Altered Regional Brain Spontaneous Activity and Functional Connectivity in Patients of Non-Acute Subcortical Stroke With versus Without Cognitive Impairment: A Resting-State fMRI Study.

Altered Regional Brain Spontaneous Activity and Functional Connectivity in Patients of Non-Acute Subcortical Stroke With versus Without Cognitive Impairment: A Resting-State fMRI Study. | 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 Altered Regional Brain Spontaneous Activity and Functional Connectivity in Patients of Non-Acute Subcortical Stroke With versus Without Cognitive Impairment: A Resting-State fMRI Study. Yao Wang, Wan Liu, Wenjie Yang, Xue Chai, Hao Yu, Hongxia Ma, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4316301/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The reasons why not all stroke survivors have cognitive dysfunction are unclear. We hypothesize that resting-state fMRI (rs-fMRI) will reveal differences in regional brain spontaneous activity and functional connectivity (FC) in stroke patients with and without cognitive impairment. We classified 62 first-ever non-acute subcortical stroke patients into two groups: post-stroke with abnormal cognition (PSAC) and with normal cognition (PSNC). Rs-MRI was utilized to assess regional homogeneity (ReHo) in 32 PSAC, 30 PSNC, and 62 age- and sex-matched healthy controls. We set regions with significant alteration within stroke groups as regions of interest and performed the seed-based whole brain FC analysis. A partial correlation analysis examined the relationship between altered ReHo or FC and Montreal Cognitive Assessment (MoCA) scores. Compared to PSNC, PSAC had decreased ReHo in the left gyrus rectus (REC) and increased ReHo in cerebellar lobules (CBL) left IX and right VIII, while FC decreased in PSAC between bilateral REC, and between the left REC and the middle temporal gyrus (MTG). In all stroke patients, ReHo value in the left REC correlated positively and in the CBL correlated negatively with MoCA. All the significant FC correlated with MoCA positively. Regional brain spontaneous activity and FC alteration in the REC, MTG, and cerebellum may be associated with cognitive impairment following non-acute subcortical stroke. Stroke Cognitive impairment Functional magnetic resonance imaging Regional homogeneity Functional connectivity Gyrus rectus Cerebellum Figures Figure 1 Figure 2 Figure 3 1. Introduction Cognitive impairment or decline is observed in more than two-thirds of stroke survivors following the event [ 1 , 2 ]. This condition presents difficulties in performing routine tasks and may serve as an indicator of an unfavorable prognosis, including suboptimal rehabilitation outcomes, increased mortality, and the potential onset of dementia [ 3 , 4 ]. The mechanisms behind functional recovery after stroke remain unclear. Rewiring of surviving brain circuits, vascular restoration, immunomodulation, and endogenous neurogenesis are among the most important considerations cited [ 5 – 7 ]. However, cognitive decline, unlike motor dysfunction or aphasia, is not entirely attributable to the stroke lesion location, and the patterns and causes are currently being explored. Cerebral infarcts in the frontal, temporal, parietal, and basal ganglia regions and their size are connected with cognitive impairment [ 8 ]. Others contended that lesion size and location cannot explain stroke-related cognitive impairment. Instead, stroke-induced harm transcends regional boundaries and has the potential to interfere with the entirety of the brain network [ 9 ]. Recently, resting-state functional magnetic resonance imaging (rs-fMRI) has gained popularity for exploring cognitive impairment neural mechanisms [ 10 , 11 ]. Growing investigators employ regional homogeneity (ReHo), which measures temporal synchronization of nearest neighbor time series and can map local spontaneous neural activity [ 12 ], for exploring the local neural activities in cerebrovascular diseases. Previous study [ 13 ] found decreased ReHo in the precuneus/cuneus and insula; and increased ReHo in the temporal lobe in patients with mild cognitive impairment (MCI) with lacunar infarction (LI), when compared to those without LI. Similarly, post-stroke patients with cognitive dysfunction revealed decreased ReHo in the anterior cingulate cortices (ACC) and posterior cingulate cortices (PCC), and positively correlated with the cognition scores, when compared to those without cognition decline [ 14 ]. Vascular cognitive impairment (VCI) patients exhibit a significant positive correlation between the ReHo value in the middle temporal gyrus (MTG) and short-term delayed memory scores [ 15 ]. Nevertheless, the distribution of brain regions and the correlation and value with cognitive impairment were different, possibly due to the selection of subjects and controls. Meanwhile, we found patients who do not acquire cognitive abnormalities after stroke are not adequately studied for brain changes by fMRI when compared to cognitively impaired and healthy persons. ReHo referred to as short-term connectivity, while functional connectivity (FC) could reflect the time consistency of spontaneous activity between regions and could be used to map long-term connectivity [ 14 ]. Previous studies revealed significant decrease in the default model network (DMN) and salience network [ 16 ], while others reported increased brain activity in DMN, frontal, fronto-temporal, and secondary visual network in stroke patients [ 11 ]. They further found significant impairment in the connectivity including superior frontal gyrus (SFG), PCC, parahippocampal gyrus (PHG) and parietal gyrus [ 17 ]. Nevertheless, there is currently a paucity of knowledge regarding the combination of brain regional activity and further connectivity analysis, which can offer more thorough insight into the brain functional network and contribute to the identification of imaging biomarkers of cognitive dysfunction following a stroke. Hence, we employ rs-fMRI to investigate the changes of ReHo in stroke patients with and without cognitive dysfunction. Then to study the long-term FC patterns in these patients based on the regions where the changed ReHo is situated as the regions of interests (ROIs). Consequently, we hypothesis (1). Post-stroke patients with abnormal cognitive dysfunction have distinct ReHo patterns than those with normal cognition. (2). In addition to altered spontaneous activity in localized brain regions, cognitively impaired participants may also experience changes in patterns of connectivity between brain regions. (3). Changes of ReHo and FC are closely related to clinical cognitive performance. 2. Materials and Methods 2.1 Subjects 129 subjects participated in the current study, which included 67 patients with stroke and 62 healthy controls (HC), were recruited from November 2021 to May 2023 at the Department of Rehabilitation Medicine, Nanjing Brain Hospital. Additionally, 62 healthy volunteers were recruited through advertisements and matched to post-stroke patients by age and gender. Stroke patients were included if: (1). adults (18–80 years old); (2). right-handedness before stroke; (3). first-ever ischemic or hemorrhagic stroke through head computed tomography (CT) or MRI with subcortical region; (4). time after stroke onset over 2 weeks; and (5). absence of serious movement dysfunction. Exclusion criteria for stroke patients and healthy controls (HCs) were: (1) neurodegenerative diseases, epilepsy, mood disorders, traumatic brain injury, or tumor; (2) clinically significant or unstable medical disorder; (3) psychiatric medication that may affect cognitive function; and (4) MRI contraindications. Control subjects with quiet brain infarctions or cognitive disorders that could impact cognitive function and FC activity were excluded. The Affiliated Brain Hospital to Nanjing Medical University Ethics Committee approved this study (No. 2022-KY086-01). All participants gave written informed consent. 2.2 Clinical Data, Neuropsychological Tests and Grouping Through surveys and medical records, education years, disease duration since stroke, stroke type, and lesion volume were collected. Participants' global cognitive function (GCF) was measured by the MoCA [ 18 ]. Stroke survivors were divided into post-stroke with abnormal cognition (PSAC) and post-stroke normal cognition (PSNC) subgroups based on MoCA scores. An adjusted MoCA score of less than 24 was recommended to identify cognitively impaired patients [ 19 ]. However, three PSAC and two PSNC participants were rejected for excessive head movement. Final enrollment was 62 stroke patients, 32 PSAC and 30 PSNC. 2.3 Brain MRI Data Acquisition MRI acquisition parameters for all individuals were summarized in Supplementary Material . 2.4 MRI Data Analysis 2.4.1 Image Preprocessing Data Processing Assistant for Resting-State fMRI (DPARSF; http://www.restfmri.net/forum/DPARSF ) was employed to preprocess data utilizing Statistical Parametric Mapping (SPM8) ( http://www.fil.ion.ucl.ac.uk/spm ) in MATLAB environment (Mathworks, Natick, MA, USA). The first 10 volumes of functional images were removed for each patient. Then, the remaining images were corrected using slice-timing and realignment, accounting for head motion, normalized to standard space using DARTEL, resampled to a 3 ⅹ 3 ⅹ 3mm 3 voxel size, regress nuisance variable, and spatially smoothed with 4mm full width at half maximum (FWHM). The nuisance variables include 24 motion parameters (six head motion parameters, six head motion parameters one time point before, and the 12 corresponding squared items), a global signal, a white matter signal, and a cerebrospinal fluid signal. Finally, a temporal filter (0.01–0.08 Hz) was applied to reduce low-frequency drift and high-frequency physiological noise. In addition, patients with excessive head motion (cumulative translation or rotation > 3.0 mm or 3.0) were excluded [ 20 ]. 2.4.2 ReHo Analysis ReHo analysis was carried out on the previously mentioned preprocessed pictures. Calculating Kendall's coefficient of concordance of a voxel's time series with its nearest neighbors (26 voxels) produced individual ReHo maps [ 21 ]. Each voxel's ReHo was normalized to the global mean to reduce individual variances. Finally, all the subjects were smoothed using a 6-mm fullwidth at half maximum Gaussian kernel. 2.4.3 FC Analysis We employed the different ReHo of brain areas between PSAC and PSNC groups as ROIs for an analysis of seed-based whole-brain FC analysis. Individual mean time series were extracted based on the coregistered seed region as the reference time series. The correlation analyses were conducted on the seed region and the whole brain within the gray matter mask. We used a Fisher’s r -to- z transformation to improve the normality of the correlation coefficients. Therefore, an entire brain z -score map was developed for each subject for subsequent statistical analyses. 