Cognitive Impairments and Neurofunctional Alterations in Children with ESES: Insights from WISC-IV and Resting-State fMRI

Cognitive Impairments and Neurofunctional Alterations in Children with ESES: Insights from WISC-IV and Resting-State fMRI | 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 Cognitive Impairments and Neurofunctional Alterations in Children with ESES: Insights from WISC-IV and Resting-State fMRI Tong Mo, Xiaoyu Wang, Jingjing Luo, Jieqiong Lin, Xianlei Meng, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5500538/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background Electrical Status Epilepticus During Sleep (ESES) is a rare pediatric epilepsy syndrome characterized by sleep-induced epileptiform discharges, leading to cognitive and behavioral impairments. We aimed to investigate the underlying neural mechanisms that are critical for advancing early diagnosis and targeted interventions. Methods Twenty-five children with ESES and 30 age- and sex-matched healthy controls were enrolled. Cognitive function was assessed via the Wechsler Intelligence Scale for Children, Fourth Edition (WISC-IV), focusing on Full-Scale IQ (FSIQ), Verbal Comprehension Index (VCI), Perceptual Reasoning Index (PRI), Working Memory Index (WMI), and Processing Speed Index (PSI). Resting-state functional MRI (rs-fMRI) was conducted to evaluate neural activity via regional homogeneity (ReHo) analysis. Correlations between ReHo values and cognitive scores were analyzed in the ESES group. Results Compared with healthy controls, children with ESES presented significantly lower FSIQ and PRI scores (P = 0.017, P = 0.016), indicating cognitive impairments in global intellectual abilities and perceptual reasoning. rs-fMRI revealed decreased ReHo in the left Superior Frontal Gyrus (premotor area), bilateral postcentral gyri (primary somatosensory cortex), right cerebellum posterior, and rolandic operculum. In contrast, increased ReHo was observed in the left precuneus and left middle frontal gyrus. ReHo in the right postcentral gyrus showed a positive correlation with FSIQ and VCI scores (r = 0.56, P = 0.01; r = 0.67, P < 0.001). Conclusions ESES is associated with significant cognitive deficits, particularly in perceptual reasoning and verbal comprehension, alongside altered neural activity patterns. ReHo analysis revealed changes in local neural activity within key brain regions linked to cognitive function. These findings highlight the potential of rs-fMRI metrics as biomarkers for assessing cognitive impairments and guiding therapeutic interventions in ESES. Electrical Status Epilepticus During Sleep Cognitive Impairment Wechsler Intelligence Scale for Children Resting-State Functional MRI Regional Homogeneity Figures Figure 1 Figure 2 Figure 3 1. Background Electrical Status Epilepticus during Sleep (ESES) is an age-dependent epileptic encephalopathy characterized by significant sleep-induced epileptiform discharges (spike-wave index ≥ 85%) and acquired cognitive or behavioral deficits [ 1 – 3 ]. As a rare but impactful syndrome, ESES poses a major threat to neurodevelopment, with prolonged activity often leading to enduring impairments in language, memory, and executive functions, even after seizure remission [ 4 – 7 ]. Consequently, elucidating the neural mechanisms underlying cognitive dysfunction in ESES is critical for advancing early diagnosis and targeted interventions. While traditional neuropsychological scales, such as the Wechsler Intelligence Scale for Children (WISC), provide valuable assessments of cognitive domains and are recognized for their comprehensiveness and reliability [ 8 , 9 ], they are limited by subjectivity and an inherent inability to detect deficits before they become clinically overt [ 10 ]. There is, therefore, an urgent need for objective biomarkers that can precisely quantify neural alterations associated with ESES-related cognitive impairment. Resting-state functional magnetic resonance imaging (rs-fMRI) offers a powerful, non-invasive window into brain function, enabling the investigation of neural circuits and cognitive processes [ 11 – 13 ]. Among its analytical methods, Regional Homogeneity (ReHo) is particularly suited for investigating local neural synchrony and has been widely used to identify localized brain dysfunction in various neurological and psychiatric disorders [ 14 – 16 ]. By measuring the temporal synchronization of neural activity within a given brain region, ReHo can reveal subtle alterations in local brain function that may serve as sensitive biomarkers. Guided by this rationale, the present study integrated the WISC-IV and rs-fMRI-based ReHo analysis to investigate the relationship between cognitive deficits and localized neural dysfunction in children with ESES. We aimed to (1) identify specific brain regions with altered ReHo in ESES patients compared to matched healthy controls, and (2) explore the correlations between these neurofunctional alterations and deficits in specific cognitive domains as measured by the WISC-IV. We hypothesize that ESES is associated with distinct patterns of abnormal local neural activity, which are linked to the characteristic cognitive profile of the syndrome. 2. Methods 2.1 Participants 2.1.1 ESES Group A cohort of twenty-five children diagnosed with ESES was recruited from Shenzhen Children's Hospital. The sample comprised 13 males and 12 females, aged between 6.75 and 12.33 years (mean age = 8.57 ± 1.99 years; refer to Table 1 ). All patients had a history of epileptic seizures before meeting the ESES diagnostic criteria, with seizure types including focal seizures (e.g., motor seizures, asymmetric tonic/clonic seizure), generalized seizures (e.g., absence, myoclonic, atonic), and characteristic negative seizures like aphasia. The EEG findings include: scattered focal spike-and-wave discharges during wakefulness, replacement of the background by diffuse and continuous spike-and-wave activity during non-rapid eye movement (NREM) sleep, and significant reduction of discharges during rapid eye movement (REM) sleep. The duration of illness was defined as the time from the definitive diagnosis of ESES to the study assessment. The mean duration from diagnosis to the study assessments (WISC-IV and fMRI) was 3.31 ± 2.02 years. The inclusion criteria for this study were as follows: a. Age between 6 and 16 years, of Han nationality, with no specifications regarding gender. b. Established right-handedness. c. The diagnosis of Electrical Status Epilepticus during Sleep (ESES) was established based on the consensus criteria proposed by the International League Against Epilepsy (ILAE). The inclusion criteria for the ESES group were as follows: ①EEG Criterion:​​ The presence of a marked increase in epileptiform activity during non-rapid eye movement (NREM) sleep, characterized by a ​Spike-Wave Index (SWI) of ≥ 85%​. The SWI is defined as the percentage of NREM sleep time occupied by near-continuous spike-wave discharges. ②Clinical Criterion:​​ The presence of ​cognitive regression/decline, ​behavioral disturbances, and/or ​motor deficits​ (e.g., ataxia, dyspraxia). ③Epilepsy Criterion:​​ The presence of seizures, which are typically mild and infrequent, and may include focal motor, generalized tonic-clonic, or atypical absence seizures. d. Negative findings on MRI. Conversely, the exclusion criteria included the following: a. the presence of systemic diseases or other neurological disorders. b. contraindications for undergoing MRI. c. Inability to comply with examination protocols. The demographic and clinical characteristics of the participants are summarized in Table 1 . 2.1.2 Healthy Controls (HCs) Thirty volunteers were recruited for this study and were matched in terms of age, sex, and handedness. The cohort comprised 17 boys and 13 girls, with ages ranging from 6.42–12 years, and a mean age of years (mean age = 9.50 ± 0.80 years; refer to Table 1 ). Table 1 Demographic and clinical data of the ESES patients and HCs Characteristics ESES HC Z P Number 25 30 Gender 1.000 a Male 13(52%) 17(57%) Female 12(48%) 13(43%) Age (m ± std, year) 8.57 ± 1.99 9.50 ± 1.80 -1.139 b 0.266 Parents’ Education(year) \(\:\le\:12\) 50% 43.7% \(\:\ge\:13\) 50% 56.3% Right Hand 25(100%) 30(100%) Han Nationality 25(100%) 30(100%) Onset Age (year) 5.26 ± 2.70 / Duration (year) 3.31 ± 2.02 / Numbers of Asm c / 0 4(16%) 1 9(36%) 2 6(24%) \(\:\ge\:\:\) 3 6(24%) 2.2.1 Intelligence assessment All the subjects enrolled in the study were tested for cognitive function via the WISC-IV, by professionals with more than 10 years of work experience in the Psychology Department of Shenzhen Children's Hospital. The test content includes 10 core subtests and 5 supplementary subtests: Similarities, Vocabulary, Comprehension, Block Design, Picture Concepts, Matrix Reasoning, Digit Span, Letter-Number Sequencing, Coding, Symbol Search, Information, Word Reasoning, etc., each with a population mean of 10 and a standard deviation of 3. The core subtests are used to create four index scores: VCI, PRI, WMI, and PSI. The FSIQ is computed from all 10 core subtests. The factor indices and FSIQ each have a population mean of 100 and a standard deviation of 15. The standard level or percentage level is used to indicate the cognitive level of each subject. 