Graph theoretical analysis of functional networks and its relationship to cognitive decline in patients with carotid stenosis.
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ABSTRACT:
SUBMITTER: Chang TY
PROVIDER: S-EPMC4820004 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:OBJECTIVE:Traumatic anosmia is a common disorder following head injury; however, little is known regarding its neural basis and influence on the functional networks. Therefore, we aimed to investigate the functional connectivity changes in patients with traumatic anosmia compared to healthy controls using resting-state functional magnetic resonance imaging (rs-fMRI). MATERIALS AND METHODS:Sixteen patients with traumatic anosmia and 12 healthy controls underwent rs-fMRI. Differences in the connectivity of the olfactory and whole brain networks were compared between the two groups. Graph theoretical parameters, such as modularity and global efficiency of the whole brain or olfactory networks, were calculated and compared. Correlation analyses were performed between the parameters and disease severity. RESULTS:Patients with traumatic anosmia showed decreased intra-network connectivity in the olfactory network (false discovery rate [FDR]-corrected p < 0.05) compared with that in healthy controls. Furthermore, the inter-network connectivity was increased in both the olfactory (FDR-corrected p < 0.05) and whole brain networks (degree-based statistic-corrected p < 0.05) in the anosmia group. The whole brain networks showed decreased modularity (p < 0.001) and increased global efficiency (p = 0.019) in patients with traumatic anosmia. The modularity and global efficiency were correlated with disease severity in patients with anosmia (p < 0.001 and p = 0.002, respectively). CONCLUSION:Traumatic anosmia increased the inter-network connectivity observed with rs-fMRI in the olfactory and global brain functional networks. rs-fMRI parameters may serve as potential biomarkers for traumatic anosmia by revealing a more widespread functional damage than previously expected.
| S-EPMC6791817 | biostudies-other
Project description:There is increasing interest in the potential of whole-brain computational models to provide mechanistic insights into resting-state brain networks. It is therefore important to determine the degree to which computational models reproduce the topological features of empirical functional brain networks. We used empirical connectivity data derived from diffusion spectrum and resting-state functional magnetic resonance imaging data from healthy individuals. Empirical and simulated functional networks, constrained by structural connectivity, were defined based on 66 brain anatomical regions (nodes). Simulated functional data were generated using the Kuramoto model in which each anatomical region acts as a phase oscillator. Network topology was studied using graph theory in the empirical and simulated data. The difference (relative error) between graph theory measures derived from empirical and simulated data was then estimated. We found that simulated data can be used with confidence to model graph measures of global network organization at different dynamic states and highlight the sensitive dependence of the solutions obtained in simulated data on the specified connection densities. This study provides a method for the quantitative evaluation and external validation of graph theory metrics derived from simulated data that can be used to inform future study designs.
| S-EPMC5312789 | biostudies-literature
Project description:Dystonia, a debilitating neurological movement disorder, is characterized by involuntary muscle contractions and develops from a complex pathophysiology. Graph theoretical analysis approaches have been employed to investigate functional network changes in patients with different forms of dystonia. In this study, we aimed to characterize the abnormal brain connectivity underlying writer's cramp, a focal hand dystonia. To this end, we examined functional magnetic resonance scans of 20 writer's cramp patients (11 females/nine males) and 26 healthy controls (10 females/16 males) performing a sequential finger tapping task with their non-dominant (and for patients non-dystonic) hand. Functional connectivity matrices were used to determine group averaged brain networks. Our data suggest that in their neuronal network writer's cramp patients recruited fewer regions that were functionally more segregated. However, this did not impair the network's efficiency for information transfer. A hub analysis revealed alterations in communication patterns of the primary motor cortex, the thalamus and the cerebellum. As we did not observe any differences in motor outcome between groups, we assume that these network changes constitute compensatory rerouting within the patient network. In a secondary analysis, we compared patients with simple writer's cramp (only affecting the hand while writing) and those with complex writer's cramp (affecting the hand also during other fine motor tasks). We found abnormal cerebellar connectivity in the simple writer's cramp group, which was less prominent in complex writer's cramp. Our preliminary findings suggest that longitudinal research concerning cerebellar connectivity during WC progression could provide insight on early compensatory mechanisms in WC.
