Brain Function Disorders Research Articles

Deciphering Adult Neural Stem Cells with Single-Cell Sequencing.

Adult neural stem cells (NSCs) are restricted to the two neurogenic regions of the mammalian brain, where they self-renew and generate progenies of multiple lineages, including neurons, astrocytes, and oligodendrocytes. Single-cell RNA sequencing technology, which reconstructs high-resolution transcriptional landscapes, provides valuable insights into cellular heterogeneity and developmental dynamics. In this review, we overviewed recent progress in the single-cell analyses of both conventional and unconventional NSCs. We discussed the heterogeneity among the stem cell pool and characterized the transcriptional alterations in aging and brain tumors. A comprehensive understanding of NSCs in physiological and pathological settings will provide insights for the rejuvenation of the aged brain and restoration of normal brain function in multiple neurological disorders.

Interventions for Changing Brain Function in Clinical Disorders

Historically, restoring brain function after injury or disease has been extremely difficult. However, over the past few decades, new techniques have emerged for reversing or postponing the deficits in behavior that accompany such injury. This paper reviews several current interventions for improving brain function in clinical settings: deep-brain stimulation, transcranial magnetic stimulation, physical exercise, and cognitive training. These interventions have been used in a wide range of clinical disorders, including Parkinson’s Disease, Alzheimer’s Disease, Huntington’s Disease, depression, stroke, and various psychiatric conditions. Findings suggest that these clinical interventions are associated with relatively modest improvements in outcome and should not be considered first-line treatments for most disorders. However, ongoing research continues to refine these techniques to establish more reliable neural pathways for improving clinical outcomes; to more precisely understand the neural mechanisms underlying various disorders; and to improve the delivery of the interventions.

Evaluation of Anticonvulsant Action of Nebivolol in Albino Mice

Background: Epilepsy is a disorder of brain function indicating periodic and unpredictable occurrence of seizures. Hypertension is the main cause of intracerebral hemorrhage which is a triggering factor for development of epilepsy. Nebivolol, a β-blocker is an anti-hypertensive drug, could decrease the glutaminergic transmission with addition of antioxidant property as a contributing factor may possibly provide anticonvulsant effect. Aim and Objective: The aim of the study was to study the anticonvulsant effect of Nebivolol in Albino mice. Materials and Methods: An either sex of Albino mice weighing between 18 and 22 g were used. Forty-eight animals (n = 48) were divided into eight groups with six in each group; four groups each for maximal electroshock (MES) and pentylenetetrazole (PTZ) models, respectively. Hind Limb Flexion, Hind Limb Extension, Clonus, and Postictal Depression were observed using MES model, Seizure latency and Duration of seizures were observed using PTZ model. Results: Nebivolol showed anticonvulsant effect with MES convulsions at both 0.25 mg/kg and 0.5 mg/kg but this effect is not equivalent to that of phenytoin in the present study. In terms of duration of tonic hind limb flexion and post-ictal depression, Nebivolol 0.5 mg/kg dose has comparable results to that of phenytoin. In PTZ model, Nebivolol decreased the seizure duration but did not delay the seizure onset, which were comparable to the standard Diazepam. Conclusion: Nebivolol may possibly be beneficial in treating generalized tonic clonic seizures and absence seizures. However, more extended studies are needed to prove the anticonvulsant effect of Nebivolol and enable its use in clinical practice.

Generalized Epileptic Seizure Prediction using Machine Learning Method

In recent years, the electroencephalography (EEG) signal identification of epileptic seizures has developed into a routine procedure to determine epilepsy. Since physically identifying epileptic seizures by expert neurologists becomes a labor-intensive, time-consuming procedure that also produces several errors. Thus, efficient, and computerized detection of epileptic seizures is required. The disordered brain function that causes epileptic seizures can have an impact on a patient's condition. Epileptic seizures can be prevented by medicine with great success if they are predicted before they start. Electroencephalogram (EEG) signals are utilized to predict epileptic seizures by using machine learning algorithms and complex computational methodologies. Furthermore, two significant challenges that affect both expectancy time and genuine positive forecast rate are feature extraction from EEG signals and noise removal from EEG signals. As a result, we suggest a model that offers trustworthy preprocessing and feature extraction techniques. To automatically identify epileptic seizures, a variety of ensemble learning-based classifiers were utilized to extract frequency-based features from the EEG signal. Our algorithm offers a higher true positive rate and diagnoses epileptic episodes with enough foresight before they begin. On the scalp EEG CHB-MIT dataset on 24 subjects, this suggested framework detects the beginning of the preictal state, the state that occurs before a few minutes of the onset of the detention, resulting in an elevated true positive rate of (91%) than conventional methods and an optimum estimation time of 33 minutes and an average time of prediction is 23 minutes and 36 seconds. Depending on the experimental findings’ The maximum accuracy, sensitivity, and specificity rates in this research were 91 %, 98%, and 84%.