2.5 Statistical Analysis One-way analysis of variance (ANOVA) and χ 2 test were used to compare demographics and cognitive scores between the stroke groups and the HC group using SPSS Statistics 25.0 on continuous variables and proportions, respectively. Statistical significance was determined at p < 0.05. A one-way analysis of covariance (ANCOVA) was used to compare ReHo and FC among HC, PSAC, and PSNC patients. The two-sample t -test was utilized for post-hoc comparisons of ReHo or FC patterns between stroke and HC groups and within stroke groups. Age, gender, education, head motion parameters and grey matter volume were covariables for three groups. For stroke groups, we added lesion volume, disease duration, and stroke type as covariates. The resultant T-maps were conducted with Gaussian Random Field Theory (GRF) correction for multiple comparisons with voxel p < 0.01, cluster p < 0.05 [ 22 ]. Finally, extracted ReHo or FCs of significantly changed regions were used for correlation analysis. After controlling for age, gender, and education, partial correlation analyses revealed associations between altered ReHo or FCs and MoCA scores. Due to the small sample size, we did not modify correlation analysis results for multiple comparisons to improve presentation. 3. RESULTS 3.1 Demographic and Neuropsychological Characteristics Table 1 showed all case features. Age, gender, disease duration, and lesion size were comparable among three groups. The lesion location was applied in Supplementary Fig. 1. The PSAC group had lower years of education (9.56 ± 4.27) compared to the HC (12.50 ± 2.76, p < 0.001) and PSNC (12.53 ± 3.38, p < 0.001) groups. Additionally, stroke types differed between the PSAC (Ischemic/Hemorrhagic: 18/14) and PSNC (I/H: 26/4, p = 0.008) groups. MoCA scores were considerably lower in PSAC (11.31 ± 5.28) compared to HC (25.76 ± 1.90, p < 0.001) and PSNC (26.60 ± 1.81, p < 0.001), respectively. Table 1 Demographic characteristics of stroke patients and healthy controls HCs (n = 62) All SPs (n = 62) PSAC (n = 32) PSNC (n = 30) F/t/χ 2 p value Gender (M/F), n 36/26 37/25 18/14 19/11 0.033 † , 0.354 ‡ 0.855 † , 0.838 ‡ Age (Mean ± SD), years 61.95 ± 6.56 60.61 ± 10.21 62.59 ± 10.09 58.50 ± 10.08 0.869 † , 2.184 ‡ 0.387 † , 0.117 ‡ , 0.729 § , 0.070 ¶ , 0.060 # Education years (Mean ± SD), years 12.50 ± 2.76 11.00 ± 4.12 9.56 ± 4.27 12.53 ± 3.38 2.382 † , 9.163 ‡ 0.019 †* , < 0.001 ‡* , < 0.001 §* , 0.964 ¶ , < 0.001 #* Disease duration 5.056 # 0.168 # 2 weeks − 1 month - 32 19 13 1–3 months - 21 8 13 3–6 months - 5 4 1 Over 6 months - 4 1 3 Stroke type (Ischemic/ Hemorrhagic) - 44/18 18/14 26/4 6.953 # 0.008 #* Lesion volume (Mean ± SD), ml - 6.75 ± 10.83 9.21 ± 14.12 4.12 ± 4.46 -1.888 # 0.064 # MoCA 25.76 ± 1.90 18.71 ± 8.66 11.31 ± 5.28 26.60 ± 1.81 6.258 † , 264.621 ‡ < 0.001 † * , < 0.001 ‡* , < 0.001 §* , 0.228 ¶ , < 0.001 #* F: Female; HC: Healthy Controls; M: Male; MoCA: Montreal Cognitive Assessment; PSAC: Post-Stroke with Abnormal Cognition; PSNC: Post-Stroke with Normal Cognition; SP: Stroke Patients. †. Represents comparison of HC vs. all stroke patients, ‡. Represents comparison in HC, PSAC and PSNC groups; §. Represents comparison of HC vs. PSAC; ¶. Represents comparison of HC vs. PSNC; #. Represents comparison of PSAC vs. PSNC. * Significant differences were found, p < 0.05. 3.2 Comparisons of ReHo values The three groups had significantly different ReHo across brain regions by ANCOVA, as shown in Supplemental Fig. 2 and Supplemental Table 1. ReHo study indicated that both stroke groups had a significant increase in the right SFG, right MTG, and decrease in right postcentral gyrus (PoCG) and left cerebellar lobules (CBL) IX compared to the HC group. The PSAC group exhibit significantly increased ReHo values in bilateral inferior temporal gyrus (ITG) than the HC group (Fig. 1 A and Table 2 ). Compared to the HC group, PSNC showed remarkably increased ReHo in the left MTG, left middle frontal gyrus (MFG), left inferior frontal gyrus (IFG), right supplementary motor area (SMA) (Fig. 1 B and Table 2 ). The left gyrus rectus (REC) ReHo value deceased in the PSAC than PSNC group, but ReHo in the left CBL IX and right CBL VIII increased (Fig. 1 C and Table 2 ). Table 2 The differences in the brain regions of ReHo by post hoc analyses among the three groups. Brain Region (AAL) Peak MNI coordinate Peak T-value Cluster number x y z PSAC HC Right Middle temporal gyrus 60 -12 -18 4.5295 88 Left Inferior temporal gyrus -63 -30 -24 4.0988 90 Right Inferior temporal gyrus 66 -36 -18 5.2676 82 Right Superior frontal gyrus 9 39 36 4.8463 103 PSNC HC Left Middle temporal gyrus -60 -15 -24 6.1397 340 Right Middle temporal gyrus 60 -12 -18 5.3146 314 Left Inferior frontal gyrus -18 18 -18 6.0293 529 Right Superior frontal gyrus 18 24 18 5.8441 294 Left Middle frontal gyrus -33 21 42 6.0466 423 Right Supplementary motor area 9 21 54 4.4843 125 PSAC PSNC Left Cerebellar lobules IX -9 -54 -63 3.9683 72 Right Cerebellar lobules VIII 9 -42 -60 3.9663 148 AAL: Automated Anatomical Labeling; HC: Healthy Controls; MNI, Montreal Neurological Institute; PSAC: Post-Stroke with Abnormal Cognition; PSNC: Post-Stroke with Normal Cognition; ReHo: Regional Homogeneity. The resultant T-maps were conducted with Gaussian Random Field Theory (GRF) correction for multiple comparisons with voxel p < 0.01, cluster p 30 voxels. 3.3 Comparison of FC The brain areas with significant clusters of strokes related ReHo changes were designated as ROIs, including left REC, left CBL IX, and right CBL VIII. However, only ROI in left REC showed significant brain region alterations, as shown in Supplemental Table 2 for ANCOVA comparison among three groups. Compared to HC, PSAC had increased FC values between left REC and left inferior occipital gyrus (IOG) (Fig. 2 A and Table 3 ), while FC values increased between left REC and left middle occipital gyrus (MOG), right REC, and left calcarine fissure (CAL) (Fig. 2 B and Table 3 ) in PSNC group. We also found FC values significantly decreased between left REC and right REC, and left MTG (Fig. 2 C and Table 3 ) in PSAC compared to PSNC. Table 3 The differences of FC based on ROIs of left REC by post hoc analyses among the three groups. Brain Region (AAL) Peak MNI coordinate Peak T-value Cluster number x y z PSAC > HC Left Inferior occipital gyrus -45 -72 -9 4.7198 60 PSNC > HC Left Middle occipital gyrus -42 -63 3 6.6043 1453 Right Gyrus rectus 6 24 -15 5.0731 139 Left Calcarine fissure and surrounding cortex -6 -69 12 4.4645 105 PSAC < PSNC Right Gyrus rectus 12 39 -21 -3.743 47 Left Middle temporal gyrus -48 -60 15 -4.0370 46 AAL: Automated Anatomical Labeling; FC: Functional Connectivity; HC: Healthy Controls; MNI, Montreal Neurological Institute; PSAC: Post-Stroke with Abnormal Cognition; PSNC: Post-Stroke with Normal Cognition; REC: Gyrus Rectus; ROIs: Regions of Interests. The resultant T-maps were conducted with Gaussian Random Field Theory (GRF) correction for multiple comparisons with voxel p < 0.01, cluster p 30 voxels. 3.4 Association Between Changes in ReHo or FC and Cognitive Function Scores Partial correlation analysis showed that stroke groups' MoCA scores were negatively correlated with ReHo values in the left CBL IX ( r = -0.360, p = 0.005, Fig. 3 A) and right CBL VIII ( r = -0.390, p = 0.002, Fig. 3 B). Altered ReHo in left REC is positively correlated to MoCA ( r = 0.570, p < 0.001, Fig. 3 C). FC between left and right REC is positively correlated with MoCA ( r = 0.576, p < 0.001, Fig. 3 D). While FC between left REC and left MTG is also positively correlated with MoCA ( r = 0.514, p < 0.001, Fig. 3 E) scores. 4. Discussion The goal of our study was to characterize the changes of ReHo and seed-based FC (SBFC) among stroke patients with impaired and normal cognition compared to healthy controls. We also explored the relationship between these changes and clinical cognitive performance. The results demonstrated that regional brain activity and FC changed compared to HC, especially between the two stroke groups. Alterations in ReHo and FC were associated with GCF impairment. These findings may enhance our understanding of the neuro-pathophysiological causes of cognitive impairment in post-stroke patients. First, in comparisons among three groups, both stroke groups had decreased ReHo values in left CBL IX and greater values in frontal and temporal cortex compared to HC group. While the PSNC cases exhibited abnormal spontaneous brain activity in the PoCG and SMA. The left REC SBFC analysis showed altered values in optimal cortex in stroke groups versus HC group. We also set an HC group to confirm prior findings [ 14 , 17 , 23 – 25 ] and compare cognitively normal stroke survivors and healthy individuals. On the contrary, the PSNC group had more spontaneous brain activity fluctuations than the disordered one. This may be due to three factors: first, we hypothesized that the increased and decreased brain regions compensated for each other to balance this cognitively apparent damage, so that their scale scores performed normally. Second, the patients we included mostly were at the subacute stage, and further follow-up to the chronic phase for all the individuals of longitudinal studies are needed. And last, the cognitively normal stroke patients we included had motor and/or swallowing dysfunction, which were quite inevitable. Actually, our focus is on different rs-fMRI performance between stroke groups. First, PSAC group had ReHo value decreased in left REC, increased in left CBL IX and right VIII than PSNC. Previous studies have used ReHo value to indicate brain regional activity variation in cerebrovascular disease patients with cognitive dysfunction [ 12 , 14 , 22 ]. In the present study, subcortical lesions in non-acute stroke patients with cognitive impairment caused localized abnormalities in spontaneous brain activity in the supratentorial core region of the left REC, which also closely correlates with cognitive severity. The REC is a component of the orbitofrontal cortex (OFC) in the medial prefrontal cortex (mPFC) subregion, situated medial to the sulcus bromide at the base of the frontal lobe [ 26 ]. Studies on specific species have demonstrated that different forms and degrees of cognitive impairment are displayed when the mPFC is damaged [ 26 , 27 ]. Among them, the OFC is involved in inhibitory control, and decision-making, emotion and social behavior control [ 28 – 31 ]. However, fewer studies have been conducted only for REC. Interestingly, neurosurgeons have been focusing on cognitive dysfunction in subarachnoid hemorrhage patients, especially those with anterior communicating artery aneurysms (ACoA), who often experience memory loss [ 32 , 33 ] and personality changes after surgery. It is generally believed that the rupture and hemorrhage of the aneurysm may have directly damaged REC and orbital gyrus at the base of the frontal lobe [ 32 ]. Subsequently, specialists identify temporary and long-term negative effect of REC resection in the categories of language and