scholarly journals Whole-brain dynamics in aging: disruptions in functional connectivity and the role of the rich club

2020 ◽  
Author(s):  
Anira Escrichs ◽  
Carles Biarnes ◽  
Josep Garre-Olmo ◽  
José Manuel Fernández-Real ◽  
Rafel Ramos ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Brain Dynamics ◽  
Whole Brain ◽  
Rich Club ◽  
Brain Functional Network ◽  
Age Related ◽  
Age Range ◽  
The Brain

AbstractNormal aging causes disruptions in the brain that can lead to cognitive decline. Resting-state fMRI studies have found significant age-related alterations in functional connectivity across various networks. Nevertheless, most of the studies have focused mainly on static functional connectivity. Studying the dynamics of resting-state brain activity across the whole-brain functional network can provide a better characterization of age-related changes. Here we employed two data-driven whole-brain approaches based on the phase synchronization of blood-oxygen-level-dependent (BOLD) signals to analyze resting-state fMRI data from 620 subjects divided into two groups (‘middle-age group’ (n=310); age range, 50-65 years vs. ‘older group’ (n=310); age range, 66-91 years). Applying the Intrinsic-Ignition Framework to assess the effect of spontaneous local activation events on local-global integration, we found that the older group showed higher intrinsic ignition across the whole-brain functional network, but lower metastability. Using Leading Eigenvector Dynamics Analysis, we found that the older group showed reduced ability to access a metastable substate that closely overlaps with the so-called rich club. These findings suggest that functional whole-brain dynamics are altered in aging, probably due to a deficiency in a metastable substate that is key for efficient global communication in the brain.

scholarly journals Whole-Brain Dynamics in Aging: Disruptions in Functional Connectivity and the Role of the Rich Club

2020 ◽  
Author(s):  
Anira Escrichs ◽  
Carles Biarnes ◽  
Josep Garre-Olmo ◽  
José Manuel Fernández-Real ◽  
Rafel Ramos ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Functional Network ◽  
Brain Dynamics ◽  
Whole Brain ◽  
Rich Club ◽  
Brain Functional Network ◽  
Age Related ◽  
Age Range ◽  
The Brain

Abstract Normal aging causes disruptions in the brain that can lead to cognitive decline. Resting-state functional magnetic resonance imaging studies have found significant age-related alterations in functional connectivity across various networks. Nevertheless, most of the studies have focused mainly on static functional connectivity. Studying the dynamics of resting-state brain activity across the whole-brain functional network can provide a better characterization of age-related changes. Here, we employed two data-driven whole-brain approaches based on the phase synchronization of blood-oxygen-level-dependent signals to analyze resting-state fMRI data from 620 subjects divided into two groups (middle-age group (n = 310); age range, 50–64 years versus older group (n = 310); age range, 65–91 years). Applying the intrinsic-ignition framework to assess the effect of spontaneous local activation events on local–global integration, we found that the older group showed higher intrinsic ignition across the whole-brain functional network, but lower metastability. Using Leading Eigenvector Dynamics Analysis, we found that the older group showed reduced ability to access a metastable substate that closely overlaps with the so-called rich club. These findings suggest that functional whole-brain dynamics are altered in aging, probably due to a deficiency in a metastable substate that is key for efficient global communication in the brain.

scholarly journals The effect of external stimulation on functional networks in the aging healthy human brain

2021 ◽  
Author(s):  
Anira Escrichs ◽  
Yonatan Sanz Perl ◽  
Noelia Martinez-Molina ◽  
Carles Biarnes ◽  
Josep Garre ◽  
...  
Keyword(s):  
In Silico ◽  
Brain Area ◽  
Resting State Fmri ◽  
Brain Dynamics ◽  
Healthy Human ◽  
Whole Brain ◽  
External Stimulation ◽  
Rich Club ◽  
Brain States ◽  
The Brain

Understanding the brain changes occurring during aging can provide new insights for developing treatments that alleviate or reverse cognitive decline. Neurostimulation techniques have emerged as potential treatments for brain disorders and to improve cognitive functions. Nevertheless, given the ethical restrictions of neurostimulation approaches, in silico perturbation protocols based on causal whole-brain models are fundamental to gaining a mechanistic understanding of brain dynamics. Furthermore, this strategy could serve as a more specific biomarker relating local activity with global brain dynamics. Here, we used a large resting-state fMRI dataset divided into middle-aged (N=310, aged < 65 years) and older adults (N=310, aged >= 65) to characterize brain states in each group as a probabilistic metastable substate (PMS) space, each with a probabilistic occurrence and frequency. Then, we fitted the PMS to a whole-brain model and applied in silico stimulations with different intensities in each node to force transitions from the brain states of the older group to the middle-age group. We found that the precuneus, a brain area belonging to the default mode network and the rich club, was the best stimulation target. These findings might have important implications for designing neurostimulation interventions to revert the effects of aging on whole-brain dynamics.

