Functional Architecture Of Brain Research Articles

Striatal-hippocampal functional connectivity contributes to real-life positive anticipatory experiences and subjective well-being.

Positive anticipatory experiences are key to daily well-being. However, the brain's functional architecture underlying real-world positive anticipatory experiences and well-being remains unexplored. In the present study, we combined an ecological momentary assessment and resting-state functional neuroimaging to identify the neural predictors of real-world positive anticipatory experiences and explore their relationships with subjective well-being (SWB). With a model-based approach, we quantified participants' accuracy in predicting positive events and the degree to which participants' affective states were influenced by the positive anticipation. We found that individuals with higher accuracy in predicting upcoming positive events showed greater SWB, and this relationship was mediated by greater positive anticipatory feelings. Importantly, functional connectivity of the dorsal and ventral striatal-hippocampal networks significantly predicted the accuracy and positive anticipatory feelings, respectively. These functional networks were further predictive of SWB. Our findings provide novel and ecologically valid evidence that the interplay between neural systems for reward-processing and memory plays an important role in real-life positive anticipatory experiences and everyday SWB.

Reductions in the white-gray functional connectome in preclinical Alzheimer's disease and their associations with amyloid and cognition.

The magnitudes and patterns of alterations of the white-gray matter (WM-GM) functional connectome in preclinical Alzheimer's disease (AD), and their associations with amyloid and cognition, remain unclear. We compared regional WM-GM functional connectivity (FC) and network properties in subjects with preclinical AD (or AD dementia) and controls (total n=344). Their associations with positron emission tomography AV45-measured amyloid beta (Aβ) load and modified Preclinical Alzheimer Cognitive Composite (mPACC) scores were examined. Preclinical AD subjects showed lower FC in specific WM-GM pairs and reduced segregation of control, dorsal attention, and somatomotor networks. A major portion of the reduced FC and network segregations were linked to elevated Aβ. Reduced FC of one WM-GM pair correlated with impaired mPACC. AD dementia exhibited broader reductions and stronger associations. The WM-GM functional connectome undergoes regional and systemic dysfunctions as early as in the preclinical stage, correlating with amyloid deposition and predicting cognitive impairment. Preclinical Alzheimer's disease (AD) subjects showed lower functional connectivity in specific white-gray matter (WM-GM) pairs and reduced segregations of control, dorsal attention, and somatomotor networks. A major portion of the reduced connectivity and network segregations were linked to elevated amyloid beta load. Only one WM-GM pair's reduced connectivity was linearly correlated with impaired cognitive composite scores. AD dementia showed more extensive reductions in connectivity, network integration, and segregation, with stronger associations with amyloid elevation and cognitive impairment. The WM-GM functional connectome offers a distinct perspective for understanding changes in brain functional architecture throughout the AD continuum.

Markov Blankets and Cognitive Dysfunction in mTBI: Insights from Simulation Models

<p>Mild Traumatic Brain Injury (mTBI) is a prevalent neurological condition that can lead to persistent cognitive impairments, disrupting memory, attention, and executive function. In this study, we explore the mechanisms of cognitive decline in mTBI through the lens of Markov blankets—a theoretical framework that delineates the statistical boundary between the brain’s internal and external states. By simulating the impact of mTBI on sensory, active, internal, and external states, we demonstrate how disruptions to the Markov blanket structure contribute to impairments in predictive coding and cognitive processing. Our simulation introduces noise and connectivity reductions that mimic the neurometabolic and synaptic changes following mTBI, revealing delayed sensory processing, impaired motor function, and cognitive instability. These findings highlight the importance of Markov blankets in maintaining cognitive integrity and offer novel insights into the pathophysiology of post-concussion syndrome. Understanding how mTBI disrupts the brain's functional architecture through Markov blanket disturbances may inform more effective diagnostic and therapeutic approaches.</p>

Complexity organization of resting-state functional-MRI networks.

