scholarly journals Lifespan Development of the Human Brain Revealed by Large-Scale Network Eigen-Entropy

Entropy ◽  
2017 ◽  
Vol 19 (9) ◽  
pp. 471 ◽  
Author(s):  
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Keyword(s):  
Human Brain ◽  
Large Scale ◽  
Lifespan Development ◽  
Large Scale Network ◽  
Scale Network

scholarly journals Turbulent-like dynamics in the human brain

2019 ◽  
Author(s):  
Gustavo Deco ◽  
Morten L. Kringelbach
Keyword(s):  
Human Brain ◽  
Brain Function ◽  
Information Transfer ◽  
Large Scale ◽  
Brain Dynamics ◽  
Whole Brain ◽  
Large Scale Network ◽  
Maximal Sensitivity ◽  
Scale Network ◽  
Best Fit

SummaryTurbulence facilitates fast energy/information transfer across scales in physical systems. These qualities are important for brain function, but it is currently unknown if the dynamic intrinsic backbone of brain also exhibits turbulence. Using large-scale neuroimaging empirical data from 1003 healthy participants, we demonstrate Kuramoto’s amplitude turbulence in human brain dynamics. Furthermore, we build a whole-brain model with coupled oscillators to demonstrate that the best fit to the data corresponds to a region of maximally developed amplitude turbulence, which also corresponds to maximal sensitivity to the processing of external stimulations (information capability). The model shows the economy of anatomy by following the Exponential Distance Rule of anatomical connections as a cost-of-wiring principle. This establishes a firm link between turbulence and optimal brain function. Overall, our results reveal a way of analysing and modelling whole-brain dynamics that suggests turbulence as the dynamic intrinsic backbone facilitating large scale network communication.

scholarly journals The metastable human brain associated with autistic-like traits

2019 ◽  
Author(s):  
Takumi Sase ◽  
Keiichi Kitajo
Keyword(s):  
Human Brain ◽  
Large Scale ◽  
Autism Spectrum ◽  
Autism Spectrum Quotient ◽  
Healthy Humans ◽  
Large Scale Network ◽  
Individual Traits ◽  
Scale Network ◽  
Phase Amplitude ◽  
Attention To Detail

AbstractRecent studies suggest that the resting brain utilizes metastability such that the large-scale network can spontaneously yield transition dynamics across a repertoire of oscillatory states. By analyzing resting-state electroencephalographic signals and the autism-spectrum quotient acquired from healthy humans, we show experimental evidence of how autistic-like traits may be associated with the metastable human brain. Observed macroscopic brain signals exhibited slow and fast oscillations forming phase-amplitude coupling (PAC) with dynamically changing modulation strengths, resulting in oscillatory states characterized by different PAC strengths. In individuals with the ability to maintain a strong focus of attention to detail and less attention switching, these transient PAC dynamics tended to stay in a state for a longer time, to visit a lower number of states, and to oscillate at a higher frequency than in individuals with a lower attention span. We further show that attractors underlying the transient PAC could be multiple tori and consistent across individuals, with evidence that the dynamic changes in PAC strength can be attributed to changes in the strength of phase-phase coupling, that is, to dynamic functional connectivity in an electrophysiological sense. Our findings suggest that the metastable human brain can organize spontaneous events dynamically and selectively in a hierarchy of macroscopic oscillations with multiple timescales, and that such dynamic organization might encode a spectrum of individual traits covering typical and atypical development.Significance StatementMetastability in the brain is thought to be a mechanism involving spontaneous transitions among oscillatory states of the large-scale network. We show experimental evidence of how autistic-like traits may be associated with the metastable human brain by analyzing resting-state electroencephalographic signals and scores for the autism-spectrum quotient acquired from healthy humans. We found that slow and fast neural oscillations can form phase-amplitude coupling with dynamically changing modulation strengths, and that these transient dynamics can depend on the ability to maintain attention to detail and to switch attention. These results suggest that the metastable human brain can encode a spectrum of individual traits by realizing the dynamic organization of spontaneous events in a hierarchy of macroscopic oscillations with multiple timescales.

Large-Scale Network Analysis for Online Social Brand Advertising

MIS Quarterly ◽  
2016 ◽  
Vol 40 (4) ◽  
pp. 849-868 ◽  
Author(s):  
Kunpeng Zhang ◽  
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Siddhartha Bhattacharyya ◽  
Sudha Ram ◽  
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...  
Keyword(s):  
Network Analysis ◽  
Large Scale ◽  
Large Scale Network ◽  
Brand Advertising ◽  
Scale Network
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