Compartment-cluster modeling of uncertainties according to determinism

10.12737/5520 ◽  
2014 ◽  
Vol 3 (2) ◽  
pp. 68-80
Author(s):  
Бурыкин ◽  
Yu. Burykin ◽  
Даянова ◽  
D. Dayanova ◽  
Козупица ◽  
...  
Keyword(s):  
Experimental Data ◽  
Chaotic Dynamics ◽  
Self Organization ◽  
Test Model ◽  
Dynamics Modeling ◽  
Cluster Modeling ◽  
Global Challenges ◽  
Human Movements ◽  
The Neural Networks ◽  
The Brain

Transition from determinism to stochastic sand further to chaos (self-organization) in the study of biomechanical systems leads to the problem of chaotic dynamics modeling of a post- ural tremor. In general, there is a problem of identifying the voluntary human movements. In other words biophysics of complex systems has approached the global challenges of voluntary and involuntary performance of any motor functions. The possibility of modeling these processes qualitatively and quantitativelyisdiscussed. Specific models demonstrate the effectiveness of the compartment-cluster modeling of biosystems and possibilities of controlof such models from the neural networks of the brain. Comparative analysis of the simulated and real recorded signals has shown a high consistent dynamics of simulated and real signals of complex biological systems. In particular, changes in tremor parameters can be described by the change in quasi-attractors which essentially depend on the mental state of a person. In experiments it is shown in the form of sight effects, which are considered in the report as a test model on experimental data.

scholarly journals Simulation of Human Limb Movement

2020 ◽  
pp. 32-43
Author(s):  
Dmitriy Gorbunov
Keyword(s):  
Experimental Data ◽  
Simulation Model ◽  
Chaotic Dynamics ◽  
Random Number Generation ◽  
Mathematical Statistics ◽  
Self Organization ◽  
Mathematical Form ◽  
Model Data ◽  
Initial State ◽  
Complex Biosystems

Simulation of any processes is based on some laws that take place inside the simulated object and outside it (changing the environment in which the object is located). In the study of complex biosystems, the identification of patterns is complicated by the fact that such systems have a chaotic structure. In such systems, it is impossible to arbitrarily repeat the initial state xi, any intermediate xn and final xk. Simulation of complex biosystems should be based on random patterns. The created simulation model works based on the random number generation. There are no static values in the model. The inclusion of regulatory mechanisms of the model is based on the search of F-solutions. Chaotic dynamics of changes in the trajectory of a person's limb is established based on experimental data. In accordance with this, in the simulation model, the level of limb retention in space changes its direction by random images in real time. In the framework of the above patterns, a mathematical model of the interaction of muscle bundles was developed to solve the problem of holding the limb in space. When analyzing the performance of the simulation model, the basis of the evaluation measure was taken. The results were obtained on the basis of mathematical statistics and the calculation of the quasiattractor parameters in the framework of the theory of chaos and self-organization. As a result, the correspondence of experimental and model data was established. In the framework of mathematical statistics, when constructing matrices of paired comparisons for experimental data, the number of pairs of matches (the word "matches" refers to the possibility of assigning the compared pairs of samples to one general set) is k = 11 %. The same number of coincidence pairs in percentage terms was established when comparing model data and model with experimental data. In the framework of the theory of chaos and self-organization, the quasiattractor parameters coincide in their area and visual assessment of phase planes. As a result of the research, high accuracy of the model is established, which is ensured by some chaotic dynamics of the model with chaotic selfregulation mechanisms. There are no constants in the mathematical form of the simulation model, which ensures the reproduction of N.A. Bernstein "repetition without repetition" hypothesis, which has been proven for experimental data. For theoretical biophysics, the constructed simulation model is able to provide understanding of the neuromuscular system functioning, as well as, with some complication and expansion of the algorithm, the central nervous system.

scholarly journals Imaging Implicit Morphological Processing: Evidence from Hebrew

2010 ◽  
Vol 22 (9) ◽  
pp. 1955-1969 ◽  
Author(s):  
Atira S. Bick ◽  
Ram Frost ◽  
Gadi Goelman
Keyword(s):  
Masked Priming ◽  
Statistical Correlation ◽  
Morphological Processing ◽  
Fine Tuning ◽  
Semantic Transparency ◽  
Lexical Structure ◽  
The Neural Networks ◽  
Distinct Aspect ◽  
The Brain

Is morphology a discrete and independent element of lexical structure or does it simply reflect a fine-tuning of the system to the statistical correlation that exists among orthographic and semantic properties of words? Hebrew provides a unique opportunity to examine morphological processing in the brain because of its rich morphological system. In an fMRI masked priming experiment, we investigated the neural networks involved in implicit morphological processing in Hebrew. In the lMFG and lIFG, activation was found to be significantly reduced when the primes were morphologically related to the targets. This effect was not influenced by the semantic transparency of the morphological prime, and was not found in the semantic or orthographic condition. Additional morphologically related decrease in activation was found in the lIPL, where activation was significantly modulated by semantic transparency. Our findings regarding implicit morphological processing suggest that morphology is an automatic and distinct aspect of visually processing words. These results also coincide with the behavioral data previously obtained demonstrating the central role of morphological processing in reading Hebrew.