Entropy measures are increasingly being used to analyze the structure of neural activity observed by functional magnetic resonance imaging (fMRI), with resting-state networks (RSNs) being of interest for their reproducible descriptions of the brain's functional architecture. Temporal correlations have shown a dichotomy among these networks: those that engage with the environment, known as extrinsic, which include the visual and sensorimotor networks; and those associated with executive control and self-referencing, known as intrinsic, which include the default mode network and the frontoparietal control network. While these inter-voxel temporal correlations enable the assessment of synchrony among the components of individual networks, entropic measures introduce an intra-voxel assessment that quantifies signal features encoded within each blood oxygen level-dependent (BOLD) time series. As a result, this framework offers insights into comprehending the representation and processing of information within fMRI signals. Multiscale entropy (MSE) has been proposed as a useful measure for characterizing the entropy of neural activity across different temporal scales. This measure of temporal entropy in BOLD data is dependent on the length of the time series; thus, high-quality data with fine-grained temporal resolution and a sufficient number of time frames is needed to improve entropy precision. We apply MSE to the Midnight Scan Club, a highly sampled and well-characterized publicly available dataset, to analyze the entropy distribution of RSNs and evaluate its ability to distinguish between different functional networks. Entropy profiles are compared across temporal scales and RSNs. Our results have shown that the spatial distribution of entropy at infra-slow frequencies (0.005-0.1 Hz) reproduces known parcellations of RSNs. We found a complexity hierarchy between intrinsic and extrinsic RSNs, with intrinsic networks robustly exhibiting higher entropy than extrinsic networks. Finally, we found new evidence that the topography of entropy in the posterior cerebellum exhibits high levels of entropy comparable to that of intrinsic RSNs.

Rorschach and resting state-fMRI: Personality Assessment and unique associations with resting-state brain networks activity

Background The Rorschach test is one of the most popular tests used in clinical settings for psychopathology and personality assessment; however, there is still little evidence regarding the functional correlates of test responses. Functional magnetic resonance imaging (fMRI) allows for the investigation of biological correlates associated with different psychological functions. Among other applications, fMRI has been used to identify different networks that reflect brain activity in the resting state (rs-fMRI), that is, when an individual is not engaged in any specific task. Among these resting-state networks (RSN), the best-known and most studied are the Default Mode Network (DMN), along with other networks such as salience, frontoparietal, sensorimotor, temporo-parietal, visual, and cerebellar networks. Methods We used this type of analysis to obtain new evidence regarding Rorschach. This study aimed to analyze the functional brain architecture underlying Rorschach’s personality variables, administered according to Exner’s Comprehensive System (CS). In particular, the aims are: 1) to ascertain the existence of correlations between CS variables and activity of the RSN, and 2) to use these profiles of activity to develop a new data-driven clustering of the CS variables. Archival data from twenty-four non-clinical subjects were analyzed. Independent Component Analysis (ICA) and partial least squares regression (PLS) were used to analyze the fMRI data. Results The results showed specific associations with the given Rorschach variables (several of which could be grouped into higher-order latent factors) and activity of the main RSN. Moreover, the cluster analysis outlined important groupings of Rorschach variables, particularly regarding their clinical implications. Conclusions Our study could be comprised in the existing literature providing strong evidence about the neurobiological validity of the Rorschach test.

Causal Cortical and Thalamic Connections in the Human Brain.

The brain's functional architecture is intricately shaped by causal connections between its cortical and subcortical structures. Here, we studied 27 participants with 4864 electrodes implanted across the anterior, mediodorsal, and pulvinar thalamic regions, and the cortex. Using data from electrical stimulation procedures and a data-driven approach informed by neurophysiological standards, we dissociated three unique spectral patterns generated by the perturbation of a given brain area. Among these, a novel waveform emerged, marked by delayed-onset slow oscillations in both ipsilateral and contralateral cortices following thalamic stimulations, suggesting a mechanism by which a thalamic site can influence bilateral cortical activity. Moreover, cortical stimulations evoked earlier signals in the thalamus than in other connected cortical areas suggesting that the thalamus receives a copy of signals before they are exchanged across the cortex. Our causal connectivity data can be used to inform biologically-inspired computational models of the functional architecture of the brain.