memory recall in patients after surgery for ruptured ACoA [ 34 , 35 ]. Accordingly, excision of the frontal rectus gyrus, which was previously assumed to not impair limb movement or sensory function, is highly susceptible to cognitive problems. Previous research revealed decreased REC grey volume and elevated ReHo rectus gyrus, supporting the role of REC in cognitive function in patients with vascular cognitive impairment [ 15 ] or acute ischemic stroke [ 23 ]. Due to the subjects' inclusion conditions and comparisons with a healthy control group, their outcomes may differ from ours. The cerebellum is now widely considered to be relevant to human cognitive function, including sensorimotor control, language, spatial, emotional, and executive functions [ 36 , 37 ]. Complex cognitive functions, including visuospatial working memory and language-related activity, are linked to activation in the posterior lobes (lobules VI-IX) of the cerebellum [ 36 ]. Early studies found reduced brain activity evaluated by ReHo or fractional amplitude of low-frequency fluctuation (fALFF) in cerebellar infarction and VaMCI patients than HC group [ 38 , 39 ]. Others reported ReHo was higher in the left posterior cerebellum of VCI patients than in the control group and adversely related to MoCA scores in subcortical VCI patients [ 40 , 41 ]. Our findings, which are comparable to those of the VCI, contribute to a wealth of knowledge regarding the involvement of the cerebellum in cognitive performance in stroke. Moreover, ReHo values in left REC were positively correlated with MoCA and negatively in the left and right CBL in all the stroke patients. In other words, the lower the ReHo of the left REC and the higher the ReHo of the CB, the more severe the cognitive function deficit. Consequently, we propose that the two groups show different patterns of spontaneous brain activity, and the left REC and bilateral cerebellar lobules are not common sites of injury but intimately associated with GCF. We made the left REC, bilateral CBL-based whole-brain FC maps for further analysis. The SBCA demonstrated that PSAC patients revealed a significant decreased FC value between left REC and the right REC and left MTG compared to PSNC patients. The FC of REC is still not well described; more research is being done on the mPFC, which is where REC is located. Studies targeting on “first-ever” post-stroke patients' cognitive performance showed conflicting results between the mPFC, a major node of the DMN 41 , and in other brain networks or structures like hippocampus, MTG, and posterior cingulate cortex (PCC) [ 17 , 24 , 25 ]. Additionally, mPFC in anterior DMN performed decreased FC even in subcortical or brainstem strokes [ 42 ]. Divergent methods have been used to explore brain network connections, but mPFC is related to the striato-pallido-thalamo-cortical circuit and frontostriatal circuitry and may result from subcortical lesions affecting connectivity between the PFC regions, including the dorsolateral prefrontal cortex and thalamic nuclei [ 43 , 44 ]. However, few studies focused on the FC of REC in stroke patients. The mPFC may also be involved in visuospatial attention function, including the REC, as evidenced by the manifestation of reduced FC of several mPFC subdistricts with the dorsal attention network nodes and the association with symptom regression [ 45 ], which is consistent with our study. MTG is recognized for its role in language and semantic memory processing [ 46 ], conceptual information retrieval and tool knowledge functions [ 47 ]. We also know that left hemisphere injury commonly causes apraxia [ 48 ], which may be attributed to the left posterior middle temporal gyrus [ 49 ] or an obstruction of the MTG-SMA connection [ 50 ]. Multimodal functional imaging including voxel-based morphometric analysis found significant grey matter volume reductions in MTG in VaMCI patients [ 51 ]. VCI also observed dramatically changed ReHo or ALFF in MTG [ 15 , 52 ]. The whole-brain function network has altered FC pattern and density in MTG, according to fMRI [ 53 – 56 ]. This study applied higher ReHo values in the right MTG of all stroke patients and the left MTG of the PSNC cases compared to HC, suggesting that elevated spontaneous MTG activity in stroke patients represents a compensatory strategy despite significant cognitive impairments. We found decreased FC between left REC and left MTG in PSAC group compared to PSNC group. Our assumption was that the two groups exhibited different brain functional connection patterns considering the left MTG was a specific region of brain damage and may impact functional connectivity in distant mPFC locations. Notably, the FC between left REC and right REC, and left MTG have a positive correlation with cognitive performance. Therefore, we speculate a decrease of the connection between the bilateral REC, the left REC and left MTG may be the diseased brain area related to damaging cognition after stroke. Combining ReHo and FC results, spontaneous brain activity and FC were different within two stroke groups, suggesting that abnormalities in these brain areas and connection with other brain regions after stroke strongly assume cognitive decline. Meanwhile, the ReHo and FC value is significantly correlated with clinical performance. Previous study has shown that post-stroke patients with cognitive deterioration had less consistent localized spontaneous brain activity in bilateral ACC, left PCC, precuneus, and left occipital lobe regions than cognition normal stroke survivors [ 14 ]. In terms of FC, post-stroke patients with cognitive loss had higher executive control network and basal ganglia network FC but lower DMN and fronto-temporal network connection [ 11 , 57 ]. The location and magnitude of the infarction do not entirely explain stroke patients' cognitive impairment, but the stroke lesion's indirect effects on whole-brain function may be the main cause [ 58 ]. This is supported by our findings. Thus, we predicted that declined spontaneous performance and connection of left REC may predominantly contribute to stroke-related cognitive loss. Spontaneously, the CB maybe in order to compensate part of the declined function. Hence, our study provides an important and novel idea that the left REC might be used as a candidate deep target of neuroregulatory techniques for early intervention. 5. Limitations Our study has several limitations. First, to ensure data authenticity, we did not censor all the data for matching demographics between groups, which led to significant differences in education years among the three groups and may confuse our results. Simultaneously, low educational attainment may also contribute to cognitive impairment susceptibility. To avoid this, we conducted all statistical analyses with age, gender, and education level as covariates. Our stroke types were different between the stroke groups, and while previous study [ 16 ] has shown no difference of image performance between ischemic and hemorrhagic strokes, it appears we still need to utilize this as a stratification criterion to investigate this further. And this part of the study is ongoing. Second, since the cross-sectional study design did not detect dynamic changes in ReHo patterns or FC alterations after stroke, long-term studies of these individuals are warranted. Third, the sample size of each group was relatively small. Therefore, replication of these findings in a longitudinal study with a larger sample size is required to confirm our results. Finally, we only utilized scales for overall cognitive function for correlation analysis, so more specific assessments of different cognitive domains will be needed, thus helping to reveal the neuropsychological pathophysiological mechanisms of cognitive impairment in stroke. 6. Conclusion In summary, compared with the PSNC group, the PSAC group showed different patterns of spontaneous brain activity mainly in the left REC, left CBL IX, and right CBL VIII. In addition, whole-brain SBFC demonstrated that the PSAC group showed reduced FC between the left REC and the right REC, and the left MTG. All of these alterations were closely related to the global level of cognitive function. Thus, we predicted that the changed brain regions and functional connections may contribute to cognitive impairment after subcortical non-acute stroke. Meanwhile, the deep prefrontal gyrus and cerebellum are involved in higher brain function, and the left REC may be a candidate target for neuromodulation techniques. Above all, these findings also provide important clues to understand the neuropathophysiological mechanisms of cognitive dysfunction after stroke. Declarations Acknowledgements : We would like to thank ZhiQiang Lin, who assist the fMRI data collection and the preprocessing data work for this study. Conflict of Interest : The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Ethics approval statement The Nanjing Medical University Affiliated Brain Hospital ethics committee approved this study (No. 2022-KY086-01). Patient consent statement All participants gave written informed consent. Funding: This study was funded by the Nanjing Municipal Special Fund Key Project for Health Science and Technology Development (Grant number of ZKX22042), and Nanjing Municipal Special Fund General Project for Health Science and Technology Development (Grant number of YKK22137). Data Availability Statement The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. 