Complexity organization of resting‐state functional‐MRI networks
Ontology highlight
ABSTRACT:
SUBMITTER: Trevino G
PROVIDER: S-EPMC11345701 | biostudies-literature | 2024 Aug
REPOSITORIES: biostudies-literature
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Project description:Altered functional characteristics have been reported in amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD); nonetheless, comprehensive analyses of the resting-state networks (RSNs) are rare. This study combined multiple imaging modalities to investigate the functional and structural changes within each RSN and between RSNs in aMCI/AD patients. Eight RSNs were identified from functional MRI data from 35 AD, 18 aMCI and 21 normal control subjects using independent component analysis. We compared functional connectivity (FC) within each RSN and found decreased FC in the several cognitive-related RSNs in AD, including the bilateral precuneus of the precuneus network, the posterior cingulate cortex and left precuneus of the posterior default mode network (DMN), and the left superior parietal lobule of the left frontoparietal network (LFP). We further compared the grey matter volumes and amplitudes of low-frequency fluctuations of these regions and found decreases in these measures in AD. Importantly, we found decreased inter-network connectivity between the visual network and the LFP and between the anterior and posterior DMNs in AD. All indices in aMCI patients were numerically between those of controls and AD patients. These results suggest that the brain networks supporting complex cognitive processes are specifically and progressively impaired over the course of AD, and the FC impairments are present not only within networks but also between networks.
| S-EPMC3647055 | biostudies-literature
Project description:Functional MRI (fMRI) studies reported disruption of resting-state networks (RSNs) in several neuropsychiatric disorders. PET with 18F-FDG captures neuronal activity that is in steady state at a longer time span and is less dependent on neurovascular coupling. Methods: In the present study, we aimed to identify RSNs in 18F-FDG PET data and compare their spatial pattern with those obtained from simultaneously acquired resting-state fMRI data in 22 middle-aged healthy subjects. Results: Thirteen and 17 meaningful RSNs could be identified in PET and fMRI data, respectively. Spatial overlap was fair to moderate for the default mode, left central executive, primary and secondary visual, sensorimotor, cerebellar, and auditory networks. Despite recording different aspects of neural activity, similar RSNs were detected by both imaging modalities. Conclusion: The results argue for the common neural substrate of RSNs and encourage testing of the clinical utility of resting-state connectivity in PET data.
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Project description: Not available
| S-EPMC11628875 | biostudies-literature
Project description:This study aimed to investigate the changes in functional connectivity (FC) within each resting-state network (RSN) and between RSNs in subcortical stroke patients who were well recovered in global motor function. Eleven meaningful RSNs were identified via functional magnetic resonance imaging data from 25 subcortical stroke patients and 22 normal controls using independent component analysis. Compared with normal controls, stroke patients exhibited increased intranetwork FC in the sensorimotor (SMN), visual (VN), auditory (AN), dorsal attention (DAN), and default mode (DMN) networks; they also exhibited decreased intranetwork FC in the frontoparietal network (FPN) and anterior DMN. Stroke patients displayed a shift from no FC in controls to negative internetwork FC between the VN and AN as well as between the VN and SMN. Stroke patients also exhibited weakened positive (anterior and posterior DMN; posterior DMN and right FPN) or negative (AN and right FPN; posterior DMN and dorsal SMN) internetwork FC when compared with normal controls. We suggest that subcortical stroke may induce connectivity changes in multiple functional networks, affecting not only the intranetwork FC within RSNs but also the internetwork FC between these RSNs.
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Project description:Covering neuroimaging evidence has demonstrated that epileptic symptoms are associated with the disrupted topological architecture of the brain network. Infantile spasms (IS) as an age-specific epileptic encephalopathy also showed abnormal structural or functional connectivity in specific brain regions or specific networks. However, little is known about the topological alterations of whole-brain functional networks in patients with IS. To fill this gap, we used the graph theoretical analysis to investigate the topological properties (whole-brain small-world property and modular interaction) in 17 patients with IS and 34 age- and gender-matched healthy controls. The functional networks in both groups showed efficient small-world architecture over the sparsity range from 0.05 to 0.4. While patients with IS showed abnormal global properties characterized by significantly decreased normalized clustering coefficient, normalized path length, small-worldness, local efficiency, and significantly increased global efficiency, implying a shift toward a randomized network. Modular analysis revealed decreased intra-modular connectivity within the default mode network (DMN) and fronto-parietal network but increased inter-modular connectivity between the cingulo-opercular network and occipital network. Moreover, the decreased intra-modular connectivity in DMN was significantly negatively correlated with seizure frequency. The inter-modular connectivity between the cingulo-opercular and occipital network also showed a significant correlation with epilepsy frequency. Together, the current study revealed the disrupted topological organization of the whole-brain functional network, which greatly advances our understanding of neuronal architecture in IS and may contribute to predict the prognosis of IS as disease biomarkers.
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Project description:BackgroundThe human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics.ResultsWe utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques.ConclusionsOur results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.