Atlas for the Lateralized Visuospatial Attention Networks (ALANs): Insights from fMRI and network analyses

Abstract Hemispheric specialization is central to human evolution and fundamental to human cognitive abilities. While being a defining feature of functional brain architecture, hemispheric specialization is overlooked to derive brain parcellations. Alongside language, which is typically lateralized in the left hemisphere, visuospatial attention is set to be its counterpart in the opposite hemisphere. However, it remains uncertain to what extent the anatomical and functional underpinnings of lateralized visuospatial attention mirror those supporting language. Building on our previous work, which established a lateralized brain atlas for language, we propose a comprehensive cerebral lateralized atlas delineating the anatomo-functional bases of visuospatial attention, Atlas for Lateralized visuospatial Attentional Networks (ALANs). Combining task and resting-state functional connectivity analyses, we identified 95 lateralized brain areas comprising three networks supporting visual (visu), motor (somato-motor), and spatial processing (posterior-medial) processes at work during a line judgment bisection task, and two large-scale networks related to integrated visuospatial attention processes, the parieto-frontal and temporo-frontal networks. We identify hubs playing a pivotal role in the intra-hemispheric interaction within visuospatial attentional networks. The rightward lateralized parieto-frontal encompasses one hub, the inferior frontal sulcus, while the temporo-frontal network encompasses two right hubs: the inferior frontal cortex (pars triangularis and the anterior insula) and the posterior part of the superior temporal sulcus. Compared with our language lateralized atlas, we demonstrated that specific regions within these networks encompass the homotope of the language network from the left hemisphere. This atlas of visuospatial attention provides valuable insights for future investigations into the variability of visuospatial attention and hemispheric specialization research. Additionally, it facilitates more effective comparisons among different studies, thereby enhancing the robustness and reliability of research in the field of attention.

Stepwise Functional Brain Architecture Correlates with Atrophy in Progressive Supranuclear Palsy.

Stepwise functional connectivity (SFC) detects whole-brain functional couplings of a selected region of interest at increasing link-step topological distances. This study applied SFC to test the hypothesis that stepwise architecture propagating from the disease epicenter would shape patterns of brain atrophy in patients with progressive supranuclear palsy-Richardson's syndrome (PSP-RS). Thirty-six patients with PSP-RS and 44 age-matched healthy control subjects underwent brain magnetic resonance imaging on a 3-T scanner. The disease epicenter was defined as the peak of atrophy observed in an independent cohort of 13 cases with postmortem confirmation of PSP pathology and used as seed region for SFC analysis. First, we explored SFC rearrangements in patients with PSP-RS, as compared with age-matched control subjects. Subsequently, we tested SFC architecture propagating from the disease epicenter as a determinant of brain atrophy distribution. The disease epicenter was identified in the left midbrain tegmental region. Compared with age-matched control subjects, patients with PSP-RS showed progressively widespread decreased SFC of the midbrain with striatal and cerebellar regions through direct connections and sensorimotor cortical regions through indirect connections. A correlation was found between average link-step distance from the left midbrain in healthy subjects and brain volumes in patients with PSP-RS (r = 0.38, P < 0.001). This study provides comprehensive insights into the topology of functional network rearrangements in PSP-RS and demonstrates that the brain architectural topology, as described by SFC propagating from the disease epicenter, shapes the pattern of atrophic changes in PSP-RS. Our findings support the view of a network-based pathology propagation in this primary tauopathy. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Leveraging the adolescent brain cognitive development study to improve behavioral prediction from neuroimaging in smaller replication samples.