2.2.2 MR Data Acquisition Conventional structural images and eye-open resting-state functional MRI data were collected via the Siemens MAGNETOM Skyra 3.0T superconducting magnetic resonance imaging system (Siemens Healthcare, Germany) and standard head coils. The subjects were placed in the supine position, their ears were stuffed with ear pads to reduce noise effects, and their heads were fixed with spongy pads to reduce head movement. A "+" on the large screen on the side of the head was observed through a mirror attached to the head coil. Before the examination, the subjects were informed of relevant matters needing attention and told that they would stay still. 2.2.2.1 Conventional structural image acquisition Conventional structural images include axial T1WI (t1_tirm_dark-fluid, TR = 200 ms, TE = 2.49 ms), T2WI (t2_tse_tra, TR = 3800 ms, TE = 112 ms), and FLAIR (t2_tirm_tra_dark-fluid, TR = 9000 ms, TE = 81ms, TI = 2500 ms). 2.2.2.2 rs-fMRI data acquisition a. rs-fMRI data were acquired by using an echo planar imaging sequence with the following parameters: 32 axial slices, 130 Volumes, Slice Thickness = 3.0 mm, Repetition Time = 2000 ms, Echo Time = 30 ms, voxel size = 3.0×3.0×3.0 mm 3 , and Flip angle = 90. b. Anatomical data: Three-dimensional magnetization prepared rapid acquisition gradient echo sequences with the following parameters: 176 sagittal slices, Slice Thickness = 1.0 mm, Spacing Between Slices = 0.5, Repetition Time = 2300 ms, Echo Time = 2.26 ms, voxel size = 1.0×1.0×1.0 mm 3 . 2.3 Data processing and analyses 2.3.1 WISC-Ⅳ data analysis All the data were analyzed by using GraphPad Prism (version 9) software. Before data analysis, the normal distribution test (Shapiro-Wilk test) and homogeneity of variance test were performed on all the data. a. A nonparametric rank sum test was used to compare the scale scores between groups. b. Spearman rank correlation analysis was used to analyze the correlation between the score and variables such as examination age and course of disease. The significance level threshold was set as 0.05. If P < 0.05, the difference or correlation between the groups was considered statistically significant. 2.3.2 fMRI data processing The data were preprocessed and analyzed using REST based on SPM12 ( http://restfmri.net/forum/index.php , http://www.fil.ion.ucl.ac.uk/spm/ ). The first 10 time points of each subject’s rs-fMRI data were discarded because of the instability of the initial MRI signal. The remaining 120 volumes were first realigned to correct for head motion before being corrected by the acquisition time delay among different slices. Data preprocessing includes: (1) Slice timing, (2) Realignment, (3) Spatial smoothing, (4) Coregistration, (5) Normalization (voxel size 3×3×3 mm 3 ), and (6) Filtering. Any subjects with head motion greater than 2 mm or 2° in any of the six parameters (x, y, z, pitch, roll, yaw) were excluded. A bandpass (0.01–0.08 Hz) filter was set up to reduce the effect of very low-frequency and high-frequency physiological noise. Individual ReHo maps were generated by calculating Kendall’s coefficient concordance (KCC, also called the ReHo value) of the time series of a given voxel with those of its nearest neighbors (26 voxels), on a voxelwise basis. The data were subsequently smoothed with a Gaussian filter of 6 mm full width at half-maximum (FWHM) to reduce noise and residual differences in gyral anatomy. The ReHo maps were generated for each subject in each group. 2.3.3 Second-level fmri data analysis One-sample t -tests were performed in each group to identify significant brain areas that were greater than the whole-brain average. The significance threshold was set at P < 0.05, and the results were corrected for multiple comparisons via FDR correction. The second-level random effects two-sample t -tests were subsequently performed to compare the ReHo results between the ESES group and the HC group within a conjunction mask. A conjunction mask was generated from one-sample t -test results. The t -map was set at a threshold of P < 0.05 (combined height threshold P < 0.01 and a minimum cluster size of 15 voxels), using the FDR correction in the REST software. 3. Results 3.1 WISC-Ⅳ Results The analysis revealed statistically significant differences in the FSIQ and PRI among the groups, with P values of 0.017 and 0.016, respectively. However, there were no statistically significant differences in the VCI, WMI, or PRI scores between the two groups, with P values of 0.111, 0.108, and 0.335, respectively (see Table 2 and Fig. 1 ). Table 2 Intergroup comparison of scale scores Groups Parameters FSIQ VCI PRI WMI PSI ESES Median 90 90.5 98 85 96.5 Interquartile Range 14.25 13 14.5 13.5 12.25 Maximum 106 103 125 109 113 Minimum 55 65 56 67 56 HC Median 98.5 94 110 95.5 100 Interquartile Range 8 9 8.5 16.5 15.75 Maximum 121 106 132 119 138 Minimum 90 81 92 75 74 P value 0.017* 0.111 0.016* 0.108 0.335 P > 0.05 indicated no significant difference between the two groups. P ≤ 0.05 indicated a statistically significant difference between groups. FSIQ: Full-Scale Intelligence Quotient; VCI: Verbal Comprehension Index; PRI: Perceptual Reasoning Index; WMI: Working Memory Index; PSI: Processing Speed Index. 3.2 fMRI Results The findings from the two-sample t -test are detailed in Table 3 and illustrated in Fig. 2 . Compared with the HC group, the ESES group demonstrated significantly lower ReHo values in several brain regions, specifically the right superior frontal gyrus, left postcentral gyrus, right postcentral gyrus, right posterior cerebellum, and right rolandic operculum. In contrast, the ESES group exhibited significantly elevated ReHo values in the left precuneus and left mid frontal gyrus. Brain Region Hemisphere Peak MNI coordinate Peak t value Cluster voxel (L/R) X Y Z ESES HC Precuneus L -6 -87 -39 5.78 1606 Frontal_Mid L -33 54 0 4.04 31 3.3 Correlations between brain regions and WISC The right postcentral gyrus demonstrated a moderate positive correlation with FSIQ and VCI scores (r = 0.56, P = 0.01; r = 0.67, P < 0.001). In contrast, the correlations observed between other brain regions and the index dimensions fail to reach statistical significance. Table 4 Correlation analysis results between brain regions and WISC scores Brain Regions FSIQ VCI PRI WMI PSI Cerebellum Posterior Lobe_R 0.07 r /0.77 P 0.22/0.33 0.00/0.99 -0.09/0.70 0.32/0.15 Precuneus_L 0.28/0.21 0.01/0.95 0.26/0.25 0.29/0.19 0.17/0.45 Frontal_Mid_L -0.20/0.38 -0.06/0.80 -0.30/0.18 -0.09/0.70 -0.06/0.78 Rolandic_Oper_R -0.07/0.77 0.03/0.90 -0.06/0.80 -0.04/0.87 -0.08/0.71 Postcentral Gyrus_R 0.56/0.01* 0.67/0.00* 0.24/0.28 0.46/0.32 0.37/0.09 Postcentral_L -0.13/0.55 0.13/0.57 -0.09/0.68 -0.30/0.17 0.15/0.49 Superior Frontal Gyrus_R -0.13/0.58 0.23/0.30 -0.06/0.78 -0.31/0.16 0.26/0.25 r represents the correlation coefficient; P represents the significance level of the hypothesis test. When P ≤ 0.05, the correlation was statistically significant. 0.00* mean P < 0.001 4. Discussion This study investigated the neural basis of cognitive dysfunction in children with ESES by integrating WISC-IV cognitive assessment and rs-fMRI ReHo analysis. Our main findings can be summarized as follows: First, children with ESES exhibited significant deficits in global intellectual ability (FSIQ) and perceptual reasoning (PRI). Second, compared to healthy controls, children with ESES showed decreased ReHo in several brain regions, including the left superior frontal gyrus (premotor area), bilateral postcentral gyri (primary somatosensory cortex), and right posterior cerebellum, while increased ReHo was observed in the left precuneus and left middle frontal gyrus. Third, and most importantly, ReHo in the right postcentral gyrus showed a significant positive correlation with both FSIQ and VCI scores. These findings not only confirm the broad impact of ESES on children's cognitive function but, more importantly, reveal specific local brain functional alterations associated with this impairment, providing new insights into the neural mechanisms of ESES. ​ 4.2 Reduced ReHo in the Right Postcentral Gyrus and Its Cognitive Implications in ESES ​ The correlation between reduced ReHo in the right postcentral gyrus and lower FSIQ/VCI scores represents the most significant finding warranting in-depth discussion. The postcentral gyrus, serving as the primary somatosensory cortex (S1), has traditionally been associated with processing basic somatosensory information such as touch, pressure, temperature, and pain​​[ 17 – 19 ]​. However, a growing body of evidence suggests that S1 is not an isolated functional area; through its extensive connections with higher-order association cortices, it participates in more complex cognitive processes, including sensory integration, working memory, and even language comprehension​​[ 20 , 21 ]​. Our findings align well with this modern perspective. The decreased local synchrony (ReHo) in the right postcentral gyrus may reflect that ESES-related abnormal discharges disrupt the normal synergistic activity within the somatosensory cortex itself and between it and cognitive-related networks[ 22 , 23 ]​. This desynchronization of local neural activity could impair the brain's ability to effectively integrate and process sensory information, consequently leading to the observed decline in global intelligence and verbal comprehension measured by the WISC-IV[ 24 ]​. Placing our findings in a broader context, while studies specifically examining ReHo alterations in children with ESES are scarce, research on other types of epilepsy or brain injury has also reported functional abnormalities in the sensorimotor cortex correlated with cognitive