B), and in the left IFG, bilateral CPL, left middle occipital gyrus (MOG), and bilateral cerebellum anterior lobe (CAL) for sFCD (Table 2 and Fig. 2 B). Post-hoc analyses subsequently revealed that both the LSS and RSS groups exhibited significantly increased gFCD and lFCD values in the left IFG and bilateral SMA when compared to the HCs (Fig. 3 A, |Cohen's d|> 0.8 in Table 2 ). Moreover, both the LSS and RSS groups demonstrated increased sFCD values in the left IFG and PreCG, and decreased sFCD values in the bilateral CPL, left MOG, and bilateral CAL, in comparison to the HCs (Fig. 3 A, |Cohen's d|> 0.8 in Table 2 ). However, no significant differences in gFCD, lFCD, or sFCD values were observed when comparing the two patient subgroups (Table 2 ). Collectively, the analyses revealed that the left IFG showed distance-independent FCD alteration, while bilateral SMA, CAL, CPL, and left MOG exhibited distance-dependent FCD alterations in stroke patients. Table 2 Regions showing significant differences in gFCD, lFCD, and sFCD among LSS, RSS, and HCs. Regions Hemisphere MNI coordinates Cluster size F value LSS vs. HCs RSS vs. HCs LSS vs. RSS x y z t value Cohen’ d t value Cohen’ d t value Cohen’ d gFCD Inferior frontal gyrus Left -45 27 3 39 11.29 4.61*** 1.23 4.54*** 1.17 0.50 0.15 Supplementary motor area Bilateral 9 3 72 23 9.29 3.96*** 1.02 4.24*** 1.15 -0.32 -0.09 lFCD Inferior frontal gyrus Left -45 27 3 39 11.31 4.62*** 1.23 4.53*** 1.17 0.51 0.15 Supplementary motor area Bilateral 9 3 72 22 9.27 3.98*** 1.02 4.25*** 1.15 -0.31 -0.09 sFCD Cerebellum posterior lobe Bilateral 0 -54 -51 73 14.33 -3.77*** -0.99 -3.74*** -1.05 0.03 0.01 Inferior frontal gyrus Left -45 18 12 57 16.24 6.11*** 1.57 4.43*** 1.17 1.19 0.35 Precentral gyrus Left 27 Middle occipital gyrus Left -24 -93 12 69 10.47 -3.84*** -0.99 -4.14*** -1.10 0.63 0.19 Cerebellum anterior lobe Bilateral 3 -33 -21 37 12.39 -4.19*** -1.10 -3.67** -0.91 -1.11 -0.33 Note: MNI, Montreal Neurological Institute; LSS, left subcortical stroke; RSS, right subcortical stroke; HCs, healthy controls; gFCD, global functional connectivity density; lFCD, long-range functional connectivity density; sFCD, short-range functional connectivity density. *, 0.01 < P < 0.05; **, 0.001 < P < 0.01; ***, P < 0.001. [Insert Table 2 , Fig. 2 , and Fig. 3 here] Association of functional reorganization with motor outcomes The sFCD in the left IFG showed negative correlations with FMA-UE ( β = -0.007, adjusted P = 0.024) and FMA-LE ( β = -0.025, adjusted P = 0.006) scores, and both gFCD ( β = -0.011, adjusted P = 0.130) and lFCD ( β = -0.011, adjusted P = 0.130) in this region negatively correlated with FMA-UE score across all stroke patients (Table 3 and Fig. 3 B). Furthermore, positive correlations were observed between gFCD ( β = 0.040, adjusted P = 0.042) and lFCD ( β = 0.040, adjusted P = 0.042) in the bilateral SMA and the FMA-LE scores across all stroke patients (Table 3 and Fig. 3 B). There were no significant correlations between the FCD and the motor outcomes in LSS or RSS group (adjusted P > 0.05, Table 3 ). More importantly, the significant correlations aforementioned were validated by a longitudinal dataset. After routine intervention, the scores of upper/lower extremities increased in all patients, while FMA-UE-related FCD in the IFG decreased in > 4/7 of patients ( Fig. 4 A ) and FMA-LE-related FCD in the SMA decreased in > 5/7 of patients (Fig. 4 B). Table 3 Correlations between FCD values and motor-related outcomes across all post-stroke patients. FMA-UE Regions Feature β R 2 t P Adjusted P Left IFG gFCD -0.011 0.202 -2.152 0.038 0.130 Bilateral SMA gFCD 0.008 0.202 1.804 0.079 0.157 Left IFG lFCD -0.011 0.202 -2.154 0.037 0.130 Bilateral SMA lFCD 0.008 0.199 1.826 0.075 0.157 Bilateral CPL sFCD 0.005 0.279 1.435 0.159 0.254 Left IFG sFCD -0.007 0.465 -3.301 0.002 0.024 Left MOG sFCD 0.235 0.189 1.028 0.310 0.465 Bilateral CAL sFCD -0.900 0.134 1.717 0.094 0.161 FMA-LE Left IFG gFCD -0.031 0.181 -1.868 0.069 0.157 Bilateral SMA gFCD 0.040 0.282 2.844 0.007 0.042 Left IFG lFCD -0.031 0.180 -1.867 0.069 0.157 Bilateral SMA lFCD 0.040 0.280 2.286 0.007 0.042 Bilateral CPL sFCD 0.010 0.257 0.906 0.370 0.522 Left IFG sFCD -0.025 0.517 -4.035 < 0.001 0.006 Left MOG sFCD 0.002 0.169 0.317 0.753 0.786 Bilateral CAL sFCD 0.009 0.083 0.740 0.464 0.554 MBI-C Left IFG gFCD -0.009 0.174 -1.764 0.085 0.157 Bilateral SMA gFCD 0.003 0.148 0.704 0.485 0.554 Left IFG lFCD -0.009 0.174 -1.768 0.085 0.1569 Bilateral SMA lFCD 0.003 0.144 0.712 0.481 0.554 Bilateral CPL sFCD 0.001 0.245 0.395 0.695 0.758 Left IFG sFCD -0.005 0.413 -2.516 0.016 0.077 Left MOG sFCD < 0.001 0.167 0.101 0.920 0.920 Bilateral CAL sFCD 0.003 0.087 0.862 0.394 0.525 Note: FMA-UE, Fugl-Meyer Assessment Upper Extremity Scale; FMA-LE, Fugl-Meyer Assessment Lower Extremity Scal; MBI-C,the Chinese version of Modified Barthel Index; IFG, inferior frontal gyrus; SMA, supplementary motor area; CPL, cerebellum posterior lobe; MOG, middle occipital gyrus; CAL, cerebellum anterior lobe; gFCD, global functional connectivity density; lFCD, long-range functional connectivity density; sFCD, short-range functional connectivity density. [Insert Table 3 and Fig. 4 here] Validation results Between-group differences in gFCD, lFCD, and sFCD among LSS, RSS, and HCs under two different distance criteria (6 mm and 18 mm) replicated the primary findings observed under the 12 mm criterion ( Supplementary Table 1 and Supplementary Table 2 ). Namely, the left IFG continued to exhibit distance-dependent FCD alteration, and the bilateral SMA and CPL consistently displayed distance-independent FCD alteration in both patient subgroups compared with HCs. Also, the post-hoc analyses between the two patient subgroups and HCs showed large effect sizes, with |Cohen's d| > 0.8 ( Supplementary Table 1 and Supplementary Table 2 ). Moreover, the LOOCV indicated the high reproducibility of FCD differences observed among the three groups, as shown in Supplementary Fig. 3 . Distance-related functional reorganizations after unilateral subcortical stroke In summary, both the LSS and RSS consistently showed distance-related FCD changes. Specifically, the left IFG displayed distance-independent FCD alterations, whereas the bilateral SMA, CAL, CPL, and left MOG exhibited distance-dependent FCD alterations. Considering the correlations between FCD and motor outcome, the increased FCD in the bilateral SMA may play a compensatory role in the restoration of motor function in the paralyzed lower limbs of stroke patients, while the increased FCD in the left IFG may indicate impairment of motor function in both the paralyzed upper and lower limbs of stroke patients. Detailed information is presented in Fig. 5 . [Insert Fig. 5 here] Discussion The present study used the distance-dependent FCD approach to investigate functional alterations in chronic stroke patients following left and right hemisphere subcortical lesions. Our results demonstrated that, compared with HCs, the LSS and RSS groups both exhibited distance-dependent FCD changes, that bilateral SMA showed increased gFCD and lFCD, while bilateral CPL/CAL and left MOG showed reduced sFCD. Interestingly, the left IFG showed a distance-independent FCD increase in both patient subgroups compared to HCs. Moreover, we found significant correlations between the FCD values in the left IFG as well as bilateral SMA and specific motor functions in stroke patients. These findings support our initial hypothesis, suggesting the presence of distance-related functional reorganization in motor and non-motor regions of chronic subcortical stroke, which may serve as valuable biomarkers for predicting motor outcomes in stroke patients. Global FCD alterations after subcortical stroke Numerous studies have utilized gFCD to explore neural activity alterations after stroke. For instance, Min et al. found higher gFCD values in the right parahippocampal gyrus in acute subcortical stroke patients than HCs [ 9 ]. Wang et al. demonstrated that subacute stroke patients with cognitive impairment exhibited significant changes in gFCD, including decreases in language-related brain regions and increases in the right middle frontal gyrus (MFG), hippocampus, and paracentral lobule, in comparison to HCs [ 2 ]. Yao et al. reported decreased gFCD values in right inferior parietal lobule and right PosCG, in subacute stroke patients compared with HCs [ 10 ]. Different from the acute and subacute stroke, the present study found that two chronic stroke subgroups both showed increased gFCD in the bilateral SMA compared with HC. As a dominant region contributing to movement control, the SMA participates in stabilizing body posture and regulating movement sequences [ 31 ]. Previous studies found that the SMA showed higher betweenness centrality [ 32 ] and increased regional homogeneity [ 33 ] in subcortical stroke patients than HCs, indicating a compensatory role of the SMA in response to motor deficits after stroke. Therefore, our findings align with previous reports, and further demonstrated that the SMA plays an important role underlying the functional reorganization in stroke patients. Distance-dependent FCD alterations after subcortical stroke Previous studies have demonstrated that schizophrenia leads to abnormal sFCD rather than the glFCD in the precuneus [ 17 ], and attention-deficit/hyperactivity disorder alters the lFCD but not the sFCD in the left superior parietal gyrus and the right MFG [ 18 ]. Patients with cognitive impairment showed increased lFCD in the left fusiform gyrus and sFCD in the left middle orbital gyrus [ 34 ]. Similarly, such distance-dependent patterns were observed in the present study that the bilateral SMA and left IFG showed increased lFCD, and the bilateral CAL/CPL and left MOG showed decreased sFCD in chronic subcortical stroke patients following left and right hemisphere subcortical lesions compared to HCs. The functional reorganizations in these regions have been reported in stroke patients, who showed decreased regional homogeneity [ 35 ] and interhemispheric connectivity [ 10 ] in the MOG and SMA, as well as increased FC in the CAL [ 32 ] and the CPL [ 36 ] compared to HCs. A recent study found an increased FCD value of the right CPL in stroke patients relative to HCs [ 2 ]. Therefore, the current study further extended the existing knowledge by emphasizing that function reorganization in the frontal-occipital cortex and cerebellum exhibits a distance-dependent pattern following subcortical stroke regardless of the lesion hemisphere. Indeed, lFCD and sFCD reflect the functional integration and