Neuroimaging is a popular method to map brain structural and functional patterns to complex human traits. Recently published observations cast doubt upon these prospects, particularly for prediction of cognitive traits from structural and resting state functional magnetic resonance imaging (MRI). We leverage baseline data from thousands of children in the Adolescent Brain Cognitive DevelopmentSM Study to inform the replication sample size required with univariate and multivariate methods across different imaging modalities to detect reproducible brain-behavior associations. We demonstrate that by applying multivariate methods to high-dimensional brain imaging data, we can capture lower dimensional patterns of structural and functional brain architecture that correlate robustly with cognitive phenotypes and are reproducible with only 41 individuals in the replication sample for working memory-related functional MRI, and ~ 100 subjects for structural and resting state MRI. Even with 100 random re-samplings of 100 subjects in discovery, prediction can be adequately powered with 66 subjects in replication for multivariate prediction of cognition with working memory task functional MRI. These results point to an important role for neuroimaging in translational neurodevelopmental research and showcase how findings in large samples can inform reproducible brain-behavior associations in small sample sizes that are at the heart of many research programs and grants.

Causal Cortical and Thalamic Connections in the Human Brain.

The brain's functional architecture is intricately shaped by causal connections between its cortical and subcortical structures. Here, we studied 27 participants with 4864 electrodes implanted across the anterior, mediodorsal, and pulvinar thalamic regions, and the cortex. Using data from electrical stimulation procedures and a data-driven approach informed by neurophysiological standards, we dissociated three unique spectral patterns generated by the perturbation of a given brain area. Among these, a novel waveform emerged, marked by delayed-onset slow oscillations in both ipsilateral and contralateral cortices following thalamic stimulations, suggesting a mechanism by which a thalamic site can influence bilateral cortical activity. Moreover, cortical stimulations evoked earlier signals in the thalamus than in other connected cortical areas suggesting that the thalamus receives a copy of signals before they are exchanged across the cortex. Our causal connectivity data can be used to inform biologically-inspired computational models of the functional architecture of the brain.

Polygenic architecture of brain structure and function, behaviors, and psychopathologies in children.

The human brain undergoes structural and functional changes during childhood, a critical period in cognitive and behavioral development. Understanding the genetic architecture of the brain development in children can offer valuable insights into the development of the brain, cognition, and behaviors. Here, we integrated brain imaging-genetic-phenotype data from over 8,600 preadolescent children of diverse ethnic backgrounds using multivariate statistical techniques. We found a low-to-moderate level of SNP-based heritability in most IDPs, which is lower compared to the adult brain. Using sparse generalized canonical correlation analysis (SGCCA), we identified several covariation patterns among genome-wide polygenic scores (GPSs) of 29 traits, 7 different modalities of brain imaging-derived phenotypes (IDPs), and 266 cognitive and psychological phenotype data. In structural MRI, significant positive associations were observed between total grey matter volume, left ventral diencephalon volume, surface area of right accumbens and the GPSs of cognition-related traits. Conversely, negative associations were found with the GPSs of ADHD, depression and neuroticism. Additionally, we identified a significant positive association between educational attainment GPS and regional brain activation during the N-back task. The BMI GPS showed a positive association with fractional anisotropy (FA) of connectivity between the cerebellum cortex and amygdala in diffusion MRI, while the GPSs for educational attainment and cannabis use were negatively associated with the same IDPs. Our GPS-based prediction models revealed substantial genetic contributions to cognitive variability, while the genetic basis for many mental and behavioral phenotypes remained elusive. This study delivers a comprehensive map of the relationships between genetic profiles, neuroanatomical diversity, and the spectrum of cognitive and behavioral traits in preadolescence.

