Differences in cortical microstructure according to body mass index in neurologically healthy populations using structural magnetic resonance imaging.

Associations between brain structure and body mass index (BMI) are increasingly gaining attention. Although BMI-related regional alterations in brain morphology have been previously reported, the effect of BMI on the microstructural profiles, which provide information on the proxy of neuronal density within the cortex, is unexplored. In this study, we investigated the links between cortical layer-specific microstructural profiles and BMI in 302 neurologically healthy young adults. Using the microstructure-sensitive proxy based on the T1-and T2-weighted ratio, we estimated microstructural profile covariance (MPC) by calculating linear correlations of cortical depth-wise intensity profiles between different brain regions. Then, low-dimensional gradients of the MPC matrix were estimated using dimensionality reduction techniques, and the gradients were associated with BMI. Significant effects in the heteromodal association areas were observed. The BMI-gradient association map was related to the geodesic distance along the cortical surface, curvature, and sulcal depth, suggesting that the microstructural alterations occurred along the cortical topology. The BMI-gradient association map was further linked to cognitive states related to negative emotions. Our findings may provide insights into understanding the atypical cortical microstructure associated with BMI.

Effectiveness and mechanism of Huoxin pill on heart failure after percutaneous coronary intervention: Study protocol for a double-blind, randomised, placebo-controlled parallel trial.

Background: Coronary heart disease (CHD) is the most common cardiovascular disease facing human beings. Cardiac remodelling is an important pathological factor for the progression of heart failure (HF) after CHD. At present, Chinese medicine is widely used in the treatment of HF, but there are still some drugs lack of evidence-based and mechanism evidence. Multi-omics techniques can deep explore candidate pathogenic factors and construct gene regulatory networks.This trial is intended to evaluate the effect on Huoxin pill (HXP) in the treatment of HF after programmable communication interface (PCI). Meantime, multi-omics analysis technique will be used to target the fundamental pathological links of cardiac remodelling, so as to study the mechanism of HXP in the treatment of HF after PCI. Methods: This study is a randomized, double-blind, placebo-controlled trial. Sixty patients with HF undergoing PCI are recruited from the First Affiliated Hospital of Henan University of CM. All selected patients will be randomly attributed to receive conventional treatment + HXP or placebo. The packaging, dosage and smell of placebo and heart activating pill were identical. The primary outcome is NYHA cardiac function grade, while the secondary outcomes included Lee's HF score, exercise tolerance test, and quality of life evaluation. Additional indicators include cardiac ultrasound, electrocardiogram, 24-h dynamic electrocardiogram, myocardial injury indicators, and energy metabolism indicators. Discussion: This study may provide a new treatment option for patients with HF after PCI and provide evidence for the treatment of CHD and HF with HXP. Trial registration: 2023-10-08 registered in China Clinical Trial Registry, registration number ChiCTR2300076402.

Tau follows principal axes of functional and structural brain organization in Alzheimer's disease.

Alzheimer's disease (AD) is a brain network disorder where pathological proteins accumulate through networks and drive cognitive decline. Yet, the role of network connectivity in facilitating this accumulation remains unclear. Using in-vivo multimodal imaging, we show that the distribution of tau and reactive microglia in humans follows spatial patterns of connectivity variation, the so-called gradients of brain organization. Notably, less distinct connectivity patterns ("gradient contraction") are associated with cognitive decline in regions with greater tau, suggesting an interaction between reduced network differentiation and tau on cognition. Furthermore, by modeling tau in subject-specific gradient space, we demonstrate that tau accumulation in the frontoparietal and temporo-occipital cortices is associated with greater baseline tau within their functionally and structurally connected hubs, respectively. Our work unveils a role for both functional and structural brain organization in pathology accumulation in AD, and supports subject-specific gradient space as a promising tool to map disease progression.

A shifting role of thalamocortical connectivity in the emergence of cortical functional organization.