specialization of brain networks, respectively [ 15 , 16 , 18 ]. Our findings suggest that chronic subcortical stroke patients exhibit long-range functional plasticity (compensatory effect) in the SMA, while the regional functional plasticity is primarily present in the cerebellum and MOG, highlighting the intricacy and flexibility of functional reorganization during the chronic phase post subcortical stroke. Distance-independent FCD increase in the left IFG after subcortical stroke In addition to its traditional roles in cognitive processes [ 37 ] and speech functions [ 38 ], the IFG assumes a core component in the mirror neuron system [ 39 ], which is closely associated with action observation [ 40 ] and motion imitation [ 41 ]. Furthermore, the IFG has been implicated in specific motor-related processes, including motor imagery [ 42 ] and task execution [ 5 ]. Multiple studies have focused on the functional plasticity of the IFG in stroke patients with motor dysfunction. For instance, Garrison et al. reported cortical activations in the bilateral IFG during hand movement in chronic stroke patients [ 43 ]. Ma et al. found increased activation in the IFG during motor imagery in subacute subcortical stroke patients compared to HCs [ 44 ]. Furthermore, diverse functional alterations in the IFG have been documented in stroke patients. Compared with HCs, stroke patients showed increased FCD in the bilateral inferior frontal-orbital gyrus [ 35 ] and decreased interhemispheric connectivity in the bilateral IFG [ 5 , 10 ]. Consistently, we found increased gFCD, lFCD, and sFCD in the left IFG in chronic subcortical stroke patients with motor impairment, compared to HCs, indicating a distance-independent functional reorganization in this region. Interestingly, our findings remain consistent regardless of the lesion hemisphere, and it should be noted that the patients recruited in our study did not exhibit aphasia. To provide a more comprehensive understanding of the post-stroke functional changes in the left IFG, the present study selected the left IFG as the seed region for a whole-brain FC analysis and found FC alternations between the left IFG and motor-related regions, such as the right PreCG, PosCG, MFG, bilateral middle temporal gyrus, and left precuneus ( Supplementary Fig. 4 and Supplementary Table 3 ), which have previously been implicated in stroke patients [ 5 , 45 ]. Thus, we revealed a reorganization of functional networks with the left IFG as the hub following subcortical stroke, thereby providing evidence for the critical role of left IFG in motor function. Association of FCD changes with motor outcomes Previous studies have reported a positive correlation between voxel-mirrored homotopic connectivity in the IFG and motor function in Parkinson’s disease [ 46 ], and a negative correlation between the lesion size of the left IFG and hand action performance in chronic stroke patients [ 47 ]. Moreover, subacute stroke patients showed significant positive correlations between the variability of amplitude of low-frequency fluctuation in the SMA and total FMA scores [ 48 ], and between betweenness centrality in the SMA and FMA-UE scores [ 49 ]. Chronic stroke patients exhibited a significantly positive correlation between mean brain entropy values in the SMA and total FMA scores [ 50 ]. These findings underscore the close association between functional alterations in the IFG and SMA and motor dysfunction following stroke. The present study found that the sFCD value in the left IFG significantly negatively correlated with the motor function in both upper and lower extremities, while the gFCD and lFCD values in the bilateral SMA significantly positively correlated with the FMA-LE scores. These correlations were also validated by the longitudinal data. Our findings indicate that the increased FCD in the bilateral SMA may function as a compensatory mechanism [ 51 , 52 ] in the recovery of motor function in the paralyzed lower limbs of stroke patients, whereas increased FCD in the left IFG may indicate impairment [ 47 ] in motor function in both the paralyzed upper and lower limbs of stroke patients. Taken together, this suggests that the FCD values in left IFG and bilateral SMA could serve as biomarkers for predicting motor outcomes after stroke. Limitations This study is subject to several limitations warranting consideration. Firstly, the sample sizes of post-stroke patients in both cross-sectional and longitudinal experiments were relatively small. Although our results displayed large effect size and were validated by two distinct methods, a large-sample study needs to verify our findings in the future. Secondly, as all stroke patients exhibit unilateral subcortical lesions, and therefore, the observed patterns of functional reorganization may not necessarily be generalized to patients with other types of brain lesions. Thirdly, there was a pronounced male predominance in the present study. Despite controlling for gender as a nuisance covariate in our statistical analyses, future studies need to maintain an appropriate gender balance to confirm our findings. Last but not least, the cross-sectional design employed in this study did not allow for a conclusion to be drawn on the causes of the functional changes in the left IFG. Therefore, how such changes contribute to motor dysfunction remains speculative. Future studies adopting a prospective design on a larger sample size and multiple brain lesion groups can facilitate a better understanding of the mechanisms underlying motor dysfunction in post-stroke patients without aphasia. Conclusion The current study explored functional alterations in chronic stroke patients following left and right hemisphere subcortical lesions, using the distance-dependent FCD approach. Our results demonstrated that the left IFG exhibited distance-independent FCD changes, while the bilateral SMA, CAL, CPL, and left MOG showed distance-related FCD alterations in stroke patients, regardless of the lesion side. Importantly, our study highlights that these changes in FCD have the potential to predict clinical function, with the correlations between FCD values in the left IFG and bilateral SMA and specific paralyzed motor function in all chronic stroke patients without aphasia. These findings offer additional evidence to comprehend the neurophysiological mechanisms underlying motor dysfunctions following chronic stroke. Abbreviations ADL activities of daily living CAL cerebellum anterior lobe CPL cerebellum posterior lobe FC functional connectivity FCD functional connectivity density FMA Fugl-Meyer Assessment FMA-LE the Fugl-Meyer Assessment Lower Extremity FMA-UE the Fugl-Meyer Assessment Upper Extremity gFCD global-range functional connectivity density HCs healthy controls IFG inferior frontal gyrus lFCD long-range functional connectivity density LOOCV leave-one-out cross-validation LSS left subcortical stroke MBI-C Chinese version of Modified Barthel Index MFG middle frontal gyrus MOG middle occipital gyrus MTG middle temporal gyrus PosCG postcentral gyrus PreCG precentral gyrus RSS right subcortical stroke sFCD short-range functional connectivity density SMA supplementary motor area Declarations Acknowledgments The authors express gratitude to all participants and their families for their contributions which were vital to the success of this work. Authors’ contributions WH, RX, and ZZ conceptualized and supervised the study. WH, ZL, and BY recruited the subjects. WH, ZL, XZ, ML, and ZY assisted in acquiring the fMRI data. ZL and Yuxin Wang contributed to behavioral data collection. WH and ZZ analyzed the data. WH, ZL, Yanan Wu, SF, MW, RX, and ZZ drafted the manuscript. All authors reviewed and approved the final manuscript. Funding This research received support from the Youth Program of the National Natural Science Foundation of China (grant number 82002378), the funding for Clinical Trials from the Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University (grant number 2022-LCYJ-PY-27), and the Medical Science and Technology Development Foundation, Nanjing Department of Health (grant number YKK20068). Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate This study was conducted in accordance with the guidelines of the Helsinki Declaration and was approved by the Ethics Committee of Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University. Prior to participation, written informed consent was obtained from all participants or from their legal guardians when applicable. Consent for publication All authors have read the manuscript and provided consent for publication. Competing interests The authors declare that they have no competing interests. Author details 1 Department of Rehabilitation Medicine, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China 2 Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China 3 School of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China 4 Binjiang Institute of Zhejiang University, Hangzhou 310014, China 5 Department of Rehabilitation Medicine, Nanjing Drum Tower Hospital, School of Medicine, Jiangsu University, Nanjing 210008, China 6 Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, China References Carter AR, Shulman GL, Corbetta M: Why use a connectivity-based approach to study stroke and recovery of function? NeuroImage 2012, 62(4):2271–2280. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3916957","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":270429051,"identity":"7751cfcf-d666-4f2d-8917-6eadda14db68","order_by":0,"name":"Wenjun Hong","email":"","orcid":"https://orcid.org/0000-0002-4298-0153","institution":"Nanjing Drum Tower Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wenjun","middleName":"","lastName":"Hong","suffix":""},{"id":270429209,"identity":"1676288a-23b4-4fa8-8bf4-6f426012bf86","order_by":1,"name":"Zaixing Liu","email":"","orcid":"","institution":"Nanjing Drum Tower 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LSS, left subcortical stroke; RSS, right subcortical stroke.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-3916957/v1/b45bd542c5a3c1e3b6aeb490.png"},{"id":50570137,"identity":"b1f0497a-b158-4c0a-8c3c-272cb56cf412","added_by":"auto","created_at":"2024-02-02 15:42:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4384492,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFCD maps in each group and their differences among three groups. \u003c/strong\u003eA represents mean FCD map in each group and B represents significant differences in FCD among LSS, RSS, and HCs.