scholarly journals Stochastic Oscillation in Self-Organized Critical States of Small Systems: Sensitive Resting State in Neural Systems

2016 ◽  
Vol 116 (1) ◽  
Author(s):  
Sheng-Jun Wang ◽  
Guang Ouyang ◽  
Jing Guang ◽  
Mingsha Zhang ◽  
K. Y. Michael Wong ◽  
...  
2003 ◽  
Vol 4 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Raymond W. Gibbs ◽  
Guy Van Orden

This paper discusses the debate over whether emotional expressions are spontaneous or intentional actions. We describe a variety of empirical evidence supporting these two possibilities. But we argue that the spontaneous-intentional distinction fails to explain the psychological dynamics of emotional expressions. We claim that a complex systems perspective on intentions, as self-organized critical states, may yield a unified view of emotional expressions as a consequence of situated action. This account simultaneously acknowledges the embodied status of environment, evolution, culture and mind in theories of emotion.


2014 ◽  
Vol 14 (03) ◽  
pp. 1450001 ◽  
Author(s):  
Anna Levina ◽  
J. Michael Herrmann

We define the Abelian distribution and study its basic properties. Abelian distributions arise in the context of neural modeling and describe the size of neural avalanches in fully-connected integrate-and-fire models of self-organized criticality in neural systems.


Fractals ◽  
2009 ◽  
Vol 17 (02) ◽  
pp. 227-232
Author(s):  
LIUJUN CHEN ◽  
WEITING CHEN ◽  
ZENGRU DI ◽  
DAHUI WANG

The behavior of sandpile far from self-organized critical states (SOCS) is investigated in this paper. The results indicate that noise plays an important role in the critical phenomenon. The critical phenomena are detected in sandpile far from SOCS when external or internal noise is applied. In contrast to self-organized criticality, the exponent of avalanche distribution in sandpile far from SOCS increases with the distance of the sandpile from SOCS. At the same time, the exponent of avalanche distribution in a sandpile far from SOCS is consistent with some real systems such as earthquake.


2015 ◽  
Vol 114 (1) ◽  
pp. 677-688 ◽  
Author(s):  
Heather R. McGregor ◽  
Paul L. Gribble

Motor learning occurs not only through direct first-hand experience but also through observation (Mattar AA, Gribble PL. Neuron 46: 153–160, 2005). When observing the actions of others, we activate many of the same brain regions involved in performing those actions ourselves (Malfait N, Valyear KF, Culham JC, Anton JL, Brown LE, Gribble PL. J Cogn Neurosci 22: 1493–1503, 2010). Links between neural systems for vision and action have been reported in neurophysiological (Strafella AP, Paus T. Neuroreport 11: 2289–2292, 2000; Watkins KE, Strafella AP, Paus T. Neuropsychologia 41: 989–994, 2003), brain imaging (Buccino G, Binkofski F, Fink GR, Fadiga L, Fogassi L, Gallese V, Seitz RJ, Zilles K, Rizzolatti G, Freund HJ. Eur J Neurosci 13: 400–404, 2001; Iacoboni M, Woods RP, Brass M, Bekkering H, Mazziotta JC, Rizzolatti G. Science 286: 2526–2528, 1999), and eye tracking (Flanagan JR, Johansson RS. Nature 424: 769–771, 2003) studies. Here we used a force field learning paradigm coupled with resting-state fMRI to investigate the brain areas involved in motor learning by observing. We examined changes in resting-state functional connectivity (FC) after an observational learning task and found a network consisting of V5/MT, cerebellum, and primary motor and somatosensory cortices in which changes in FC were correlated with the amount of motor learning achieved through observation, as assessed behaviorally after resting-state fMRI scans. The observed FC changes in this network are not due to visual attention to motion or observation of movement errors but rather are specifically linked to motor learning. These results support the idea that brain networks linking action observation and motor control also facilitate motor learning.


Biomedicines ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 82
Author(s):  
Junhyung Kim ◽  
Yong-Ku Kim

Alzheimer’s disease (AD) is the most common type of dementia, and depression is a risk factor for developing AD. Epidemiological studies provide a clinical correlation between late-life depression (LLD) and AD. Depression patients generally remit with no residual symptoms, but LLD patients demonstrate residual cognitive impairment. Due to the lack of effective treatments, understanding how risk factors affect the course of AD is essential to manage AD. Advances in neuroimaging, including resting-state functional MRI (fMRI), have been used to address neural systems that contribute to clinical symptoms and functional changes across various psychiatric disorders. Resting-state fMRI studies have contributed to understanding each of the two diseases, but the link between LLD and AD has not been fully elucidated. This review focuses on three crucial and well-established networks in AD and LLD and discusses the impacts on cognitive decline, clinical symptoms, and prognosis. Three networks are the (1) default mode network, (2) executive control network, and (3) salience network. The multiple properties emphasized here, relevant for the hypothesis of the linkage between LLD and AD, will be further developed by ongoing future studies.


2018 ◽  
Author(s):  
Masa Tsuchiya ◽  
Alessandro Giuliani ◽  
Kenichi Yoshikawa

AbstractIn our current studies on whole genome expression in several biological processes, we have demonstrated the actual existence of self-organized critical control (SOC) of gene expression at both population and single cell level. SOC allows for cell-fate change by critical transition encompassing the entire genome expression that, in turn, is partitioned into distinct response domains (critical states).In this paper, we go more in depth into the elucidation of SOC control of genome expression focusing on the determination of critical point (CP) and associated distinct critical states in single-cell genome expression. This leads us to the proposal of a potential universal model with genome-engine mechanism for cell-fate change. Our findings suggest that the CP is fixed point in terms of temporal expression variance, where the CP (set of critical genes) becomes active (ON) for cell-fate change (‘super-critical’ in genome-state) or else inactive (OFF) state (‘sub-critical’ in genome-state); this may lead to a novel scenario of the cell-fate control through activating or inactivating CP.


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