The cortical patterning principle has been a long-standing question in neuroscience, yet how this translates to macroscale functional specialization in the human brain remains largely unknown. Here we examine age-dependent differences in resting-state thalamocortical connectivity to investigate its role in the emergence of large-scale functional networks during early life, using a primarily cross-sectional but also longitudinal approach. We show that thalamocortical connectivity during infancy reflects an early differentiation of sensorimotor networks and genetically influenced axonal projection. This pattern changes in childhood, when connectivity is established with the salience network, while decoupling externally and internally oriented functional systems. A developmental simulation using generative network models corroborated these findings, demonstrating that thalamic connectivity contributes to developing key features of the mature brain, such as functional segregation and the sensory-association axis, especially across 12-18 years of age. Our study suggests that the thalamus plays an important role in functional specialization during development, with potential implications for studying conditions with compromised internal and external processing.

Shifts in structural connectome organization in the limbic and sensory systems of patients with episodic migraine.

Migraine is a complex neurological condition characterized by recurrent headaches, which is often accompanied by various neurological symptoms. Magnetic resonance imaging (MRI) is a powerful tool for investigating whole-brain connectivity patterns; however, systematic assessment of structural connectome organization has rarely been performed. In the present study, we aimed to examine the changes in structural connectivity in patients with episodic migraines using diffusion MRI. First, we computed structural connectivity using diffusion MRI tractography, after which we applied dimensionality reduction techniques to the structural connectivity and generated three low-dimensional eigenvectors. We subsequently calculated the manifold eccentricity, defined as the Euclidean distance between each data point and the center of the data in the manifold space. We then compared the manifold eccentricity between patients with migraines and healthy controls, revealing significant between-group differences in the orbitofrontal cortex, temporal pole, and sensory/motor regions. Between-group differences in subcortico-cortical connectivity further revealed significant changes in the amygdala, accumbens, and caudate nuclei. Finally, supervised machine learning effectively classified patients with migraines and healthy controls using cortical and subcortical structural connectivity features, highlighting the importance of the orbitofrontal and sensory cortices, in addition to the caudate, in distinguishing between the groups. Our findings confirmed that episodic migraine is related to the structural connectome changes in the limbic and sensory systems, suggesting its potential utility as a diagnostic marker for migraine.

Connectome reorganization associated with temporal lobe pathology and its surgical resection.

Network neuroscience offers a unique framework to understand the organizational principles of the human brain. Despite recent progress, our understanding of how the brain is modulated by focal lesions remains incomplete. Resection of the temporal lobe is the most effective treatment to control seizures in pharmaco-resistant temporal lobe epilepsy (TLE), making this syndrome a powerful model to study lesional effects on network organization in young and middle-aged adults. Here, we assessed the downstream consequences of a focal lesion and its surgical resection on the brain's structural connectome, and explored how this reorganization relates to clinical variables at the individual patient level. We included adults with pharmaco-resistant TLE (n = 37) who underwent anterior temporal lobectomy between two imaging time points, as well as age- and sex-matched healthy controls who underwent comparable imaging (n = 31). Core to our analysis was the projection of high-dimensional structural connectome data-derived from diffusion MRI tractography from each subject-into lower-dimensional gradients. We then compared connectome gradients in patients relative to controls before surgery, tracked surgically-induced connectome reconfiguration from pre- to postoperative time points, and examined associations to patient-specific clinical and imaging phenotypes. Before surgery, individuals with TLE presented with marked connectome changes in bilateral temporo-parietal regions, reflecting an increased segregation of the ipsilateral anterior temporal lobe from the rest of the brain. Surgery-induced connectome reorganization was localized to this temporo-parietal subnetwork, but primarily involved postoperative integration of contralateral regions with the rest of the brain. Using a partial least-squares analysis, we uncovered a latent clinical imaging signature underlying this pre- to postoperative connectome reorganization, showing that patients who displayed postoperative integration in bilateral fronto-occipital cortices also had greater preoperative ipsilateral hippocampal atrophy, lower seizure frequency and secondarily generalized seizures. Our results bridge the effects of focal brain lesions and their surgical resections with large-scale network reorganization and interindividual clinical variability, thus offering new avenues to examine the fundamental malleability of the human brain.