243 Intracranial Theta-burst Stimulation Modulates Cortical Excitability in a Dose and Location-dependent Fashion

INTRODUCTION: Direct electrical stimulation is a powerful therapeutic approach to treating a wide range of brain disorders. In particular, theta-burst stimulation (TBS) which delivers electrical pulses in rhythmic bursts of 3-8 Hz to mimic endogenous brain rhythms, has been increasingly used to improve cognitive processes and relieve symptoms of depression. However, how TBS alters underlying neural activity is poorly understood. METHODS: In nine neurosurgical epilepsy subjects undergoing intracranial monitoring, we applied direct cortical TBS at varying stimulation amplitudes and locations (prefrontal, temporal, parietal). We obtained single-pulse corticocortical evoked potentials (CCEPs) prior to stimulation to map functional connectivity. Intracranial EEG (iEEG) was recorded from non-stimulated electrodes before, during and after TBS. RESULTS: We found that TBS evoked consistent responses after each burst. These responses were observed in regions with high amplitude CCEPs and resting spontaneous delta (1-4 Hz) phase-locking to the stimulation site, consistent with our hypothesis that the underlying functional brain architecture guides information flow after stimulation. Furthermore, we observed changes in cortical excitability over time as measured by changes in amplitude of the TBS evoked responses both within stimulation burst trains and across burst trains. The degree of change in cortical excitability was modulated by anatomical location, proximity of the stimulating electrode to white matter, and current amplitude. CONCLUSIONS: These results indicate that direct cortical TBS produces neural effects that can be measured over time and correlate with baseline biophysical parameters. Thus, personalizing stimulation parameters might be critical to predictably maximize our ability to alter disease-relevant brain networks.

Personalized connectivity-based network targeting model of transcranial magnetic stimulation for treatment of psychiatric disorders: computational feasibility and reproducibility.

Repetitive transcranial magnetic stimulation (rTMS) holds promise for treating psychiatric disorders; however, the variability in treatment efficacy among individuals underscores the need for further improvement. Growing evidence has shown that TMS induces a broad network modulatory effect, and its effectiveness may rely on accurate modulation of the pathological network specific to each disorder. Therefore, determining the optimal TMS coil setting that will engage the functional pathway delivering the stimulation is crucial. Compared to group-averaged functional connectivity (FC), individual FC provides specific information about a person's brain functional architecture, offering the potential for more accurate network targeting for personalized TMS. However, the low signal-to-noise ratio (SNR) of FC poses a challenge when utilizing individual resting-state FC. To overcome this challenge, the proposed solutions include increasing the scan duration and employing the cluster method to enhance the stability of FC. This study aimed to evaluate the stability of a personalized FC-based network targeting model in individuals with major depressive disorder or schizophrenia with auditory verbal hallucinations. Using resting-state functional magnetic resonance imaging data from the Human Connectome Project, we assessed the model's stability. We employed longer scan durations and cluster methodologies to improve the precision in identifying optimal individual sites. Our findings demonstrate that a scan duration of 28 minutes and the utilization of the cluster method achieved stable identification of individual sites, as evidenced by the intraindividual distance falling below the ~1cm spatial resolution of TMS. The current model provides a feasible approach to obtaining stable personalized TMS targets from the scalp, offering a more accurate method of TMS targeting in clinical applications.

Cortical changes in the brain of patients with hemifacial spasm.

Hemifacial spasm (HFS) is a movement disorder characterized by involuntary muscle contractions on one side of the face. It is associated with disturbances in the brain's functional architecture. Despite this, the structural alterations in the brain related to HFS remain poorly understood. In this study, we investigated the cortical morphology changes in patients with HFS compared to healthy controls (HCs). We analyzed 3D T1-weighted MRI images from 33 patients with left-sided primary HFS and 33 age- and sex-matched HCs. Measurements of cortical thickness (CTh), sulcal depth, local gyrification index (lGI), and fractal dimension were taken using a computational anatomy toolbox. A general linear model, accounting for age, gender, and total brain volume, was applied for statistical analyses. Significant clusters were then assessed for correlations with clinical parameters. The HFS patients displayed several cortical abnormalities when compared to HCs, including reduced CTh in the contralateral precentral gyrus and left orbitofrontal cortex, decreased sulcal depth in the left orbitofrontal cortex, and increased lGI in the right insula and superior temporal cortex. However, fractal dimension did not differ significantly between the groups. Additionally, in HFS patients, a notable negative correlation was found between the sulcal depth in the left orbitofrontal cortex and the Beck Depression Inventory-II scores. Our findings reveal that HFS is associated with specific surface-based morphological changes in the brain. These alterations contribute to a deeper understanding of the neurophysiological mechanisms involved in HFS and may have implications for future research and treatment strategies.