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Aberrant brain regional homogeneity and functional connectivity of entorhinal cortex in vascular mild cognitive impairment: a resting-state functional mri study. Front Neurol, 9:1177. Diciotti S, Orsolini S, Salvadori E, Giorgio A, Toschi N, Ciulli S, et al (2017). Resting state fmri regional homogeneity correlates with cognition measures in subcortical vascular cognitive impairment. J Neurol Sci, 373:1-6. Zhuang Y, Shi Y, Zhang J, Kong D, Guo L, Bo G, et al (2021). Neurologic factors in patients with vascular mild cognitive impairment based on fmri. World Neurosurg, 149:461-9. Chen H, Shi M, Zhang H, Zhang YD, Geng W, Jiang L, et al (2019). Different patterns of functional connectivity alterations within the default-mode network and sensorimotor network in basal ganglia and pontine stroke. Med Sci Monit, 25:9585-93. Benjamin P, Lawrence AJ, Lambert C, Patel B, Chung AW, MacKinnon AD, et al (2014). Strategic lacunes and their relationship to cognitive impairment in cerebral small vessel disease. Neuroimage Clin, 4:828-37. Orth L, Meeh J, Gur RC, Neuner I, Sarkheil P (2022). Frontostriatal circuitry as a target for fmri-based neurofeedback interventions: a systematic review. Front Hum Neurosci, 16:933718. Cao L, Ye L, Xie H, Zhang Y, Song W (2022). Neural substrates in patients with visual-spatial neglect recovering from right-hemispheric stroke. Front Neurosci, 16:974653. Papeo L, Agostini B, Lingnau A (2019). The large-scale organization of gestures and words in the middle temporal gyrus. J Neurosci, 39:5966-74. Kable JW, Kan IP, Wilson A, Thompson-Schill SL, Chatterjee A (2005). Conceptual representations of action in the lateral temporal cortex. J Cogn Neurosci, 17:1855-70. Timpert DC, Weiss PH, Vossel S, Dovern A, Fink GR (2015). Apraxia and spatial inattention dissociate in left hemisphere stroke. Cortex, 71:349-58. De Renzi E, Lucchelli F (1988). Ideational apraxia. Brain, 111 ( Pt 5):1173-85. Ramayya AG, Glasser MF, Rilling JK (2010). A dti investigation of neural substrates supporting tool use. Cereb Cortex, 20:507-16. Stebbins GT, Nyenhuis DL, Wang C, Cox JL, Freels S, Bangen K, et al (2008). Gray matter atrophy in patients with ischemic stroke with cognitive impairment. Stroke, 39:785-93. Li C, Yang J, Yin X, Liu C, Zhang L, Zhang X, et al (2015). Abnormal intrinsic brain activity patterns in leukoaraiosis with and without cognitive impairment. Behav Brain Res, 292:409-13. Sun YW, Qin LD, Zhou Y, Xu Q, Qian LJ, Tao J, et al (2011). Abnormal functional connectivity in patients with vascular cognitive impairment, no dementia: a resting-state functional magnetic resonance imaging study. Behav Brain Res, 223:388-94. Yi L, Wang J, Jia L, Zhao Z, Lu J, Li K, et al (2012). Structural and functional changes in subcortical vascular mild cognitive impairment: a combined voxel-based morphometry and resting-state fmri study. Plos One, 7:e44758. Liu J, Wang Q, Liu F, Song H, Liang X, Lin Z, et al (2017). Altered functional connectivity in patients with post-stroke memory impairment: a resting fmri study. Exp Ther Med, 14:1919-28. Li H, Gao S, Jia X, Jiang T, Li K (2021). Distinctive alterations of functional connectivity strength between vascular and amnestic mild cognitive impairment. Neural Plast, 2021:8812490. Liu Ting GXLL (2022). Changes of dmn and ecnin patients with post-strokeearlycognitive impairment based onfunctional magneticresonanceimaging. (In chinese). ChinJ Geriatr Heart Brain Vessel Dis, 24:1164-8. Veldsman M, Cheng HJ, Ji F, Werden E, Khlif MS, Ng KK, et al (2020). Degeneration of structural brain networks is associated with cognitive decline after ischaemic stroke. Brain Commun, 2:a155. Additional Declarations No competing interests reported. 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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-4316301","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":295612205,"identity":"b1375a76-a883-4165-a117-a3850f7fa6ea","order_by":0,"name":"Yao Wang","email":"","orcid":"","institution":"The Affiliated Brain Hospital of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yao","middleName":"","lastName":"Wang","suffix":""},{"id":295612207,"identity":"193d5dd2-2e98-48aa-bac3-6b1d6a0c3e8b","order_by":1,"name":"Wan Liu","email":"","orcid":"","institution":"The Affiliated Brain Hospital of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wan","middleName":"","lastName":"Liu","suffix":""},{"id":295612210,"identity":"4156d1fd-7f1e-42de-810f-289808551b10","order_by":2,"name":"Wenjie Yang","email":"","orcid":"","institution":"The Affiliated Brain Hospital of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wenjie","middleName":"","lastName":"Yang","suffix":""},{"id":295612213,"identity":"d157040d-6f04-4ac3-a4b5-93a4e19db534","order_by":3,"name":"Xue Chai","email":"","orcid":"","institution":"The Affiliated Brain Hospital of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xue","middleName":"","lastName":"Chai","suffix":""},{"id":295612215,"identity":"07f3790d-7f56-4343-bf4c-fe0b34a2df70","order_by":4,"name":"Hao Yu","email":"","orcid":"","institution":"Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"Yu","suffix":""},{"id":295612217,"identity":"7875e8bc-9859-4cf4-9d5a-1fab02597bb8","order_by":5,"name":"Hongxia Ma","email":"","orcid":"","institution":"Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hongxia","middleName":"","lastName":"Ma","suffix":""},{"id":295612219,"identity":"53b56cf9-c254-444a-b205-939b7731aaba","order_by":6,"name":"Li Liu","email":"","orcid":"","institution":"The Affiliated Brain Hospital of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Liu","suffix":""},{"id":295612220,"identity":"72dda2bf-92a5-45e1-8147-5236e61fdd31","order_by":7,"name":"Jiang Rao","email":"","orcid":"","institution":"The Affiliated Brain Hospital of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jiang","middleName":"","lastName":"Rao","suffix":""},{"id":295612222,"identity":"713a3a4f-4770-4044-9fb3-75f3163a6fd3","order_by":8,"name":"GuangXu Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYFAD9gYGAzDjANFaeA6QrEUiAcogpMXgRvo1iZ87ahM33Hx7oOhmG4Mc340Exs8FeLRIzsgpk+w9c9zY4HZegnFuG4Ox5I0EZukZeLTwS+SkSfC2HZMzuJ1jANKSuOFGAhszDx4tbEAtkn/bjvEY3DwD1lJPUAu/RPoxad62GjmDGzxgLQkGhLRI9rxhtpZtO2AseQbosJxzEoYzzzxslsanxeB4+sObb9vqEvuOnzEzzimzkec7nnzwMz4twCgEReBhsL+ALAkgzdiAVwMwoTwAEnUgFvMDAkpHwSgYBaNghAIAQ4pLxVjKao4AAAAASUVORK5CYII=","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":true,"prefix":"","firstName":"GuangXu","middleName":"","lastName":"Xu","suffix":""},{"id":295612224,"identity":"9c1ce3f9-7081-489f-ab6a-91bb5ac34971","order_by":9,"name":"Zhibin Hu","email":"","orcid":"","institution":"Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhibin","middleName":"","lastName":"Hu","suffix":""}],"badges":[],"createdAt":"2024-04-24 07:39:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4316301/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4316301/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55765785,"identity":"5cf39f3b-77d7-4d5a-854b-7c3fca67784d","added_by":"auto","created_at":"2024-05-02 20:08:04","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":517575,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in ReHo among the three groups. Regions exhibiting substantial differences in ReHo values of (\u003cstrong\u003eA\u003c/strong\u003e) PSAC vs. HC group, (\u003cstrong\u003eB\u003c/strong\u003e) PSNC vs. HC group, and (\u003cstrong\u003eC\u003c/strong\u003e) PSAC vs. PSNC group.\u003c/p\u003e\n\u003cp\u003eThe resultant T-maps were conducted with Gaussian Random Field Theory (GRF) correction for multiple comparisons with voxel \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, cluster \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05, and cluster size \u0026gt; 30 voxels.\u003c/p\u003e\n\u003cp\u003eHC: Healthy Controls; PSAC: Post-Stroke with Abnormal Cognition; PSNC: Post-Stroke with Normal Cognition; ReHo: Regional Homogeneity.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4316301/v1/691bf59da623274eb1fc6f80.jpeg"},{"id":55767154,"identity":"c36244f0-ec79-47c9-9fa4-1824af944ded","added_by":"auto","created_at":"2024-05-02 20:16:03","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":511869,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in FC based on ROIs of left REC among the three groups. Regions exhibiting substantial differences in FC values of (\u003cstrong\u003eA\u003c/strong\u003e) PSAC vs. HC group, (\u003cstrong\u003eB\u003c/strong\u003e) PSNC vs. HC group, and (\u003cstrong\u003eC\u003c/strong\u003e) PSAC vs. PSNC group.\u003c/p\u003e\n\u003cp\u003eThe resultant T-maps were conducted with Gaussian Random Field Theory (GRF) correction for multiple comparisons with voxel \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, cluster \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, and cluster size \u0026gt; 30 voxels.\u003c/p\u003e\n\u003cp\u003eFC: Functional Connectivity; HC: Healthy Controls; PSAC: Post-Stroke with Abnormal Cognition; PSNC: Post-Stroke with Normal Cognition; REC: Gyrus Rectus; ROIs: Regions of Interests.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4316301/v1/360d0e3862e7c0bc275455e9.jpeg"},{"id":55765787,"identity":"593e3d64-d484-4ad4-96e5-0a10649bb713","added_by":"auto","created_at":"2024-05-02 20:08:04","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":163533,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlations between \u003cstrong\u003e(A) \u003c/strong\u003ethe mean ReHo value in the left CBL IX. \u003cstrong\u003e(B) \u003c/strong\u003ethe mean ReHo value in the right CBL VIII. \u003cstrong\u003e(C) \u003c/strong\u003ethe mean ReHo value in the left REC. (\u003cstrong\u003eD\u003c/strong\u003e) the FC between left REC and right REC. (\u003cstrong\u003eE\u003c/strong\u003e) the FC between left REC and left MTG and MoCA scores in all stroke patients.\u003c/p\u003e\n\u003cp\u003eCBL: Cerebellum lobules; FC: Functional Connectivity; MoCA: Montreal Cognitive Assessment; MTG: Middle Temporal Gyrus; REC: Gyrus Rectus; ReHo: Regional Homogeneity.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4316301/v1/2618eb4dbef859092c8d4933.jpeg"},{"id":57047235,"identity":"c92976aa-b755-480f-892d-caec988c8a0b","added_by":"auto","created_at":"2024-05-24 01:36:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1973597,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4316301/v1/f623159b-f0c2-4cb1-ba2f-929d2fd74e9a.pdf"},{"id":55765788,"identity":"d558ffe4-1e98-439e-a9aa-7297461939df","added_by":"auto","created_at":"2024-05-02 20:08:04","extension":"zip","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2346635,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementalfiles.zip","url":"https://assets-eu.researchsquare.com/files/rs-4316301/v1/19a6846f14af330065de67d8.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Altered Regional Brain Spontaneous Activity and Functional Connectivity in Patients of Non-Acute Subcortical Stroke With versus Without Cognitive Impairment: A Resting-State fMRI Study.","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCognitive impairment or decline is observed in more than two-thirds of stroke survivors following the event [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This condition presents difficulties in performing routine tasks and may serve as an indicator of an unfavorable prognosis, including suboptimal rehabilitation outcomes, increased mortality, and the potential onset of dementia [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe mechanisms behind functional recovery after stroke remain unclear. Rewiring of surviving brain circuits, vascular restoration, immunomodulation, and endogenous neurogenesis are among the most important considerations cited [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, cognitive decline, unlike motor dysfunction or aphasia, is not entirely attributable to the stroke lesion location, and the patterns and causes are currently being explored. Cerebral infarcts in the frontal, temporal, parietal, and basal ganglia regions and their size are connected with cognitive impairment [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Others contended that lesion size and location cannot explain stroke-related cognitive impairment. Instead, stroke-induced harm transcends regional boundaries and has the potential to interfere with the entirety of the brain network [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecently, resting-state