deficits[ 25 , 26 ]​. Furthermore, in typical development and certain neurodevelopmental disorders, the functional connectivity properties of the postcentral gyrus have been shown to be closely related to cognitive abilities​​[ 27 ]​. Therefore, our study links the cognitive dysfunction in ESES to a specific, measurable neuroimaging biomarker, laying the groundwork for future research. Based on the above analysis, we propose a potential pathophysiological model: the persistent epileptiform discharges during sleep in ESES interfere with normal functional reorganization and synaptic pruning processes in the brain. This interference particularly affects brain regions with clear topographic organization like the primary somatosensory cortex, leading to impaired synchronization of local neuronal activity (manifested as decreased ReHo). As S1 is a key node within multiple distributed brain networks, its local functional disruption may propagate through connected networks, thereby affecting higher-order cognitive processing and ultimately manifesting as widespread cognitive dysfunction. The right postcentral gyrus might play a critical "bottleneck" role in this pathological process. Of course, this hypothesis requires validation through future longitudinal studies incorporating task-based fMRI, diffusion tensor imaging (DTI), and other techniques. For instance, designing sensory integration cognitive tasks while observing the brain activation patterns and functional connectivity states of children with ESES during task performance could provide further insights. 5. Limitations and future directions This study has several limitations that should be acknowledged. First, the small sample size, though common in rare disease studies, may affect the statistical power and generalizability of our findings. Future multi-center collaborations are needed to validate these results with larger cohorts. Although the sample size is limited, we employed non-parametric statistical methods (such as Spearman correlation analysis and Mann-Whitney U test) for analysis. These methods are more robust for small sample data and can, to some extent, mitigate the statistical power issues caused by the limited sample size. Second, the cross-sectional design limits causal inference between ESES, neural changes, and cognitive deficits. Longitudinal studies tracking patients over time are essential to establish temporal relationships. Third, while ReHo effectively identifies local neural disturbances, it does not capture inter-regional functional connectivity. Combining ReHo with functional connectivity analyses in future work could reveal network-level dysfunctions in ESES. Despite these limitations, our findings provide a foundation for understanding ESES-related neural alterations and highlight the need for more comprehensive research approaches. 6. Conclusion In summary, our study demonstrates that cognitive impairments in children with ESES are linked to aberrant local neural activity, particularly evidenced by reduced Regional Homogeneity (ReHo) in the right postcentral gyrus. This association not only underscores the role of the somatosensory cortex in higher-order cognitive processes but also provides a quantifiable neuroimaging biomarker for ESES-related cognitive dysfunction. The convergence of neuropsychological assessment and rs-fMRI metrics in this study offers a robust framework for understanding the neural substrates of ESES. The identified biomarker paves the way for future research aimed at developing targeted interventions to normalize neural synchrony and improve cognitive outcomes in this vulnerable population. Abbreviations ESES Electrical Status Epilepticus During Sleep WISC -IV Wechsler Intelligence Scale for Children, Fourth Edition FSIQ Full-Scale Intelligence Quotient VCI Verbal Comprehension Index PRI Perceptual Reasoning Index WMI Working Memory Inde PSI Processing Speed Index rs-fMRI Resting-state functional Magnetic Resonance Imaging ReHo Regional Homogeneity SWI Spike-Wave Index ILAE International League Against Epilepsy ICA Independent Component Analysis ALFF Amplitude of Low-Frequency Fluctuations HC Healthy Controls FWHM Width at half-Maximum DCML Dorsal Column Medial Lemniscus Declarations 8.1 Ethics approval and consent to participate All participants agreed to participate, and informed consent was obtained from their parents or legal guardians. The study protocol received approval from the Medical Ethics Committee of Shenzhen Children's Hospital (No. 201904102). 8.2 Consent for publication Written informed consent for publication was obtained from the parents or legal guardians of all child participants included in this study. 8.4 Competing interests The authors declare that they have no competing interests. 8.8 Authors' information Department of Radiology, Shenzhen Children’s Hospital, Shenzhen, Guangdong, China Tong Mo, Xiaoyu Wang, Jingjing Luo, Jieqiong Lin, Xianlei Meng & Hongwu Zeng Department of Neurology, Shenzhen Children’s Hospital, Shenzhen, Guangdong, China Zhanqi Hu, Li Chen, Yan Chen & Jianxiang Liao Pediatric Health Care Department, Shenzhen Children’s Hospital, Shenzhen, Guangdong, China Linlin Zhang Epilepsy Surgery Department, Shenzhen Children’s Hospital, Shenzhen, Guangdong, China Dezhi Cao 8.5 Funding This project was supported by the Sanming Project of Medicine in Shenzhen (No. SZSM202011005), the Sciences and Technology Project of Shenzhen (No. JCYJ20220530155805012), the Natural Science Foundation of Guangdong Province (No. 2022A1515011427), and the Guangdong High-level Hospital Construction Fund (ynkt2021-zz47). Author Contribution TM and XYW contributed to the study design and drafted the manuscript. JJL and JQL performed the data analysis and interpretation. XLM assisted in collecting the fMRI data. ZQH, LC, YC, and DZC supported patient recruitment and clinical data management. LLZ assisted in completing the WISC assessments. JXL and HWZ supervised the study and provided overall guidance. All the authors read and approved the final manuscript. 8.7 Acknowledgement The authors express their gratitude to all the individuals who participated in this research. Data Availability The datasets analyzed during the current study are not publicly available due to patient privacy and ethical restrictions but are available from the corresponding author upon reasonable request. References Patry G, Lyagoubi S, Tassinari CA, et al. Subclinical electrical status epilepticus induced by sleep in children. A clinical and electroencephalographic study of six cases. Arch Neurol. 1971;24(3):242–52. 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Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyu","middleName":"","lastName":"Wang","suffix":""},{"id":550079227,"identity":"e6e5c0ee-0bb7-4a39-92be-6c93a1c81e33","order_by":2,"name":"Jingjing Luo","email":"","orcid":"","institution":"Shenzhen Children’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jingjing","middleName":"","lastName":"Luo","suffix":""},{"id":550079229,"identity":"a5697bda-5161-4571-a874-6cb36880cd26","order_by":3,"name":"Jieqiong Lin","email":"","orcid":"","institution":"Shenzhen Children’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jieqiong","middleName":"","lastName":"Lin","suffix":""},{"id":550079231,"identity":"da31b0e5-50f6-4382-91df-062d3479e10f","order_by":4,"name":"Xianlei Meng","email":"","orcid":"","institution":"Shenzhen Children’s 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06:24:39","extension":"xml","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":96317,"visible":true,"origin":"","legend":"","description":"","filename":"25d7bb2b0f7b4618aa614a3489065ef81structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-5500538/v1/0cc82c0ad9c3dd553a85252e.xml"},{"id":96787265,"identity":"49e9c19c-5f7f-4f9d-bbb2-b405ada78245","added_by":"auto","created_at":"2025-11-26 06:24:40","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":107908,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-5500538/v1/de58f93e0613e4f0cf339a80.html"},{"id":96917246,"identity":"7945991a-ac19-42eb-910f-49515c96141e","added_by":"auto","created_at":"2025-11-27 14:09:26","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":53350,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in WISC scores between ESES and HC groups\u003c/p\u003e\n\u003cp\u003eThe analysis revealed statistically significant differences in FSIQ and PRI among the groups, with P values of 0.017 and 0.016.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5500538/v1/a994e00ef695062578aa369c.jpg"},{"id":96915553,"identity":"d4f74a71-8075-490f-9d64-2dda4e1f894f","added_by":"auto","created_at":"2025-11-27 14:07:22","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":261828,"visible":true,"origin":"","legend":"\u003cp\u003eTwo sample \u003cem\u003et\u003c/em\u003e-test results\u003c/p\u003e\n\u003cp\u003eReHo Changes shown as a comparison of KCC maps between patients with ESES and controls (P \u0026lt; 0.01, minimum cluster \u0026gt; 15, with FDR correction). T score bars are shown on the right. Hot (red) and cold (blue) colors indicate ESES group ReHo increases and decreases, respectively.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5500538/v1/dd76c7eea9b02caad76cfba5.jpg"},{"id":96787258,"identity":"9f5ac308-f667-4de4-a980-b39d17c80572","added_by":"auto","created_at":"2025-11-26 06:24:40","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":164529,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelations between brain regions and WISC\u003c/p\u003e\n\u003cp\u003eThe right Postcentral Gyrus correlates moderately positively with FSIQ and VCI dimensions. In contrast, the correlations observed between other brain regions and the index dimensions fail to attain statistical significance.