Four correlates of complex behavioral networks: Differentiation, behavior, connectivity, and compartmentalization: Carving networks at their joints

Changizi, Mark A.; He, Darren

doi:10.1002/cplx.20085

Cited by 8 publications

(4 citation statements)

References 137 publications

(108 reference statements)

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“…Nevertheless, within a community, people coordinate in multiple social groups at various spatiotemporal scales–a complex organization that is far from uniform synchronization [ 68 – 70 ]. In fact, the components of living systems often compartmentalize into distinct communities or modules, highlighted by dense interactions within communities and loose interactions between communities [ 71 , 72 ]. This form of organization, embracing both integration and segregation among its elements, can lead to greater persistence and robustness of the system [ 73 – 76 ], and influence structural and functional complexity depending on the scale of integration [ 77 – 79 ].…”

Section: Discussionmentioning

confidence: 99%

Critical diversity: Divided or united states of social coordination

2018

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Much of our knowledge of coordination comes from studies of simple, dyadic systems or systems containing large numbers of components. The huge gap ‘in between’ is seldom addressed, empirically or theoretically. We introduce a new paradigm to study the coordination dynamics of such intermediate-sized ensembles with the goal of identifying key mechanisms of interaction. Rhythmic coordination was studied in ensembles of eight people, with differences in movement frequency (‘diversity’) manipulated within the ensemble. Quantitative change in diversity led to qualitative changes in coordination, a critical value separating régimes of integration and segregation between groups. Metastable and multifrequency coordination between participants enabled communication across segregated groups within the ensemble, without destroying overall order. These novel findings reveal key factors underlying coordination in ensemble sizes previously considered too complicated or 'messy' for systematic study and supply future theoretical/computational models with new empirical checkpoints.

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Section: Discussionmentioning

confidence: 99%

Critical diversity: Divided or united states of social coordination

2018

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“…The square root compartment invariance -i.e., the constraint that the average number of neurons per area scales proportionally to the total number of areas -can be explained by a hypothesis that, given that invariant well-connectedness must (for whatever reason) be satisfi ed across neocortices of varying size, the most economical way of satisfying invariant well-connectedness is to scale the number of areas proportionally to the average number of neurons per area. This is called 'economical well-connectedness' [Changizi, 2001[Changizi, , 2003b[Changizi, , 2005Changizi and He, 2005].…”

Section: Discussionmentioning

confidence: 99%

Parcellation and Area-Area Connectivity as a Function of Neocortex Size

Changizi

Shimojo

2005

Brain Behav Evol

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Via the accumulation of data from across the neuroanatomy literature, we estimate the manner in which (i) the number of neocortical areas varies with neocortex size, and (ii) the number of area-area connections varies with neocortex size. Concerning parcellation, we find that the number of areas scales approximately as the 1/3 power of gray matter volume, or, equivalently, as the square root of the total number of neocortical neurons. A consequence of this is that the average number of neurons per area also scales approximately as the square root of the total number of areas. Concerning area-area connectivity, we find evidence that the total number of area-area connections scales as the square of the number of areas. These scaling results help constrain theories about the principles underlying neocortical organization.

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“…This is mainly due to its wide applications in many areas ranging from physics to biological, mathematics, social, economic, and computer sciences. Therefore, investigating the relation dynamical of complex networks is quite important .…”

Section: Introductionmentioning

confidence: 99%

“…E-mail addresses: pinghecn@qq.com economic, and computer sciences. Therefore, investigating the relation dynamical of complex networks is quite important [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Robust decentralized adaptive synchronization of general complex networks with coupling delayed and uncertainties

Jing

Fan

et al. 2013

Complexity

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The problem of robust decentralized adaptive synchronization of general complex networks with coupling delayed and uncertainties is investigated in this article. It is only assumed that the upper normal bound of uncertain inner and outer coupling matrices is positive but its concrete structure is not also required to be known. The time‐varying coupling delay is a any nonnegative continuous and bounded function and not require its derivative to be less than one, that is, general time‐varying coupling delays and uncertainties. For such a class of uncertain complex networks, a new synchronization scheme is presented by a class of continuous memoryless robust decentralized adaptive synchronization controllers. It is also shown that the synchronization error dynamics of uncertain complex networks can be guaranteed as uniformly exponentially convergent toward a ball that can be as small as desired. Finally, numerical simulations are provided to demonstrate the effectiveness and robustness of proposed complex networks synchronization schemes. © 2013 Wiley Periodicals, Inc. Complexity 19: 10–26, 2014

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Four correlates of complex behavioral networks: Differentiation, behavior, connectivity, and compartmentalization: Carving networks at their joints

Abstract: Some of the most complex networks are those that (i) have been engineered under selective pressure (either economic or evolutionary), and (ii)

Cited by 8 publications

References 137 publications

Critical diversity: Divided or united states of social coordination

Critical diversity: Divided or united states of social coordination

Parcellation and Area-Area Connectivity as a Function of Neocortex Size

Robust decentralized adaptive synchronization of general complex networks with coupling delayed and uncertainties

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