Dynamical Criticality: Overview and Open Questions

Roli, Andrea; Villani, Marco; Filisetti, Alessandro; Serra, Roberto

doi:10.1007/s11424-017-6117-5

Cited by 89 publications

(74 citation statements)

References 88 publications

(113 reference statements)

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“…The importance of critical systems is now widely established [45][46][47][48], and more recently enhanced consistency and stability of subcritical systems have also been recognised as important features [36][37][38]. In addition to affect the dynamics of systems [32,49,50] and improve performance in several aspects [31,33], heterogeneity can also lead to functional diversity in which the dynamics of subgroups are tuned to different dynamical regimes.…”

Section: Discussionmentioning

confidence: 99%

Coexistence of critical sensitivity and subcritical specificity can yield optimal population coding

Gollo

2017

J. R. Soc. Interface.

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The vicinity of phase transitions selectively amplifies weak stimuli, yielding optimal sensitivity to distinguish external input. Along with this enhanced sensitivity, enhanced levels of fluctuations at criticality reduce the specificity of the response. Given that the specificity of the response is largely compromised when the sensitivity is maximal, the overall benefit of criticality for signal processing remains questionable. Here, it is shown that this impasse can be solved by heterogeneous systems incorporating , in which critical and subcritical components coexist. The subnetwork of critical elements has optimal sensitivity, and the subnetwork of subcritical elements has enhanced specificity. Combining segregated features extracted from the different subgroups, the resulting collective response can maximize the trade-off between sensitivity and specificity measured by the dynamic-range-to-noise ratio. Although numerous benefits can be observed when the entire system is critical, our results highlight that optimal performance is obtained when only a small subset of the system is at criticality.

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Section: Discussionmentioning

confidence: 99%

Coexistence of critical sensitivity and subcritical specificity can yield optimal population coding

Gollo

2017

J. R. Soc. Interface.

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“…SOC represents a "global" systems description in terms of universality and critical exponents, and applications to real systems for interpretation of the dynamics must be done with great care, as is evident from a history of successes, controversies and open questions. [82,84,85,103,104]…”

Section: Brain Network Show Self-organized Critical Dynamicsmentioning

confidence: 99%

Can Biological Quantum Networks Solve NP‐Hard Problems?

Wendin

2019

Adv Quantum Tech

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There is a widespread view that the human brain is so complex that it cannot be efficiently simulated by universal Turing machines, let alone ordinary classical computers. During the last decades the question has therefore been raised whether it is needed to consider quantum effects to explain the imagined cognitive power of a conscious mind. Not surprisingly, the conclusion is that quantum‐enhanced cognition and intelligence are very unlikely to be found in biological brains. Quantum effects may certainly influence signaling pathways at the molecular level in the brain network, like ion ports, synapses, sensors, and enzymes. This might evidently influence the functionality of some nodes and perhaps even the overall intelligence of the brain network, but hardly give it any dramatically enhanced functionality. The conclusion is that biological quantum networks can only approximately solve small instances of nonpolynomial (NP)‐hard problems. On the other hand, artificial intelligence and machine learning implemented in complex dynamical systems based on genuine quantum networks can certainly be expected to show enhanced performance and quantum advantage compared with classical networks. Nevertheless, even quantum networks can only be expected to solve NP‐hard problems approximately. In the end it is a question of precision—Nature is approximate.

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“…95 Nevertheless, from a theoretical standpoint, the universality of criticality is still 96 under examination and is known as the Criticality Hypothesis, which states that 97 systems in a dynamic regime shifting between order and disorder, attain the highest 98 level of computational capabilities and achieve an optimal trade-off between robustness 99 and flexibility. Recent results in cell and evolutionary biology, neuroscience and 100 computer science have great interest in the criticality hypothesis, emphasizing its role as 101 a viable candidate general law in the realm of adaptive complex systems (see [38] and 102 references therein).…”

Section: Figmentioning

confidence: 99%

Assessing sustainability in North America’s ecosystems using criticality and information theory

Ramírez-Carrillo

López-Corona

Toledo-Roy

et al. 2018

Preprint

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Sustainability is a key concept in economic and policy debates. Nevertheless, it is usually treated only in a qualitative way and has eluded quantitative analysis. Here, we propose a sustainability index based on the premise that sustainable systems do not lose or gain Fisher Information over time. We test this approach using time series data from the AmeriFlux network that measures ecosystem respiration, water and energy fluxes in order to elucidate two key sustainability features: ecosystem health and stability. A novel definition of ecosystem health is developed based on the concept of criticality, which implies that if a system’s fluctuations are scale invariant then the system is in a balance between robustness and adaptability. We define ecosystem stability by taking an information theory approach that measures its entropy and Fisher information. Analysis of the Ameriflux consortium big data set of ecosystem respiration time series is contrasted with land condition data. In general we find a good agreement between the sustainability index and land condition data. However, we acknowledge that the results are a preliminary test of the approach and further verification will require a multi-signal analysis. For example, high values of the sustainability index for some croplands are counter-intuitive and we interpret these results as ecosystems maintained in artificial health due to continuous human-induced inflows of matter and energy in the form of soil nutrients and control of competition, pests and disease.

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Dynamical Criticality: Overview and Open Questions

Cited by 89 publications

References 88 publications

Coexistence of critical sensitivity and subcritical specificity can yield optimal population coding

Coexistence of critical sensitivity and subcritical specificity can yield optimal population coding

Can Biological Quantum Networks Solve NP‐Hard Problems?

Assessing sustainability in North America’s ecosystems using criticality and information theory

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