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5500538/v1/d166a2eba84e27fc52f93296.jpg"},{"id":96922772,"identity":"635ba6dd-f2e6-4509-9e1e-393ede7795a5","added_by":"auto","created_at":"2025-11-27 14:19:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1454949,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5500538/v1/14fcc11f-e97d-45a6-9a1a-711ac55be1c3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Cognitive Impairments and Neurofunctional Alterations in Children with ESES: Insights from WISC-IV and Resting-State fMRI","fulltext":[{"header":"1. Background","content":"\u003cp\u003eElectrical Status Epilepticus during Sleep (ESES) is an age-dependent epileptic encephalopathy characterized by significant sleep-induced epileptiform discharges (spike-wave index\u0026thinsp;\u0026ge;\u0026thinsp;85%) and acquired cognitive or behavioral deficits [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. As a rare but impactful syndrome, ESES poses a major threat to neurodevelopment, with prolonged activity often leading to enduring impairments in language, memory, and executive functions, even after seizure remission [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Consequently, elucidating the neural mechanisms underlying cognitive dysfunction in ESES is critical for advancing early diagnosis and targeted interventions.\u003c/p\u003e\u003cp\u003eWhile traditional neuropsychological scales, such as the Wechsler Intelligence Scale for Children (WISC), provide valuable assessments of cognitive domains and are recognized for their comprehensiveness and reliability [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], they are limited by subjectivity and an inherent inability to detect deficits before they become clinically overt [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. There is, therefore, an urgent need for objective biomarkers that can precisely quantify neural alterations associated with ESES-related cognitive impairment.\u003c/p\u003e\u003cp\u003eResting-state functional magnetic resonance imaging (rs-fMRI) offers a powerful, non-invasive window into brain function, enabling the investigation of neural circuits and cognitive processes [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Among its analytical methods, Regional Homogeneity (ReHo) is particularly suited for investigating local neural synchrony and has been widely used to identify localized brain dysfunction in various neurological and psychiatric disorders [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. By measuring the temporal synchronization of neural activity within a given brain region, ReHo can reveal subtle alterations in local brain function that may serve as sensitive biomarkers.\u003c/p\u003e\u003cp\u003eGuided by this rationale, the present study integrated the WISC-IV and rs-fMRI-based ReHo analysis to investigate the relationship between cognitive deficits and localized neural dysfunction in children with ESES. We aimed to (1) identify specific brain regions with altered ReHo in ESES patients compared to matched healthy controls, and (2) explore the correlations between these neurofunctional alterations and deficits in specific cognitive domains as measured by the WISC-IV. We hypothesize that ESES is associated with distinct patterns of abnormal local neural activity, which are linked to the characteristic cognitive profile of the syndrome.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Participants\u003c/h2\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e\u003ch2\u003e2.1.1 ESES Group\u003c/h2\u003e\u003cp\u003eA cohort of twenty-five children diagnosed with ESES was recruited from Shenzhen Children's Hospital. The sample comprised 13 males and 12 females, aged between 6.75 and 12.33 years (mean age\u0026thinsp;=\u0026thinsp;8.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.99 years; refer to Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All patients had a history of epileptic seizures before meeting the ESES diagnostic criteria, with seizure types including focal seizures (e.g., motor seizures, asymmetric tonic/clonic seizure), generalized seizures (e.g., absence, myoclonic, atonic), and characteristic negative seizures like aphasia. The EEG findings include: scattered focal spike-and-wave discharges during wakefulness, replacement of the background by diffuse and continuous spike-and-wave activity during non-rapid eye movement (NREM) sleep, and significant reduction of discharges during rapid eye movement (REM) sleep.\u003c/p\u003e\u003cp\u003eThe duration of illness was defined as the time from the definitive diagnosis of ESES to the study assessment. The mean duration from diagnosis to the study assessments (WISC-IV and fMRI) was 3.31\u0026thinsp;\u0026plusmn;\u0026thinsp;2.02 years.\u003c/p\u003e\u003cp\u003eThe inclusion criteria for this study were as follows: a. Age between 6 and 16 years, of Han nationality, with no specifications regarding gender. b. Established right-handedness. c. The diagnosis of Electrical Status Epilepticus during Sleep (ESES) was established based on the consensus criteria proposed by the International League Against Epilepsy (ILAE). The inclusion criteria for the ESES group were as follows: ①EEG Criterion:​​ The presence of a marked increase in epileptiform activity during non-rapid eye movement (NREM) sleep, characterized by a ​Spike-Wave Index (SWI) of \u0026ge;\u0026thinsp;85%​. The SWI is defined as the percentage of NREM sleep time occupied by near-continuous spike-wave discharges. ②Clinical Criterion:​​ The presence of ​cognitive regression/decline, ​behavioral disturbances, and/or ​motor deficits​ (e.g., ataxia, dyspraxia). ③Epilepsy Criterion:​​ The presence of seizures, which are typically mild and infrequent, and may include focal motor, generalized tonic-clonic, or atypical absence seizures. d. Negative findings on MRI.\u003c/p\u003e\u003cp\u003eConversely, the exclusion criteria included the following: a. the presence of systemic diseases or other neurological disorders. b. contraindications for undergoing MRI. c. Inability to comply with examination protocols.\u003c/p\u003e\u003cp\u003eThe demographic and clinical characteristics of the participants are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.1.2 Healthy Controls (HCs)\u003c/h2\u003e\u003cp\u003eThirty volunteers were recruited for this study and were matched in terms of age, sex, and handedness. The cohort comprised 17 boys and 13 girls, with ages ranging from 6.42\u0026ndash;12 years, and a mean age of years (mean age\u0026thinsp;=\u0026thinsp;9.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80 years; refer to Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\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 and clinical data of the ESES patients and HCs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eESES\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eZ\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\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\u003cp\u003e1.000 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13(52%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17(57%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12(48%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13(43%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (m\u0026thinsp;\u0026plusmn;\u0026thinsp;std, year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.139\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.266\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParents\u0026rsquo; Education(year)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\le\\:12\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\ge\\:13\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRight Hand\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25(100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30(100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHan Nationality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25(100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30(100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOnset Age (year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.26\u0026thinsp;\u0026plusmn;\u0026thinsp;2.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration (year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.31\u0026thinsp;\u0026plusmn;\u0026thinsp;2.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumbers of Asm \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4(16%)\u003c/p\u003e\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9(36%)\u003c/p\u003e\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6(24%)\u003c/p\u003e\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\ge\\:\\:\\)\u003c/span\u003e\u003c/span\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6(24%)\u003c/p\u003e\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\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.2.1 Intelligence assessment\u003c/h2\u003e\u003cp\u003eAll the subjects enrolled in the study were tested for cognitive function via the WISC-IV, by professionals with more than 10 years of work experience in the Psychology Department of Shenzhen Children's Hospital. The test content includes 10 core subtests and 5 supplementary subtests: Similarities, Vocabulary, Comprehension, Block Design, Picture Concepts, Matrix Reasoning, Digit Span, Letter-Number Sequencing, Coding, Symbol Search, Information, Word Reasoning, etc., each with a population mean of 10 and a standard deviation of 3. The core subtests are used to create four index scores: VCI, PRI, WMI, and PSI. The FSIQ is computed from all 10 core subtests. The factor indices and FSIQ each have a population mean of 100 and a standard deviation of 15. The standard level or percentage level is used to indicate the cognitive level of each subject.