\u003cstrong\u003e \u003c/strong\u003eLSS, left subcortical stroke; RSS, right subcortical stroke; gFCD, global functional connectivity density; lFCD, long-range functional connectivity density; sFCD, short-range functional connectivity density; SMA, supplementary motor area; IFG, inferior frontal gyrus; CPL, cerebellum posterior lobe; MOG, middle occipital gyrus; CAL, cerebellum anterior lobe.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-3916957/v1/f7059b7f34d566afc9363576.png"},{"id":50569771,"identity":"c2a72c3f-738c-4f7b-89d9-41328fd45aa2","added_by":"auto","created_at":"2024-02-02 15:34:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1488148,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSignificant differences between LSS/RSS and HCs in FCD and their correlations with motor performance. \u003c/strong\u003eA represents regions showing significant differences among LSS, RSS, and HCs and B represents correlations between altered FCD patterns and hemiplegic motor performance across all stroke patients.\u003cstrong\u003e \u003c/strong\u003eLSS, left subcortical stroke; RSS, right subcortical stroke; gFCD, global functional connectivity density; lFCD, long-range functional connectivity density; sFCD, short-range functional connectivity density; SMA, supplementary motor area; IFG, inferior frontal gyrus; CPL, cerebellum posterior lobe; MOG, middle occipital gyrus; CAL, cerebellum anterior lobe; FMA-UE, Fugl-Meyer Assessment Upper Extremity Scale; FMA-LE, Fugl-Meyer Assessment Lower Extremity Scale. *, 0.01\u0026lt; \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; **, 0.001\u0026lt; \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; ***, \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001; ns, not significant.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-3916957/v1/689dddf4e1abfe5505284a04.png"},{"id":50569770,"identity":"0f988c8c-db69-4e30-8228-3be1e2546b5c","added_by":"auto","created_at":"2024-02-02 15:34:30","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":509931,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe changes of FCD and motor outcome in stroke patients after routine intervention\u003c/strong\u003e. A represents the FCD alterations related to FMA-UE and B represents the FCD alterations related to FMA-LE. IFG, inferior frontal gyrus; SMA, supplementary motor area; gFCD, global functional connectivity density; lFCD, long-range functional connectivity density; sFCD, short-range functional connectivity density; FMA-UE, Fugl-Meyer Assessment Upper Extremity Scale; FMA-LE, Fugl-Meyer Assessment Lower Extremity Scale.\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-3916957/v1/cec505611e7f7a626c40874f.png"},{"id":50569773,"identity":"a30f8178-89df-42cd-877b-6ce6932cb060","added_by":"auto","created_at":"2024-02-02 15:34:31","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":515297,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistance-related cortical functional reorganization after subcortical stroke. \u003c/strong\u003eFCD, functional connectivity density; SMA, supplementary motor area; IFG, inferior frontal gyrus; CPL, cerebellum posterior lobe; MOG, middle occipital gyrus; CAL, cerebellum anterior lobe. Created with BioRender.com.\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-3916957/v1/6f653e71c59a0cfb612ea3f2.png"},{"id":58530700,"identity":"c5942d48-b849-4c37-a690-c065567b4e85","added_by":"auto","created_at":"2024-06-18 00:34:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":13780397,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3916957/v1/9cfbd2d2-1215-46f7-b038-ba5ef4aa7fb7.pdf"},{"id":50569772,"identity":"f40ce06d-4283-45a4-81eb-91e3659ac053","added_by":"auto","created_at":"2024-02-02 15:34:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3111190,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary material is available at \u003cem\u003eBMC Medicine online.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-3916957/v1/2c96f0e8465155f429d5c909.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDistance-related functional reorganization predicts motor outcome in stroke patients\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eDuring the chronic stroke stage, survivors continue to undergo a dynamic process of functional reorganization associated with post-stroke recovery [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Resting-state fMRI (rs-fMRI) has emerged as a promising avenue to explore brain functional integration and separation after stroke [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Our prior rs-fMRI studies found decreased functional connectivity (FC) between hippocampal subfields and left postcentral gyrus (PosCG) as well as right middle occipital gyrus (MOG) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], between cerebellum posterior lobe and left precentral gyrus (PreCG), inferior frontal gyrus (IFG) as well as middle temporal gyrus [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], and increased FC from the ipsilesional M1 to the ipsilesional occipital lobes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] in chronic stroke patients compared with healthy controls (HCs). However, the FC analysis needs a predefined selection of regions of interest, which is a challenging issue in neuroimaging. To overcome this limitation, a data-driven analysis called functional connectivity density (FCD) mapping was proposed, treating each voxel as a seed and calculating the number of connections it holds with other voxels, thereby indirectly elucidating the spatial distribution and importance of brain regions within the whole brain [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Thus, the FCD provides an unbiased search of functional connectome abnormalities within the whole brain without prior hypothesis [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This method has been used to detect functional reorganization patterns across diverse diseases, such as stroke [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], depression [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and Parkinson\u0026rsquo;s disease [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIncreasing evidence has indicated that the FC between brain regions is closely associated with their anatomical locations [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Recent studies divided the FCD into short-range FCD (sFCD) and long-range FCD (lFCD) based on a distance criterion [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], representing functional specialization and integration of brain networks, respectively [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This approach has identified distance-dependent FCD alterations in neuropsychiatric disorders. For instance, a schizophrenia study revealed a significant interaction between genotype and diagnosis in the sFCD but not in the lFCD [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Another study found altered lFCD, but not altered sFCD, in the frontoparietal areas in children with attention-deficit/hyperactivity disorder [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The bipolar disorder patients showed a positive correlation between increased sFCD in the left fusiform gyrus and depressive episodes and a negative correlation between decreased lFCD in the left angular gyrus and depressive severity [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The major depressive patients displayed significantly negative correlations between decreased sFCD in the left PreCG/PosCG and depressive severity, which were not observed in the lFCD [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, previous FCD studies in stroke have not accounted for the effect of distance on functional reorganization, and it still remains unclear whether the FCD shows distance-dependent alterations in chronic stroke patients.\u003c/p\u003e \u003cp\u003eThe present study aimed to explore whether the functional organization in cerebral and cerebellar cortices correlates with the spatial distances between brain regions in chronic stroke patients following left and right hemisphere subcortical lesions using the FCD approach. Based on the prior reports on stroke [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], we hypothesized that chronic stroke patients with unilateral subcortical lesions would show distance-dependent FCD changes in motor and non-motor brain regions, such as sensorimotor cortex, frontoparietal cortex, and cerebellum, which would correlate with the motor function of the patients and might serve as potential biomarkers to predict motor outcome after stroke.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003e A cohort of sixty-four patients who had suffered from a unilateral chronic stroke and forty-one HCs were initially recruited from the Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University and local community. The study was structured into two components: a cross-sectional investigation involving fifty-four patients and all HCs, and a longitudinal experiment with ten patients. The inclusion criteria for stroke patients were as follows: (1) confirmation of first-episode, unilateral, subcortical stroke using CT or MRI; (2) age\u0026thinsp;\u0026gt;\u0026thinsp;18 years; (3) right-handedness prior to the stroke event; (4) stroke duration\u0026thinsp;\u0026gt;\u0026thinsp;three months; and (5) normal or corrected-to-normal hearing and vision. Patients were excluded if they met any of the following conditions: (1) contraindication for MRI; (2) coexistence of neuropsychiatric disorders other than stroke, including but not limited to anxiety disorders, major depressive disorders, schizophrenia, and bipolar disorder; (3) unstable medical conditions, such as severe atrial fibrillation; (4) prior exposure to transcranial electromagnetic and ultrasound stimulation; and (5) a history of tobacco, alcohol, or other drug addiction. The unilateral stroke patient cohort in cross-sectional dataset was further subdivided into two subgroups based on the location of the subcortical lesion: left subcortical stroke (LSS) and right subcortical stroke (RSS) groups. As for the inclusion criteria for the HCs group, participants were required to satisfy the following conditions: (1) closely matched age and educational levels with the stroke patient cohort, and (2) right-handedness. Exclusion criteria for the HCs group entailed the presence of (1) noticeable physical or neuropsychiatric disorders and (2) a history of tobacco, alcohol, or other drug addiction.