scholarly journals Structural Features of the Human Connectome That Facilitate the Switching of Brain Dynamics via Noradrenergic Neuromodulation

2021 ◽  
Vol 15 ◽  
Author(s):  
Carlos Coronel-Oliveros ◽  
Samy Castro ◽  
Rodrigo Cofré ◽  
Patricio Orio

The structural connectivity of human brain allows the coexistence of segregated and integrated states of activity. Neuromodulatory systems facilitate the transition between these functional states and recent computational studies have shown how an interplay between the noradrenergic and cholinergic systems define these transitions. However, there is still much to be known about the interaction between the structural connectivity and the effect of neuromodulation, and to what extent the connectome facilitates dynamic transitions. In this work, we use a whole brain model, based on the Jasen and Rit equations plus a human structural connectivity matrix, to find out which structural features of the human connectome network define the optimal neuromodulatory effects. We simulated the effect of the noradrenergic system as changes in filter gain, and studied its effects related to the global-, local-, and meso-scale features of the connectome. At the global-scale, we found that the ability of the network of transiting through a variety of dynamical states is disrupted by randomization of the connection weights. By simulating neuromodulation of partial subsets of nodes, we found that transitions between integrated and segregated states are more easily achieved when targeting nodes with greater connection strengths—local feature—or belonging to the rich club—meso-scale feature. Overall, our findings clarify how the network spatial features, at different levels, interact with neuromodulation to facilitate the switching between segregated and integrated brain states and to sustain a richer brain dynamics.

2017 ◽  
Vol 4 (5) ◽  
pp. e375 ◽  
Author(s):  
Jan-Patrick Stellmann ◽  
Sibylle Hodecker ◽  
Bastian Cheng ◽  
Nadine Wanke ◽  
Kim Lea Young ◽  
...  

Objective:To investigate whether the structural connectivity of the brain's rich-club organization is altered in patients with primary progressive MS and whether such changes to this fundamental network feature are associated with disability measures.Methods:We recruited 37 patients with primary progressive MS and 21 healthy controls for an observational cohort study. Structural connectomes were reconstructed based on diffusion-weighted imaging data using probabilistic tractography and analyzed with graph theory.Results:We observed the same topological organization of brain networks in patients and controls. Consistent with the originally defined rich-club regions, we identified superior frontal, precuneus, superior parietal, and insular cortex in both hemispheres as rich-club nodes. Connectivity within the rich club was significantly reduced in patients with MS (p = 0.039). The extent of reduced rich-club connectivity correlated with clinical measurements of mobility (Kendall rank correlation coefficient τ = −0.20, p = 0.047), hand function (τ = −0.26, p = 0.014), and information processing speed (τ = −0.20, p = 0.049).Conclusions:In patients with primary progressive MS, the fundamental organization of the structural connectome in rich-club and peripheral nodes was preserved and did not differ from healthy controls. The proportion of rich-club connections was altered and correlated with disability measures. Thus, the rich-club organization of the brain may be a promising network phenotype for understanding the patterns and mechanisms of neurodegeneration in MS.


2021 ◽  
Author(s):  
Anira Escrichs ◽  
Yonatan Sanz Perl ◽  
Noelia Martinez-Molina ◽  
Carles Biarnes ◽  
Josep Garre ◽  
...  

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.


2017 ◽  
Author(s):  
Tengda Zhao ◽  
Virendra Mishra ◽  
Tina Jeon ◽  
Minhui Ouyang ◽  
Qinmu Peng ◽  
...  

AbstractDuring the 3rd trimester, large-scale of neural circuits are formed in the human brain, resulting in the adult-like brain networks at birth. However, how the brain circuits develop into a highly efficient and segregated connectome during this period is unknown. We hypothesized that faster increases of connectivity efficiency and strength at the brain hubs and rich-club are critical for emergence of an efficient and segregated brain connectome. Here, using high resolution diffusion MRI of 77 preterm-born and term-born neonates scanned at 31-42 postmenstrual weeks (PMW), we constructed the structural connectivity matrices and performed graph-theory-based analyses. We found faster increases of nodal efficiency mainly at the brain hubs, distributed in primary sensorimotor regions, superior-middle frontal and posterior cingulate gyrus during 31-42PMW. The rich-club and within-module connections were characterized by higher rates of edge strength increases. Edge strength of short-range connections increased faster than that of long-range connections. The nodal efficiencies of the hubs predicted individual postmenstrual ages more accurately than those of non-hubs. Collectively, these findings revealed regionally differentiated maturation in the baby brain structural connectome and more rapid increases of the hub and rich-club connections, which underlie network segregation and differentiated brain function emergence.


2021 ◽  
Vol 42 (7) ◽  
pp. 2181-2200
Author(s):  
Daniela Zöller ◽  
Corrado Sandini ◽  
Marie Schaer ◽  
Stephan Eliez ◽  
Danielle S. Bassett ◽  
...  