Reorganization of integration and segregation networks in brain-based visual impairment

Growing evidence suggests that cerebral connectivity changes its network organization by altering modular topology in response to developmental and environmental experience. However, changes in cerebral connectivity associated with visual impairment due to early neurological injury are still not fully understood. Cerebral visual impairment (CVI) is a brain-based visual disorder associated with damage and maldevelopment of retrochiasmal pathways and areas implicated in visual processing. In this study, we used a multimodal imaging approach and connectomic analyses based on structural (voxel-based morphometry; VBM) and resting state functional connectivity (rsfc) to investigate differences in weighted degree and link-level connectivity in individuals with CVI compared to controls with neurotypical development. We found that participants with CVI showed significantly reduced grey matter volume within the primary visual cortex and intraparietal sulcus (IPS) compared to controls. Participants with CVI also exhibited marked reorganization characterized by increased integration of visual connectivity to somatosensory and multimodal integration areas (dorsal and ventral attention regions) and lower connectivity from visual to limbic and default mode networks. Link-level functional changes in CVI were also associated with key clinical outcomes related to visual function and development. These findings provide early insight into how visual impairment related to early brain injury distinctly reorganizes the functional network architecture of the human brain.

The individualized neural tuning model: Precise and generalizable cartography of functional architecture in individual brains.

Quantifying how brain functional architecture differs from person to person is a key challenge in human neuroscience. Current individualized models of brain functional organization are based on brain regions and networks, limiting their use in studying fine-grained vertex-level differences. In this work, we present the individualized neural tuning (INT) model, a fine-grained individualized model of brain functional organization. The INT model is designed to have vertex-level granularity, to capture both representational and topographic differences, and to model stimulus-general neural tuning. Through a series of analyses, we demonstrate that (a) our INT model provides a reliable individualized measure of fine-grained brain functional organization, (b) it accurately predicts individualized brain response patterns to new stimuli, and (c) for many benchmarks, it requires only 10-20 minutes of data for good performance. The high reliability, specificity, precision, and generalizability of our INT model affords new opportunities for building brain-based biomarkers based on naturalistic neuroimaging paradigms.

Brain functional segregation, handedness and cognition in situs inversus totalis: A replication study

Situs inversus totalis (SIT) is a rare congenital anomaly in which the arrangement of the visceral organs is completely left-right mirrored. A previous study by our lab suggests that SIT (N = 15) correlated with more heterogeneous asymmetrical brain organization and increased left-handedness. In addition, visceral reversal correlated with poorer cognitive performance, especially when hemisphere organization was atypical. The current study sought to replicate these findings in a larger sample. We scanned 23 volunteers with SIT as well as an equal number of controls with usual organ arrangement, and used fMRI to determine their hemisphere dominance for two left hemisphere functions (language and manual praxis) and two right hemisphere functions (spatial attention and face recognition). Effects of SIT etiology were explored by pooling data from the original cohort with the replication sample. Our results reveal that each of those four cognitive functions demonstrated the expected population dominance in SIT, albeit they were less pronounced – but not significantly so – compared to controls. Unusual patterns of hemispheric crowding and mirror-reversal of functional brain organization was observed more often in SIT (48%) than in the controls (30%), but this difference also did not reach statistical significance. However, left-handedness was found to be significantly more common in SIT (26%) than in the overall population (10.6%). Finally, cognitive ability, as assessed by a neuropsychological test battery, was not associated with organ situs or hemisphere organization. Taken together, our data adds to the growing evidence that the determinants of visceral and neural asymmetries are largely independent from one another and that complete situs inversus does not co-occur with an obligatory transposition of the brain's functional architecture. There nevertheless might be instances in which (genetic) mechanisms could simultaneously cause complete visceral reversal and atypical brain laterality.