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.2.2 MR Data Acquisition\u003c/h2\u003e\u003cp\u003eConventional structural images and eye-open resting-state functional MRI data were collected via the Siemens MAGNETOM Skyra 3.0T superconducting magnetic resonance imaging system (Siemens Healthcare, Germany) and standard head coils. The subjects were placed in the supine position, their ears were stuffed with ear pads to reduce noise effects, and their heads were fixed with spongy pads to reduce head movement. A \"+\" on the large screen on the side of the head was observed through a mirror attached to the head coil. Before the examination, the subjects were informed of relevant matters needing attention and told that they would stay still.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section4\"\u003e\u003ch2\u003e2.2.2.1 Conventional structural image acquisition\u003c/h2\u003e\u003cp\u003eConventional structural images include axial T1WI (t1_tirm_dark-fluid, TR\u0026thinsp;=\u0026thinsp;200 ms, TE\u0026thinsp;=\u0026thinsp;2.49 ms), T2WI (t2_tse_tra, TR\u0026thinsp;=\u0026thinsp;3800 ms, TE\u0026thinsp;=\u0026thinsp;112 ms), and FLAIR (t2_tirm_tra_dark-fluid, TR\u0026thinsp;=\u0026thinsp;9000 ms, TE\u0026thinsp;=\u0026thinsp;81ms, TI\u0026thinsp;=\u0026thinsp;2500 ms).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section4\"\u003e\u003ch2\u003e2.2.2.2 rs-fMRI data acquisition\u003c/h2\u003e\u003cp\u003ea. rs-fMRI data were acquired by using an echo planar imaging sequence with the following parameters: 32 axial slices, 130 Volumes, Slice Thickness\u0026thinsp;=\u0026thinsp;3.0 mm, Repetition Time\u0026thinsp;=\u0026thinsp;2000 ms, Echo Time\u0026thinsp;=\u0026thinsp;30 ms, voxel size\u0026thinsp;=\u0026thinsp;3.0\u0026times;3.0\u0026times;3.0 mm\u003csup\u003e3\u003c/sup\u003e, and Flip angle\u0026thinsp;=\u0026thinsp;90. b. Anatomical data: Three-dimensional magnetization prepared rapid acquisition gradient echo sequences with the following parameters: 176 sagittal slices, Slice Thickness\u0026thinsp;=\u0026thinsp;1.0 mm, Spacing Between Slices\u0026thinsp;=\u0026thinsp;0.5, Repetition Time\u0026thinsp;=\u0026thinsp;2300 ms, Echo Time\u0026thinsp;=\u0026thinsp;2.26 ms, voxel size\u0026thinsp;=\u0026thinsp;1.0\u0026times;1.0\u0026times;1.0 mm\u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Data processing and analyses\u003c/h2\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e2.3.1 WISC-Ⅳ data analysis\u003c/h2\u003e\u003cp\u003eAll the data were analyzed by using GraphPad Prism (version 9) software. Before data analysis, the normal distribution test (Shapiro-Wilk test) and homogeneity of variance test were performed on all the data. a. A nonparametric rank sum test was used to compare the scale scores between groups. b. Spearman rank correlation analysis was used to analyze the correlation between the score and variables such as examination age and course of disease. The significance level threshold was set as 0.05. If P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, the difference or correlation between the groups was considered statistically significant.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003e2.3.2 fMRI data processing\u003c/h2\u003e\u003cp\u003eThe data were preprocessed and analyzed using REST based on SPM12 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://restfmri.net/forum/index.php\u003c/span\u003e\u003cspan address=\"http://restfmri.net/forum/index.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, \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). The first 10 time points of each subject\u0026rsquo;s rs-fMRI data were discarded because of the instability of the initial MRI signal. The remaining 120 volumes were first realigned to correct for head motion before being corrected by the acquisition time delay among different slices.\u003c/p\u003e\u003cp\u003eData preprocessing includes: (1) Slice timing, (2) Realignment, (3) Spatial smoothing, (4) Coregistration, (5) Normalization (voxel size 3\u0026times;3\u0026times;3 mm\u003csup\u003e3\u003c/sup\u003e), and (6) Filtering. Any subjects with head motion greater than 2 mm or 2\u0026deg; in any of the six parameters (x, y, z, pitch, roll, yaw) were excluded. A bandpass (0.01\u0026ndash;0.08 Hz) filter was set up to reduce the effect of very low-frequency and high-frequency physiological noise. Individual ReHo maps were generated by calculating Kendall\u0026rsquo;s coefficient concordance (KCC, also called the ReHo value) of the time series of a given voxel with those of its nearest neighbors (26 voxels), on a voxelwise basis. The data were subsequently smoothed with a Gaussian filter of 6 mm full width at half-maximum (FWHM) to reduce noise and residual differences in gyral anatomy. The ReHo maps were generated for each subject in each group.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e2.3.3 Second-level fmri data analysis\u003c/h2\u003e\u003cp\u003eOne-sample \u003cem\u003et\u003c/em\u003e-tests were performed in each group to identify significant brain areas that were greater than the whole-brain average. The significance threshold was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and the results were corrected for multiple comparisons via FDR correction. The second-level random effects two-sample \u003cem\u003et\u003c/em\u003e-tests were subsequently performed to compare the ReHo results between the ESES group and the HC group within a conjunction mask. A conjunction mask was generated from one-sample \u003cem\u003et\u003c/em\u003e-test results. The \u003cem\u003et\u003c/em\u003e-map was set at a threshold of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (combined height threshold P\u0026thinsp;\u0026lt;\u0026thinsp;0.01 and a minimum cluster size of 15 voxels), using the FDR correction in the REST software.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.1 WISC-Ⅳ Results\u003c/h2\u003e\u003cp\u003eThe analysis revealed statistically significant differences in the FSIQ and PRI among the groups, with P values of 0.017 and 0.016, respectively. However, there were no statistically significant differences in the VCI, WMI, or PRI scores between the two groups, with P values of 0.111, 0.108, and 0.335, respectively (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\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\u003eIntergroup comparison of scale scores\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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGroups\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFSIQ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVCI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePRI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eWMI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePSI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eESES\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e90.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e96.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInterquartile Range\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e13.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMaximum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e106\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e103\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e113\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMinimum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eHC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e98.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInterquartile Range\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e15.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMaximum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e106\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e138\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMinimum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e74\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.017*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.016*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.108\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.335\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eP\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05 indicated no significant difference between the two groups. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05 indicated a statistically significant difference between groups.\u003c/p\u003e\u003cp\u003eFSIQ: Full-Scale Intelligence Quotient; VCI: Verbal Comprehension Index; PRI: Perceptual Reasoning Index; WMI: Working Memory Index; PSI: Processing Speed Index.