Gradients of structure–function tethering across neocortex

NREM sleep stages specifically alter dynamical integration of large-scale brain networks.

Loss of nonstationary connectivity in a subcortical fronto-temporoparietal network distinguishes patients with minimal conscious state and unresponsive wakefulness state, strongly supporting the mesocircuit hypothesis.

Brain Connectivity: A Journal of Clinical Neurology, Neuroscience, & Neuroimaging Advancing the Field of Neurology

The word 'aging' often brings to mind an image of general physical decline and mental disintegration. Not surprisingly, the vast body of aging research is focused on describing losses and deterioration. However, a closer examination of individual differences in fact reveals great heterogeneity among healthy older adults. A subgroup called 'superagers' maintain youthful memory despite their advanced age (60 and above). They have been consistently characterized by youthful brain morphometry (i.e., thickness or volume of brain structures) in two core functional networks, the default mode network (DMN) and salience network (SN), both of which are implicated in memory. Importantly, regions belonging to the same functional network by definition show synchronized activities (functional connectivity) and are often physically linked by white matter tracts (structural connectivity). To further our understanding of how superagers achieve superior memory performance, it is crucial to investigate the structural and functional connectivity within the DMN and SN as well as their contributions to memory. Across two studies, we examined the intrinsic functional connectivity and structural connectivity within the DMN and SN in 41 young (24.5±3.6 years old) and 40 older adults (66.9±5.5 years old). Superaging was defined as youthful performance on a memory recall task, the California Verbal Learning Test (CVLT). As hypothesized, within both DMN and SN, superagers had stronger functional as well as structural connectivity compared to typical older adults and similar connectivity compared to young adults. Stronger functional and structural connectivity within the DMN robustly predicted better recall and recognition memory in older adults. Stronger functional connectivity, not structural connectivity, within the SN was associated with better recall memory. These results demonstrate the utility of superaging as a model of successful aging as it reliably links youthful performance on a well-established verbal recall measure to multimodal preservation of theDMN and SN in the brain.

Resting-State Functional Connectome in Patients with Brain Tumors Before and After Surgical Resection

It is poorly understood why patients with mesial temporal lobe epilepsy (TLE) have cognitive deficits and brain network changes that extend beyond the temporal lobe, including altered extratemporal intrinsic connectivity networks (ICNs). However, subcortical arousal structures project broadly to the neocortex, are affected by TLE, and thus may contribute to these widespread network effects. The authors' objective was to examine functional connectivity (FC) patterns between subcortical arousal structures and neocortical ICNs, possible neurocognitive relationships, and FC changes after epilepsy surgery. The authors obtained resting-state functional magnetic resonance imaging (fMRI) in 50 adults with TLE and 50 controls. They compared nondirected FC (correlation) and directed FC (Granger causality laterality index) within the salience network, default mode network, and central executive network, as well as between subcortical arousal structures; these 3 ICNs were also compared between patients and controls. They also used an fMRI-based vigilance index to relate alertness to arousal center FC. Finally, fMRI was repeated in 29 patients > 12 months after temporal lobe resection. Nondirected FC within the salience (p = 0.042) and default mode (p = 0.0008) networks, but not the central executive network (p = 0.79), was decreased in patients in comparison with controls (t-tests, corrected). Nondirected FC between the salience network and subcortical arousal structures (nucleus basalis of Meynert, thalamic centromedian nucleus, and brainstem pedunculopontine nucleus) was reduced in patients in comparison with controls (p = 0.0028-0.015, t-tests, corrected), and some of these connectivity abnormalities were associated with lower processing speed index, verbal comprehension, and full-scale IQ. Interestingly, directed connectivity measures suggested a loss of top-down influence from the salience network to the arousal nuclei in patients. After resection, certain FC patterns between the arousal nuclei and salience network moved toward control values in the patients, suggesting that some postoperative recovery may be possible. Although an fMRI-based vigilance measure suggested that patients exhibited reduced alertness over time, FC abnormalities between the salience network and arousal structures were not influenced by the alertness levels during the scans. FC abnormalities between subcortical arousal structures and ICNs, such as the salience network, may be related to certain neurocognitive deficits in TLE patients. Although TLE patients demonstrated vigilance abnormalities, baseline FC perturbations between the arousal and salience networks are unlikely to be driven solely by alertness level, and some may improve after surgery. Examination of the arousal network and ICN disturbances may improve our understanding of the downstream clinical effects of TLE.