\u003c/p\u003e \u003cp\u003eFollowing the exclusion of nine participants due to incomplete MRI scans (three LSS patients, two RSS patients, and two HCs) and the presence of excessive head motion (two LSS patients, as elaborated in the Data preprocessing), a final cohort of twenty-five LSS patients, twenty-two RSS patients, and thirty-nine HCs constituted the cross-sectional dataset for subsequent analysis. A \u003cem\u003epost-hoc\u003c/em\u003e power analysis was calculated for a one-way analysis of covariance (ANCOVA) using the G*Power tool. With an effect size of 0.5, \u003cem\u003eα\u003c/em\u003e set at 0.05, a total sample size of 86 participants, and three groups under consideration, the power (1 - \u003cem\u003eβ\u003c/em\u003e) stood at 0.95. Moreover, the sample size in the current study was also similar to those reported in the previous studies investigating functional reorganization after stroke [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. For the longitudinal dataset, seven patients were included in the subsequent analysis because three patients failed to complete the second MRI scans.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eBehavioral instruments\u003c/h2\u003e \u003cp\u003eBefore MRI scanning, each stroke patient underwent evaluations of motor performance and activities of daily living (ADL) utilizing the Fugl-Meyer Assessment (FMA) and the Chinese version of Modified Barthel Index (MBI-C), respectively. For non-acute stroke patients, achieving a score of 9 (sensitivity: 80.39%, specificity: 70%) up to 10 (sensitivity: 97.62%, specificity: 89.66%) on the FMA Upper Extremity (FMA-UE) scale indicates a higher likelihood of experiencing clinical improvement in disability [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Furthermore, the FMA Lower Extremity (FMA-LE) scale demonstrates commendable sensitivity (0.87) and specificity (0.81) in differentiating levels of lower extremity function among chronic stroke survivors [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The MBI-C measures the ADL of stroke survivors and can be categorized into functional performance and physiological needs. Notably, the MBI-C exhibits comparable validity and reliability to the original version at the item level, with kappa statistics ranging from 0.63 to 1.00 [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is noteworthy that seven patients in the longitudinal dataset underwent two identical behavioral assessments with an averaged interval of twenty days, during which the patients received routine rehabilitation treatments, such as physical and/or occupational therapy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMRI data acquisition\u003c/h2\u003e \u003cp\u003eAll MRI data were acquired at a 3.0 T MRI scanner (Philips Healthcare, Netherlands). Resting-state fMRI was scanned using an echo-planar imaging (EPI) sequence with the following parameters: repetition time (TR)\u0026thinsp;=\u0026thinsp;2000 ms, echo time (TE)\u0026thinsp;=\u0026thinsp;30 ms, matrix\u0026thinsp;=\u0026thinsp;64 \u0026times; 64, slice thickness\u0026thinsp;=\u0026thinsp;4 mm, field of view\u0026thinsp;=\u0026thinsp;192 mm \u0026times; 192 mm, voxel size\u0026thinsp;=\u0026thinsp;3 mm \u0026times; 3 mm \u0026times; 4 mm, flip angle\u0026thinsp;=\u0026thinsp;90\u0026deg;, 38 axial slices, 230 volumes, and scan time\u0026thinsp;=\u0026thinsp;8 min 08 s. Furthermore, three-dimensional high-resolution T1-weighted images were obtained using a three-dimensional fast field-echo sequence with the following parameters: TR\u0026thinsp;=\u0026thinsp;9.9 ms, TE\u0026thinsp;=\u0026thinsp;4.6 ms, matrix\u0026thinsp;=\u0026thinsp;256 \u0026times; 256, slice thickness\u0026thinsp;=\u0026thinsp;1 mm, field of view\u0026thinsp;=\u0026thinsp;256 mm \u0026times; 256 mm, 192 sagittal slices, voxel size\u0026thinsp;=\u0026thinsp;1 mm \u0026times; 1 mm \u0026times; 1 mm, flip angle\u0026thinsp;=\u0026thinsp;8\u0026deg;, and scan time\u0026thinsp;=\u0026thinsp;6 min 47 s. Additionally, T2-weighted images were collected using a MultiVane sequence with the following parameters: TR\u0026thinsp;=\u0026thinsp;4,000 ms, TE\u0026thinsp;=\u0026thinsp;91 ms, matrix\u0026thinsp;=\u0026thinsp;230 \u0026times; 230, slice thickness\u0026thinsp;=\u0026thinsp;5 mm, field of view\u0026thinsp;=\u0026thinsp;230 mm \u0026times; 230 mm, 30 axial slices, voxel size\u0026thinsp;=\u0026thinsp;1 mm \u0026times; 1 mm\u0026times; 5 mm, flip angle\u0026thinsp;=\u0026thinsp;90\u0026deg;, and scan time\u0026thinsp;=\u0026thinsp;1 min 4 s. Notably, seven patients in the longitudinal dataset underwent two MRI scans with an averaged interval of twenty days.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eLesion overlap analysis\u003c/h2\u003e \u003cp\u003eUsing MRIcron software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nitrc.org/projects/mricron\u003c/span\u003e\u003cspan address=\"https://www.nitrc.org/projects/mricron\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), two physicians, who were blinded to the clinical data, determined the lesion outline on T2-weighted images for each stroke patient. Then, the lesion masks of all stroke patients were normalized to the MNI space based on the EPI template. Finally, all the normalized lesion masks were summed to generate a lesion overlap map within each patient subgroup. The group-level lesion overlap map and the precise lesion locations for each patient are displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Supplementary Materials (\u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e), respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e[Insert Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e here]\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData preprocessing\u003c/h2\u003e \u003cp\u003eResting-state fMRI data were preprocessed using the \u003cem\u003eAdvanced\u003c/em\u003e Data Processing Assistant for Resting-State fMRI (DPARSF) software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://rfmri.org/DPARSF\u003c/span\u003e\u003cspan address=\"http://rfmri.org/DPARSF\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The preprocessing procedure included the following steps: (1) removal of the first 10 volumes; (2) slice-timing correction; (3) head motion correction, with the exclusion of two LSS patients who exhibited excessive motion exceeding 2.5 mm of translation or greater than 2.5 degrees of rotation in any direction; (4) regression of the linear trend, white matter and cerebrospinal fluid signals, and the 24 head motion parameters [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]; (5) spatial normalization using a diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL) method, and resampled every 3 mm; (6) spatial smoothing with a full width at a half maximum (FWHM)\u0026thinsp;=\u0026thinsp;6 mm, and (7) temporal bandpass filtering (0.01\u0026ndash;0.1 Hz).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDistance-dependent FCD analysis\u003c/h2\u003e \u003cp\u003eTo explore the effect of distance on functional connections, the three-dimensional anatomical distance between every pair of voxels (\u003cem\u003ei\u003c/em\u003e and \u003cem\u003ej\u003c/em\u003e) was approximated using the Euclidean distance:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$${D}_{ij}= \\sqrt{{({x}_{i}-{x}_{j})}^{2}+{({y}_{i}-{y}_{j})}^{2}+{({z}_{i}-{z}_{j})}^{2}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere (x\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e, y\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e, z\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e) and (x\u003csub\u003ej\u003c/sub\u003e, y\u003csub\u003ej\u003c/sub\u003e, z\u003csub\u003ej\u003c/sub\u003e) are stereotaxic coordinates for voxels \u003cem\u003ei\u003c/em\u003e and \u003cem\u003ej\u003c/em\u003e, respectively, in the MNI space. The FCD of a voxel indicates the average strength of its functional connection with all other voxels. The functional connections of each voxel were classified as either short- or long-range based on a distance criterion of 12 mm [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. To improve normality, the FCD maps were converted to \u003cem\u003ez\u003c/em\u003e-values using Fisher\u0026rsquo;s \u003cem\u003er\u003c/em\u003e-to-\u003cem\u003ez\u003c/em\u003e transformation. Here, the FCD was calculated using the absolute weighted value of the functional connection. Finally, each subject yielded three \u003cem\u003ez\u003c/em\u003e-maps representing global, long-range, and short-range FCD (gFCD/lFCD/sFCD).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eStatistical analyses were conducted using the Statistical Package for Social Sciences (SPSS) version 21 for Windows to compare the demographic characteristics and clinical assessments between LSS, RSS, and HCs in the cross-sectional dataset, and between pre- and post-observations in the longitudinal dataset.\u003c/p\u003e \u003cp\u003eIn the cross-sectional dataset, we first performed ANCOVA analysis to compare differences in FCD values among the three groups, controlling for age, gender, education, and head motion as covariates (with Gaussian Random Field (GRF) correction, voxel-level \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, and cluster-level \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, two-tailed). Then, \u003cem\u003epost-hoc\u003c/em\u003e two-sample \u003cem\u003et\u003c/em\u003e-tests were conducted to explore differences between all paired groups. Moreover, a linear regression analysis was employed to assess the relationship between the FCD values and the scores on clinical assessments (FMA-UE, FMA-LE, and MBI-C scales) while controlling for age, gender, education, head motion, and lesion volume in the cross-sectional dataset. This regression analysis was conducted separately for the LSS, RSS, and total patients, with false discovery rate (FDR) correction (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eValidation analysis\u003c/h2\u003e \u003cp\u003eConsidering the relatively small sample size of each group in the current study, we performed three distinct validations as follows: (1) we recalculated the lFCD and sFCD using alternative distance thresholds of 6 mm and 18 mm, respectively; (2) we carried out a leave-one-out cross-validation (LOOCV) methodology [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Specifically, one stroke patient was left out of the sample, and the ANCOVA analysis was performed on permuted datasets (i.e., 24 LSS vs. 22 RSS vs. 39 HC or 25 LSS vs. 21 RSS vs. 39 HC). The LOOCV resulted in a total of 47 \u003cem\u003eF\u003c/em\u003e maps, which were then used to compute voxel-wise reproducibility by calculating the number of a voxel that exhibited significant differences among the three groups across 47 ANCOVA tests; and (3) we validated the associations between FCD values and clinical assessments in the longitudinal dataset.