\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\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.2 fMRI Results\u003c/h2\u003e\u003cp\u003eThe findings from the two-sample \u003cem\u003et\u003c/em\u003e-test are detailed in Table\u0026nbsp;3 and illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Compared with the HC group, the ESES group demonstrated significantly lower ReHo values in several brain regions, specifically the right superior frontal gyrus, left postcentral gyrus, right postcentral gyrus, right posterior cerebellum, and right rolandic operculum. In contrast, the ESES group exhibited significantly elevated ReHo values in the left precuneus and left mid frontal gyrus.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eBrain Region\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHemisphere\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003ePeak MNI coordinate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePeak \u003cem\u003et\u003c/em\u003e value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCluster voxel\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(L/R)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eX\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eY\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\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\u003eESES\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\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSuperior Frontal Gyrus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-4.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e124\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePostcentral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eL\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-12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-4.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePostcentral Gyrus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-3.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCerebellum Posterior\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-4.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRolandic_Oper\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-3.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eESES\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\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrecuneus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eL\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\u003e-87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1606\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFrontal_Mid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Correlations between brain regions and WISC\u003c/h2\u003e\u003cp\u003eThe right postcentral gyrus demonstrated a moderate positive correlation with FSIQ and VCI scores (r\u0026thinsp;=\u0026thinsp;0.56, P\u0026thinsp;=\u0026thinsp;0.01; r\u0026thinsp;=\u0026thinsp;0.67, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In contrast, the correlations observed between other brain regions and the index dimensions fail to reach statistical significance.\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 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelation analysis results between brain regions and WISC scores\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBrain Regions\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFSIQ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVCI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePRI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eWMI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePSI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCerebellum Posterior Lobe_R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.07\u003csup\u003er\u003c/sup\u003e/0.77\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.22/0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.00/0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.09/0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.32/0.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrecuneus_L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.28/0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.01/0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.26/0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.29/0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.17/0.45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFrontal_Mid_L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.20/0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.06/0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.30/0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.09/0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.06/0.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRolandic_Oper_R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.07/0.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.03/0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.06/0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.04/0.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.08/0.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePostcentral Gyrus_R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.56/0.01*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.67/0.00*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.24/0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.46/0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.37/0.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePostcentral_L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.13/0.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.13/0.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.09/0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.30/0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.15/0.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSuperior Frontal Gyrus_R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.13/0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.23/0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.06/0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.31/0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.26/0.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003er represents the correlation coefficient; P represents the significance level of the hypothesis test. When P\u0026thinsp;\u0026le;\u0026thinsp;0.05, the correlation was statistically significant. 0.00* mean P\u0026thinsp;\u0026lt;\u0026thinsp;0.001\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\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study investigated the neural basis of cognitive dysfunction in children with ESES by integrating WISC-IV cognitive assessment and rs-fMRI ReHo analysis. Our main findings can be summarized as follows:\u003c/p\u003e\u003cp\u003eFirst, children with ESES exhibited significant deficits in global intellectual ability (FSIQ) and perceptual reasoning (PRI). Second, compared to healthy controls, children with ESES showed decreased ReHo in several brain regions, including the left superior frontal gyrus (premotor area), bilateral postcentral gyri (primary somatosensory cortex), and right posterior cerebellum, while increased ReHo was observed in the left precuneus and left middle frontal gyrus. Third, and most importantly, ReHo in the right postcentral gyrus showed a significant positive correlation with both FSIQ and VCI scores.\u003c/p\u003e\u003cp\u003eThese findings not only confirm the broad impact of ESES on children's cognitive function but, more importantly, reveal specific local brain functional alterations associated with this impairment, providing new insights into the neural mechanisms of ESES.\u003c/p\u003e\u003cp\u003e​\u003cb\u003e4.2 Reduced ReHo in the Right Postcentral Gyrus and Its Cognitive Implications in ESES\u003c/b\u003e​\u003c/p\u003e\u003cp\u003eThe correlation between reduced ReHo in the right postcentral gyrus and lower FSIQ/VCI scores represents the most significant finding warranting in-depth discussion. The postcentral gyrus, serving as the primary somatosensory cortex (S1), has traditionally been associated with processing basic somatosensory information such as touch, pressure, temperature, and pain​​[\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]​.\u003c/p\u003e\u003cp\u003eHowever, a growing body of evidence suggests that S1 is not an isolated functional area; through its extensive connections with higher-order association cortices, it participates in more complex cognitive processes, including sensory integration, working memory, and even language comprehension​​[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]​.\u003c/p\u003e\u003cp\u003eOur findings align well with this modern perspective. The decreased local synchrony (ReHo) in the right postcentral gyrus may reflect that ESES-related abnormal discharges disrupt the normal synergistic activity within the somatosensory cortex itself and between it and cognitive-related networks[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]​. This desynchronization of local neural activity could impair the brain's ability to effectively integrate and process sensory information, consequently leading to the observed decline in global intelligence and verbal comprehension measured by the WISC-IV[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]​.