Event-Related Potentials (ERPs): a technique to study brain functioning during information processing

Event-related potentials (ERPs) electrophysiological technique has been used for decades as a reliable neurophysiological toolfor the study of sensory, motor, and cognitive processes. This technique captures the brain’s electrical activity signalsynchronized with a particular event, such as the appearance of an auditory stimulus, a written word, or an image. Given thehigh temporal resolution offered by ERPs, it is possible to study rigorously the course and temporal dynamics of the neuralprocesses involved in information processing. Furthermore, ERPs are also reliable neurophysiological markers for thediagnosis of sensitive pathways disorders and are useful in the study of brain function disorders such as injuries,neurodegenerative diseases, and neuropsychiatric disorders such as Parkinson's disease, and schizophrenia. Accordingly, weconsider it relevant to carry out a general review of the theoretical and methodological fundamentals of ERPs.

Association of kidney function and brain health: A systematic review and meta-analysis of cohort studies.

This study aimed to evaluate the bidirectional association between the kidney dysfunction and the brain health, including structural and functional abnormalities. Systematic review and meta-analysis with network meta-analysis for outcomes with different estimated glomerular filtration rate (eGFR) ranges. PubMed, Embase database, Cochrane library and Web of Science (up to Dec. 2021). Longitudinal studies that provided evidence of the impact of kidney function estimated from eGFR and urine albumin-to-creatinine ratio (UACR) or chronic kidney disease (CKD) on structural and functional brain abnormalities, and those that provided evidence of the opposite relationship. Studies with study population mean age under 18 years old were excluded. Two independent reviewers screened the included studies, extracted the data, and assessed the risk of bias. We performed a random-effects meta-analysis and a network meta-analysis for outcomes with compatible data. We assessed the risk of bias using the Newcastle-Ottawa Quality Assessment Scale criteria (NOS). Subgroup and sensitivity analyses were conducted to explore heterogeneity in the meta-analyses. Inconsistency analyses using the node-splitting method were performed to confirm the results of network meta-analysis. A total of 53 studies with 3037,357 participants were included in the current systematic review. Among these, 16 provided evidence of structural brain abnormalities, and 38 provided evidence of cognitive impairment and dementia. Analysis of evidence of categorical kidney function showed a positive association between kidney dysfunction and cerebral small vessel disease (cSVD) (relative risk (RR) 1.77, 95% confidence interval (CI) 1.40-2.24, I2 =0.0%), but such results were not found in the analyses of evidence where the kidney function was measured as a continuous variable. Meanwhile, analysis of 28 prior longitudinal studies with 194 compatible sets of data showed that the worse kidney function as categorical variables was related to a greater risk of global brain cognitive disorder (RR 1.28, 95% CI 1.20-1.36, I2 = 82.5%). In this systematic review and meta-analysis, we found a positive association between CKD and functional brain disorders. However, the relationship between the kidney dysfunction and structural abnormalities in the brain remains controversial. As for the opposite relationship, structural brain abnormalities, especially cerebral microbleeds and silent infarction, but not functional brain abnormalities, are associated with worse renal function. In addition, a higher UACR, but not a lower eGFR, was associated with a higher risk of Alzheimer's disease and vascular dementia.

Isoflavone and Antioxidant of Instant Cream Soup Made from Pumpkin and Tempeh and Their Active Compound in Ovariohysterectomy Rat-Induced Alzheimer's Disease.