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eDemographic characteristics and clinical assessment\u003c/h2\u003e\n \u003cp\u003eFor the cross-sectional dataset, 9 participants were excluded due to incomplete MRI scans for personal reasons (3 LSS patients, 2 RSS patients, and 2 HCs) and excessive head motion (2 LSS patients). The final analysis included 25 LSS patients, 22 RSS patients, and 39 HCs. These groups were well-matched in age, gender, education level, head motion, and handedness (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). For the longitudinal dataset, 3 patients were excluded from the analysis due to incomplete the second session of MRI scans for personal reasons. The detailed demographic characteristics and clinical assessments for both stroke patients and HCs are presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDemographics and clinical details of the participants.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eCross-sectional dataset\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eLongitudinal dataset\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLSS group\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRSS group\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHCs group\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF/t\u003c/em\u003e/\u0026chi;\u003csup\u003e2\u003c/sup\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.72\u0026thinsp;\u0026plusmn;\u0026thinsp;10.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.55\u0026thinsp;\u0026plusmn;\u0026thinsp;9.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.90\u0026thinsp;\u0026plusmn;\u0026thinsp;8.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.37 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e52.43\u0026thinsp;\u0026plusmn;\u0026thinsp;6.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender (male: female, \u003cem\u003en\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 : 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 : 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 : 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e6 : 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducation (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.40\u0026thinsp;\u0026plusmn;\u0026thinsp;2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.86\u0026thinsp;\u0026plusmn;\u0026thinsp;2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.92\u0026thinsp;\u0026plusmn;\u0026thinsp;3.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.79 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e11.29\u0026thinsp;\u0026plusmn;\u0026thinsp;3.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHand dominance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eright-side\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eright-side\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eright-sided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eright-sided\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDuration of illness (months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.47\u0026thinsp;\u0026plusmn;\u0026thinsp;10.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.02\u0026thinsp;\u0026plusmn;\u0026thinsp;10.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.86 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e14.86\u0026thinsp;\u0026plusmn;\u0026thinsp;12.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLesion volume (ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;3.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.34 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.92\u0026thinsp;\u0026plusmn;\u0026thinsp;4.68 (pre)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.70\u0026thinsp;\u0026plusmn;\u0026thinsp;4.86 (post)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHead motion (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.44 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04 (pre)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 (post)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFMA-UE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.40\u0026thinsp;\u0026plusmn;\u0026thinsp;19.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.59\u0026thinsp;\u0026plusmn;\u0026thinsp;17.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.69 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.43\u0026thinsp;\u0026plusmn;\u0026thinsp;9.54 (pre)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.14\u0026thinsp;\u0026plusmn;\u0026thinsp;10.89 (post)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFMA-LE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.96\u0026thinsp;\u0026plusmn;\u0026thinsp;5.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.68\u0026thinsp;\u0026plusmn;\u0026thinsp;6.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.29\u0026thinsp;\u0026plusmn;\u0026thinsp;3.73 (pre)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.94 (post)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMBI-C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79.20\u0026thinsp;\u0026plusmn;\u0026thinsp;22.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87.73\u0026thinsp;\u0026plusmn;\u0026thinsp;14.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.12 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72.86\u0026thinsp;\u0026plusmn;\u0026thinsp;5.31 (pre)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76.57\u0026thinsp;\u0026plusmn;\u0026thinsp;5.32 (post)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e \u003csup\u003ea\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003eANOVA\u003csup\u003e\u0026nbsp;\u003c/sup\u003efor three groups and Independent \u003cem\u003et\u003c/em\u003e-test for two groups\u0026nbsp;in cross-sectional study,\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003eChi-square test in cross-sectional study. LSS, left subcortical stroke; RSS, right subcortical stroke; HCs, healthy controls; FMA-UE, Fugl-Meyer Assessment of upper extremity; FMA-LE, Fugl-Meyer Assessment of lower extremity; MBI-C, the Chinese version of Modified Barthel Index.\u0026emsp;\u003c/p\u003e\n \u003cp\u003e[Insert Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e here]\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eDisrupted distance-related FCD in the stroke groups\u003c/h2\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA displays the mean FCD maps for each group. At the whole-brain level, the LSS group exhibited significantly higher mean values of gFCD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001, Cohen\u0026apos;s \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.89), lFCD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001, Cohen\u0026apos;s \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.89), and sFCD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002, Cohen\u0026apos;s \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.83) compared to the HCs (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;2\u003c/strong\u003e). However, no significant differences in the three FCD values were found between other paired groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). At the voxel level, the ANCOVA analysis showed significant group differences in the left IFG and bilateral supplementary motor gyrus (SMA) for both gFCD and lFCD (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB), and in the left IFG, bilateral CPL, left middle occipital gyrus (MOG), and bilateral cerebellum anterior lobe (CAL) for sFCD (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB). \u003cem\u003ePost-hoc\u003c/em\u003e analyses subsequently revealed that both the LSS and RSS groups exhibited significantly increased gFCD and lFCD values in the left IFG and bilateral SMA when compared to the HCs (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA, |Cohen\u0026apos;s \u003cem\u003ed|\u0026gt;\u003c/em\u003e0.8 in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Moreover, both the LSS and RSS groups demonstrated increased sFCD values in the left IFG and PreCG, and decreased sFCD values in the bilateral CPL, left MOG, and bilateral CAL, in comparison to the HCs (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA, |Cohen\u0026apos;s \u003cem\u003ed|\u0026gt;\u003c/em\u003e0.8 in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). However, no significant differences in gFCD, lFCD, or sFCD values were observed when comparing the two patient subgroups (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Collectively, the analyses revealed that the left IFG showed distance-independent FCD alteration, while bilateral SMA, CAL, CPL, and left MOG exhibited distance-dependent FCD alterations in stroke patients.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRegions showing significant differences in gFCD, lFCD, and sFCD among LSS, RSS, and HCs.