\u003c/p\u003e\u003cp\u003ePlacing our findings in a broader context, while studies specifically examining ReHo alterations in children with ESES are scarce, research on other types of epilepsy or brain injury has also reported functional abnormalities in the sensorimotor cortex correlated with cognitive deficits[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]​. Furthermore, in typical development and certain neurodevelopmental disorders, the functional connectivity properties of the postcentral gyrus have been shown to be closely related to cognitive abilities​​[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]​. Therefore, our study links the cognitive dysfunction in ESES to a specific, measurable neuroimaging biomarker, laying the groundwork for future research.\u003c/p\u003e\u003cp\u003eBased on the above analysis, we propose a potential pathophysiological model: the persistent epileptiform discharges during sleep in ESES interfere with normal functional reorganization and synaptic pruning processes in the brain. This interference particularly affects brain regions with clear topographic organization like the primary somatosensory cortex, leading to impaired synchronization of local neuronal activity (manifested as decreased ReHo). As S1 is a key node within multiple distributed brain networks, its local functional disruption may propagate through connected networks, thereby affecting higher-order cognitive processing and ultimately manifesting as widespread cognitive dysfunction. The right postcentral gyrus might play a critical \"bottleneck\" role in this pathological process.\u003c/p\u003e\u003cp\u003eOf course, this hypothesis requires validation through future longitudinal studies incorporating task-based fMRI, diffusion tensor imaging (DTI), and other techniques. For instance, designing sensory integration cognitive tasks while observing the brain activation patterns and functional connectivity states of children with ESES during task performance could provide further insights.\u003c/p\u003e"},{"header":"5. Limitations and future directions","content":"\u003cp\u003eThis study has several limitations that should be acknowledged. First, the small sample size, though common in rare disease studies, may affect the statistical power and generalizability of our findings. Future multi-center collaborations are needed to validate these results with larger cohorts. Although the sample size is limited, we employed non-parametric statistical methods (such as Spearman correlation analysis and Mann-Whitney U test) for analysis. These methods are more robust for small sample data and can, to some extent, mitigate the statistical power issues caused by the limited sample size.\u003c/p\u003e\u003cp\u003eSecond, the cross-sectional design limits causal inference between ESES, neural changes, and cognitive deficits. Longitudinal studies tracking patients over time are essential to establish temporal relationships.\u003c/p\u003e\u003cp\u003eThird, while ReHo effectively identifies local neural disturbances, it does not capture inter-regional functional connectivity. Combining ReHo with functional connectivity analyses in future work could reveal network-level dysfunctions in ESES.\u003c/p\u003e\u003cp\u003eDespite these limitations, our findings provide a foundation for understanding ESES-related neural alterations and highlight the need for more comprehensive research approaches.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eIn summary, our study demonstrates that cognitive impairments in children with ESES are linked to aberrant local neural activity, particularly evidenced by reduced Regional Homogeneity (ReHo) in the right postcentral gyrus. This association not only underscores the role of the somatosensory cortex in higher-order cognitive processes but also provides a quantifiable neuroimaging biomarker for ESES-related cognitive dysfunction.\u003c/p\u003e\u003cp\u003eThe convergence of neuropsychological assessment and rs-fMRI metrics in this study offers a robust framework for understanding the neural substrates of ESES. The identified biomarker paves the way for future research aimed at developing targeted interventions to normalize neural synchrony and improve cognitive outcomes in this vulnerable population.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eESES\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eElectrical Status Epilepticus During Sleep\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eWISC\u003c/b\u003e\u003cb\u003e-IV\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eWechsler Intelligence Scale for Children, Fourth Edition\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eFSIQ\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFull-Scale Intelligence Quotient\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eVCI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eVerbal Comprehension Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003ePRI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePerceptual Reasoning Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eWMI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eWorking Memory Inde\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003ePSI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eProcessing Speed Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003ers-fMRI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eResting-state functional Magnetic Resonance Imaging\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eReHo\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRegional Homogeneity\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eSWI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSpike-Wave Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eILAE\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInternational League Against Epilepsy\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eICA\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eIndependent Component Analysis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eALFF\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAmplitude of Low-Frequency Fluctuations\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eHC\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHealthy Controls\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eFWHM\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eWidth at half-Maximum\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eDCML\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDorsal Column Medial Lemniscus\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e8.1 Ethics approval and consent to participate\u003c/strong\u003e\u003cp\u003e All participants agreed to participate, and informed consent was obtained from their parents or legal guardians. The study protocol received approval from the Medical Ethics Committee of Shenzhen Children's Hospital (No. 201904102).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e8.2 Consent for publication\u003c/strong\u003e\u003cp\u003e Written informed consent for publication was obtained from the parents or legal guardians of all child participants included in this study.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003e8.4 Competing interests\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003e8.8 Authors' information\u003c/h2\u003e\u003cp\u003eDepartment of Radiology, Shenzhen Children\u0026rsquo;s Hospital, Shenzhen, Guangdong, China\u003c/p\u003e\u003cp\u003eTong Mo, Xiaoyu Wang, Jingjing Luo, Jieqiong Lin, Xianlei Meng \u0026amp; Hongwu Zeng\u003c/p\u003e\u003cp\u003eDepartment of Neurology, Shenzhen Children\u0026rsquo;s Hospital, Shenzhen, Guangdong, China\u003c/p\u003e\u003cp\u003eZhanqi Hu, Li Chen, Yan Chen \u0026amp; Jianxiang Liao\u003c/p\u003e\u003cp\u003ePediatric Health Care Department, Shenzhen Children\u0026rsquo;s Hospital, Shenzhen, Guangdong, China\u003c/p\u003e\u003cp\u003eLinlin Zhang\u003c/p\u003e\u003cp\u003eEpilepsy Surgery Department, Shenzhen Children\u0026rsquo;s Hospital, Shenzhen, Guangdong, China\u003c/p\u003e\u003cp\u003eDezhi Cao\u003c/p\u003e\u003c/p\u003e\u003ch2\u003e8.5 Funding\u003c/h2\u003e\u003cp\u003eThis project was supported by the Sanming Project of Medicine in Shenzhen (No. SZSM202011005), the Sciences and Technology Project of Shenzhen (No. JCYJ20220530155805012), the Natural Science Foundation of Guangdong Province (No. 2022A1515011427), and the Guangdong High-level Hospital Construction Fund (ynkt2021-zz47).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eTM and XYW contributed to the study design and drafted the manuscript. JJL and JQL performed the data analysis and interpretation. XLM assisted in collecting the fMRI data. ZQH, LC, YC, and DZC supported patient recruitment and clinical data management. LLZ assisted in completing the WISC assessments. JXL and HWZ supervised the study and provided overall guidance. All the authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003e8.7 Acknowledgement\u003c/h2\u003e\u003cp\u003eThe authors express their gratitude to all the individuals who participated in this research.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets analyzed during the current study are not publicly available due to patient privacy and ethical restrictions but are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePatry G, Lyagoubi S, Tassinari CA, et al. Subclinical electrical status epilepticus induced by sleep in children. A clinical and electroencephalographic study of six cases. Arch Neurol. 1971;24(3):242\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTassinari CA, Michelucci R, Forti A, et al. The electrical status epilepticus syndrome. Epilepsy Res Suppl. 1992;6:111\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBerg AT, Berkovic SF, Brodie MJ, van Boas E, et al. Revised terminology and concepts for organization of seizures and epilepsies: report of the ILAE Commission on Classification and Terminology, 2005\u0026ndash;2009. Epilepsia. 