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"Neuronal avalanches"

Dong-Ping Yang, Hai-Jun Zhou, Changsong Zhou
The brain is highly energy consuming, therefore is under strong selective pressure to achieve cost-efficiency in both cortical connectivities and activities. However, cost-efficiency as a design principle for cortical activities has been rarely studied. Especially it is not clear how cost-efficiency is related to ubiquitously observed multi-scale properties: irregular firing, oscillations and neuronal avalanches. Here we demonstrate that these prominent properties can be simultaneously observed in a generic, biologically plausible neural circuit model that captures excitation-inhibition balance and realistic dynamics of synaptic conductance...
February 2017: PLoS Computational Biology
D E Nichols, M W Johnson, C D Nichols
Scientific interest in serotonergic psychedelics (e.g., psilocybin and LSD; 5-HT2A receptor agonists) has dramatically increased within the last decade. Clinical studies administering psychedelics with psychotherapy have shown preliminary evidence of robust efficacy in treating anxiety and depression, as well as addiction to tobacco and alcohol. Moreover, recent research has suggested that these compounds have potential efficacy against inflammatory diseases through novel mechanisms, with potential advantages over existing antiinflammatory agents...
February 2017: Clinical Pharmacology and Therapeutics
Andreas Klaus, Dietmar Plenz
During quiet resting behavior, involuntary movements are suppressed. Such movement control is attributed to cortico-basal ganglia loops, yet population dynamics within these loops during resting and their relation to involuntary movements are not well characterized. Here, we show by recording cortical and striatal ongoing population activity in awake rats during quiet resting that intrastriatal inhibition maintains a low-correlation striatal resting state in the presence of cortical neuronal avalanches. Involuntary movements arise from disturbed striatal resting activity through two different population dynamics...
December 2016: PLoS Biology
Yuichiro Yada, Takeshi Mita, Akihiro Sanada, Ryuichi Yano, Ryohei Kanzaki, Douglas J Bakkum, Andreas Hierlemann, Hirokazu Takahashi
Self-organized criticality (SoC), a spontaneous dynamic state established and maintained in networks of moderate complexity, is a universal characteristic of neural systems. Such systems produce cascades of spontaneous activity that are typically characterized by power-law distributions and rich, stable spatiotemporal patterns (i.e., neuronal avalanches). Since the dynamics of the critical state confer advantages in information processing within neuronal networks, it is of great interest to determine how criticality emerges during development...
November 30, 2016: Neuroscience
Oshrit Arviv, Mordekhay Medvedovsky, Liron Sheintuch, Abraham Goldstein, Oren Shriki
The framework of criticality provides a unifying perspective on neuronal dynamics from in vitro cortical cultures to functioning human brains. Recent findings suggest that a healthy cortex displays critical dynamics, giving rise to scale-free spatiotemporal cascades of activity, termed neuronal avalanches. Pharmacological manipulations of the excitation-inhibition balance (EIB) in cortical cultures were previously shown to result in deviations from criticality and from the power law scaling of avalanche size distribution...
November 30, 2016: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
Ludmila Brochini, Ariadne de Andrade Costa, Miguel Abadi, Antônio C Roque, Jorge Stolfi, Osame Kinouchi
Phase transitions and critical behavior are crucial issues both in theoretical and experimental neuroscience. We report analytic and computational results about phase transitions and self-organized criticality (SOC) in networks with general stochastic neurons. The stochastic neuron has a firing probability given by a smooth monotonic function Φ(V) of the membrane potential V, rather than a sharp firing threshold. We find that such networks can operate in several dynamic regimes (phases) depending on the average synaptic weight and the shape of the firing function Φ...
November 7, 2016: Scientific Reports
L Michiels van Kessenich, L de Arcangelis, H J Herrmann
Neuronal avalanches measured in vitro and in vivo in different cortical networks consistently exhibit power law behaviour for the size and duration distributions with exponents typical for a mean field self-organized branching process. These exponents are also recovered in neuronal network simulations implementing various neuronal dynamics on different network topologies. They can therefore be considered a very robust feature of spontaneous neuronal activity. Interestingly, this scaling behaviour is also observed on regular lattices in finite dimensions, which raises the question about the origin of the mean field behavior observed experimentally...