Gradients of Brain Organization: Smooth Sailing from Methods Development to User Community.

Multimodal neuroimaging grants a powerful in vivo window into the structure and function of the human brain. Recent methodological and conceptual advances have enabled investigations of the interplay between large-scale spatial trends - or gradients - in brain structure and function, offering a framework to unify principles of brain organization across multiple scales. Strong community enthusiasm for these techniques has been instrumental in their widespread adoption and implementation to answer key questions in neuroscience. Following a brief review of current literature on this framework, this perspective paper will highlight how pragmatic steps aiming to make gradient methods more accessible to the community propelled these techniques to the forefront of neuroscientific inquiry. More specifically, we will emphasize how interest for gradient methods was catalyzed by data sharing, open-source software development, as well as the organization of dedicated workshops led by a diverse team of early career researchers. To this end, we argue that the growing excitement for brain gradients is the result of coordinated and consistent efforts to build an inclusive community and can serve as a case in point for future innovations and conceptual advances in neuroinformatics. We close this perspective paper by discussing challenges for the continuous refinement of neuroscientific theory, methodological innovation, and real-world translation to maintain our collective progress towards integrated models of brain organization.

[Network Meta-analysis of Chinese patent medicine in treatment of heart failure with preserved ejection fraction].

This study systematically evaluated the efficacy and safety of different Chinese patent medicines combined with conventional western medicine in the treatment of heart failure with preserved ejection fraction(HFpEF) and ranked for the drug selection. Randomized controlled trial(RCT) on Chinese patent medicines in treatment of HFpEF were obtained from the CNKI, Wanfang, VIP, SinoMed, PubMed, Cochrane Library, EMbase, Web of Science, and other databases from the inception to October 9, 2022. The included RCT was quantitatively analyzed using gemtc and rjags packages of R software for the network Meta-analysis. 74 RCTs were included, with a total of 7 192 patients enrolled, involving 11 different Chinese patent medicines(Shenfu Injection, Shenmai Injection, Qili Qiangxin Capsules, Shexiang Baoxin Pills, Xuezhikang Capsules, Salvia Miltiorrhiza Polyphenols Injection, Tanshinone Ⅱ_A Sulfonate Injection, Xinmailong Injection, Yangxinshi Tablets, Qishen Yiqi Dripping Pills, and Yixinshu Capsules). The results of network Meta-analysis are shown as followed.(1)In terms of improving clinical effective rate, for injection preparations, Xinmailong Injection + conventional western medicine was recommended. while for oral preparations, Shexiang Baoxin Pills + conventional western medicine, Qishen Yiqi Dripping Pills + conventional western medicine, and Qili Qiangxin Capsules + conventional western medicine were preferred.(2)In terms of improving the mitral ratio of peak early to late diastolic filling velocity(E/A), for injection preparations, Shenmai Injection + Salvia Miltiorrhiza Polyphenols Injection + conventional western medicine, Shenmai Injection + conventional western medicine, Shenfu Injection + conventional western medicine were preferred. While for oral preparations, Yixinshu Capsules + conventional western medicine was preferred.(3)In terms of reducing the ratio of early diastolic mitral inflow to early diastolic mitral annular velocity(E/e'), Shenfu Injection + conventional western medicine could be used as injection preparation, and Qili Qiangxin Capsules + conventional western medicine, Qishen Yiqi Dripping Pills + conventional western medicine for oral preparations.(4)In terms of improving 6-minute walking trail(6MWT), the injection preparations such as Shenmai Injection + conventional western medicine, Xinmailong Injection + conventional western medicine were suitable, while oral preparations like Qishen Yiqi Dripping Pills + conventional western medicine, Qili Qiangxin Capsules + conventional western medicine were recommended.(5)In terms of reducing N-terminal pro B-type natriuretic peptide(NT-proBNP), Qili Qiangxin Capsules + conventional western medicine were preferred.(6)In terms of reducing B-type natriuretic peptide(BNP), Xinmailong Injection + conventional western medicine could be used for injection preparation and Qili Qiangxin Capsules + conventional western medicine can be used for oral preparation. In terms of adverse drug reactions, there was no significant difference between Chinese patent medicine combined with conventional western conventional and traditional western medicine alone. The results showe that Chinese patent medicine combined with conventional western medicine in treating HFpEF is superior to conventional western medicine alone in reducing clinical symptoms, improving cardiac function, and improving exercise tolerance, which also has good drug safety. However, the existing evidence is still limited by the quality and quantity of included studies, so the above conclusion requires further validation through more prospective RCT.