2010;51(4):676\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evan den Munckhof B, van Dee V, Sagi L, et al. Treatment of electrical status epilepticus in sleep: A pooled analysis of 575 cases. Epilepsia. 2015;56(11):1738\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKramer U, Sagi L, Goldberg-Stern H, et al. Clinical spectrum and medical treatment of children with electrical status epilepticus in sleep (ESES). Epilepsia. 2009;50(6):1517\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHughes JR. A review of the relationships between Landau-Kleffner syndrome, electrical status epilepticus during sleep, and continuous spike-waves during sleep. Epilepsy Behav. 2011;20(2):247\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Vries EE, van den Munckhof B, Braun KPJ, et al. Inflammatory mediators in human epilepsy: A systematic review and meta-analysis. Neurosci Biobehav Rev. 2016;63:177\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWatkins MW, Canivez GL, Dombrowski SC, et al. Long-term stability of Wechsler Intelligence Scale for Children-fifth edition scores in a clinical sample. Appl Neuropsychol Child. 2021;11(3):422\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGreen Bartoi M, Issner JB, Hetterscheidt L, et al. Attention Problems and Stability of WISC-IV Scores Among Clinically Referred Children. Appl Neuropsychol Child. 2014;4(3):133\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchuck NW, Niv Y. Sequential replay of nonspatial task states in the human hippocampus. Science. 2019;364(6447):eaaw5181.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGao J, Fu Y, Fu Y, et al. MinD-3D++: Advancing fMRI-Based 3D Reconstruction With High-Quality Textured Mesh Generation and a Comprehensive Dataset. IEEE Trans Pattern Anal Mach Intell. 2025;47(12):11802\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKarakasis PA, Liavas AP, Sidiropoulos ND, et al. Multisubject Task-Related fMRI Data Processing via a Two-Stage Generalized Canonical Correlation Analysis. IEEE Trans Image Process. 2022;31:4011\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUeda M, Usami K, Yamao Y, et al. Correlation between brain functional connectivity and neurocognitive function in patients with left frontal glioma. Sci Rep. 2022;12(1):18302.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZang Y, Jiang T, Lu Y, He Y, et al. Regional homogeneity approach to fMRI data analysis. NeuroImage. 2004;22(1):394\u0026ndash;400.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHamdi H, Albader F, Spatola G, et al. Long-term cognitive outcome after radiosurgery in epileptic hypothalamic hamartomas and review of the literature. Epilepsia. 2021;62(6):1369\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJuli\u0026aacute;-Palacios N, Olivella M, Sigatullina Bondarenko M, et al. L-serine treatment in patients with GRIN-related encephalopathy: a phase 2A, non-randomized study. Brain. 2024;147(5):1653\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e​Kandel ER, Schwartz JH, Jessell TM, et al. ​​ Principles of Neural Science. 5th ed. McGraw-Hill; 2012.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePenfield W, Boldrey E. ​​ Somatic motor and sensory representation in the cerebral cortex of man. Brain. 1937;60(4):389\u0026ndash;443.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e​Kaas JH, Collins CE. ​​ The evolution of parietal cortex in primates: from sensation to cognition. In: Kaas JH, Ghazanfar AA, editors. Evolution of Nervous Systems. Volume 3. Academic; 2007. pp. 1\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeyer K, Kaplan JT, Essex R, et al. ​​ Seeing touch is correlated with content-specific activity in primary somatosensory cortex. Cereb Cortex. 2011;21(9):2113\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePoeppel D, Assaneo MF. ​​ Speech rhythms and their neural foundations. Nat Rev Neurosci. 2020;21(6):322\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e​Seeley WW, Menon V, Schatzberg AF, et al. ​​ Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci. 2007;27(9):2349\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e​Menon V. ​​ Large-scale brain networks and psychopathology: a unifying triple network model. Trends Cogn Sci. 2011;15(10):483\u0026ndash;506.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e​Ghazanfar AA, Schroeder CE. ​​ Is neocortex essentially multisensory? Trends Cogn Sci. 2006;10(6):278\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVannest J, Szaflarski JP, Eaton KP, et al. ​​ Functional MRI of language networks in pre-surgical epilepsy patients. Epilepsy Res. 2013;107(1\u0026ndash;2):165\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e​Widjaja E, Zamyadi M, Raybaud C, et al. ​​ Abnormal white matter correlates with neurocognitive impairment in children with localization-related epilepsy. Epilepsia. 2013;54(6):1065\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e​Supekar K, Uddin LQ, Prater K, et al. ​​ Development of functional and structural connectivity within the default mode network in young children. NeuroImage. 2010;52(1):290\u0026ndash;301.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmed","sideBox":"Learn more about [BMC Medicine](http://bmcmedicine.biomedcentral.com/)","snPcode":"12916","submissionUrl":"https://submission.nature.com/new-submission/12916/3","title":"BMC Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Electrical Status Epilepticus During Sleep, Cognitive Impairment, Wechsler Intelligence Scale for Children, Resting-State Functional MRI, Regional Homogeneity","lastPublishedDoi":"10.21203/rs.3.rs-5500538/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5500538/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eElectrical Status Epilepticus During Sleep (ESES) is a rare pediatric epilepsy syndrome characterized by sleep-induced epileptiform discharges, leading to cognitive and behavioral impairments. We aimed to investigate the underlying neural mechanisms that are critical for advancing early diagnosis and targeted interventions.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eTwenty-five children with ESES and 30 age- and sex-matched healthy controls were enrolled. Cognitive function was assessed via the Wechsler Intelligence Scale for Children, Fourth Edition (WISC-IV), focusing on Full-Scale IQ (FSIQ), Verbal Comprehension Index (VCI), Perceptual Reasoning Index (PRI), Working Memory Index (WMI), and Processing Speed Index (PSI). Resting-state functional MRI (rs-fMRI) was conducted to evaluate neural activity via regional homogeneity (ReHo) analysis. Correlations between ReHo values and cognitive scores were analyzed in the ESES group.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eCompared with healthy controls, children with ESES presented significantly lower FSIQ and PRI scores (P\u0026thinsp;=\u0026thinsp;0.017, P\u0026thinsp;=\u0026thinsp;0.016), indicating cognitive impairments in global intellectual abilities and perceptual reasoning. rs-fMRI revealed decreased ReHo in the left Superior Frontal Gyrus (premotor area), bilateral postcentral gyri (primary somatosensory cortex), right cerebellum posterior, and rolandic operculum. In contrast, increased ReHo was observed in the left precuneus and left middle frontal gyrus. ReHo in the right postcentral gyrus showed a positive correlation with FSIQ and VCI scores (r\u0026thinsp;=\u0026thinsp;0.56, P\u0026thinsp;=\u0026thinsp;0.01; r\u0026thinsp;=\u0026thinsp;0.67, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eESES is associated with significant cognitive deficits, particularly in perceptual reasoning and verbal comprehension, alongside altered neural activity patterns. ReHo analysis revealed changes in local neural activity within key brain regions linked to cognitive function. These findings highlight the potential of rs-fMRI metrics as biomarkers for assessing cognitive impairments and guiding therapeutic interventions in ESES.\u003c/p\u003e","manuscriptTitle":"Cognitive Impairments and Neurofunctional Alterations in Children with ESES: Insights from WISC-IV and Resting-State fMRI","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-26 06:24:35","doi":"10.21203/rs.3.rs-5500538/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-16T08:35:31+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-05T12:51:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"236450728501596106063260670282841064969","date":"2026-02-05T12:04:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-24T16:26:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-13T12:05:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medicine","date":"2025-11-12T15:47:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmed","sideBox":"Learn more about [BMC Medicine](http://bmcmedicine.biomedcentral.com/)","snPcode":"12916","submissionUrl":"https://submission.nature.com/new-submission/12916/3","title":"BMC Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f64d0934-11bc-40b0-a6e2-c4b5709f95c0","owner":[],"postedDate":"November 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-26T10:38:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-26 06:24:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5500538","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5500538","identity":"rs-5500538","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}