Does the<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mn>1</mml:mn><mml:mo>/</mml:mo><mml:mi>f</mml:mi></mml:math>Frequency Scaling of Brain Signals Reflect Self-Organized Critical States?

Bédard, Claude; Kröger, H.; Destexhe, Alain

doi:10.1103/physrevlett.97.118102

Cited by 370 publications

(388 citation statements)

References 28 publications

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“…This result is in agreement with observations from neuronal dynamics in cat association cortex ( Fig. 2C; Bedard et al, 2006). This provides evidence that the experimental observations of Poisson dynamics (exponential ISI distributions) and absence of avalanche dynamics, are all consistent with self-generated irregular states in cortical networks.…”

Section: Discussionsupporting

confidence: 92%

“…7, right). These data show that the apparent Poisson statistics and absence of avalanche dynamics observed in cat association cortex (Bedard et al, 2006) is also found in network models.…”

Section: Comparison Of Models To Experimental Datasupporting

confidence: 61%

“…2B). Third, we performed a similar avalanche analysis as performed for the experimental data (Bedard et al, 2006). This analysis also failed to evidence power-law scaling behavior but rather indicates exponential distributions (Fig.…”

Section: Comparison Of Models To Experimental Datamentioning

confidence: 93%

“…To perform such an analysis, the avalanches are detected as clusters of temporally contiguous spikes separated by silences, and the sign of self-organized critical state is a power-law behavior of the distribution of avalanche sizes (see Beggs and Plenz, 2003, and references therein). Such an avalanche analysis was performed from multielectrode recordings in awake cats (Bedard et al, 2006), and did not reveal the typical power-law scaling behavior of critical states, but rather exponential distributions (Fig. 2C).…”

Section: Experimental Characterization Of Activated Cortical Statesmentioning

confidence: 97%

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Activated cortical states: Experiments, analyses and models

Boustani

Pospischil

Rudolph-Lilith

et al. 2007

Journal of Physiology-Paris

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In awake animals, the cerebral cortex displays an ''activated'' state, with distinct characteristics compared to other states like slow-wave sleep or anesthesia. These characteristics include a sustained depolarized membrane potential (V m ) and irregular firing activity. In the present paper, we evaluate our understanding of cortical activated states from a computational neuroscience point of view. We start by reviewing the electrophysiological characteristics of activated cortical states based on recordings and analysis performed in awake cat association cortex. These analyses show that cortical activity is characterized by an apparent Poisson-distributed stochastic dynamics, both at the single-cell and population levels, and that single cells display a high-conductance state dominated by inhibition. We next overview computational models of the ''awake'' cortex, and perform the same analyses as in the experiments. Many properties identified experimentally are indeed reproduced by models, such as depolarized V m , irregular firing with apparent Poisson statistics, and the determinant role of inhibitory fluctuations on spiking. However, other features are not well reproduced, such as firing statistics and the conductance state of the membrane, suggesting that the network state displayed by models is not entirely correct. We also show how networks can approach a correct conductance state, suggesting ways by which future models will generate activity fully consistent with experimental data.

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Section: Discussionsupporting

confidence: 92%

“…7, right). These data show that the apparent Poisson statistics and absence of avalanche dynamics observed in cat association cortex (Bedard et al, 2006) is also found in network models.…”

Section: Comparison Of Models To Experimental Datasupporting

confidence: 61%

Section: Comparison Of Models To Experimental Datamentioning

confidence: 93%

Section: Experimental Characterization Of Activated Cortical Statesmentioning

confidence: 97%

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Activated cortical states: Experiments, analyses and models

Boustani

Pospischil

Rudolph-Lilith

et al. 2007

Journal of Physiology-Paris

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“…Consequently, for most combinations of parameters the number of firing neurons is an almost constant but noisy time series. This is in correspondence with the behaviour of the real brain: it is a commonplace in neuroscience that electroencephalograms (EEG) are noisy signals with a spectrum 1/f which has been associated with self-organized criticality [47] although, in the case of the brain, that explanation has been dismissed [48]. On the other hand, in some clinical cases, a regular synchronous oscillation appears.…”

Section: The Phase Diagrammentioning

confidence: 99%

Firing patterns in a random network cellular automata model of the brain

Acedo¹,

Lamprianidou²,

Moraño³

et al. 2015

Physica A: Statistical Mechanics and its Applications

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One of the main challenges in the simulation of even reduced areas of the brain is the presence of a large number of neurons and a large number of connections among them. Even from a theoretical point of view, the behaviour of dynamical models of complex networks with high connectivity is unknown, precisely because the cost of computation is still unaffordable and it will likely be in the near future. In this paper we discuss the simulation of a cellular automata network model of the brain including up to one million sites with a maximum average of three hundred connections per neuron. This level of connectivity was achieved thanks to a distributed computing environment based on the BOINC (Berkeley Open Infrastructure for Network Computing) platform. Moreover, in this work we consider the interplay among excitatory neurons (which induce the excitation of their neighbours) and inhibitory neurons (which prevent resting neurons from firing and induce firing neurons to pass to the refractory state). Our objective is to classify the normal (noisy but asymptotically constant patterns) and the abnormal (high oscillations with spindle-like behaviour) patterns of activity in the model brain and their stability and parameter * e-mail: luiacrod@imm.upv.es 1 ranges in order to determine the role of excitatory and inhibitory compensatory effects in healthy and diseased individuals.

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Investigation of Low‐Current Direct Stimulation for Rehabilitation Treatment Related to Muscle Function Loss Using Self‐Powered TENG System

et al. 2019

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Muscle function loss is characterized as abnormal or completely lost muscle capabilities, and it can result from neurological disorders or nerve injuries. The currently available clinical treatment is to electrically stimulate the diseased muscles. Here, a self‐powered system of a stacked‐layer triboelectric nanogenerator (TENG) and a multiple‐channel epimysial electrode to directly stimulate muscles is demonstrated. Then, the two challenges regarding direct TENG muscle stimulation are further investigated. For the first challenge of improving low‐current TENG stimulation efficiency, it is found that the optimum stimulation efficiency can be achieved by conducting a systematic mapping with a multiple‐channel epimysial electrode. The second challenge is TENG stimulation stability. It is found that the force output generated by TENGs is more stable than using the conventional square wave stimulation and enveloped high frequency stimulation. With modelling and in vivo measurements, it is confirmed that the two factors that account for the stable stimulation using TENGs are the long pulse duration and low current amplitude. The current waveform of TENGs can effectively avoid synchronous motoneuron recruitment at the two stimulation electrodes to reduce force fluctuation. Here, after investigating these two challenges, it is believed that TENG direct muscle stimulation could be used for rehabilitative and therapeutic purpose of muscle function loss treatment.

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Does the1/fFrequency Scaling of Brain Signals Reflect Self-Organized Critical States?

Cited by 370 publications

References 28 publications

Activated cortical states: Experiments, analyses and models

Activated cortical states: Experiments, analyses and models

Firing patterns in a random network cellular automata model of the brain

Investigation of Low‐Current Direct Stimulation for Rehabilitation Treatment Related to Muscle Function Loss Using Self‐Powered TENG System

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