scholarly journals A computational framework for finding parameter sets associated with chaotic dynamics

2021 ◽  
pp. 1-11
Author(s):  
S. Koshy-Chenthittayil ◽  
E. Dimitrova ◽  
E.W. Jenkins ◽  
B.C. Dean
Keyword(s):  
Experimental Data ◽  
Dynamical Systems ◽  
Lyapunov Exponents ◽  
Parameter Space ◽  
Chaotic Dynamics ◽  
Chaotic Behavior ◽  
Computational Framework ◽  
Independent Variables ◽  
Systems Model ◽  
Small Support

Many biological ecosystems exhibit chaotic behavior, demonstrated either analytically using parameter choices in an associated dynamical systems model or empirically through analysis of experimental data. In this paper, we use existing software tools (COPASI, R) to explore dynamical systems and uncover regions with positive Lyapunov exponents where thus chaos exists. We evaluate the ability of the software’s optimization algorithms to find these positive values with several dynamical systems used to model biological populations. The algorithms have been able to identify parameter sets which lead to positive Lyapunov exponents, even when those exponents lie in regions with small support. For one of the examined systems, we observed that positive Lyapunov exponents were not uncovered when executing a search over the parameter space with small spacings between values of the independent variables.

COVID-19 Beyond the Lungs

2022 ◽  
pp. 109-126
Author(s):  
Omar El Hiba ◽  
Hicham Chatoui ◽  
Nadia Zouhairi ◽  
Lahoucine Bahi ◽  
Lhoussaine Ammouta ◽  
...  
Keyword(s):  
Experimental Data ◽  
Nervous System ◽  
Clinical Symptoms ◽  
Case Reports ◽  
The World ◽  
Acute Pneumonia ◽  
The Brain ◽  
Cardinal Feature ◽  
Shed Light

Since December 2019, the world has been shaken by the spread of a highly pathogen virus, causing severe acute respiratory syndrome (SARS-Cov2), which emerged in Wuhan, China. SARS-Cov2 is known to cause acute pneumonia: the cardinal feature of coronavirus disease 2019 (COVID-19). Clinical features of the disease include respiratory distress, loss of spontaneous breathing, and sometimes neurologic signs such as headache and nausea and anosmia, leading to suppose a possible involvement of the nervous system as a potential target of SARS-CoV2. The chapter will shed light on the recent clinical and experimental data sustaining the involvement of the nervous system in the pathophysiology of COVID-19, based on several case reports and experimental data reporting the possible transmission of SARS-CoV2 throughout the peripheral nerves to the brain cardiorespiratory centers. Thus, understanding the role of the nervous system in the course of clinical symptoms of COVID-19 is important in determining the appropriate therapeutic approach to combat the disease.

Neuro-occupation: A self-organizing approach to conflate the brain, context, and occupation

2019 ◽  
Vol 87 (1) ◽  
pp. 12-20
Author(s):  
Seyed Alireza Derakhshanrad ◽  
Emily Piven
Keyword(s):  
Occupational Therapists ◽  
The Self ◽  
Self Organization ◽  
Theoretical Assumptions ◽  
Qualitative Descriptive ◽  
Occupational Participation ◽  
Circular Causality ◽  
Matrix Construction ◽  
The Brain ◽  
Descriptive Method

Background. Neuro-occupation was coined to conflate three distinctly different concepts: the brain, context, and occupation. Discussing neuro-occupation has been more of an academic exercise rather than cogently researched for everyday practice, perhaps due to the seemingly incongruity among the concepts. Purpose. This article traces the self-organization approach, an assumption of complex systems, to understand how the concepts can be conflated. Method. Deductive category application, a qualitative descriptive method for tracing theoretical assumptions, was drawn from the lived experiences of 11 Iranian participants with cerebrovascular accidents. Matrix construction aided collection of data for analysis. Findings. The self-organization approach, underpinning neuro-occupation, was shown to be traceable, explaining how occupational participation may be influenced by the brain circular causality and perturbations provided by the context. Implications. By understanding the dynamics of self-organization, occupational therapists can identify and create salient features that may motivate and enable clients to enhance occupational participation.