[Evidence map of clinical research on Chinese patent medicines for post-acute myocardial infarction heart failure].

An evidence map was established to comprehensively sort out the clinical research in the treatment of post-acute myocardial infarction heart failure(P-AMI-HF) with Chinese patent medicines, so as to reveal the distribution of evidence in this field. CNKI, Wanfang, VIP, SinoMed, PubMed, Cochrane Library, and EMbase were searched for the randomized controlled trial(RCT), systematic reviews/Meta-analysis, and guidelines/consensus in this field. The evidence was analyzed and displayed in the form of a combination of text, charts, bubble charts, and bar charts, and the quality of RCT, systematic reviews/Meta-analysis, and guidelines/consensus were evaluated by RoB 1.0, AMSTAR2, and AGREE Ⅱ, respectively. A total of 163 RCTs, 4 systematic reviews/Meta-analysis, 1 network Meta-analysis, 2 observational studies, and 5 guidelines/consensus were included. In recent years, the total number of publications in this field has shown an upward trend. There were a variety of Chinese patent medicines in the treatment of P-AMI-HF, among which Shenfu Injection received the most attention. The clinical RCT and systematic reviews/Meta-analysis generally had poor quality, and the RCT mostly had a small size, a single center, and a short cycle. The outcome indicators mainly included cardiac function indicators, myocardial injury markers, total response rate, hemodynamic indicators, and safety indicators, while the characteristic efficacy indicators of TCM received insufficient attention. The development processes of some guidelines/consensus lack standardization, which compromised their authority and rationality. Chinese patent medicines have advantages in the treatment of P-AMI-HF, while there are also problems, which remain to be solved by more high-quality evidence. That is, more large-sample and multi-center clinical studies should be carried out in the future, and the formulation process of relevant systematic reviews/Meta-analysis and guideline/consensus should be standardized and the quality of evidence should be improved. In this way, the effectiveness and safety of Chinese patent medicines in the treatment of P-AMI-HF can be explored.

Association Study of Pleural Mesothelioma and Oncogenic Simian Virus 40 in the Crocidolite-Contaminated Area of Dayao County, Yunnan Province, Southwest China.

Background: In Dayao County, Chuxiong Yi Autonomous Prefecture, Yunnan Province, Southwest China, 5% of the surface is scattered with blue asbestos, which has a high incidence of pleural mesothelioma (PMe). Simian virus 40 (SV40) is a small circular double-stranded DNA polyomavirus that can cause malignant transformation of normal cells of various human and animal tissue types and promote tumor growth. In this study, we investigate whether oncogenic SV40 is associated with the occurrence of PMe in the crocidolite-contaminated area of Dayao County, Yunnan Province, Southwest China. Methods: Tumor tissues from 51 patients with PMe (40 of whom had a history of asbestos exposure) and pleural tissues from 12 non-PMe patients (including diseases such as pulmonary maculopathy and pulmonary tuberculosis) were collected. Three pairs of low-contamination risk primers (SVINT, SVfor2, and SVTA1) were used to detect the gene fragment of SV40 large T antigen (T-Ag) by polymerase chain reaction (PCR). The presence of SV40 T-Ag in PMe tumor tissues and PMe cell lines was detected by Western blotting and immunohistochemical staining with SV40-related antibodies (PAb 101 and PAb 416). Results: PCR, Western blotting, and immunohistochemical staining results showed that the Met5A cell line was positive for SV40 and contained the SV40 T-Ag gene and protein. In contrast, the various PMe cell lines NCI-H28, NCI-H2052, and NCI-H2452 were negative for SV40. PCR was negative for all three sets of low-contamination risk primers in 12 non-PMe tissues and 51 PMe tissues. SV40 T-Ag was not detected in 12 non-PMe tissues or 51 PMe tissues by immunohistochemical staining. Conclusion: Our data suggest that the occurrence of PMe in the crocidolite-contaminated area of Yunnan Province may not be related to SV40 infection and that crocidolite exposure may be the main cause of PMe. The Clinical Trial Registration number: 2020-YXLL20.