2016: Scientific Reports
Todd Zorick, Jason Smith
Recent advances in neuroscience have raised the hypothesis that the underlying pattern of neuronal activation which results in electroencephalography (EEG) signals is via power-law distributed neuronal avalanches, while EEG signals are nonstationary. Therefore, spectral analysis of EEG may miss many properties inherent in such signals. A complete understanding of such dynamical systems requires knowledge of the underlying nonequilibrium thermodynamics. In recent work by Fielitz and Borchardt (2011, 2014), the concept of information equilibrium (IE) in information transfer processes has successfully characterized many different systems far from thermodynamic equilibrium...
2016: Computational and Mathematical Methods in Medicine
F Lombardi, H J Herrmann, D Plenz, L de Arcangelis
Ongoing cortical activity consists of sequences of synchronized bursts, named neuronal avalanches, whose size and duration are power law distributed. These features have been observed in a variety of systems and conditions, at all spatial scales, supporting scale invariance, universality and therefore criticality. However, the mechanisms leading to burst triggering, as well as the relationship between bursts and quiescence, are still unclear. The analysis of temporal correlations constitutes a major step towards a deeper understanding of burst dynamics...
April 20, 2016: Scientific Reports
Aleena Shaukat, Jean-Philippe Thivierge
Neural avalanches are a prominent form of brain activity characterized by network-wide bursts whose statistics follow a power-law distribution with a slope near 3/2. Recent work suggests that avalanches of different durations can be rescaled and thus collapsed together. This collapse mirrors work in statistical physics where it is proposed to form a signature of systems evolving in a critical state. However, no rigorous statistical test has been proposed to examine the degree to which neuronal avalanches collapse together...
2016: Frontiers in Computational Neuroscience
Tiago L Ribeiro, Sidarta Ribeiro, Mauro Copelli
Neuronal avalanches measured as consecutive bouts of thresholded field potentials represent a statistical signature that the brain operates near a critical point. In theory, criticality optimizes stimulus sensitivity, information transmission, computational capability and mnemonic repertoires size. Field potential avalanches recorded via multielectrode arrays from cortical slice cultures are repeatable spatiotemporal activity patterns. It remains unclear whether avalanches of action potentials observed in forebrain regions of freely-behaving rats also form recursive repertoires, and whether these have any behavioral relevance...
2016: Frontiers in Neural Circuits
Todd Zorick, Mark A Mandelkern
Electroencephalography (EEG) is typically viewed through the lens of spectral analysis. Recently, multiple lines of evidence have demonstrated that the underlying neuronal dynamics are characterized by scale-free avalanches. These results suggest that techniques from statistical physics may be used to analyze EEG signals. We utilized a publicly available database of fourteen subjects with waking and sleep stage 2 EEG tracings per subject, and observe that power-law dynamics of critical-state neuronal avalanches are not sufficient to fully describe essential features of EEG signals...
2015: Frontiers in Human Neuroscience
S Amin Moosavi, Afshin Montakhab
Critical dynamics of cortical neurons have been intensively studied over the past decade. Neuronal avalanches provide the main experimental as well as theoretical tools to consider criticality in such systems. Experimental studies show that critical neuronal avalanches show mean-field behavior. There are structural as well as recently proposed [Phys. Rev. E 89, 052139 (2014)] dynamical mechanisms that can lead to mean-field behavior. In this work we consider a simple model of neuronal dynamics based on threshold self-organized critical models with synaptic noise...
2015: Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
Eric S Kuebler, Joseph S Tauskela, Amy Aylsworth, Xigeng Zhao, Jean-Philippe Thivierge
Neuronal activity in vitro exhibits network bursts characterized by brief periods of increased spike rates. Recent work shows that a subpopulation of neurons reliably predicts the occurrence of network bursts. Here, we examined the role of burst predictors in cultures undergoing an in vitro model of cerebral ischemia. Dissociated primary cortical neurons were plated on multielectrode arrays and spontaneous activity was recorded at 17 days in vitro (DIV). This activity was characterized by neuronal avalanches where burst statistics followed a power law...