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eRegions\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eHemisphere\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eMNI coordinates\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCluster size\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eLSS vs. HCs\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eRSS vs. HCs\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eLSS vs. RSS\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ey\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ez\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCohen\u0026rsquo;\u003cem\u003ed\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eCohen\u0026rsquo;\u003cem\u003ed\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCohen\u0026rsquo;\u003cem\u003ed\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"14\"\u003e\n \u003cp\u003e\u003cem\u003egFCD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInferior frontal gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.61***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.54***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupplementary motor area\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.96***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.24***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"14\"\u003e\n \u003cp\u003e\u003cem\u003elFCD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInferior frontal gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.62***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e4.53***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupplementary motor area\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.98***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e4.25***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"14\"\u003e\n \u003cp\u003e\u003cem\u003esFCD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCerebellum posterior lobe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.77***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-3.74***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInferior frontal gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.11***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e4.43***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrecentral gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle occipital gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.84***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-4.14***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCerebellum anterior lobe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.19***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-3.67**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003eNote: MNI, Montreal Neurological Institute; LSS, left subcortical stroke; RSS, right subcortical stroke; HCs, healthy controls; gFCD, global functional connectivity density; lFCD, long-range functional connectivity density; sFCD, short-range functional connectivity density. *, 0.01\u0026thinsp;\u0026lt;\u0026thinsp;\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **, 0.001\u0026thinsp;\u0026lt;\u0026thinsp;\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e[Insert Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, and Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e here]\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eAssociation of functional reorganization with motor outcomes\u003c/h2\u003e\n \u003cp\u003eThe sFCD in the left IFG showed negative correlations with FMA-UE (\u003cem\u003e\u0026beta;\u003c/em\u003e = -0.007, adjusted \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024) and FMA-LE (\u003cem\u003e\u0026beta;\u003c/em\u003e = -0.025, adjusted \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006) scores, and both gFCD (\u003cem\u003e\u0026beta;\u003c/em\u003e = -0.011, adjusted \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.130) and lFCD (\u003cem\u003e\u0026beta;\u003c/em\u003e = -0.011, adjusted \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.130) in this region negatively correlated with FMA-UE score across all stroke patients (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB). Furthermore, positive correlations were observed between gFCD (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.040, adjusted \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.042) and lFCD (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.040, adjusted \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.042) in the bilateral SMA and the FMA-LE scores across all stroke patients (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB). There were no significant correlations between the FCD and the motor outcomes in LSS or RSS group (adjusted \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). More importantly, the significant correlations aforementioned were validated by a longitudinal dataset. After routine intervention, the scores of upper/lower extremities increased in all patients, while FMA-UE-related FCD in the IFG decreased in \u0026gt;\u0026thinsp;4/7 of patients \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA\u003cstrong\u003e)\u003c/strong\u003e and FMA-LE-related FCD in the SMA decreased in \u0026gt;\u0026thinsp;5/7 of patients (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCorrelations between FCD values and motor-related outcomes across all post-stroke patients.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cem\u003eFMA-UE\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRegions\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFeature\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjusted \u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft IFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral SMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.804\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft IFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral SMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.826\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral CPL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.254\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft IFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft MOG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.465\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral CAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.717\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cem\u003eFMA-LE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft IFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.868\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral SMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.844\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft IFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral SMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral CPL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.906\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.522\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft IFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft MOG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.753\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.786\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral CAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.554\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cem\u003eMBI-C\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft IFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.764\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral SMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.485\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.554\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft IFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1569\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral SMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.554\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral CPL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.695\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.758\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft IFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft MOG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral CAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.862\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.525\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eNote: FMA-UE, Fugl-Meyer Assessment Upper Extremity Scale; FMA-LE, Fugl-Meyer Assessment Lower Extremity Scal; MBI-C,the Chinese version of Modified Barthel Index; IFG, inferior frontal gyrus; SMA, supplementary motor area; CPL, cerebellum posterior lobe; MOG, middle occipital gyrus; CAL, cerebellum anterior lobe; gFCD, global functional connectivity density; lFCD, long-range functional connectivity density; sFCD, short-range functional connectivity density.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e[Insert Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e here]\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eValidation results\u003c/h2\u003e\n \u003cp\u003eBetween-group differences in gFCD, lFCD, and sFCD among LSS, RSS, and HCs under two different distance criteria (6 mm and 18 mm) replicated the primary findings observed under the 12 mm criterion (\u003cstrong\u003eSupplementary Table\u0026nbsp;1\u003c/strong\u003e and \u003cstrong\u003eSupplementary Table\u0026nbsp;2\u003c/strong\u003e). Namely, the left IFG continued to exhibit distance-dependent FCD alteration, and the bilateral SMA and CPL consistently displayed distance-independent FCD alteration in both patient subgroups compared with HCs. Also, the \u003cem\u003epost-hoc\u003c/em\u003e analyses between the two patient subgroups and HCs showed large effect sizes, with |Cohen\u0026apos;s \u003cem\u003ed| \u0026gt;\u003c/em\u003e 0.8 (\u003cstrong\u003eSupplementary Table\u0026nbsp;1\u003c/strong\u003e and \u003cstrong\u003eSupplementary Table\u0026nbsp;2\u003c/strong\u003e). Moreover, the LOOCV indicated the high reproducibility of FCD differences observed among the three groups, as shown in \u003cstrong\u003eSupplementary Fig.\u0026nbsp;3\u003c/strong\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003eDistance-related functional reorganizations after unilateral subcortical stroke\u003c/h2\u003e\n \u003cp\u003eIn summary, both the LSS and RSS consistently showed distance-related FCD changes. Specifically, the left IFG displayed distance-independent FCD alterations, whereas the bilateral SMA, CAL, CPL, and left MOG exhibited distance-dependent FCD alterations. Considering the correlations between FCD and motor outcome, the increased FCD in the bilateral SMA may play a compensatory role in the restoration of motor function in the paralyzed lower limbs of stroke patients, while the increased FCD in the left IFG may indicate impairment of motor function in both the paralyzed upper and lower limbs of stroke patients. Detailed information is presented in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e[Insert Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e here]\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study used the distance-dependent FCD approach to investigate functional alterations in chronic stroke patients following left and right hemisphere subcortical lesions. Our results demonstrated that, compared with HCs, the LSS and RSS groups both exhibited distance-dependent FCD changes, that bilateral SMA showed increased gFCD and lFCD, while bilateral CPL/CAL and left MOG showed reduced sFCD. Interestingly, the left IFG showed a distance-independent FCD increase in both patient subgroups compared to HCs. Moreover, we found significant correlations between the FCD values in the left IFG as well as bilateral SMA and specific motor functions in stroke patients. These findings support our initial hypothesis, suggesting the presence of distance-related functional reorganization in motor and non-motor regions of chronic subcortical stroke, which may serve as valuable biomarkers for predicting motor outcomes in stroke patients.