Diffusion time-related structure-function coupling reveals differential association with inter-individual variations in body mass index.

Body mass index (BMI) is an indicator of obesity, and recent neuroimaging studies have demonstrated that inter-individual variations in BMI are associated with altered brain structure and function. However, the mechanism underlying the alteration of structure-function correspondence according to BMI is under-investigated. In this study, we studied structural and functional connectivity derived from diffusion MRI tractography and inter-regional correlations of functional MRI time series, respectively. We combined the structural and functional connectivity information using the Riemannian optimization approach. First, the low-dimensional principal eigenvectors (i.e., gradients) of the structural connectivity were generated by applying diffusion map embedding with varying diffusion times. A transformation was identified so that the structural and functional embeddings share the same coordinate system, and subsequently, the functional connectivity matrix was simulated. Then, we generated gradients from the simulated functional connectivity matrix. We found the most apparent cortical hierarchical organization differentiating between low-level sensory and higher-order transmodal regions in the middle of the diffusion time, indicating that the hierarchical organization of the brain may reflect the intermediate mechanisms of mono- and polysynaptic communications. Associations between the functional gradients and BMI were strongest when the hierarchical structure was the most evident. Moreover, the gradient-BMI association map was related to the microstructural features, and the findings indicated that the BMI-related structure-function coupling was significantly associated with brain microstructure, particularly in higher-order transmodal areas. Finally, transcriptomic association analysis revealed the potential biological underpinnings specifying gene enrichment in the striatum, hypothalamus, and cortical cells. Our findings provide evidence that structure-function correspondence is strongly coupled with BMI when hierarchical organization is the most apparent and that the associations are related to the multiscale properties of the brain, leading to an advanced understanding of the neural mechanisms related to BMI.

GAN-MAT: Generative adversarial network-based microstructural profile covariance analysis toolbox.

Multimodal magnetic resonance imaging (MRI) provides complementary information for investigating brain structure and function; for example, an in vivo microstructure-sensitive proxy can be estimated using the ratio between T1- and T2-weighted structural MRI. However, acquiring multiple imaging modalities is challenging in patients with inattentive disorders. In this study, we proposed a comprehensive framework to provide multiple imaging features related to the brain microstructure using only T1-weighted MRI. Our toolbox consists of (i) synthesizing T2-weighted MRI from T1-weighted MRI using a conditional generative adversarial network; (ii) estimating microstructural features, including intracortical covariance and moment features of cortical layer-wise microstructural profiles; and (iii) generating a microstructural gradient, which is a low-dimensional representation of the intracortical microstructure profile. We trained and tested our toolbox using T1- and T2-weighted MRI scans of 1,104 healthy young adults obtained from the Human Connectome Project database. We found that the synthesized T2-weighted MRI was very similar to the actual image and that the synthesized data successfully reproduced the microstructural features. The toolbox was validated using an independent dataset containing healthy controls and patients with episodic migraine as well as the atypical developmental condition of autism spectrum disorder. Our toolbox may provide a new paradigm for analyzing multimodal structural MRI in the neuroscience community and is openly accessible at https://github.com/CAMIN-neuro/GAN-MAT.

Whole-brain structural connectome asymmetry in autism.