December 9, 2015: Scientific Reports
Oshrit Arviv, Abraham Goldstein, Oren Shriki
UNLABELLED: In recent years, numerous studies have found that the brain at resting state displays many features characteristic of a critical state. Here we examine whether stimulus-evoked activity can also be regarded as critical. Additionally, we investigate the relation between resting-state activity and stimulus-evoked activity from the perspective of criticality. We found that cortical activity measured by magnetoencephalography (MEG) is near critical and organizes as neuronal avalanches at both resting-state and stimulus-evoked activities...
October 14, 2015: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
Zalán Rajna, Janne Kananen, Anja Keskinarkaus, Tapio Seppänen, Vesa Kiviniemi
Recent studies pinpoint visually cued networks of avalanches with MEG/EEG data. Co-activation pattern (CAP) analysis can be used to detect single brain volume activity profiles and hemodynamic fingerprints of neuronal avalanches as sudden high signal activity peaks in classical fMRI data. In this study, we aimed to detect dynamic patterns of brain activity spreads with the use of ultrafast MR encephalography (MREG). MREG achieves 10 Hz whole brain sampling, allowing the estimation of spatial spread of an avalanche, even with the inherent hemodynamic delay of the BOLD signal...
2015: Frontiers in Human Neuroscience
Timothy Bellay, Andreas Klaus, Saurav Seshadri, Dietmar Plenz
Spontaneous fluctuations in neuronal activity emerge at many spatial and temporal scales in cortex. Population measures found these fluctuations to organize as scale-invariant neuronal avalanches, suggesting cortical dynamics to be critical. Macroscopic dynamics, though, depend on physiological states and are ambiguous as to their cellular composition, spatiotemporal origin, and contributions from synaptic input or action potential (AP) output. Here, we study spontaneous firing in pyramidal neurons (PNs) from rat superficial cortical layers in vivo and in vitro using 2-photon imaging...
2015: ELife
Alexander Zhigalov, Gabriele Arnulfo, Lino Nobili, Satu Palva, J Matias Palva
A growing body of evidence suggests that the neuronal dynamics are poised at criticality. Neuronal avalanches and long-range temporal correlations (LRTCs) are hallmarks of such critical dynamics in neuronal activity and occur at fast (subsecond) and slow (seconds to hours) timescales, respectively. The critical dynamics at different timescales can be characterized by their power-law scaling exponents. However, insight into the avalanche dynamics and LRTCs in the human brain has been largely obtained with sensor-level MEG and EEG recordings, which yield only limited anatomical insight and results confounded by signal mixing...
April 1, 2015: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
Erik D Fagerholm, Romy Lorenz, Gregory Scott, Martin Dinov, Peter J Hellyer, Nazanin Mirzaei, Clare Leeson, David W Carmichael, David J Sharp, Woodrow L Shew, Robert Leech
The analysis of neuronal avalanches supports the hypothesis that the human cortex operates with critical neural dynamics. Here, we investigate the relationship between cascades of activity in electroencephalogram data, cognitive state, and reaction time in humans using a multimodal approach. We recruited 18 healthy volunteers for the acquisition of simultaneous electroencephalogram and functional magnetic resonance imaging during both rest and during a visuomotor cognitive task. We compared distributions of electroencephalogram-derived cascades to reference power laws for task and rest conditions...
March 18, 2015: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
Timothée Leleu, Kazuyuki Aihara
A robust method for inferring the structure of networks is presented based on the one-to-one correspondence between the expected composition of cascades of bursts of activity, called crackling noise or avalanches, and the weight matrix. Using a model of neuronal avalanches as a paradigmatic example, we derive this correspondence exactly by calculating the closed-form expression of the joint probability distribution of avalanche sizes obtained by counting separately the number of elements active in each subnetwork during avalanches...
February 2015: Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
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