| S-EPMC8650489 | biostudies-literature
Project description:Purpose: Previous studies have found that there are significant changes in functional network properties for patients with moderate to severe carotid artery stenosis. Our study aimed to explore the topology properties of brain functional network in asymptomatic patients with carotid plaque without significant stenosis. Methods: A total of 61 asymptomatic patients with carotid plaque (mean age 61.79 ± 7.35 years) and 25 healthy control subjects (HC; 58.12 ± 6.79 years) were recruited. General data collection, carotid ultrasound examination and resting state functional magnetic resonance imaging were performed on all subjects. Graph-theory was applied to examine the differences in the brain functional network topological properties between two groups. Results: In the plaque group, Eloc(P = 0.03), γ (P = 0.01), and σ (P = 0.01) were significantly higher than in the HC group. The degree centrality of left middle frontal gyrus and the nodal efficiency of left middle frontal gyrus and right inferior parietal angular gyrus were significantly higher in the plaque group than in HC. The degree centrality and betweenness centrality of right middle temporal gyrus, as well as the nodal efficiency of right middle temporal gyrus, were significantly lower in the plaque group than in HC. Conclusions: The brain functional networks of patients with carotid plaques differ from those of healthy controls. Asymptomatic patients with carotid plaques exhibit increased local and global connectivity, which may reflect subtle reorganizations in response to early brain damage.
| S-EPMC8375554 | biostudies-literature
Project description:Asymptomatic low-grade carotid artery stenosis (LGCS) is a common finding in patients with manifest arterial disease, however its relationship with brain MRI changes and cognitive decline is unclear. We included 902 patients (58 ± 10 years; 81% male) enrolled in the Second Manifestations of Arterial Disease - Magnetic Resonance (SMART-MR) study without a history of cerebrovascular disease. LGCS was defined as 1-49% stenosis on baseline carotid ultrasound, whereas no LGCS (reference category) was defined as absence of carotid plaque. Brain and white matter hyperintensity (WMH) volumes and cognitive function were measured at baseline and after 4 (n = 480) and 12 years (n = 222) of follow-up. Using linear mixed-effects models, we investigated associations of LGCS with progression of brain atrophy, WMH, and cognitive decline. LGCS was associated with greater progression of global brain atrophy (estimate -0.03; 95%CI, -0.06 to -0.01; p = 0.002), and a greater decline in executive functioning (estimate -0.02; 95%CI, -0.031 to -0.01; p < 0.001) and memory (estimate -0.012; 95%CI, -0.02 to -0.001; p = 0.032), independent of demographics, cardiovascular risk factors, and incident brain infarcts on MRI. No association was observed between LGCS and progression of WMH. Our results indicate that LGCS may represent an early marker of greater future brain atrophy and cognitive decline.
| S-EPMC9903227 | biostudies-literature
Project description:As the world ages, it becomes urgent to unravel the mechanisms underlying brain aging and find ways of intervening with them. While for decades cognitive aging has been related to localized brain changes, growing attention is now being paid to alterations in distributed brain networks. Functional connectivity magnetic resonance imaging (fcMRI) has become a particularly useful tool to explore large-scale brain networks; yet, the temporal course of connectivity lifetime changes has not been established. Here, an extensive cross-sectional sample (21-85 years old, N = 887) from a public fcMRI database was used to characterize adult lifespan connectivity dynamics within and between seven brain networks: the default mode, salience, dorsal attention, fronto-parietal control, auditory, visual and motor networks. The entire cohort was divided into young (21-40 years, mean ± SD: 25.5 ± 4.8, n = 543); middle-aged (41-60 years, 50.6 ± 5.4, n = 238); and old (61 years and above, 69.0 ± 6.3, n = 106) subgroups. Correlation matrices as well as a mixed model analysis of covariance indicated that within high-order cognitive networks a considerable connectivity decline is already evident by middle adulthood. In contrast, a motor network shows increased connectivity in middle adulthood and a subsequent decline. Additionally, alterations in inter-network interactions are noticeable primarily in the transition between young and middle adulthood. These results provide evidence that aging-related neural changes start early in adult life.