functional magnetic resonance imaging (rs-fMRI) has gained popularity for exploring cognitive impairment neural mechanisms [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Growing investigators employ regional homogeneity (ReHo), which measures temporal synchronization of nearest neighbor time series and can map local spontaneous neural activity [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], for exploring the local neural activities in cerebrovascular diseases. Previous study [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] found decreased ReHo in the precuneus/cuneus and insula; and increased ReHo in the temporal lobe in patients with mild cognitive impairment (MCI) with lacunar infarction (LI), when compared to those without LI. Similarly, post-stroke patients with cognitive dysfunction revealed decreased ReHo in the anterior cingulate cortices (ACC) and posterior cingulate cortices (PCC), and positively correlated with the cognition scores, when compared to those without cognition decline [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Vascular cognitive impairment (VCI) patients exhibit a significant positive correlation between the ReHo value in the middle temporal gyrus (MTG) and short-term delayed memory scores [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Nevertheless, the distribution of brain regions and the correlation and value with cognitive impairment were different, possibly due to the selection of subjects and controls. Meanwhile, we found patients who do not acquire cognitive abnormalities after stroke are not adequately studied for brain changes by fMRI when compared to cognitively impaired and healthy persons.\u003c/p\u003e \u003cp\u003eReHo referred to as short-term connectivity, while functional connectivity (FC) could reflect the time consistency of spontaneous activity between regions and could be used to map long-term connectivity [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Previous studies revealed significant decrease in the default model network (DMN) and salience network [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], while others reported increased brain activity in DMN, frontal, fronto-temporal, and secondary visual network in stroke patients [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. They further found significant impairment in the connectivity including superior frontal gyrus (SFG), PCC, parahippocampal gyrus (PHG) and parietal gyrus [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Nevertheless, there is currently a paucity of knowledge regarding the combination of brain regional activity and further connectivity analysis, which can offer more thorough insight into the brain functional network and contribute to the identification of imaging biomarkers of cognitive dysfunction following a stroke.\u003c/p\u003e \u003cp\u003eHence, we employ rs-fMRI to investigate the changes of ReHo in stroke patients with and without cognitive dysfunction. Then to study the long-term FC patterns in these patients based on the regions where the changed ReHo is situated as the regions of interests (ROIs). Consequently, we hypothesis (1). Post-stroke patients with abnormal cognitive dysfunction have distinct ReHo patterns than those with normal cognition. (2). In addition to altered spontaneous activity in localized brain regions, cognitively impaired participants may also experience changes in patterns of connectivity between brain regions. (3). Changes of ReHo and FC are closely related to clinical cognitive performance.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Subjects\u003c/h2\u003e \u003cp\u003e129 subjects participated in the current study, which included 67 patients with stroke and 62 healthy controls (HC), were recruited from November 2021 to May 2023 at the Department of Rehabilitation Medicine, Nanjing Brain Hospital. Additionally, 62 healthy volunteers were recruited through advertisements and matched to post-stroke patients by age and gender. Stroke patients were included if: (1). adults (18\u0026ndash;80 years old); (2). right-handedness before stroke; (3). first-ever ischemic or hemorrhagic stroke through head computed tomography (CT) or MRI with subcortical region; (4). time after stroke onset over 2 weeks; and (5). absence of serious movement dysfunction. Exclusion criteria for stroke patients and healthy controls (HCs) were: (1) neurodegenerative diseases, epilepsy, mood disorders, traumatic brain injury, or tumor; (2) clinically significant or unstable medical disorder; (3) psychiatric medication that may affect cognitive function; and (4) MRI contraindications. Control subjects with quiet brain infarctions or cognitive disorders that could impact cognitive function and FC activity were excluded.\u003c/p\u003e \u003cp\u003e The Affiliated Brain Hospital to Nanjing Medical University Ethics Committee approved this study (No. 2022-KY086-01). All participants gave written informed consent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Clinical Data, Neuropsychological Tests and Grouping\u003c/h2\u003e \u003cp\u003eThrough surveys and medical records, education years, disease duration since stroke, stroke type, and lesion volume were collected. Participants' global cognitive function (GCF) was measured by the MoCA [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Stroke survivors were divided into post-stroke with abnormal cognition (PSAC) and post-stroke normal cognition (PSNC) subgroups based on MoCA scores. An adjusted MoCA score of less than 24 was recommended to identify cognitively impaired patients [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, three PSAC and two PSNC participants were rejected for excessive head movement. Final enrollment was 62 stroke patients, 32 PSAC and 30 PSNC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Brain MRI Data Acquisition\u003c/h2\u003e \u003cp\u003eMRI acquisition parameters for all individuals were summarized in \u003cb\u003eSupplementary Material\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 MRI Data Analysis\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1 Image Preprocessing\u003c/h2\u003e \u003cp\u003eData Processing Assistant for Resting-State fMRI (DPARSF; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.restfmri.net/forum/DPARSF\u003c/span\u003e\u003cspan address=\"http://www.restfmri.net/forum/DPARSF\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was employed to preprocess data utilizing Statistical Parametric Mapping (SPM8) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.fil.ion.ucl.ac.uk/spm\u003c/span\u003e\u003cspan address=\"http://www.fil.ion.ucl.ac.uk/spm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) in MATLAB environment (Mathworks, Natick, MA, USA). The first 10 volumes of functional images were removed for each patient. Then, the remaining images were corrected using slice-timing and realignment, accounting for head motion, normalized to standard space using DARTEL, resampled to a 3 ⅹ 3 ⅹ 3mm\u003csup\u003e3\u003c/sup\u003e voxel size, regress nuisance variable, and spatially smoothed with 4mm full width at half maximum (FWHM). The nuisance variables include 24 motion parameters (six head motion parameters, six head motion parameters one time point before, and the 12 corresponding squared items), a global signal, a white matter signal, and a cerebrospinal fluid signal. Finally, a temporal filter (0.01\u0026ndash;0.08 Hz) was applied to reduce low-frequency drift and high-frequency physiological noise. In addition, patients with excessive head motion (cumulative translation or rotation\u0026thinsp;\u0026gt;\u0026thinsp;3.0 mm or 3.0) were excluded [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.4.2 ReHo Analysis\u003c/h2\u003e \u003cp\u003eReHo analysis was carried out on the previously mentioned preprocessed pictures. Calculating Kendall's coefficient of concordance of a voxel's time series with its nearest neighbors (26 voxels) produced individual ReHo maps [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Each voxel's ReHo was normalized to the global mean to reduce individual variances. Finally, all the subjects were smoothed using a 6-mm fullwidth at half maximum Gaussian kernel.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.4.3 FC Analysis\u003c/h2\u003e \u003cp\u003eWe employed the different ReHo of brain areas between PSAC and PSNC groups as ROIs for an analysis of seed-based whole-brain FC analysis. Individual mean time series were extracted based on the coregistered seed region as the reference time series. The correlation analyses were conducted on the seed region and the whole brain within the gray matter mask. We used a Fisher\u0026rsquo;s \u003cem\u003er\u003c/em\u003e-to-\u003cem\u003ez\u003c/em\u003e transformation to improve the normality of the correlation coefficients. Therefore, an entire brain \u003cem\u003ez\u003c/em\u003e-score map was developed for each subject for subsequent statistical analyses.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical Analysis\u003c/h2\u003e \u003cp\u003eOne-way analysis of variance (ANOVA) and \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e test were used to compare demographics and cognitive scores between the stroke groups and the HC group using SPSS Statistics 25.0 on continuous variables and proportions, respectively. Statistical significance was determined at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. A one-way analysis of covariance (ANCOVA) was used to compare ReHo and FC among HC, PSAC, and PSNC patients. The two-sample \u003cem\u003et\u003c/em\u003e-test was utilized for post-hoc comparisons of ReHo or FC patterns between stroke and HC groups and within stroke groups. Age, gender, education, head motion parameters and grey matter volume were covariables for three groups. For stroke groups, we added lesion volume, disease duration, and stroke type as covariates. The resultant T-maps were conducted with Gaussian Random Field Theory (GRF) correction for multiple comparisons with voxel \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, cluster \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Finally, extracted ReHo or FCs of significantly changed regions were used for correlation analysis. After controlling for age, gender, and education, partial correlation analyses revealed associations between altered ReHo or FCs and MoCA scores. Due to the small sample size, we did not modify correlation analysis results for multiple comparisons to improve presentation.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Demographic and Neuropsychological Characteristics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e showed all case features. Age, gender, disease duration, and lesion size were comparable among three groups. The lesion location was applied in Supplementary Fig.