Neuronal avalanche dynamics indicates different universality classes in neuronal cultures

Yaghoubi, Mohammad; Graaf, Ty de; Orlandi, Javier G.; Girotto, Fernando; Colicos, Michael A.; Davidsen, Jörn

doi:10.1038/s41598-018-21730-1

Cited by 70 publications

(61 citation statements)

References 32 publications

(49 reference statements)

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“…Comparative studies of the functional benefits of the different critical points promise to be an interesting topic of future research, not only for the goal of basic understanding of nervous systems, but also for augmented machine learning efficiency based on critical dynamics 56,57 . Early and late criticality bear an intriguing similarity to the two different universality classes for cultured neuronal networks found by Yaghoubi et al 28 . In their study, the two universality classes were found in two different types of neuronal cultures that either had or didn't have an acid metabolite 5M4Hfolate in the culture medium.…”

Section: Discussionsupporting

confidence: 66%

“…The two regimes-we again refer to them as the "early" and "late" criticality, due to their temporal occurrence-bear strong similarities to the two critical regimes exhibited above in our theoretical model and to what ref. 28 found experimentally. Below we present the analysis of data from primarily two selected cultures with conditioned media ("Cultures 1-2", see our Supplementary Notes for additional cultures).…”

Section: Figmentioning

confidence: 84%

“…The distinct temporal foci affected several experimental parameters, such as the used culture neural densities (5000 cells mm −2 vs. our density of 800 cells mm −2 ) and necessitated constraints in data acquisition. More recently, a study of dissociated hippocampal neurons co-cultured with glia cells (from newborn P0 Sprague Dawley rats) evidenced a second criticality regime with substantially larger exponents (τ % 2:2, α % 3:3) 28 , in addition to the "expected" critical exponents. The observation of the second critical regime was, however, under condition of a specific pharmacological treatment (5M4Hfolate), which left open (in the work and to the reader) the question of how much importance should be attributed to this new regime.…”

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confidence: 98%

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Fingerprints of a second order critical line in developing neural networks

et al. 2020

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Patterns of biological activity with properties similar to critical states of statistical mechanics have received much attention, as they were mostly seen as indicators of computational optimality. Commonly, a single regime around an isolated critical point is expected. Our experimental data and our network simulations of developing neural cultures indicate the possibility of transitions between different critical regimes. In the latter, the addition of further fundamental neurophysiological principles to the standard neurodynamics branching model generates steeper power laws that have been observed in various experiments. Our analysis exhibits two populations of neurons, each composed of inhibitory and excitatory sites, that have distinct dynamical and topological properties. This generates a line of second order critical points, similar to what is known from the thermodynamics of two-component alloys. An analysis of two major critical regimes found in the experiments suggests that different critical regimes may express distinct computational roles.

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Section: Discussionsupporting

confidence: 66%

Section: Figmentioning

confidence: 84%

mentioning

confidence: 98%

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Fingerprints of a second order critical line in developing neural networks

et al. 2020

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“…In particular, the avalanche size exponent τ 1.5 originally observed by Beggs and Plenz [2] coincides with any model in the MF-DP universality class. But other experimental setups have revealed different exponents [9,30,35]. Likewise, models with different topologies or ingredients in their dynamics might give rise to exponents which differ from those of MF-DP.…”

Section: Discussionmentioning

confidence: 97%

Modeling neuronal avalanches and long-range temporal correlations at the emergence of collective oscillations: continuously varying exponents mimic M/EEG results

Porta

Copelli

2018

Preprint

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We revisit the CROS ("CRitical OScillations") model which was recently proposed as an attempt to reproduce both scale-invariant neuronal avalanches and long-range time correlations. With excitatory and inhibitory stochastic neurons locally connected in a two-dimensional disordered network, the model exhibits a transition from an active to an oscillating state. Precisely at the transition, the fluctuations of the network activity have detrended fluctuation analysis (DFA) exponents close to one, and avalanches (defined as supra-threshold activity) have power law distributions of size and duration. By simulating larger system sizes, we show that, differently from previous results, the exponents governing the distributions of avalanche size and duration are not necessarily those of the mean-field directed percolation universality class (3/2 and 2, respectively). Instead, exponents obtained via a maximum-likelihood estimator vary continuously in a narrow region of parameter space. Around that critical region, moreover, the values of avalanche and DFA exponents display a spread with negative correlations, in qualitative agreement with the interindividual variability that was experimentally observed in M/EEG data.

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“…Moreover, here we consider a fully connected system. However, it has been shown [62] that network topology has an effect on power laws, and thus models with weaker connections can produce distributions with exponents significantly larger than 1.25, even with additional input. Our result is a first step towards understanding the diversity of power-law exponents reported in the neuronal data.…”

Section: Resultsmentioning

confidence: 99%

Critical Neuronal Models with Relaxed Timescale Separation

Das

Levina

2019

Phys. Rev. X

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Power laws in nature are considered to be signatures of complexity. The theory of self-organized criticality (SOC) was proposed to explain their origins. A longstanding principle of SOC is the separation of timescales axiom. It dictates that external input is delivered to the system at a much slower rate compared to the timescale of internal dynamics. The statistics of neural avalanches in the brain was demonstrated to follow a power law, indicating closeness to critical state. Moreover, criticality was shown to be a beneficial state for various computations leading to the hypothesis, that the brain is a SOC system. However, for neuronal systems that are constantly bombarded by incoming signals, separation of timescales assumption is unnatural. Recently it was experimentally demonstrated that a proper correction of the avalanche detection algorithm to account for the increased drive during task performance leads to a change of the power-law exponent from 1.5 to approximately 1.3, but there is so far no theoretical explanation for this change. Here we investigate the importance of timescales separation, by partly abandoning it in various models. We achieve it by allowing for external input during the avalanche, without compromising the separation of avalanches. We

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Neuronal avalanche dynamics indicates different universality classes in neuronal cultures

Cited by 70 publications

References 32 publications

Fingerprints of a second order critical line in developing neural networks

Fingerprints of a second order critical line in developing neural networks

Modeling neuronal avalanches and long-range temporal correlations at the emergence of collective oscillations: continuously varying exponents mimic M/EEG results

Critical Neuronal Models with Relaxed Timescale Separation

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