Menopause period associated with brain function disorders can caused by decreasing estradiol levels and increasing oxidative stress in the body. Antioxidant agents are required to balance oxidative stress in the body. Instant cream soup made from pumpkin and tempeh is a supplementary food containing isoflavone and antioxidant agents. This study is aimed at analyzing the content of antioxidant level and isoflavones (genistein and daidzein) in instant cream soup and their effect on ovariohysterectomy (OVx) rats. Instant pumpkin cream soup with and without tempeh were subjected to isoflavone content and antioxidant analysis. Serum estradiol was analyzed using enzyme-linked immunosorbent assay. Liver concentration of malondialdehyde (MDA) and activities of superoxide dismutase (SOD) were measured by spectrophotometric methods. The study showed that the isoflavone content (genistein 370.86 g/100 g, daidzein 185.61 g/100 g) was only present in the pumpkin instant cream soup with tempeh (IPTS). IPTS has higher antioxidant levels (134.25 mg AEAC/100 g) than instant pumpkin cream soup without tempeh (IPS). In vivo study, experimental rats showed that OVx increased malondialdehyde (MDA) levels up to 5.85-6.07 nmol mL-1 as compared to control (4.47 nmol mL-1). Moreover, instant pumpkin cream soup with tempeh treatments significantly increased serum estradiol levels (2.37-3.63 μg) and superoxide dismutase (SOD) levels of 497.49-558.89 U mL-1. This study concluded that instant pumpkin cream soup and tempeh contained isoflavone and antioxidant, and it increased estradiol serum and SOD level.

Development of highly sensitive, flexible dual L-glutamate and GABA microsensors for in vivo brain sensing

Real-time tracking of neurotransmitter levels in vivo has been technically challenging due to the low spatiotemporal resolution of current methods. Since the imbalance of cortical excitation/inhibition (E:I) ratios are associated with a variety of neurological disorders, accurate monitoring of excitatory and inhibitory neurotransmitter levels is crucial for investigating the underlying neural mechanisms of these conditions. Specifically, levels of the excitatory neurotransmitter L-glutamate, and the inhibitory neurotransmitter GABA, are assumed to play critical roles in the E:I balance. Therefore, in this work, a flexible electrochemical microsensor is developed for real-time simultaneous detection of L-glutamate and GABA. The flexible polyimide substrate was used for easier handling during implantation and measurement, along with less brain damage. Further, by electrochemically depositing Pt-black nanostructures on the sensor’s surface, the active surface area was enhanced for higher sensitivity. This dual neurotransmitter sensor probe was validated under various settings for its performance, including in vitro, ex vivo tests with glutamatergic neuronal cells and in vivo test with anesthetized rats. Additionally, the sensor’s performance has been further investigated in terms of longevity and biocompatibility. Overall, our dual L-glutamate:GABA sensor microprobe has its unique features to enable accurate, real-time, and long-term monitoring of the E:I balance in vivo. Thus, this new tool should aid investigations of neural mechanisms of normal brain function and various neurological disorders.

Transepithelial Effect of Probiotics in a Novel Model of Gut Lumen to Nerve Signaling.

Recent studies have shown that the gut microbiome changes brain function, behavior, and psychiatric and neurological disorders. The Gut-Brain Axis (GBA) provides a neuronal pathway to explain this. But exactly how do commensal bacteria signal through the epithelial layer of the large intestine to activate GBA nerve afferents? An in vitro model is described. We differentiated two human cell lines: Caco2Bbe1 into mature epithelium on 0.4-micron filters and then SH-SY5Y into mature neurons in 24-well plates. These were co-cultured by placing the epithelium-laden filters 1 mm above the neurons. Twenty-four hours later they were tri-cultured by apical addition of 107Lactobacillus rhamnosus or Lactobacillus fermentum which settled on the epithelium. Alone, the Caco2bbe1 cells stimulated neurite outgrowth in underlying SH-SY5Y. Beyond this, the lactobacilli were well tolerated and stimulated further neurite outgrowth by 24 h post-treatment, though not passing through the filters. The results provide face validity for a first-of-kind model of transepithelial intestinal lumen-to nerve signaling. The model displays the tight junctional barrier characteristics found in the large intestine while at the same time translating stimulatory signals from the bacteria through epithelial cells to attracted neurons. The model is easy to set-up with components widely available.

Cnpy32xHA mice reveal neuronal expression of Cnpy3 in the brain

BackgroundIdentification of biallelic CNPY3 mutations in patients with epileptic encephalopathy and abnormal electroencephalography findings of Cnpy3 knock-out mice have indicated that the loss of CNPY3 function causes neurological disorders such as epilepsy. However, the basic property of CNPY3 in the brain remains unclear. New methodWe generated C-terminal 2xHA-tag knock-in Cnpy3 mice by i-GONAD in vivo genome editing system to investigate the expression and function of Cnpy3 in the mouse brain. Results2xHA-tagged Cnpy3 was confirmed by immunoblot analysis using anti-HA and CNPY3 antibodies, although HA tagging caused the decreased Cnpy3 protein level. Immunohistochemical analysis of Cnpy32xHA knock-in mice showed that Cnpy3-2xHA was predominantly expressed in the neuron. In addition, Cnpy3 and Cnpy3-2xHA were both localized in the endoplasmic reticulum and synaptosome and showed age-dependent expression changes in the brain. Comparison with existing methodsConventional Cnpy3 antibodies could not allow us to investigate the distribution of Cnpy3 expression in the brain, while HA-tagging revealed the expression of CNPY3 in neuronal cells. ConclusionsTaken together, we demonstrated that Cnpy32xHA knock-in mice would be useful to further elucidate the property of Cnpy3 in brain function and neurological disorders.