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eGlobal FCD alterations after subcortical stroke\u003c/h2\u003e \u003cp\u003eNumerous studies have utilized gFCD to explore neural activity alterations after stroke. For instance, Min et al. found higher gFCD values in the right parahippocampal gyrus in acute subcortical stroke patients than HCs [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Wang et al. demonstrated that subacute stroke patients with cognitive impairment exhibited significant changes in gFCD, including decreases in language-related brain regions and increases in the right middle frontal gyrus (MFG), hippocampus, and paracentral lobule, in comparison to HCs [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Yao et al. reported decreased gFCD values in right inferior parietal lobule and right PosCG, in subacute stroke patients compared with HCs [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Different from the acute and subacute stroke, the present study found that two chronic stroke subgroups both showed increased gFCD in the bilateral SMA compared with HC. As a dominant region contributing to movement control, the SMA participates in stabilizing body posture and regulating movement sequences [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Previous studies found that the SMA showed higher betweenness centrality [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and increased regional homogeneity [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] in subcortical stroke patients than HCs, indicating a compensatory role of the SMA in response to motor deficits after stroke. Therefore, our findings align with previous reports, and further demonstrated that the SMA plays an important role underlying the functional reorganization in stroke patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eDistance-dependent FCD alterations after subcortical stroke\u003c/h2\u003e \u003cp\u003ePrevious studies have demonstrated that schizophrenia leads to abnormal sFCD rather than the glFCD in the precuneus [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], and attention-deficit/hyperactivity disorder alters the lFCD but not the sFCD in the left superior parietal gyrus and the right MFG [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Patients with cognitive impairment showed increased lFCD in the left fusiform gyrus and sFCD in the left middle orbital gyrus [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Similarly, such distance-dependent patterns were observed in the present study that the bilateral SMA and left IFG showed increased lFCD, and the bilateral CAL/CPL and left MOG showed decreased sFCD in chronic subcortical stroke patients following left and right hemisphere subcortical lesions compared to HCs. The functional reorganizations in these regions have been reported in stroke patients, who showed decreased regional homogeneity [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and interhemispheric connectivity [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] in the MOG and SMA, as well as increased FC in the CAL [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and the CPL [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] compared to HCs. A recent study found an increased FCD value of the right CPL in stroke patients relative to HCs [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Therefore, the current study further extended the existing knowledge by emphasizing that function reorganization in the frontal-occipital cortex and cerebellum exhibits a distance-dependent pattern following subcortical stroke regardless of the lesion hemisphere. Indeed, lFCD and sFCD reflect the functional integration and specialization of brain networks, respectively [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Our findings suggest that chronic subcortical stroke patients exhibit long-range functional plasticity (compensatory effect) in the SMA, while the regional functional plasticity is primarily present in the cerebellum and MOG, highlighting the intricacy and flexibility of functional reorganization during the chronic phase post subcortical stroke.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eDistance-independent FCD increase in the left IFG after subcortical stroke\u003c/h2\u003e \u003cp\u003eIn addition to its traditional roles in cognitive processes [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and speech functions [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], the IFG assumes a core component in the mirror neuron system [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], which is closely associated with action observation [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] and motion imitation [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Furthermore, the IFG has been implicated in specific motor-related processes, including motor imagery [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] and task execution [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Multiple studies have focused on the functional plasticity of the IFG in stroke patients with motor dysfunction. For instance, Garrison et al. reported cortical activations in the bilateral IFG during hand movement in chronic stroke patients [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Ma et al. found increased activation in the IFG during motor imagery in subacute subcortical stroke patients compared to HCs [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Furthermore, diverse functional alterations in the IFG have been documented in stroke patients. Compared with HCs, stroke patients showed increased FCD in the bilateral inferior frontal-orbital gyrus [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and decreased interhemispheric connectivity in the bilateral IFG [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Consistently, we found increased gFCD, lFCD, and sFCD in the left IFG in chronic subcortical stroke patients with motor impairment, compared to HCs, indicating a distance-independent functional reorganization in this region. Interestingly, our findings remain consistent regardless of the lesion hemisphere, and it should be noted that the patients recruited in our study did not exhibit aphasia. To provide a more comprehensive understanding of the post-stroke functional changes in the left IFG, the present study selected the left IFG as the seed region for a whole-brain FC analysis and found FC alternations between the left IFG and motor-related regions, such as the right PreCG, PosCG, MFG, bilateral middle temporal gyrus, and left precuneus (\u003cb\u003eSupplementary Fig.\u0026nbsp;4\u003c/b\u003e and \u003cb\u003eSupplementary Table\u0026nbsp;3\u003c/b\u003e), which have previously been implicated in stroke patients [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Thus, we revealed a reorganization of functional networks with the left IFG as the hub following subcortical stroke, thereby providing evidence for the critical role of left IFG in motor function.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eAssociation of FCD changes with motor outcomes\u003c/h2\u003e \u003cp\u003ePrevious studies have reported a positive correlation between voxel-mirrored homotopic connectivity in the IFG and motor function in Parkinson\u0026rsquo;s disease [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], and a negative correlation between the lesion size of the left IFG and hand action performance in chronic stroke patients [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Moreover, subacute stroke patients showed significant positive correlations between the variability of amplitude of low-frequency fluctuation in the SMA and total FMA scores [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], and between betweenness centrality in the SMA and FMA-UE scores [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Chronic stroke patients exhibited a significantly positive correlation between mean brain entropy values in the SMA and total FMA scores [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. These findings underscore the close association between functional alterations in the IFG and SMA and motor dysfunction following stroke. The present study found that the sFCD value in the left IFG significantly negatively correlated with the motor function in both upper and lower extremities, while the gFCD and lFCD values in the bilateral SMA significantly positively correlated with the FMA-LE scores. These correlations were also validated by the longitudinal data. Our findings indicate that the increased FCD in the bilateral SMA may function as a compensatory mechanism [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] in the recovery of motor function in the paralyzed lower limbs of stroke patients, whereas increased FCD in the left IFG may indicate impairment [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] in motor function in both the paralyzed upper and lower limbs of stroke patients. Taken together, this suggests that the FCD values in left IFG and bilateral SMA could serve as biomarkers for predicting motor outcomes after stroke.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study is subject to several limitations warranting consideration. Firstly, the sample sizes of post-stroke patients in both cross-sectional and longitudinal experiments were relatively small. Although our results displayed large effect size and were validated by two distinct methods, a large-sample study needs to verify our findings in the future. Secondly, as all stroke patients exhibit unilateral subcortical lesions, and therefore, the observed patterns of functional reorganization may not necessarily be generalized to patients with other types of brain lesions. Thirdly, there was a pronounced male predominance in the present study. Despite controlling for gender as a nuisance covariate in our statistical analyses, future studies need to maintain an appropriate gender balance to confirm our findings. Last but not least, the cross-sectional design employed in this study did not allow for a conclusion to be drawn on the causes of the functional changes in the left IFG. Therefore, how such changes contribute to motor dysfunction remains speculative. Future studies adopting a prospective design on a larger sample size and multiple brain lesion groups can facilitate a better understanding of the mechanisms underlying motor dysfunction in post-stroke patients without aphasia.