| S-EPMC5223363 | biostudies-literature
Project description:BackgroundGraph theory has been recently introduced to characterize complex brain networks, making it highly suitable to investigate altered connectivity in neurologic disorders. A current model proposes autism spectrum disorder (ASD) as a developmental disconnection syndrome, supported by converging evidence in both non-syndromic and syndromic ASD. However, the effects of abnormal connectivity on network properties have not been well studied, particularly in syndromic ASD. To close this gap, brain functional networks of electroencephalographic (EEG) connectivity were studied through graph measures in patients with Tuberous Sclerosis Complex (TSC), a disorder with a high prevalence of ASD, as well as in patients with non-syndromic ASD.MethodsEEG data were collected from TSC patients with ASD (n = 14) and without ASD (n = 29), from patients with non-syndromic ASD (n = 16), and from controls (n = 46). First, EEG connectivity was characterized by the mean coherence, the ratio of inter- over intra-hemispheric coherence and the ratio of long- over short-range coherence. Next, graph measures of the functional networks were computed and a resilience analysis was conducted. To distinguish effects related to ASD from those related to TSC, a two-way analysis of covariance (ANCOVA) was applied, using age as a covariate.ResultsAnalysis of network properties revealed differences specific to TSC and ASD, and these differences were very consistent across subgroups. In TSC, both with and without a concurrent diagnosis of ASD, mean coherence, global efficiency, and clustering coefficient were decreased and the average path length was increased. These findings indicate an altered network topology. In ASD, both with and without a concurrent diagnosis of TSC, decreased long- over short-range coherence and markedly increased network resilience were found.ConclusionsThe altered network topology in TSC represents a functional correlate of structural abnormalities and may play a role in the pathogenesis of neurological deficits. The increased resilience in ASD may reflect an excessively degenerate network with local overconnection and decreased functional specialization. This joint study of TSC and ASD networks provides a unique window to common neurobiological mechanisms in autism.
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Project description:Individuals with an at-risk mental state (ARMS) have a risk of developing a psychotic disorder significantly greater than the general population. However, it is not currently possible to predict which ARMS individuals will develop psychosis from clinical assessment alone. Comparison of ARMS subjects who do, and do not, develop psychosis can reveal which factors are critical for the onset of illness. In the present study, 37 patients with an ARMS were followed clinically at least 24 months subsequent to initial referral. Functional MRI data were collected at the beginning of the follow-up period during performance of an executive task known to recruit frontal lobe networks and to be impaired in psychosis. Graph theoretical analysis was used to compare the organization of a functional brain network in ARMS patients who developed a psychotic disorder following the scan (ARMS-T) to those who did not become ill during the same follow-up period (ARMS-NT) and aged-matched controls. The global properties of each group's representative network were studied (density, efficiency, global average path length) as well as regionally-specific contributions of network nodes to the organization of the system (degree, farness-centrality, betweenness-centrality). We focused our analysis on the dorsal anterior cingulate cortex (ACC), a region known to support executive function that is structurally and functionally impaired in ARMS patients. In the absence of between-group differences in global network organization, we report a significant reduction in the topological centrality of the ACC in the ARMS-T group relative to both ARMS-NT and controls. These results provide evidence that abnormalities in the functional organization of the brain predate the onset of psychosis, and suggest that loss of ACC topological centrality is a potential biomarker for transition to psychosis.