Autism spectrum disorder is a common neurodevelopmental condition that manifests as a disruption in sensory and social skills. Although it has been shown that the brain morphology of individuals with autism is asymmetric, how this differentially affects the structural connectome organization of each hemisphere remains under-investigated. We studied whole-brain structural connectivity-based brain asymmetry in individuals with autism using diffusion magnetic resonance imaging obtained from the Autism Brain Imaging Data Exchange initiative. By leveraging dimensionality reduction techniques, we constructed low-dimensional representations of structural connectivity and calculated their asymmetry index. Comparing the asymmetry index between individuals with autism and neurotypical controls, we found atypical structural connectome asymmetry in the sensory and default-mode regions, particularly showing weaker asymmetry towards the right hemisphere in autism. Network communication provided topological underpinnings by demonstrating that the inferior temporal cortex and limbic and frontoparietal regions showed reduced global network communication efficiency and decreased send-receive network navigation in the inferior temporal and lateral visual cortices in individuals with autism. Finally, supervised machine learning revealed that structural connectome asymmetry could be used as a measure for predicting communication-related autistic symptoms and nonverbal intelligence. Our findings provide insights into macroscale structural connectome alterations in autism and their topological underpinnings.

Identifying subgroups of eating behavior traits unrelated to obesity using functional connectivity and feature representation learning.

Eating behavior is highly heterogeneous across individuals and cannot be fully explained using only the degree of obesity. We utilized unsupervised machine learning and functional connectivity measures to explore the heterogeneity of eating behaviors measured by a self-assessment instrument using 424 healthy adults (mean ± standard deviation [SD] age = 47.07 ± 18.89 years; 67% female). We generated low-dimensional representations of functional connectivity using resting-state functional magnetic resonance imaging and estimated latent features using the feature representation capabilities of an autoencoder by nonlinearly compressing the functional connectivity information. The clustering approaches applied to latent features identified three distinct subgroups. The subgroups exhibited different levels of hunger traits, while their body mass indices were comparable. The results were replicated in an independent dataset consisting of 212 participants (mean ± SD age = 38.97 ± 19.80 years; 35% female). The model interpretation technique of integrated gradients revealed that the between-group differences in the integrated gradient maps were associated with functional reorganization in heteromodal association and limbic cortices and reward-related subcortical structures such as the accumbens, amygdala, and caudate. The cognitive decoding analysis revealed that these systems are associated with reward- and emotion-related systems. Our findings provide insights into the macroscopic brain organization of eating behavior-related subgroups independent of obesity.

Structural connectome alterations between individuals with autism and neurotypical controls using feature representation learning.

Autism spectrum disorder is one of the most common neurodevelopmental conditions associated with sensory and social communication impairments. Previous neuroimaging studies reported that atypical nodal- or network-level functional brain organization in individuals with autism was associated with autistic behaviors. Although dimensionality reduction techniques have the potential to uncover new biomarkers, the analysis of whole-brain structural connectome abnormalities in a low-dimensional latent space is underinvestigated. In this study, we utilized autoencoder-based feature representation learning for diffusion magnetic resonance imaging-based structural connectivity in 80 individuals with autism and 61 neurotypical controls that passed strict quality controls. We generated low-dimensional latent features using the autoencoder model for each group and adopted an integrated gradient approach to assess the contribution of the input data for predicting latent features during the encoding process. Subsequently, we compared the integrated gradient values between individuals with autism and neurotypical controls and observed differences within the transmodal regions and between the sensory and limbic systems. Finally, we identified significant associations between integrated gradient values and communication abilities in individuals with autism. Our findings provide insights into the whole-brain structural connectome in autism and may help identify potential biomarkers for autistic connectopathy.

Two-dimensional liquid chromatography measurement of meropenem concentration in synovial fluid of patients with periprosthetic joint infection.