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Project description:When performing cognitively demanding tasks, people tend to experience momentary distractions or personal associations that intercept their stream of consciousness. This phenomenon is known as Mind Wandering (MW) and it has become a subject of neuroscientific investigations. Off-task thoughts can be analyzed during task performance, but currently, MW is also understood as a dimension of individual differences in cognitive processing. We wanted to recognize the intrinsically-organized functional networks that could be considered the neuronal basis for MW dispositional variability. To achieve this goal we recruited a group of normal adults, and eventually divided the group in half, based on participants’ scores on the scale measuring dispositional MW. Next, these groups were compared regarding the arrangement of preselected intrinsic functional networks, which were reconstructed based on multi-channel signal-source resting-state EEG. It appeared that subjects who tend to mind wander often exhibited decreased synchronization within the default mode network, and, simultaneously, strengthened connectivity between ‘on-task’ networks of diverse functional specificity. Such within- and between networks integrity patterns might suggest that greater Mind Wanderers present an atypical organization of resting-state brain activity, which may translate into attenuated resources needed to maintain attentional control in task-related conditions.
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Project description:Spontaneous fluctuations in the blood oxygenation level dependent signal measured through resting-state functional magnetic resonance imaging have been corroborated to aggregate into multiple functional networks. Abnormal resting brain activity is observed in mood disorder patients, however with inconsistent results. How do such alterations relate to clinical symptoms; e.g., level of depression and rumination tendencies? Here we recovered spatially and temporally overlapping functional networks from 31 mood disorder patients and healthy controls during rest, by applying novel methods that identify transient changes in spontaneous brain activity. Our unique approach disentangles the dynamic engagement of resting-state networks unconstrained by the slow hemodynamic response. This time-varying characterization provides moment-to-moment information about functional networks in terms of their durations and dynamic coupling, and offers novel evidence for selective contributionsto particular clinical symptoms. Patients showed increased duration of default-mode network (DMN), increased duration and occurrence of posterior DMN as well as insula- and amygdala-centered networks, but decreased occurrence of visual and anterior salience networks. Coupling between limbic (insula and amygdala) networks was also reduced. Depression level modulated DMN duration, whereas intrusive thoughts correlated with occurrence of insula and posterior DMN. Anatomical network organization was similar to controls. In sum, altered brain dynamics in mood disorder patients appear to mediate distinct clinical dimensions including increased self-processing, and decreased attention to external world.
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Project description:We aimed to investigate alterations in functional brain networks and assess the relationship between functional impairment and topological network changes in cerebral small vessel disease (CSVD) patients with and without cerebral microbleeds (CMBs). We constructed individual whole-brain, region of interest (ROI) level functional connectivity (FC) networks for 24 CSVD patients with CMBs (CSVD-c), 42 CSVD patients without CMBs (CSVD-n), and 36 healthy controls (HCs). Then, we used graph theory analysis to investigate the global and nodal topological disruptions between groups and relate network topological alterations to clinical parameters. We found that both the CSVD and control groups showed efficient small-world organization in FC networks. However, compared to CSVD-n patients and controls, CSVD-c patients exhibited a significantly decreased clustering coefficient, global efficiency, and local efficiency and an increased shortest path length, indicating a disrupted balance between local specialization and global integration in FC networks. Although both the CSVD and control groups showed highly similar hub distributions, the CSVD-c group exhibited significantly altered nodal betweenness centrality (BC), mainly distributed in the default mode network (DMN), attention, and visual functional areas. There were almost no global or regional alterations between CSVD-n patients and controls. Furthermore, the altered nodal BC of the right anterior/posterior cingulate gyrus and left cuneus were significantly correlated with cognitive parameters in CSVD patients. These results suggest that CSVD patients with and without CMBs had segregated disruptions in the topological organization of the intrinsic functional brain network. This study advances our current understanding of the pathophysiological mechanisms underlying CSVD.
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Project description:Understanding the relationship between functional connectivity (FC) of higher-order neurocognitive networks and age-related cognitive decline is a complex and evolving field of research. Decreases in FC have been associated with cognitive decline in persons with Alzheimer's disease and related dementias (ADRD). However, the contributions of FC have been less straightforward in typical cognitive aging. Some investigations suggest relatively robust FC within neurocognitive networks differentiates unusually successful cognitive aging from average aging, while others do not. Methodologic limitations in data processing and varying definitions of 'successful aging' may have contributed to the inconsistent results to date. The current study seeks to address previous limitations by optimized MRI methods to examine FC in the well-established SuperAging phenotype, defined by age and cognitive performance as individuals 80 and older with episodic memory performance equal to or better than 50-to-60-year-olds. Within- and between-network FC of large-scale neurocognitive networks were compared between 24 SuperAgers and 16 cognitively average older-aged control (OACs) with stable cognitive profiles using resting-state functional MRI (rs-fMRI) from a single visit. Group classification was determined based on measures of episodic memory, executive functioning, verbal fluency and picture naming. Inclusion criteria required stable cognitive status across two visits. First, we investigated the FC within and between seven resting-state networks from a common atlas parcellation. A separate index of network segregation was also compared between groups. Second, we investigated the FC between six subcomponents of the default mode network (DMN), the neurocognitive network commonly associated with memory performance and disrupted in persons with ADRD. For each analysis, FCs were compared across groups using two-sample independent t-tests and corrected for multiple comparisons. There were no significant between-group differences in demographic characteristics including age, sex and education. At the group-level, within-network FC, between-network FC, and segregation measurements of seven large-scale networks, including subcomponents of the DMN, were not a primary differentiator between cognitively average aging and SuperAging phenotypes. Thus, FC within or between large-scale networks does not appear to be a primary driver of the exceptional memory performance observed in SuperAgers. These results have relevance for differentiating the role of FC changes associated with cognitive aging from those associated with ADRD.
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