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe current study explored functional alterations in chronic stroke patients following left and right hemisphere subcortical lesions, using the distance-dependent FCD approach. Our results demonstrated that the left IFG exhibited distance-independent FCD changes, while the bilateral SMA, CAL, CPL, and left MOG showed distance-related FCD alterations in stroke patients, regardless of the lesion side. Importantly, our study highlights that these changes in FCD have the potential to predict clinical function, with the correlations between FCD values in the left IFG and bilateral SMA and specific paralyzed motor function in all chronic stroke patients without aphasia. These findings offer additional evidence to comprehend the neurophysiological mechanisms underlying motor dysfunctions following chronic stroke.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eADL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003eactivities of daily living\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eCAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003ecerebellum anterior lobe\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eCPL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003ecerebellum posterior lobe\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eFC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003efunctional connectivity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003efunctional connectivity density\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eFMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003eFugl-Meyer Assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eFMA-LE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003ethe Fugl-Meyer Assessment Lower Extremity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eFMA-UE\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003ethe Fugl-Meyer Assessment Upper Extremity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003egFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003eglobal-range functional connectivity density\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eHCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003ehealthy controls\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eIFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003einferior frontal gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003elFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003elong-range functional connectivity density\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eLOOCV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003eleave-one-out cross-validation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eLSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003eleft subcortical stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eMBI-C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003eChinese version of Modified Barthel Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eMFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003emiddle frontal gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eMOG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003emiddle occipital gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eMTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003emiddle temporal gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003ePosCG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003epostcentral gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003ePreCG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003eprecentral gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eRSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003eright subcortical stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003esFCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003eshort-range functional connectivity density\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.49728752260398%\" valign=\"top\"\u003e\n \u003cp\u003eSMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.50271247739602%\" valign=\"top\"\u003e\n \u003cp\u003esupplementary motor area\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express gratitude to all participants and their families for their contributions which were vital to the success of this work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWH, RX, and ZZ conceptualized and supervised the study. WH, ZL, and BY recruited the subjects. WH, ZL, XZ, ML, and ZY assisted in acquiring the fMRI data. ZL and Yuxin Wang contributed to behavioral data collection. WH and ZZ analyzed the data. WH, ZL, Yanan Wu, SF, MW, RX, and ZZ drafted the manuscript. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received support from the Youth Program of the National Natural Science Foundation of China (grant number 82002378), the funding for Clinical Trials from the Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University (grant number 2022-LCYJ-PY-27), and the Medical Science and Technology Development Foundation, Nanjing Department of Health (grant number YKK20068).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the guidelines of the Helsinki Declaration and was approved by the Ethics Committee of Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University. Prior to participation, written informed consent was obtained from all participants or from their legal guardians when applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have read the manuscript and provided consent for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1 Department of Rehabilitation Medicine, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China\u003c/p\u003e\n\u003cp\u003e2 Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China\u003c/p\u003e\n\u003cp\u003e3 School of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e4 Binjiang Institute of Zhejiang University, Hangzhou 310014, China\u003c/p\u003e\n\u003cp\u003e5 Department of Rehabilitation Medicine, Nanjing Drum Tower Hospital, School of Medicine, Jiangsu University, Nanjing 210008, China\u003c/p\u003e\n\u003cp\u003e6 Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering \u0026amp; Instrument Science, Zhejiang University, Hangzhou 310027, China\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCarter AR, Shulman GL, Corbetta M: Why use a connectivity-based approach to study stroke and recovery of function? \u003cem\u003eNeuroImage\u003c/em\u003e 2012, 62(4):2271\u0026ndash;2280.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu F, Chen C, Hong W, Bai Z, Wang S, Lu H, Lin Q, Zhao Z, Tang C: Selectively disrupted sensorimotor circuits in chronic stroke with hand dysfunction. 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Neurology 2021, 96(21):e2587-e2598.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"ce842527-88cd-4f8b-942c-601321bd2a88","identifier":"10.13039/501100001809","name":"National Natural Science Foundation of China","awardNumber":"82002378","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"Nanjing Drum Tower Hospital","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Stroke, Distance, Functional Connectivity Density, Motor Function, Resting-state fMRI, Biomarker","lastPublishedDoi":"10.21203/rs.3.rs-3916957/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3916957/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAnalyzing distance-dependent functional connectivity density (FCD) yield valuable insights into patterns of brain activity. Nevertheless, whether alterations of FCD in chronic stroke patients are associated with the anatomical distance between brain regions remains unclear. This study aimed to explore the distance-related functional reorganization in chronic stroke patients following left and right hemisphere subcortical lesions, and its relationship with clinical assessments.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn this study, we used resting-state fMRI to calculate distance-dependent (i.e., short- and long-range) FCD in 25 left subcortical stroke (LSS) patients, 22 right subcortical stroke (RSS) patients, and 39 well-matched healthy controls (HCs). Then, we compared FCD differences among the three groups and assessed the correlation between FCD alterations and paralyzed motor function using linear regression analysis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOur findings demonstrated that the left inferior frontal gyrus (IFG) displayed distance-independent FCD changes, while the bilateral supplementary motor area (SMA), cerebellum, and left middle occipital gyrus exhibited distance-dependent FCD alterations in two patient subgroups compared with HCs. Furthermore, we observed a positive correlation between increased FCD in the bilateral SMA and the motor function of lower limbs, and a negative correlation between increased FCD in the left IFG and the motor function of both upper and lower limbs across all stroke patients. These associations were validated by using a longitudinal dataset.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe FCD in the cerebral and cerebellar cortices shows distance-related changes in chronic stroke patients with motor dysfunction, which may serve as potential biomarkers for predicting motor outcomes after stroke. These findings enhance our comprehension of the neurobiological mechanisms driving chronic stroke.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTrial registration\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAll data for the present study were obtained from a research trial registered with the ClinicalTrials.gov database (NCT05648552, registered 05 December 2022).\u003c/p\u003e","manuscriptTitle":"Distance-related functional reorganization predicts motor outcome in stroke patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-02 15:34:26","doi":"10.21203/rs.3.rs-3916957/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9ce77fca-f036-4c4c-8292-72e42d6bb8dc","owner":[],"postedDate":"February 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":28505105,"name":"Neurology"}],"tags":[{"value":"featured","date":"2024-02-02 20:02:03"}],"updatedAt":"2024-06-18T00:33:51+00:00","versionOfRecord":{"articleIdentity":"rs-3916957","link":"https://doi.org/10.1186/s12916-024-03435-7","journal":{"identity":"bmc-medicine","isVorOnly":false,"title":"BMC Medicine"},"publishedOn":"2024-06-18 00:33:51","publishedOnDateReadable":"June 18th, 2024"},"versionCreatedAt":"2024-02-02 15:34:26","video":"","vorDoi":"10.1186/s12916-024-03435-7","vorDoiUrl":"https://doi.org/10.1186/s12916-024-03435-7","workflowStages":[]},"version":"v1","identity":"rs-3916957","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3916957","identity":"rs-3916957","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}