Effects of Donepezil Treatment on Brain Metabolites, Gut Microbiota, and Gut Metabolites in an Amyloid Beta-Induced Cognitive Impairment Mouse Pilot Model.

Accumulated clinical and biomedical evidence indicates that the gut microbiota and their metabolites affect brain function and behavior in various central nervous system disorders. This study was performed to investigate the changes in brain metabolites and composition of the fecal microbial community following injection of amyloid β (Aβ) and donepezil treatment of Aβ-injected mice using metataxonomics and metabolomics. Aβ treatment caused cognitive dysfunction, while donepezil resulted in the successful recovery of memory impairment. The Aβ + donepezil group showed a significantly higher relative abundance of Verrucomicrobia than the Aβ group. The relative abundance of 12 taxa, including Blautia and Akkermansia, differed significantly between the groups. The Aβ + donepezil group had higher levels of oxalate, glycerol, xylose, and palmitoleate in feces and oxalate, pyroglutamic acid, hypoxanthine, and inosine in brain tissues than the Aβ group. The levels of pyroglutamic acid, glutamic acid, and phenylalanine showed similar changes in vivo and in vitro using HT-22 cells. The major metabolic pathways in the brain tissues and gut microbiota affected by Aβ or donepezil treatment of Aβ-injected mice were related to amino acid pathways and sugar metabolism, respectively. These findings suggest that alterations in the gut microbiota might influence the induction and amelioration of Aβ-induced cognitive dysfunction via the gut–brain axis. This study could provide basic data on the effects of Aβ and donepezil on gut microbiota and metabolites in an Aβ-induced cognitive impairment mouse model.

Fluorescent transgenic mouse models for whole-brain imaging in health and disease.

A paradigm shift is occurring in neuroscience and in general in life sciences converting biomedical research from a descriptive discipline into a quantitative, predictive, actionable science. Living systems are becoming amenable to quantitative description, with profound consequences for our ability to predict biological phenomena. New experimental tools such as tissue clearing, whole-brain imaging, and genetic engineering technologies have opened the opportunity to embrace this new paradigm, allowing to extract anatomical features such as cell number, their full morphology, and even their structural connectivity. These tools will also allow the exploration of new features such as their geometrical arrangement, within and across brain regions. This would be especially important to better characterize brain function and pathological alterations in neurological, neurodevelopmental, and neurodegenerative disorders. New animal models for mapping fluorescent protein-expressing neurons and axon pathways in adult mice are key to this aim. As a result of both developments, relevant cell populations with endogenous fluorescence signals can be comprehensively and quantitatively mapped to whole-brain images acquired at submicron resolution. However, they present intrinsic limitations: weak fluorescent signals, unequal signal strength across the same cell type, lack of specificity of fluorescent labels, overlapping signals in cell types with dense labeling, or undetectable signal at distal parts of the neurons, among others. In this review, we discuss the recent advances in the development of fluorescent transgenic mouse models that overcome to some extent the technical and conceptual limitations and tradeoffs between different strategies. We also discuss the potential use of these strains for understanding disease.

Anti-seizures therapeutics in patients with epilepsy: an approach to levetiracetam – review

Epilepsy is a chronic condition that consists of a transient disorder of brain function manifested by recurrent and unprovoked seizures affecting approximately 50 million people worldwide. Antiepileptic treatment is aimed at possible improvement the quality of life by reducing epilepsy seizures with the lowest possible side effects. One of the newest broad spectrum antiepileptic drug (AED) for the treatment of wide range of epilepsies – focal, partial, myoclonic, tonic-clonic and primary generalized seizures that can be used in both children and adults is levetiracetam. Levetiracetam is believed to bind to SV2A (synaptic vesicle protein 2A) in the brain, prevent the release of calcium stores from neurons and inhibit GABA and glycine activity. Due to the unique mechanism of action, high bioavailability (in both oral and intravenous administration), rapid absorption, metabolism based on the hydrolysis of acetamide groups in the blood (independent of the liver) and the lack of activity of the resulting metabolites, the drug is considered to be safe and effective in reducing and stopping seizures. In this review, we present the latest reports on the effectiveness of levetiracetam and its potential in the treatment of epilepsy in children and adults.