Resting-State Networks (RSNs) shown in functional magnetic resonance imaging (fMRI) have been consistently and reliably identified. Amongst these, the Default Mode Network (DMN) has been most well researched and shown to have age-related decrease in functional connectivity and negative consequences for cognition. There are two other distinct RSNs, Salience Network (SN) and Executive Control Network (ECN), shown to co-activate during fMRI tasks. The SN has been suggested to be correlated with cognitive decline in healthy aging, however, the age-related dynamics between these three RSNs are not well understood. The current study examined the DMN, SN and ECN during resting-state fMRI in young and elderly from Japan and Singapore using data-driven independent component analysis (ICA) and functional network connectivity (FNC). We further investigated if the functional connectivity of the DMN and SN varied across tasks of different cognitive demands between young and elderly. Interestingly, the elderly had increased intrinsic activity that deviated from the expected DMN, SN and ECN, and increased functional connectivity within the anterior SN relative to the young during resting-state fMRI. For task fMRI, the elderly showed decreased activation in the primary networks of visual and motor processing, and increased task related activity for higher cognitive processes. However, the DMN and SN for task fMRI revealed consistent increased activity shifted outside the expected regions for the elderly. Difference in functional connectivity between young and elderly was varied across tasks. The elderly had marginally less number of correlated component pairs compared to the young, suggesting a decline in functional network integrity in aging. The current study demonstrated that resting-state data could be combined across two sites using ICA, as well as the use of DMN and SN as reliable networks to examine age-related changes in rest and task fMRI. Understanding the dynamics of these networks in relation to aging will provide potential neuroimaging markers for enhancing cognition, as well as detecting pathological decline.

Objectives: The specific intrinsic network coupling abnormalities in mild traumatic brain injury (mTBI) patients are poorly understood. Our objective is to compare the correlations among the default mode, salience, and central executive networks in patients with mTBI and healthy controls.Methods: This 2-year prospective study included 32 acute mTBI patients and 37 healthy comparisons. We calculated the functional connectivity scores among the default mode, salience, and central executive networks. Then we conducted multilevel correlation analysis to investigate component correlations, global graph, and local functional connectivity changes.Results: Patients with mTBI showed significant increased functional connectivity between the anterior part of the default mode network and the salience network compared with controls (p = 0.013, false discovery rate correction). Hyper-connectivity between the default mode and salience network was significantly positively correlated with the dimensional change card sort score in patients with mTBI (r = 0.40, p = 0.037). The average path length of mTBI patients was significantly higher than that of controls (p = 0.028).Conclusions: Aberrant functional coupling between the default mode and salience networks were identified in acute mTBI patients. Our finding has great potential to improve our understanding of the network architecture of mTBI.

目的 探讨精神分裂症患者脑静息态默认网络、中心执行网络及突显网络的网络内及网络间的功能连接特点.方法 对74例精神分裂症患者(患者组)和79名相匹配的健康者(对照组)进行静息态fMRI扫描.采取功能连接分析方法,以内侧前额叶皮质及右侧前岛叶为感兴趣区域分别提取默认网络、中心执行网络及突显网络,分析3个网络内及网络间静息态功能连接情况;并对有差异的功能连接与精神症状及病程等进行偏相关分析.结果 与对照组相比,患者组内侧前额叶皮质与双侧背外侧前额叶皮质(左侧-0.02±0.18与-0.12±0.12,t=4.25,P＜0.01;右侧-0.02±0.11与-0.10±0.10,t=5.40,P＜0.01)、双侧豆状壳核(左侧0.14±0.12与0.04±0.10,t=5.03,P＜0.01;右侧0.13±0.11与0.03±0.98,t=4.96,P＜0.01)的功能连接增强;右侧前岛叶与左侧额中回(-0.05±0.17与-0.07±0.17,t=4.60,P＜0.01)及楔前叶/后扣带回(0.01±0.13与-0.09±0.14,t=4.01,P＜0.01)的功能连接增强(均采用高斯随机场理论校正,体素水平P＜0.01,簇水平P＜0.05);默认网络与中心执行网络、突显网络间的负向功能连接减小甚至消失(Bonferroni校正P＜0.05).患者组PANSS阳性症状分与右侧前岛叶与楔前叶/后扣带回皮质间的功能连接呈正相关(r=0.232,P=0.025);患者组病程与右侧前岛叶与左侧额中回(r=0.288,P=0.007)、楔前叶/后扣带回(r=0.196,P=0.049)间的功能连接呈正相关.结论 精神分裂症患者存在静息态默认网络、中心执行网络及突显网络3个网络间的连接异常,可能与精神分裂症的病理机制有关.