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 970
Author(s):  
Maedeh Khalilian ◽  
Kamran Kazemi ◽  
Mahshid Fouladivanda ◽  
Malek Makki ◽  
Mohammad Sadegh Helfroush ◽  
...  

The majority of network studies of human brain structural connectivity are based on single-shell diffusion-weighted imaging (DWI) data. Recent advances in imaging hardware and software capabilities have made it possible to acquire multishell (b-values) high-quality data required for better characterization of white-matter crossing-fiber microstructures. The purpose of this study was to investigate the extent to which brain structural organization and network topology are affected by the choice of diffusion magnetic resonance imaging (MRI) acquisition strategy and parcellation scale. We performed graph-theoretical network analysis using DWI data from 35 Human Connectome Project subjects. Our study compared four single-shell (b = 1000, 3000, 5000, 10,000 s/mm2) and multishell sampling schemes and six parcellation scales (68, 200, 400, 600, 800, 1000 nodes) using five graph metrics, including small-worldness, clustering coefficient, characteristic path length, modularity and global efficiency. Rich-club analysis was also performed to explore the rich-club organization of brain structural networks. Our results showed that the parcellation scale and imaging protocol have significant effects on the network attributes, with the parcellation scale having a substantially larger effect. Regardless of the parcellation scale, the brain structural networks exhibited a rich-club organization with similar cortical distributions across the parcellation scales involving at least 400 nodes. Compared to single b-value diffusion acquisitions, the deterministic tractography using multishell diffusion imaging data consisting of shells with b-values higher than 5000 s/mm2 resulted in significantly improved fiber-tracking results at the locations where fiber bundles cross each other. Brain structural networks constructed using the multishell acquisition scheme including high b-values also exhibited significantly shorter characteristic path lengths, higher global efficiency and lower modularity. Our results showed that both parcellation scale and sampling protocol can significantly impact the rich-club organization of brain structural networks. Therefore, caution should be taken concerning the reproducibility of connectivity results with regard to the parcellation scale and sampling scheme.


NeuroImage ◽  
2021 ◽  
pp. 118551
Author(s):  
J.A. Galadí ◽  
S. Silva Pereira ◽  
Y. Sanz Perl ◽  
M.L. Kringelbach ◽  
I. Gayte ◽  
...  

2020 ◽  
Vol 1 (4) ◽  
pp. 50-54
Author(s):  
K. K. Murataev ◽  
◽  
S. M. Krykbayeva ◽  

The article deals with insufficiently studied theoretical aspects of revealing and analyzing new elements and motives of artistic and compositional means of expression in folk art, as well as topical issues concerning determining principles and possible options for their creative development in modern decorative and applied art, design, and artistic practice in general. The most important structural features of shaping in traditional art in the ontologically interrelated system "nature — man — object" are analyzed. The main structurally stable elements and components in Kazakh folk ornament are distinguished and characterized, these are the circle, S-shaped element, cruciform and triangular components. The evolution of their ideological and figurative interpretation and symbolism is traced, and their role in the genesis of folk art traditions formed over thousands of years is revealed. The selected basic elements of folk ornament, as the main components of means of artistic expression, are proposed to be defined and developed in line with modern interpretations of artistic and aesthetic categories — dynamics, statics, harmony and their decorative variations in accordance with the volumetric and spatial features of form.


2017 ◽  
Vol 24 (3) ◽  
pp. 277-293 ◽  
Author(s):  
Selen Atasoy ◽  
Gustavo Deco ◽  
Morten L. Kringelbach ◽  
Joel Pearson

A fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at “rest.” Here, we introduce the concept of harmonic brain modes—fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; that is, connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal, and network-level changes in the brain across different mental states ( wakefulness, sleep, anesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal, and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.


2021 ◽  
Author(s):  
Jordi Mayneris-Perxachs ◽  
María Arnoriaga-Rodríguez ◽  
Miquel Martín ◽  
Aurelijus Burokas ◽  
Gerard Blasco ◽  
...  

Abstract The microbiota-gut-brain axis has emerged as a novel target in depression, a disorder with low treatment efficacy. However, the field is dominated by underpowered studies focusing on major depression not addressing microbiome functionality, compositional nature, or confounding factors. We applied a multi-omics approach combining pre-clinical models with three human cohorts including mild-depressed patients. Microbial functions and metabolites converging into glutamate/GABA metabolism, particularly proline, were linked to depression. Whole-brain dynamics revealed rich club network disruptions associated with depression and circulating proline. Proline supplementation in mice exacerbated depression along with microbial translocation. Human microbiota transplantation induced an emotional-impaired phenotype in mice and alterations in GABA-, proline-, and extracellular matrix-related pre-frontal cortex genes. Targeting the microbiome and dietary proline may open new windows for an efficient depression treatment.


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