\u0026nbsp;1. The PSAC group had lower years of education (9.56\u0026thinsp;\u0026plusmn;\u0026thinsp;4.27) compared to the HC (12.50\u0026thinsp;\u0026plusmn;\u0026thinsp;2.76, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and PSNC (12.53\u0026thinsp;\u0026plusmn;\u0026thinsp;3.38, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) groups. Additionally, stroke types differed between the PSAC (Ischemic/Hemorrhagic: 18/14) and PSNC (I/H: 26/4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008) groups. MoCA scores were considerably lower in PSAC (11.31\u0026thinsp;\u0026plusmn;\u0026thinsp;5.28) compared to HC (25.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and PSNC (26.60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.81, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics of stroke patients and healthy controls\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHCs\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAll SPs\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePSAC\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;32)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSNC\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eF/t/χ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (M/F), n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36/26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37/25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18/14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19/11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.033\u003csup\u003e\u0026dagger;\u003c/sup\u003e, 0.354\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.855\u003csup\u003e\u0026dagger;\u003c/sup\u003e, 0.838\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD), years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.95\u0026thinsp;\u0026plusmn;\u0026thinsp;6.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.61\u0026thinsp;\u0026plusmn;\u0026thinsp;10.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.59\u0026thinsp;\u0026plusmn;\u0026thinsp;10.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.50\u0026thinsp;\u0026plusmn;\u0026thinsp;10.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.869\u003csup\u003e\u0026dagger;\u003c/sup\u003e, 2.184\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.387\u003csup\u003e\u0026dagger;\u003c/sup\u003e, 0.117\u003csup\u003e\u0026Dagger;\u003c/sup\u003e, 0.729\u003csup\u003e\u0026sect;\u003c/sup\u003e, 0.070\u003csup\u003e\u0026para;\u003c/sup\u003e, 0.060\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation years (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD), years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.50\u0026thinsp;\u0026plusmn;\u0026thinsp;2.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.56\u0026thinsp;\u0026plusmn;\u0026thinsp;4.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.53\u0026thinsp;\u0026plusmn;\u0026thinsp;3.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.382\u003csup\u003e\u0026dagger;\u003c/sup\u003e, 9.163\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026dagger;*\u003c/b\u003e\u003c/sup\u003e, \u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026Dagger;*\u003c/b\u003e\u003c/sup\u003e, \u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026sect;*\u003c/b\u003e\u003c/sup\u003e, 0.964\u003csup\u003e\u0026para;\u003c/sup\u003e, \u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e#*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.056\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.168\u003csup\u003e\u003cb\u003e#\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 weeks \u0026minus;\u0026thinsp;1 month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;3 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;6 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOver 6 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroke type (Ischemic/ Hemorrhagic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44/18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18/14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26/4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.953\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003csup\u003e\u003cb\u003e#*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLesion volume (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD), ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.75\u0026thinsp;\u0026plusmn;\u0026thinsp;10.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.21\u0026thinsp;\u0026plusmn;\u0026thinsp;14.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.12\u0026thinsp;\u0026plusmn;\u0026thinsp;4.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1.888\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.064\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.71\u0026thinsp;\u0026plusmn;\u0026thinsp;8.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.31\u0026thinsp;\u0026plusmn;\u0026thinsp;5.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.258\u003csup\u003e\u0026dagger;\u003c/sup\u003e, 264.621\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u0026dagger;\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e, \u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026Dagger;*\u003c/b\u003e\u003c/sup\u003e, \u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026sect;*\u003c/b\u003e\u003c/sup\u003e, 0.228\u003csup\u003e\u0026para;\u003c/sup\u003e, \u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e#*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eF: Female; HC: Healthy Controls; M: Male; MoCA: Montreal Cognitive Assessment; PSAC: Post-Stroke with Abnormal Cognition; PSNC: Post-Stroke with Normal Cognition; SP: Stroke Patients.\u003c/p\u003e \u003cp\u003e\u0026dagger;. Represents comparison of HC vs. all stroke patients, \u0026Dagger;. Represents comparison in HC, PSAC and PSNC groups; \u0026sect;. Represents comparison of HC vs. PSAC; \u0026para;. Represents comparison of HC vs. PSNC; #. Represents comparison of PSAC vs. PSNC.\u003c/p\u003e \u003cp\u003e* Significant differences were found, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Comparisons of ReHo values\u003c/h2\u003e \u003cp\u003eThe three groups had significantly different ReHo across brain regions by ANCOVA, as shown in Supplemental Fig.\u0026nbsp;2 and Supplemental Table\u0026nbsp;1. ReHo study indicated that both stroke groups had a significant increase in the right SFG, right MTG, and decrease in right postcentral gyrus (PoCG) and left cerebellar lobules (CBL) IX compared to the HC group. The PSAC group exhibit significantly increased ReHo values in bilateral inferior temporal gyrus (ITG) than the HC group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Compared to the HC group, PSNC showed remarkably increased ReHo in the left MTG, left middle frontal gyrus (MFG), left inferior frontal gyrus (IFG), right supplementary motor area (SMA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The left gyrus rectus (REC) ReHo value deceased in the PSAC than PSNC group, but ReHo in the left CBL IX and right CBL VIII increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe differences in the brain regions of ReHo by post hoc analyses among the three groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBrain Region (AAL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ePeak MNI coordinate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePeak T-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCluster number\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ey\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ez\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePSAC\u0026thinsp;\u0026lt;\u0026thinsp;HC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft Cerebellar obules IX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-4.2431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight Postcentral gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-4.0183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePSAC\u0026thinsp;\u0026gt;\u0026thinsp;HC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight Middle temporal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.5295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft Inferior temporal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.0988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight Inferior temporal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.2676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight Superior frontal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.8463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePSNC\u0026thinsp;\u0026lt;\u0026thinsp;HC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft Cerebellar lobules IX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-6.0934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e811\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight Postcentral gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-5.0586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e243\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePSNC\u0026thinsp;\u0026gt;\u0026thinsp;HC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft Middle temporal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.1397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e340\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight Middle temporal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.3146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e314\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft Inferior frontal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.0293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e529\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight Superior frontal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.8441\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e294\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft Middle frontal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.0466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e423\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight Supplementary motor area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.4843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePSAC\u0026thinsp;\u0026lt;\u0026thinsp;PSNC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft Gyrus rectus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-4.2535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePSAC\u0026thinsp;\u0026gt;\u0026thinsp;PSNC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft Cerebellar lobules IX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.9683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight Cerebellar lobules VIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.9663\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e AAL: Automated Anatomical Labeling; HC: Healthy Controls; MNI, Montreal Neurological Institute; PSAC: Post-Stroke with Abnormal Cognition; PSNC: Post-Stroke with Normal Cognition; ReHo: Regional Homogeneity.