Inter-Hemispherical Investigations on the Functional Connectivity in Controls and Autism Spectrum Using Resting State fMRI

2020 ◽  
pp. 169-186
Author(s):  
S. Vidhusha ◽  
A. Kavitha
Keyword(s):  
Functional Connectivity ◽  
Granger Causality ◽  
Resting State ◽  
Cognitive Task ◽  
Resting State Fmri ◽  
Autism Spectrum ◽  
Control Group ◽  
Neural Connectivity ◽  
Activation Patterns ◽  
The Brain

Autism spectrum disorders are connected with disturbances of neural connectivity. Functional connectivity is typically examined during a cognitive task, but also exists in the absence of a task. While a number of studies have performed functional connectivity analysis to differentiate controls and autism individuals, this work focuses on analyzing the brain activation patterns not only between controls and autistic subjects, but also analyses the brain behaviour present within autism spectrum. This can bring out more intuitive ways to understand that autism individuals differ individually. This has been performed between autism group relative to the control group using inter-hemispherical analysis. Indications of under connectivity were exhibited by the Granger Causality (GC) and Conditional Granger Causality (CGC) in autistic group. Results show that as connectivity decreases, the GC and CGC values also get decreased. Further, to demark the differences present within the spectrum of autistic individuals, GC and CGC values have been calculated.

scholarly journals ALTERED BRAIN FUNCTIONAL CONNECTIVITY FOLLOWING A SEASON OF COMPETITIVE FEMALE HIGH SCHOOL SOCCER AND THE EFFECT OF A JUGULAR VEIN COMPRESSION COLLAR: A NETWORK-BASED STATISTICS ANALYSIS

2020 ◽  
Vol 8 (4_suppl3) ◽  
pp. 2325967120S0026
Author(s):  
Jonathan A. Dudley ◽  
Jed A. Diekfuss ◽  
Weihong Yuan ◽  
Kim D. Barber Foss ◽  
Christopher A. DiCesare ◽  
...  
Keyword(s):  
High School ◽  
Functional Connectivity ◽  
Resting State ◽  
Female Athletes ◽  
Jugular Vein ◽  
Resting State Fmri ◽  
Head Impacts ◽  
Brain Functional Network ◽  
Female High School ◽  
Brain Functional Connectivity

Background: Cumulative exposure to repetitive sub-concussive head impacts in contact sports may have deleterious effects on brain function, even in the absence of acute symptoms. Moreover, anatomical and biomechanical factors may predispose female athletes to higher risk compared to males. At present, there is no effective injury prevention strategy to protect female athletes from sports-related head impact. Hypothesis/Purpose: (1). We aimed to use resting-state fMRI to investigate the effect of a full season of competitive soccer on brain functional network integrity in female high school athletes. (2). We also aimed to evaluate the efficacy of a jugular vein compression neck collar device, designed to mitigate potential injury by reducing the brain slosh effect. Methods: A total of 125 high school female soccer athletes were included in this study. These athletes were assigned randomly to a non-collar (n=55, age=16.06±1.06 yrs) or collar group (n=70, 15.81±0.95 yrs) before the season started. High resolution 3D T1-weighted images and resting-state fMRI data were collected prospectively at pre-season and again at post-season. Data processing and analysis were conducted in the MATLAB-based programs Statistical Parametric Mapping (SPM12) and Connectivity Toolbox (Conn). Functional connectivity was computed between each pair of 105 anatomically delineated regions of interest (ROI). Network Based Statistics were applied to detect coherent patterns of altered connectivity from pre- to post-season. Results: The non-collar group showed a significant pattern of altered connectivity (p-FWE = 0.047) spanning 60% of ROIs (63/105) and 1.7% of ROI-ROI connections (94/5,460). 65 of the 94 altered connections were weakened from pre-to-post season and tended to occur in the right hemisphere. 29 of the 94 altered connections were strengthened from pre-to-post season and tended to involve regions in the occipital lobe. The collar group did not show any statistically significant change (p-FWE = 0.223). Conclusion: The results of this study indicate that exposure to repetitive sub-concussive head impacts during a single season of competitive female soccer induces changes in brain functional connectivity. The observed increases and decreases of functional connectivity strength comprising the pattern of altered connectivity are congruent with a heterogeneous response to insult wherein some connections are reduced in strength due to neuronal damage and other “detour” connections are strengthened to preserve network function. Comparatively, the absence of alterations in the collar group suggest that the jugular vein compression collar may have generated a potentially protective effect to preserve brain functional network integrity during exposure to head impacts. [Figure: see text]

scholarly journals Multiscale dynamic mean field model to relate resting-state brain dynamics with local cortical excitatory-inhibitory neurotransmitter homeostasis in health and disease

2018 ◽  
Author(s):  
Amit Naskar ◽  
Anirudh Vattikonda ◽  
Gustavo Deco ◽  
Dipanjan Roy ◽  
Arpan Banerjee
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Diffusion Tensor ◽  
Mean Field ◽  
Clustering Coefficient ◽  
Brain Dynamics ◽  
Whole Brain ◽  
Health And Disease ◽  
The Impact ◽  
Tractography Data

AbstractPrevious neuro-computational studies have established the connection of spontaneous resting-state brain activity with “large-scale” neuronal ensembles using dynamic mean field approach and showed the impact of local excitatory−inhibitory (E−I) balance in sculpting dynamical patterns. Here, we argue that whole brain models that link multiple scales of physiological organization namely brain metabolism that governs synaptic concentrations of gamma-aminobutyric acid (GABA) and glutamate on one hand and neural field dynamics that operate on the macroscopic scale. The multiscale dynamic mean field (MDMF) model captures the synaptic gating dynamics over a cortical macrocolumn as a function of neurotransmitter kinetics. Multiple MDMF units were placed in brain locations guided by an anatomical parcellation and connected by tractography data from diffusion tensor imaging. The resulting whole-brain model generates the resting-state functional connectivity and also reveal that optimal configurations of glutamate and GABA captures the dynamic working point of the brain, that is the state of maximum metsatability as observed in BOLD signals. To demonstrate test-retest reliability we validate the observation that healthy resting brain dynamics is governed by optimal glutamate-GABA configurations using two different brain parcellations for model set-up. Furthermore, graph theoretical measures of segregation (modularity and clustering coefficient) and integration (global efficiency and characteristic path length) on the functional connectivity generated from healthy and pathological brain network studies could be explained by the MDMF model. In conclusion, the MDMF model could relate the various scales of observations from neurotransmitter concentrations to dynamics of synaptic gating to whole-brain resting-state network topology in health and disease.

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