Perceived financial well-being and its association with frontostriatal functional connectivity, real-life anticipatory experiences, and everyday happiness

Perceived financial well-being (FWB) is an important aspect of life that can affect one’s attitude toward future experiences and happiness. However, the relationship between FWB, anticipatory experiences, and happiness, and the brain’s functional architecture underlying this relationship remain unknown. Here, we combined an experience sampling method, multilevel modeling, and functional neuroimaging to identify the neural correlates of FWB and their associations with real-world anticipatory experiences and everyday happiness. Behaviorally, we found that individuals with greater FWB felt more positive and more interested when they expected positive events to occur, which in turn resulted in increased everyday happiness. Furthermore, the level of FWB was significantly associated with the strength of functional connectivity (FC) between the nucleus accumbens (NAc) and ventromedial prefrontal cortex (vmPFC) and the local coherence within the vmPFC. The frontostriatal FC and local coherence within the vmPFC were further predictive of everyday happiness via the anticipatory response involving interestedness during positive expectations. Our findings suggest that individual differences in FWB could be reflected in the functional architecture of brain’s reward system that may contribute to shaping positive anticipatory experiences and happiness in daily life.

Alterations in the global brain network in older adults with poor sleep quality: A resting-state fMRI study

ObjectivesOlder adults often experience more fragmented and less restful sleep than younger individuals. However, the mechanisms in the brain that underlie these phenomena have been rarely studied. The aim of this study was to identify the differences in global brain network properties between older adults with good and poor sleep quality and to explore the relationship between these network properties and symptoms of insomnia. MethodsWe performed a graph-theoretic analysis of resting-state functional magnetic resonance imaging data from two groups of older adults: 59 with good sleep quality and 59 with poor sleep quality. Functional connectivity among 264 brain regions of interest was estimated, and undirected graphs were constructed. Network topological properties were compared using one-way repeated-measures analysis of variance. Pearson's correlation analysis assessed the relationship between the mean scores of the global network properties across network sparsity and insomnia symptoms, as measured using the global Pittsburgh Sleep Quality Index score. ResultsOlder adults with poor sleep quality displayed increased small-world-ness, global efficiency and modularity in the functional brain network during rest. Conversely, they exhibited decreased local efficiency, characteristic path length and clustering coefficient. In the total population, we found associations between insomnia symptoms and global network characteristics, except for betweenness centrality and modularity. ConclusionsIn older adults with poor sleep quality, global network measures revealed a functional brain architecture that tended towards integration rather than segregation. Further research is needed to better understand what these findings mean about the effects of aging on poor sleep quality.

Altered stability of dynamic brain functional architecture in primary open-angle glaucoma: a surface-based resting-state fMRI study.

Delineating the neuropathological characteristics of primary open-angle glaucoma (POAG) is critical for understanding its pathophysiology. While temporal stability represents a crucial aspect of the brain's functional architecture, the specific patterns underlying its contribution to POAG remain unclear. This study aims to analyze the brain functional abnormalities in POAG using functional stability, a dynamic functional connectivity (DFC) approach based on resting-state functional magnetic resonance imaging (rs-fMRI). Seventy patients with POAG and forty-five healthy controls underwent rs-fMRI and ophthalmological examinations. The stability of DFC was calculated as the concordance of DFC over time using a sliding-window approach, and the differences in stability between the two groups were compared. Subsequently, Spearman's correlation analyses were conducted to examine the relationship between functional stability and clinical indicators. Compared with healthy controls, patients with POAG exhibited significantly decreased functional stability in the visual network, including the early visual center, ventral and dorsal stream visual cortex in both hemispheres. Conversely, stability values increased in the bilateral inferior parietal gyrus and right inferior frontal cortex. In POAG patients, the dynamic stability of the left early visual cortex and ventral stream visual cortex correlated with the mean deviation of visual field defects (r = 0.251, p = 0.037). The evidence from this study suggests that functional stability may provide a new understanding of brain alterations in the progression of POAG.