\u003c/p\u003e \u003cp\u003eThe resultant T-maps were conducted with Gaussian Random Field Theory (GRF) correction for multiple comparisons with voxel \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, cluster \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and cluster size\u0026thinsp;\u0026gt;\u0026thinsp;30 voxels.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Comparison of FC\u003c/h2\u003e \u003cp\u003eThe brain areas with significant clusters of strokes related ReHo changes were designated as ROIs, including left REC, left CBL IX, and right CBL VIII. However, only ROI in left REC showed significant brain region alterations, as shown in Supplemental Table\u0026nbsp;2 for ANCOVA comparison among three groups. Compared to HC, PSAC had increased FC values between left REC and left inferior occipital gyrus (IOG) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), while FC values increased between left REC and left middle occipital gyrus (MOG), right REC, and left calcarine fissure (CAL) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) in PSNC group. We also found FC values significantly decreased between left REC and right REC, and left MTG (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) in PSAC compared to PSNC.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe differences of FC based on ROIs of left REC by post hoc analyses among the three groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBrain Region (AAL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ePeak MNI coordinate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePeak T-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCluster number\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ey\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ez\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePSAC\u0026thinsp;\u0026gt;\u0026thinsp;HC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft Inferior occipital gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.7198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePSNC\u0026thinsp;\u0026gt;\u0026thinsp;HC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft Middle occipital gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.6043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1453\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight Gyrus rectus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.0731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft Calcarine fissure and surrounding cortex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.4645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePSAC\u0026thinsp;\u0026lt;\u0026thinsp;PSNC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight Gyrus rectus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-3.743\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft Middle temporal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-4.0370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAAL: Automated Anatomical Labeling; FC: Functional Connectivity; HC: Healthy Controls; MNI, Montreal Neurological Institute; PSAC: Post-Stroke with Abnormal Cognition; PSNC: Post-Stroke with Normal Cognition; REC: Gyrus Rectus; ROIs: Regions of Interests.\u003c/p\u003e \u003cp\u003eThe resultant T-maps were conducted with Gaussian Random Field Theory (GRF) correction for multiple comparisons with voxel \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, cluster \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and cluster size\u0026thinsp;\u0026gt;\u0026thinsp;30 voxels.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e3.4 Association Between Changes in ReHo or FC and Cognitive Function Scores\u003c/b\u003e\u003c/h2\u003e \u003cp\u003ePartial correlation analysis showed that stroke groups' MoCA scores were negatively correlated with ReHo values in the left CBL IX (\u003cem\u003er\u003c/em\u003e = -0.360, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA) and right CBL VIII (\u003cem\u003er\u003c/em\u003e = -0.390, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Altered ReHo in left REC is positively correlated to MoCA (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.570, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eFC between left and right REC is positively correlated with MoCA (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.576, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). While FC between left REC and left MTG is also positively correlated with MoCA (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.514, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE) scores.\u003c/p\u003e "},{"header":"4. Discussion","content":"\u003cp\u003eThe goal of our study was to characterize the changes of ReHo and seed-based FC (SBFC) among stroke patients with impaired and normal cognition compared to healthy controls. We also explored the relationship between these changes and clinical cognitive performance. The results demonstrated that regional brain activity and FC changed compared to HC, especially between the two stroke groups. Alterations in ReHo and FC were associated with GCF impairment. These findings may enhance our understanding of the neuro-pathophysiological causes of cognitive impairment in post-stroke patients.\u003c/p\u003e \u003cp\u003eFirst, in comparisons among three groups, both stroke groups had decreased ReHo values in left CBL IX and greater values in frontal and temporal cortex compared to HC group. While the PSNC cases exhibited abnormal spontaneous brain activity in the PoCG and SMA. The left REC SBFC analysis showed altered values in optimal cortex in stroke groups versus HC group. We also set an HC group to confirm prior findings [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and compare cognitively normal stroke survivors and healthy individuals. On the contrary, the PSNC group had more spontaneous brain activity fluctuations than the disordered one. This may be due to three factors: first, we hypothesized that the increased and decreased brain regions compensated for each other to balance this cognitively apparent damage, so that their scale scores performed normally. Second, the patients we included mostly were at the subacute stage, and further follow-up to the chronic phase for all the individuals of longitudinal studies are needed. And last, the cognitively normal stroke patients we included had motor and/or swallowing dysfunction, which were quite inevitable.\u003c/p\u003e \u003cp\u003eActually, our focus is on different rs-fMRI performance between stroke groups. First, PSAC group had ReHo value decreased in left REC, increased in left CBL IX and right VIII than PSNC. Previous studies have used ReHo value to indicate brain regional activity variation in cerebrovascular disease patients with cognitive dysfunction [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In the present study, subcortical lesions in non-acute stroke patients with cognitive impairment caused localized abnormalities in spontaneous brain activity in the supratentorial core region of the left REC, which also closely correlates with cognitive severity. The REC is a component of the orbitofrontal cortex (OFC) in the medial prefrontal cortex (mPFC) subregion, situated medial to the sulcus bromide at the base of the frontal lobe [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Studies on specific species have demonstrated that different forms and degrees of cognitive impairment are displayed when the mPFC is damaged [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Among them, the OFC is involved in inhibitory control, and decision-making, emotion and social behavior control [\u003cspan additionalcitationids=\"CR29 CR30\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, fewer studies have been conducted only for REC.\u003c/p\u003e \u003cp\u003eInterestingly, neurosurgeons have been focusing on cognitive dysfunction in subarachnoid hemorrhage patients, especially those with anterior communicating artery aneurysms (ACoA), who often experience memory loss [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] and personality changes after surgery. It is generally believed that the rupture and hemorrhage of the aneurysm may have directly damaged REC and orbital gyrus at the base of the frontal lobe [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Subsequently, specialists identify temporary and long-term negative effect of REC resection in the categories of language and memory recall in patients after surgery for ruptured ACoA [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Accordingly, excision of the frontal rectus gyrus, which was previously assumed to not impair limb movement or sensory function, is highly susceptible to cognitive problems. Previous research revealed decreased REC grey volume and elevated ReHo rectus gyrus, supporting the role of REC in cognitive function in patients with vascular cognitive impairment [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] or acute ischemic stroke [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Due to the subjects' inclusion conditions and comparisons with a healthy control group, their outcomes may differ from ours.\u003c/p\u003e \u003cp\u003eThe cerebellum is now widely considered to be relevant to human cognitive function, including sensorimotor control, language, spatial, emotional, and executive functions [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Complex cognitive functions, including visuospatial working memory and language-related activity, are linked to activation in the posterior lobes (lobules VI-IX) of the cerebellum [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Early studies found reduced brain activity evaluated by ReHo or fractional amplitude of low-frequency fluctuation (fALFF) in cerebellar infarction and VaMCI patients than HC group [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Others reported ReHo was higher in the left posterior cerebellum of VCI patients than in the control group and adversely related to MoCA scores in subcortical VCI patients [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Our findings, which are comparable to those of the VCI, contribute to a wealth of knowledge regarding the involvement of the cerebellum in cognitive performance in stroke.\u003c/p\u003e \u003cp\u003eMoreover, ReHo values in left REC were positively correlated with MoCA and negatively in the left and right CBL in all the stroke patients. In other words, the lower the ReHo of the left REC and the higher the ReHo of the CB, the more severe the cognitive function deficit. Consequently, we propose that the two groups show different patterns of spontaneous brain activity, and the left REC and bilateral cerebellar lobules are not common sites of injury but intimately associated with GCF.\u003c/p\u003e \u003cp\u003eWe made the left REC, bilateral CBL-based whole-brain FC maps for further analysis. The SBCA demonstrated that PSAC patients revealed a significant decreased FC value between left REC and the right REC and left MTG compared to PSNC patients.