Periprosthetic joint infection (PJI) is a catastrophic complication following joint replacement surgery. One potential treatment approach for PJI could be the combination of one-stage revision and intra-articular infusion of antibiotics. Meropenem is one of the commonly used intra-articular antibiotics in our institution. Determining the concentration of meropenem in the joint cavity could be crucial for optimizing its local application, effectively eradicating biofilm infection, and improving PJI treatment outcomes. In this study, we developed a simple, precise, and accurate method of two-dimensional liquid chromatography (2D-LC) for determining the concentration of meropenem in human synovial fluid. The method was then validated based on the guidelines of the Food and Drug Administration and the Chinese Pharmacopoeia. Meropenem showed good linearity in the range of 0.31-25.01 µg/mL (r ≥ .999). Selectivity, intra-day and inter-day precision and accuracy, extraction recovery, and stability validation results were all within the acceptance range. This method has been successfully applied to the determination of synovial fluid samples from PJI patients, providing a useful detection method for meropenem therapeutic drug monitoring (TDM) in PJI patients.

Connectome-wide structure-function coupling models implicate polysynaptic alterations in autism.

Autism spectrum disorder (ASD) is one of the most common neurodevelopmental diagnoses. Although incompletely understood, structural and functional network alterations are increasingly recognized to be at the core of the condition. We utilized multimodal imaging and connectivity modeling to study structure-function coupling in ASD and probed mono- and polysynaptic mechanisms on structurally-governed network function. We examined multimodal magnetic resonance imaging data in 80 ASD and 61 neurotypical controls from the Autism Brain Imaging Data Exchange (ABIDE) II initiative. We predicted intrinsic functional connectivity from structural connectivity data in each participant using a Riemannian optimization procedure that varies the times that simulated signals can unfold along tractography-derived personalized connectomes. In both ASD and neurotypical controls, we observed improved structure-function prediction at longer diffusion time scales, indicating better modeling of brain function when polysynaptic mechanisms are accounted for. Prediction accuracy differences (∆prediction accuracy) were marked in transmodal association systems, such as the default mode network, in both neurotypical controls and ASD. Differences were, however, lower in ASD in a polysynaptic regime at higher simulated diffusion times. We compared regional differences in ∆prediction accuracy between both groups to assess the impact of polysynaptic communication on structure-function coupling. This analysis revealed that between-group differences in ∆prediction accuracy followed a sensory-to-transmodal cortical hierarchy, with an increased gap between controls and ASD in transmodal compared to sensory/motor systems. Multivariate associative techniques revealed that structure-function differences reflected inter-individual differences in autistic symptoms and verbal as well as non-verbal intelligence. Our network modeling approach sheds light on atypical structure-function coupling in autism, and suggests that polysynaptic network mechanisms are implicated in the condition and that these can help explain its wide range of associated symptoms.

Differences in structural connectome organization across sleep quality.

Sleep quality, which measures satisfaction with overall sleep, is an important factor affecting an individual's health. Although previous neuroimaging studies based on magnetic resonance imaging (MRI) have observed altered regional morphology and functional activation related to poor sleep quality, the impact of sleep quality on whole-brain structural connectome organization is relatively under-investigated. To address this gap, we utilized dimensionality reduction techniques to estimate low-dimensional eigenvectors of structural connectivity derived from diffusion MRI tractography, and assessed their associations with measures of sleep quality. We found significant effects in the unimodal association and limbic regions. Additionally, the meta-analytic cognitive decoding analysis revealed associations with negative terms, including nociceptive and pain. Our findings suggest a link between alterations in the whole-brain structural organization and sleep quality, providing insights into the relationship between sleep quality and brain structure.

Atypical structural connectome asymmetry and associations with network communication in autism spectrum disorder.

Autism spectrum disorder is a common neurodevelopmental condition showing connectome disorganization in sensory and transmodal cortices. However, alterations in the inter-hemispheric asymmetry of structural connectome are remained to be investigated. Here, we studied structural connectome asymmetry in individuals with autism using dimensionality reduction techniques and assessed its topological underpinnings by associating with network communication measures. We found that the sensory and heteromodal association regions showed significant between-group differences in inter-hemispheric asymmetry between individuals with autism and neurotypical controls. In addition, the network communication ability was particularly altered between visual and limbic areas. Our findings provide insights for understanding structural connectome alteration in autism and its topological underpinnings.Clinical Relevance- This study provides insights into the understanding of atypical macroscale structural connectome organization in individuals with autism.