Scale-free outbursts of activity are commonly observed in physical, geological, and biological systems. The idea self-organized criticality (SOC), introduced back 1987 by Bak, Tang Wiesenfeld suggests that, under certain circumstances, natural systems can seemingly self-tune to a critical state with its concomitant power-laws scaling. Theoretical progress allowed for rationalization how SOC works relating properties those standard non-equilibrium second-order phase transition that separates...

This paper analyzes what type of phase transitions from synchronous to asynchronous phases are able exhibit concomitantly scale-free avalanches synchronized activity right at their critical point, discussing the possible relevance them in neuroscience.

High-level information processing in the mammalian cortex requires both segregated specialized circuits and integration across multiple circuits. One possible way to implement these seemingly opposing demands is by flexibly switching between states with different levels of synchrony. However, mechanisms behind control complex synchronization patterns neuronal networks remain elusive. Here, we use precision neuroengineering manipulate stimulate cortical neurons vitro, combination an silico...

Self-organized bistability (SOB) is the counterpart of 'self-organized criticality' (SOC), for systems tuning themselves to edge a discontinuous phase transition, rather than critical point continuous one. The equations defining mathematical theory SOB turn out bear strong resemblance (Landau-Ginzburg) recently proposed analyze dynamics cerebral cortex. This describes neuronal activity coupled mesoscopic patches cortex, homeostatically regulated by short-term synaptic plasticity. cortex...

Many of the amazing functional capabilities brain are collective properties stemming from interactions large sets individual neurons. In particular, most salient phenomena in activity oscillations, which require synchronous activation many Here, we analyse parsimonious dynamical models neural synchronisation running on top synthetic networks that capture essential aspects actual anatomical connectivity such as a hierarchical-modular and core-periphery structure. These reveal emergence...

The celebrated Ott-Antonsen for coupled oscillators provides a useful framework working with deterministic systems in the thermodynamic limit, but it fails to capture many features of stochastic systems. Several solutions have been recently proposed accurately describe behavior order parameters oscillator However, fluctuating description such has still elusive. In this Letter, I construct first time general mesoscopic finite-size populations subject white noise. theory allows one derive...

The resting state of the human brain is characterized by a perpetual, ongoing activity that believed to be crucial for its function. A simple network model excitatory and inhibitory binary units able reproduce remarkably well many such nontrivial features.

ABSTRACT Neuronal cultures in vitro are a versatile system for studying the fundamental properties of individual neurons and neuronal networks. Recently, this approach has gained attention as precision medicine tool. Mature exhibit synchronized collective dynamics called network bursting. If analyzed appropriately, activity could offer insights into network’s properties, such its composition, topology, developmental pathological processes. A promising method investigating networks is to map...

Balanced neural networks, in which excitatory and inhibitory inputs compensate each other on average, give rise to a dynamical phase dominated by fluctuations called an asynchronous state, crucial for brain functioning. However, structural disorder, is inherent random can hinder such excitation-inhibition balance. Indeed, synaptic heterogeneities generate extended regions space akin critical points, Griffiths phases, with features very different from those of states. Here we study simple...

The cortex exhibits self-sustained highly-irregular activity even under resting conditions, whose origin and function need to be fully understood. It is believed that this can described as an "asynchronous state" stemming from the balance between excitation inhibition, with important consequences for information-processing, though a competing hypothesis claims it stems critical dynamics. By analyzing parsimonious neural-network model excitatory inhibitory interactions, we elucidate...

Pathogen transmission and virulence are main evolutionary variables broadly assumed to be linked through trade-offs. In well-mixed populations, these trade-offs often ascribed physiological restrictions, while populations with spatial self-structuring might evolve emergent Here, we reexamine a model of the latter kind proposed by Ballegooijen Boerlijst aim characterising mechanisms causing emergence trade-off its structural robustness. Using invadability criteria, establish conditions under...

Studies of neural avalanches across different data modalities led to the prominent hypothesis that brain operates near a critical point. The observed exponents often indicate mean-field directed-percolation universality class, leading fully connected or random network models study avalanche dynamics. However, cortical networks have distinct nonrandom features and spatial organization is known affect exponents. Here we show empirical arise in with topology depend on size. In particular, find...

Cortical neurons are versatile and efficient coding units that develop strong preferences for specific stimulus characteristics. The sharpness of tuning efficiency is hypothesized to be controlled by delicately balanced excitation inhibition. These observations suggest a need detailed co-tuning excitatory inhibitory populations. Theoretical studies have demonstrated combination plasticity rules can lead the emergence excitation/inhibition (E/I) in driven independent, low-noise signals....

The celebrated Ott-Antonsen ansatz for coupled oscillators provides a useful framework to work with deterministic systems in the thermodynamic limit, but remains just an approximation stochastic models. In this paper, I construct general mesoscopic description of finite-sized populations and apply it study Kuramoto model. From such is possible obtain natural, multiplicative fluctuations oscillator ensemble. analysis allows one derive highly accurate, closed expressions model's order...

Feature selectivity, the ability of neurons to respond preferentially specific stimulus configurations, is a fundamental building block cortical functions. Various mechanisms have been proposed explain its origins, differing primarily in their assumptions about connectivity between neurons. Some models attribute selectivity structured, tuning-dependent feedforward or recurrent connections, whereas others suggest it can emerge within randomly connected networks when interactions are...

Cortical neurons are versatile and efficient coding units that develop strong preferences for specific stimulus characteristics. The sharpness of tuning efficiency is hypothesized to be controlled by delicately balanced excitation inhibition. These observations suggest a need detailed co-tuning excitatory inhibitory populations. Theoretical studies have demonstrated combination plasticity rules can lead the emergence excitation/inhibition (E/I) cotuning in driven independent, low-noise...

The essential ingredient for studying the phenomena of emergence is ability to generate and manipulate emergent systems that span large scales. Cellular automata are model class particularly known their effective scalability but also typically constrained by fixed local rules. In this paper, we propose a new adaptive cellular allows generation scalable expressive models. We show how implement computation-effective adaptation coupling update rule automaton with itself system state in...

Balanced neural networks -- in which excitatory and inhibitory inputs compensate each other on average give rise to a dynamical phase dominated by fluctuations called asynchronous state, crucial for brain functioning. However, structural disorder is inherent random can hinder such an excitation-inhibition balance. Indeed, synaptic heterogeneities generate extended regions space akin critical points, Griffiths phases, with features very different from those of states. Here, we study simple...

The branching process is the minimal model for propagation dynamics, avalanches and criticality, broadly used in neuroscience. A simple extension of it, adding inhibitory nodes, induces a much-richer phenomenology, including, an intermediate phase, between quiescence saturation, that exhibits key features "asynchronous states" cortical networks. Remarkably, inhibition-dominated case, it extremely-rich phase diagram, captures wealth non-trivial spontaneous brain activity, such as collective...

Brain functions require both segregated processing of information in specialized circuits, as well integration across circuits to perform high-level processing. One possible way implement these seemingly opposing demands is by flexibly switching between synchronous and less states. Understanding how complex synchronization patterns are controlled the interaction network architecture external perturbations thus a central challenge neuroscience, but mechanisms behind such interactions remain...

Multiple studies of neural avalanches across different data modalities led to the prominent hypothesis that brain operates near a critical point. The observed exponents often indicate mean-field directed-percolation universality class, leading fully-connected or random network models study avalanche dynamics. However, cortical networks have distinct non-random features and spatial organization is known affect exponents. Here we show empirical arise in with topology depend on size. In...