\u003c/p\u003e \u003cp\u003eThe FC of REC is still not well described; more research is being done on the mPFC, which is where REC is located. Studies targeting on \u0026ldquo;first-ever\u0026rdquo; post-stroke patients' cognitive performance showed conflicting results between the mPFC, a major node of the DMN \u003csup\u003e41\u003c/sup\u003e, and in other brain networks or structures like hippocampus, MTG, and posterior cingulate cortex (PCC) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Additionally, mPFC in anterior DMN performed decreased FC even in subcortical or brainstem strokes [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Divergent methods have been used to explore brain network connections, but mPFC is related to the striato-pallido-thalamo-cortical circuit and frontostriatal circuitry and may result from subcortical lesions affecting connectivity between the PFC regions, including the dorsolateral prefrontal cortex and thalamic nuclei [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, few studies focused on the FC of REC in stroke patients. The mPFC may also be involved in visuospatial attention function, including the REC, as evidenced by the manifestation of reduced FC of several mPFC subdistricts with the dorsal attention network nodes and the association with symptom regression [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], which is consistent with our study.\u003c/p\u003e \u003cp\u003eMTG is recognized for its role in language and semantic memory processing [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], conceptual information retrieval and tool knowledge functions [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. We also know that left hemisphere injury commonly causes apraxia [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], which may be attributed to the left posterior middle temporal gyrus [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] or an obstruction of the MTG-SMA connection [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Multimodal functional imaging including voxel-based morphometric analysis found significant grey matter volume reductions in MTG in VaMCI patients [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. VCI also observed dramatically changed ReHo or ALFF in MTG [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. The whole-brain function network has altered FC pattern and density in MTG, according to fMRI [\u003cspan additionalcitationids=\"CR54 CR55\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. This study applied higher ReHo values in the right MTG of all stroke patients and the left MTG of the PSNC cases compared to HC, suggesting that elevated spontaneous MTG activity in stroke patients represents a compensatory strategy despite significant cognitive impairments. We found decreased FC between left REC and left MTG in PSAC group compared to PSNC group. Our assumption was that the two groups exhibited different brain functional connection patterns considering the left MTG was a specific region of brain damage and may impact functional connectivity in distant mPFC locations. Notably, the FC between left REC and right REC, and left MTG have a positive correlation with cognitive performance. Therefore, we speculate a decrease of the connection between the bilateral REC, the left REC and left MTG may be the diseased brain area related to damaging cognition after stroke.\u003c/p\u003e \u003cp\u003eCombining ReHo and FC results, spontaneous brain activity and FC were different within two stroke groups, suggesting that abnormalities in these brain areas and connection with other brain regions after stroke strongly assume cognitive decline. Meanwhile, the ReHo and FC value is significantly correlated with clinical performance. Previous study has shown that post-stroke patients with cognitive deterioration had less consistent localized spontaneous brain activity in bilateral ACC, left PCC, precuneus, and left occipital lobe regions than cognition normal stroke survivors [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In terms of FC, post-stroke patients with cognitive loss had higher executive control network and basal ganglia network FC but lower DMN and fronto-temporal network connection [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. The location and magnitude of the infarction do not entirely explain stroke patients' cognitive impairment, but the stroke lesion's indirect effects on whole-brain function may be the main cause [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. This is supported by our findings. Thus, we predicted that declined spontaneous performance and connection of left REC may predominantly contribute to stroke-related cognitive loss. Spontaneously, the CB maybe in order to compensate part of the declined function. Hence, our study provides an important and novel idea that the left REC might be used as a candidate deep target of neuroregulatory techniques for early intervention.\u003c/p\u003e"},{"header":"5. Limitations","content":"\u003cp\u003eOur study has several limitations. First, to ensure data authenticity, we did not censor all the data for matching demographics between groups, which led to significant differences in education years among the three groups and may confuse our results. Simultaneously, low educational attainment may also contribute to cognitive impairment susceptibility. To avoid this, we conducted all statistical analyses with age, gender, and education level as covariates. Our stroke types were different between the stroke groups, and while previous study [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] has shown no difference of image performance between ischemic and hemorrhagic strokes, it appears we still need to utilize this as a stratification criterion to investigate this further. And this part of the study is ongoing. Second, since the cross-sectional study design did not detect dynamic changes in ReHo patterns or FC alterations after stroke, long-term studies of these individuals are warranted. Third, the sample size of each group was relatively small. Therefore, replication of these findings in a longitudinal study with a larger sample size is required to confirm our results. Finally, we only utilized scales for overall cognitive function for correlation analysis, so more specific assessments of different cognitive domains will be needed, thus helping to reveal the neuropsychological pathophysiological mechanisms of cognitive impairment in stroke.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eIn summary, compared with the PSNC group, the PSAC group showed different patterns of spontaneous brain activity mainly in the left REC, left CBL IX, and right CBL VIII. In addition, whole-brain SBFC demonstrated that the PSAC group showed reduced FC between the left REC and the right REC, and the left MTG. All of these alterations were closely related to the global level of cognitive function. Thus, we predicted that the changed brain regions and functional connections may contribute to cognitive impairment after subcortical non-acute stroke. Meanwhile, the deep prefrontal gyrus and cerebellum are involved in higher brain function, and the left REC may be a candidate target for neuromodulation techniques. Above all, these findings also provide important clues to understand the neuropathophysiological mechanisms of cognitive dysfunction after stroke.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe would like to thank ZhiQiang Lin, who assist the fMRI data collection and the preprocessing data work for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Nanjing Medical University Affiliated Brain Hospital ethics committee approved this study (No. 2022-KY086-01).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants gave written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Nanjing\u0026nbsp;Municipal Special Fund Key Project for Health Science and Technology Development\u0026nbsp;(Grant number of ZKX22042), and\u0026nbsp;Nanjing\u0026nbsp;Municipal Special Fund General Project for Health Science and Technology Development\u0026nbsp;(Grant number of YKK22137).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eQu Y, Zhuo L, Li N, Hu Y, Chen W, Zhou Y, et al (2015). 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Brain Commun, 2:a155.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"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, Cognitive impairment, Functional magnetic resonance imaging, Regional homogeneity, Functional connectivity, Gyrus rectus, Cerebellum","lastPublishedDoi":"10.21203/rs.3.rs-4316301/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4316301/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe reasons why not all stroke survivors have cognitive dysfunction are unclear. We hypothesize that resting-state fMRI (rs-fMRI) will reveal differences in regional brain spontaneous activity and functional connectivity (FC) in stroke patients with and without cognitive impairment. We classified 62 first-ever non-acute subcortical stroke patients into two groups: post-stroke with abnormal cognition (PSAC) and with normal cognition (PSNC). Rs-MRI was utilized to assess regional homogeneity (ReHo) in 32 PSAC, 30 PSNC, and 62 age- and sex-matched healthy controls. We set regions with significant alteration within stroke groups as regions of interest and performed the seed-based whole brain FC analysis. A partial correlation analysis examined the relationship between altered ReHo or FC and Montreal Cognitive Assessment (MoCA) scores. Compared to PSNC, PSAC had decreased ReHo in the left gyrus rectus (REC) and increased ReHo in cerebellar lobules (CBL) left IX and right VIII, while FC decreased in PSAC between bilateral REC, and between the left REC and the middle temporal gyrus (MTG). In all stroke patients, ReHo value in the left REC correlated positively and in the CBL correlated negatively with MoCA. All the significant FC correlated with MoCA positively. Regional brain spontaneous activity and FC alteration in the REC, MTG, and cerebellum may be associated with cognitive impairment following non-acute subcortical stroke.\u003c/p\u003e","manuscriptTitle":"Altered Regional Brain Spontaneous Activity and Functional Connectivity in Patients of Non-Acute Subcortical Stroke With versus Without Cognitive Impairment: A Resting-State fMRI Study.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-02 20:07:59","doi":"10.21203/rs.3.rs-4316301/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":"d667a8e4-3bcd-4bd7-8352-7205de2ce3e9","owner":[],"postedDate":"May 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-29T09:11:28+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-02 20:07:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4316301","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4316301","identity":"rs-4316301","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}