Microtransplantation of Synaptic Membranes to Reactivate Human Synaptic Receptors for Functional Studies.

Excitatory and inhibitory ionotropic receptors are the major gates of ion fluxes that determine the activity of synapses during physiological neuronal communication. Therefore, alterations in their abundance, function, and relationships with other synaptic elements have been observed as a major correlate of alterations in brain function and cognitive impairment in neurodegenerative diseases and mental disorders. Understanding how the function of excitatory and inhibitory synaptic receptors is altered by disease is of critical importance for the development of effective therapies. To gain disease-relevant information, it is important to record the electrical activity of neurotransmitter receptors that remain functional in the diseased human brain. So far this is the closest approach to assess pathological alterations in receptors' function. In this work, a methodology is presented to perform microtransplantation of synaptic membranes, which consists of reactivating synaptic membranes from snap frozen human brain tissue containing human receptors, by its injection and posterior fusion into the membrane of Xenopus laevis oocytes. The protocol also provides the methodological strategy to obtain consistent and reliable responses of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and γ-aminobutyric acid (GABA) receptors, as well as novel detailed methods that are used for normalization and rigorous data analysis.

Altered Microstate Dynamics and Spatial Complexity in Late-Life Schizophrenia

BackgroundResting-state EEG microstate and omega complexity analyses have been widely used to explore deviant brain function in various neuropsychiatric disorders. This study aimed to investigate the features of microstate dynamics and spatial complexity in patients with late-life schizophrenia (LLS).MethodMicrostate and omega complexity analyses were performed on resting-state EEG data from 39 in patients with LLS and compared with 40 elderly normal controls (NCs).ResultThe duration of microstate classes A and D were significantly higher in patients with LLS compared with NCs. The occurrence of microstate classes A, B, and C was significantly lower in patients with LLS compared with NCs. LLS patients have a lower time coverage of microstate class A and a higher time coverage of class D than NCs. Transition probabilities from microstate class A to B and from class A to C were significantly lower in patients with LLS compared with NCs. Transition probabilities between microstate class B and D were significantly higher in patients with LLS compared with NCs. Global omega complexity and anterior omega complexity were significantly higher in patients with LLS compared with NCs.ConclusionThis study revealed an altered pattern of microstate dynamics and omega complexity in patients with LLS. This may reflect the disturbed neural basis underlying LLS and enhance the understanding of the pathophysiology of LLS.

Melatonin and the Brain-Heart Crosstalk in Neurocritically Ill Patients-From Molecular Action to Clinical Practice.

Brain injury, especially traumatic brain injury (TBI), may induce severe dysfunction of extracerebral organs. Cardiac dysfunction associated with TBI is common and well known as the brain–heart crosstalk, which broadly refers to different cardiac disorders such as cardiac arrhythmias, ischemia, hemodynamic insufficiency, and sudden cardiac death, which corresponds to acute disorders of brain function. TBI-related cardiac dysfunction can both worsen the brain damage and increase the risk of death. TBI-related cardiac disorders have been mainly treated symptomatically. However, the analysis of pathomechanisms of TBI-related cardiac dysfunction has highlighted an important role of melatonin in the prevention and treatment of such disorders. Melatonin is a neurohormone released by the pineal gland. It plays a crucial role in the coordination of the circadian rhythm. Additionally, melatonin possesses strong anti-inflammatory, antioxidative, and antiapoptotic properties and can modulate sympathetic and parasympathetic activities. Melatonin has a protective effect not only on the brain, by attenuating its injury, but on extracranial organs, including the heart. The aim of this study was to analyze the molecular activity of melatonin in terms of TBI-related cardiac disorders. Our article describes the benefits resulting from using melatonin as an adjuvant in protection and treatment of brain injury-induced cardiac dysfunction.