An Electronic Model of a Neural Correlate to Experience Obtained When the Stimulus Object is a Straight Line or a Circle

1967 ◽  
Vol 25 (1) ◽  
pp. 189-202 ◽  
Author(s):  
Kristian Holt-Hansen
Keyword(s):  
Experimental Data ◽  
Brain Function ◽  
Stimulus Object ◽  
The Other ◽  
Neural Correlate ◽  
Close Analogy ◽  
Straight Line ◽  
Electronic Model ◽  
Close Relationship ◽  
The Brain

An attempt was made to present an electronic model of the neural correlate to the experiences of straightness and circularity on the basis of experimental data. Two sets of experiments were described. In one Ss had numerous kinds of experience when the stimulus object was a straight line or a circle. These experiments demonstrated a close relationship between a straight line and a circle in experience. The other set of experiments consisted of adjusting the electric voltages fed into a cathode ray oscilloscope so that the displays on the screen corresponded closely to some of the experiences reported by subjects in the first set of experiments. A plausible working hypothesis was put forward on the basis that the electronic functions underlying the working of a cathode ray oscilloscope suggest a close analogy with the brain function underlying the experiences obtained when the stimulus object is a straight line or a circle.

Finite Element Analysis of Brain Injury due to Head Impact

2003 ◽  
Vol 17 (08n09) ◽  
pp. 1355-1361
Author(s):  
Chang Min Suh ◽  
Sung Ho Kim ◽  
Werner Goldsmith
Keyword(s):  
Experimental Data ◽  
Finite Element ◽  
Brain Injury ◽  
Head Impact ◽  
Stress And Strain ◽  
Resonance Imaging ◽  
Element Analysis ◽  
External Impact ◽  
Magnetic Resonance Imaging Mri ◽  
The Brain

Traumatic Brain Injury (TBI) due to head impact by external impactor was analyzed using Finite Element Method (FEM). Two-dimensiona modeling was performed according to Magnetic Resonance Imaging (MRI) data of Mongolian subject. Pressure variation in a cranium due to external impact was analyzed in order to simulate Nahum et al.'s cadaver test.6 And, analyzed results were compared with Nahum et al.'s experimental data.6 As results, stress and strain behaviors of the brain during impact were accorded with experimental data qualitatively even though there were some differences in quantitative values. In addition, they were accorded with other references about brain injury as well.

Looking into a Deluded Brain through a Neuroimaging Lens

2020 ◽  
pp. 107385842093617
Author(s):  
Shokouh Arjmand ◽  
Kristi A. Kohlmeier ◽  
Mina Behzadi ◽  
Mehran Ilaghi ◽  
Shahrzad Mazhari ◽  
...  
Keyword(s):  
Neural Networks ◽  
Parkinson’S Disease ◽  
Animal Models ◽  
Cognitive Modeling ◽  
Human Experience ◽  
Common Symptom ◽  
Brain Disorders ◽  
False Beliefs ◽  
The Neural Networks ◽  
The Brain

Delusions are irrational, tenacious, and incorrigible false beliefs that are the most common symptom of a range of brain disorders including schizophrenia, Alzheimer’s, and Parkinson’s disease. In the case of schizophrenia and other primary delusional disorders, their appearance is often how the disorder is first detected and can be sufficient for diagnosis. At this time, not much is known about the brain dysfunctions leading to delusions, and hindering our understanding is that the complexity of the nature of delusions, and their very unique relevance to the human experience has hampered elucidation of their underlying neurobiology using either patients or animal models. Advances in neuroimaging along with improved psychiatric and cognitive modeling offers us a new opportunity to look with more investigative power into the deluded brain. In this article, based on data obtained from neuroimaging studies, we have attempted to draw a picture of the neural networks involved when delusion is present and evaluate whether different manifestations of delusions engage different regions of the brain.

scholarly journals Self-Organization of Motor-Propelled Cytoskeletal Filaments at Topographically Defined Borders

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Alf Månsson ◽  
Richard Bunk ◽  
Mark Sundberg ◽  
Lars Montelius
Keyword(s):  
Molecular Motor ◽  
Direct Consequence ◽  
Self Organization ◽  
Test Model ◽  
Structured Surfaces ◽  
Microstructured Surfaces ◽  
Living Organisms ◽  
Edge Tracing ◽  
Motor Density

Self-organization phenomena are of critical importance in living organisms and of great interest to exploit in nanotechnology. Here we describe in vitro self-organization of molecular motor-propelled actin filaments, manifested as a tendency of the filaments to accumulate in high density close to topographically defined edges on nano- and microstructured surfaces. We hypothesized that this “edge-tracing” effect either (1) results from increased motor density along the guiding edges or (2) is a direct consequence of the asymmetric constraints on stochastic changes in filament sliding direction imposed by the edges. The latter hypothesis is well captured by a model explicitly defining the constraints of motility on structured surfaces in combination with Monte-Carlo simulations [cf. Nitta et al. (2006)] of filament sliding. In support of hypothesis 2 we found that the model reproduced the edge tracing effect without the need to assume increased motor density at the edges. We then used model simulations to elucidate mechanistic details. The results are discussed in relation to nanotechnological applications and future experiments to test model predictions.

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