| S-EPMC3757719 | biostudies-literature
Project description:It is well-established that both volume conduction and the choice of recording reference (montage) affect the correlation measures obtained from scalp EEG, both in the time and frequency domains. As a result, a number of correlation measures have been proposed aiming to reduce these effects. In our previous work, we have showed that scalp-EEG based functional brain networks in patients with epilepsy exhibit clear periodic patterns at different time scales and that these patterns are strongly correlated to seizure onset, particularly at shorter time scales (around 3 and 5 h), which has important clinical implications. In the present work, we use the same long-duration clinical scalp EEG data (multiple days) to investigate the extent to which the aforementioned results are affected by the choice of reference choice and correlation measure, by considering several widely used montages as well as correlation metrics that are differentially sensitive to the effects of volume conduction. Specifically, we compare two standard and commonly used linear correlation measures, cross-correlation in the time domain, and coherence in the frequency domain, with measures that account for zero-lag correlations: corrected cross-correlation, imaginary coherence, phase lag index, and weighted phase lag index. We show that the graphs constructed with corrected cross-correlation and WPLI are more stable across different choices of reference. Also, we demonstrate that all the examined correlation measures revealed similar periodic patterns in the obtained graph measures when the bipolar and common reference (Cz) montage were used. This includes circadian-related periodicities (e.g., a clear increase in connectivity during sleep periods as compared to awake periods), as well as periodicities at shorter time scales (around 3 and 5 h). On the other hand, these results were affected to a large degree when the average reference montage was used in combination with standard cross-correlation, coherence, imaginary coherence, and PLI, which is likely due to the low number of electrodes and inadequate electrode coverage of the scalp. Finally, we demonstrate that the correlation between seizure onset and the brain network periodicities is preserved when corrected cross-correlation and WPLI were used for all the examined montages. This suggests that, even in the standard clinical setting of EEG recording in epilepsy where only a limited number of scalp EEG measurements are available, graph-theoretic quantification of periodic patterns using appropriate montage, and correlation measures corrected for volume conduction provides useful insights into seizure onset.
| S-EPMC6436604 | biostudies-literature
Project description:Background and purposeStudies of carotid artery disease have suggested that high-grade stenosis can affect cognition, even without stroke. The presence and degree of cognitive impairment in such patients have not been reported and compared with a demographically matched population-based cohort.MethodsWe studied cognition in 1000 consecutive CREST-2 (Carotid Revascularization and Medical Management for Asymptomatic Carotid Stenosis Trial) patients, a treatment trial for asymptomatic carotid disease. Cognitive assessment was after randomization but before assigned treatment. The cognitive battery was developed in the general population REGARDS Study (Reasons for Geographic and Racial Differences in Stroke), involving Word List Learning Sum, Word List Recall, and Word List fluency for animal names and the letter F. The carotid stenosis patients were >45 years old with ≥70% asymptomatic carotid stenosis and no history of prevalent stroke. The distribution of cognitive performance for the patients was standardized, accounting for age, race, and education using performance from REGARDS, and after further adjustment for hypertension, diabetes, dyslipidemia, and smoking. Using the Wald Test, we tabulated the proportion of Z scores less than the anticipated deviate for the population-based cohort for representative percentiles.ResultsThere were 786 baseline assessments. Mean age was 70 years, 58% men, and 52% right-sided stenosis. The overall Z score for patients was significantly below expected for higher percentiles (P<0.0001 for 50th, 75th, and 95th percentiles) and marginally below expected for the 25th percentile (P=0.015). Lower performance was attributed largely to Word List Recall (P<0.0001 for all percentiles) and for Word List Learning (50th, 75th, and 95th percentiles below expected, P≤0.01). The scores for left versus right carotid disease were similar.ConclusionsBaseline cognition of patients with severe carotid stenosis showed below normal cognition compared to the population-based cohort, controlling for demographic and cardiovascular risk factors. This cohort represents the largest group to date to demonstrate that poorer cognition, especially memory, in this disease. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02089217.
| S-EPMC8608701 | biostudies-literature