Elevation of N-acetyltransferase 10 in hippocampal neurons mediates depression- and anxiety-like behaviors

Major depressive disorder (MDD) is one of the most debilitating and severe mental diseases globally. Increasing evidence has shown that epigenetics is critical for understanding brain function and brain disorders, including MDD. N-acetyltransferase 10 (NAT10), acting on histones, mRNA and other substrates, has been reported to be involved in epigenetic events, including histone acetylation and mRNA modifications. NAT10 is highly expressed in the brain. However, the potential effects of NAT10 on MDD are still unknown. Here, we exploited chronic mild stress (CMS) to induce anxiety- and depression-like behaviors in mice and found that the expression of NAT10 in the mouse hippocampus was upregulated after CMS treatment. Inhibition of NAT10 by pharmacological methods produced anxiolytic- and antidepressant-like effects. Neuron-specific overexpression of NAT10 in the hippocampus resulted in anxiety- and depression-like behaviors, accompanied by higher SIRT1 protein levels, and lower dendritic spine densities. Overall, it was found that elevation of NAT10 in hippocampal neurons is involved in the occurrence of anxiety- and depression-like behaviors, suggesting that NAT10 could be a potential new target for developing anxiolytics and antidepressants.

Real-time imaging of glutamate transients in the extracellular space of acute human brain slices using a single-wavelength glutamate fluorescence nanosensor

Glutamate is the most important excitatory neurotransmitter in the brain. The ability to assess glutamate release and re-uptake with high spatial and temporal resolution is crucial to understand the involvement of this primary excitatory neurotransmitter in both normal brain function and different neurological disorders. Real-time imaging of glutamate transients by fluorescent nanosensors has been accomplished in rat brain slices. We performed for the first time single-wavelength glutamate nanosensor imaging in human cortical brain slices obtained from patients who underwent epilepsy surgery. The glutamate fluorescence nanosensor signals of the electrically stimulated human cortical brain slices showed steep intensity increase followed by an exponential decrease. The spatial distribution and the time course of the signal were in good agreement with the position of the stimulation electrode and the dynamics of the electrical stimulation, respectively. Pharmacological manipulation of glutamate release and reuptake was associated with corresponding changes in the glutamate fluorescence nanosensor signals. We demonstrated that the recently developed fluorescent nanosensors for glutamate allow to detect neuronal activity in acute human cortical brain slices with high spatiotemporal precision. Future application to tissue samples from different pathologies may provide new insights into pathophysiology without the limitations of an animal model.

Is there mathematics to madness?

It’s hard to understand how heart failure can cause shortness of breath without some understanding of the role a pump plays in maintaining pressure gradients. The brain performs functions which are of a computational nature. Hence, a computational approach is likely necessary if we are to deeply understand disorders of brain function—particularly psychiatric disorders, where biological disturbances can be very subtle. More broadly, an understanding of the functions of an organ is critical if we are to comprehend the symptoms arising from disease in that organ. Computational psychiatry is a young field that attempts to harness the advances in computational progress for improved understanding, prognosis and treatment of mental illness. It lies at the interface of psychiatry, experimental and clinical psychology, neuroscience, machine learning, artificial intelligence and computational neuroscience.1 Computational psychiatry broadly encompasses two types of approaches. Data-driven approaches harness the advances in artificial intelligence, computational resources and big datasets. The theoretical branch, on the other hand, attempts to build mathematical or computational models of the relevant neural, circuit or cognitive processes.2

Altered cortical structure network in children with obstructive sleep apnea.

Obstructive sleep apnea (OSA) is characterized by recurrent airway collapse during sleep, resulting in intermittent hypoxia and sleep fragmentation that may contribute to alternations in brain structure and function. We hypothesized that OSA in children reorganizes and alters cortical structure, which can cause changes in cortical thickness correlation between brain regions across subjects. We constructed cortical structure networks based on cortical thickness measurements from 41 controls (age 15.54 ± 1.66 years, male 19) and 50 children with OSA (age 15.32 ± 1.65 years, male 29). The global (clustering coefficient [CC], path length, and small-worldness) and regional (nodal betweenness centrality, NBC) network properties and hub region distributions were examined between groups. We found increased CCs in OSA compared to controls across a wide range of network densities (p-value < .05) and lower NBC area under the curve in left caudal anterior cingulate, left caudal middle frontal, left fusiform, left transverse temporal, right pars opercularis, and right precentral gyri (p-value < .05). In addition, while most of the hub regions were the same between groups, the OSA group had fewer hub regions and a different hub distribution compared to controls. Our findings suggest that children with OSA exhibit altered global and regional network characteristics compared to healthy controls. Our approach to the investigation of cortical structure in children with OSA could prove useful in understanding the etiology of OSA-related brain functional disorders.