Reproducibility of regional structural and functional MRI networks in cerebral small vessel disease compared to age matched and stroke-free controls.

Unprecedented 4D spatiotemporal infant regional cerebral blood flow framework and region-specific physiology–function coupling across infancy were elucidated, highlighting strong physiology–function coupling specifically at the default-mode network to meet extraneuronal metabolic demand for network emergence.

ObjectivesNewly diagnosed focal epilepsy (NDfE) is rarely studied, particularly using advanced neuroimaging techniques. Many patients with NDfE experience cognitive impairments, particularly with respect to memory, sustained attention, mental flexibility, and executive functioning. Cognitive impairments have been related to alterations in resting‐state functional brain networks in patients with neurological disorders. In the present study, we investigated whether patients with NDfE had altered connectivity in large‐scale functional networks using resting‐state functional MRI.MethodsWe recruited 27 adults with NDfE and 36 age‐ and sex‐matched healthy controls. Resting‐state functional MRI was analyzed using the Functional Connectivity Toolbox (CONN). We investigate reproducibly determined large‐scale functional networks, including the default mode, salience, fronto‐parietal attention, sensorimotor, and language networks using a seed‐based approach. Network comparisons between patients and controls were thresholded using a FDR cluster‐level correction approach.ResultsWe found no significant differences in functional connectivity between seeds within the default mode, salience, sensorimotor, and language networks and other regions of the brain between patients and controls. However, patients with NDfE had significantly reduced connectivity between intraparietal seeds within the fronto‐parietal attention network and predominantly frontal and temporal cortical regions relative to controls; this finding was demonstrated including and excluding the patients with brain lesions. No common alteration in brain structure was observed in patients using voxel‐based morphometry. Findings were not influenced by treatment outcome at 1 year.ConclusionsPatients with focal epilepsy have brain functional connectivity alterations at diagnosis. Functional brain abnormalities are not necessarily a consequence of the chronicity of epilepsy and are present when seizures first emerge.

Major depressive disorder (MDD) is a serious mental illness characterized by dysfunctional connectivity among distributed brain regions. Previous connectome studies based on functional magnetic resonance imaging (fMRI) have focused primarily on undirected functional connectivity and existing directed effective connectivity (EC) studies concerned mostly task‐based fMRI and incorporated only a few brain regions. To overcome these limitations and understand whether MDD is mediated by within‐network or between‐network connectivities, we applied spectral dynamic causal modeling to estimate EC of a large‐scale network with 27 regions of interests from four distributed functional brain networks (default mode, executive control, salience, and limbic networks), based on large sample‐size resting‐state fMRI consisting of 100 healthy subjects and 100 individuals with first‐episode drug‐naive MDD. We applied a newly developed parametric empirical Bayes (PEB) framework to test specific hypotheses. We showed that MDD altered EC both within and between high‐order functional networks. Specifically, MDD is associated with reduced excitatory connectivity mainly within the default mode network (DMN), and between the default mode and salience networks. In addition, the network‐averaged inhibitory EC within the DMN was found to be significantly elevated in the MDD. The coexistence of the reduced excitatory but increased inhibitory causal connections within the DMNs may underlie disrupted self‐recognition and emotional control in MDD. Overall, this study emphasizes that MDD could be associated with altered causal interactions among high‐order brain functional networks.

BackgroundCircumscribed patterns of pathological tau propagation along functional networks have been observed in normal aging and amnestic Alzheimer’s disease (AD), including in two cognition‐relevant networks: the default mode network (DMN) and the salience network (SN). It remains unclear if atypical phenotypes of AD demonstrate a direct relationship between tau and functional connectivity within and between these networks.MethodTwenty‐six amyloid‐positive patients diagnosed with atypical phenotypes of AD (12 PCA, 10 lvPPA, and 4 dysexecutive; mean age = 66 years, 9M/17F) were examined with tau (18F‐AV‐1451) PET and resting state functional MRI (rs‐fMRI). Hub regions within the DMN and SN were defined from the literature within the bilateral posterior cingulate cortex (PCC) and anterior insula (aI), respectively. ROI‐to‐ROI connectivity was calculated to determine within‐ and between‐network connectivity. Bivariate correlation analyses were conducted to determine if the magnitude of partial volume corrected tau PET signal in each network’s hub region was related to the within‐network functional connectivity of the DMN and SN, as well as between the hub regions of the DMN and SN.ResultWe found that higher tau signal in bilateral PCC was associated with diminished DMN connectivity (PCC to posterior angular gyrus) in both hemispheres (left: r = ‐0.50, p = 0.009; right: r = ‐0.47, p = 0.01). We did not observe any relationship between tau and functional connectivity within the SN. Our novel observation was that higher tau signal in the PCC was associated with increased connectivity between the DMN and SN within both hemispheres (left: r = 0.55, p = 0.004; right: r = 0.47, p = 0.02), with some patients demonstrating pathologically positive functional connectivity between the DMN and SN.ConclusionOur findings support the posited relationship between tau pathology and aberrant functional network connectivity reported in aging and amnestic AD by demonstrating that higher tau burden within the PCC is related to fractured DMN connectivity and pathologically increased DMN‐SN connectivity in a group of non‐amnestic AD patients. These findings may help explain how tau deposition in key hub regions of the DMN bring about dysfunctional inter‐network connectivity with the SN, likely contributing to the cognitive and affective dysfunction observed across the clinical spectrum of AD.

BackgroundMenstrually-related migraine (MRM) is a subtype of migraine associated with the ovarian cycle that imposes a significant burden on female patients. Although MRM and non-menstrual migraine (NMM) differ in clinical presentation and treatment response, their distinct neural mechanisms remain unclear. Emerging evidence suggests that alterations in intrinsic functional connectivity (FC) within and between large-scale brain networks may underlie the phenotypic heterogeneity of migraine subtypes. This study investigated FC alterations between patients with MRM and NMM, explored their correlations with clinical characteristics, and assessed the preliminary utility of FC in subtype differentiation.MethodsResting-state functional magnetic resonance imaging (MRI) with independent component analysis was used to examine whole-brain FC in 50 patients with MRM, 50 with NMM and 50 age-balanced healthy controls (HC). We analyzed within- and between-network connectivity across major resting-state networks, including the frontoparietal, default mode, salience and dorsal attention networks, and applied logistic regression to test whether FC values could classify migraine subtypes. Correlation analyses were further performed between FC measures and clinical indices, including disease duration, headache frequency, visual analog scale scores and Headache Impact Test (HIT-6) scores.ResultsBoth MRM and NMM groups showed weaker within-network connectivity compared to HCs, primarily in the right frontoparietal, default mode and salience networks. Compared with NMM, the MRM group exhibited significantly stronger connectivity in the left frontoparietal network and weaker between-network connectivity between the dorsal attention and default mode networks. In the women with migraine, FC within the dorsal attention network (DAN) was negatively correlated with disease duration (r = -0.200, p = 0.046) and HIT-6 score (r = -0.183, p = 0.049). Furthermore, FC between the DAN and auditory network was inversely associated with disease duration (r = -0.225, p = 0.025). The logistic regression model achieved an area under the receiver operating characteristic curve of 0.73 (sensitivity = 0.70; specificity = 0.64) in distinguishing MRM from NMM.ConclusionsOur findings reveal both shared and distinct alterations in large-scale brain networks in MRM and NMM, potentially explaining differences in clinical presentation and treatment response. This enhanced understanding of migraine pathophysiology supports the development of subtype-specific diagnostic tools and targeted therapies and underscores the value of resting-state fMRI as a non-invasive tool for migraine phenotyping and personalized care.Registration NumberChiCTR2200065586.