scholarly journals The Banach-Tarski Paradox Dictates Snyergistic Routes for Scale-Free Neurodynamics

2020 ◽  
Author(s):  
Arturo Tozzi ◽  
James F. Peters
Keyword(s):  
Information Transfer ◽  
Neural Dynamics ◽  
Free Oscillations ◽  
Scale Invariant ◽  
Brain Areas ◽  
Scale Free ◽  
Cortical Oscillations ◽  
The Central Nervous System ◽  
Self Similar ◽  
Physical Changes

Neuroscientists are able to detect physical changes in information entropy in available neurodata. However, the information paradigm is inadequate to fully describe nervous dynamics and mental activities such as perception. This paper provides an effort to build explanations to neural dynamics alternative to thermodynamic and information accounts. We recall the Banach–Tarski paradox (BTP), which informally states that, when pieces of a ball are moved and rotated without changing their shape, a synergy between two balls of the same volume is achieved instead of the original one. We show how and why BTP might display this physical and biological synergy meaningfully, making it possible to tackle nervous activities. The anatomical and functional structure of the central nervous system’s nodes and edges allows to perform a sequence of moves inside the connectome that doubles the amount of available cortical oscillations. In particular, a BTP-based mechanism permits scale-invariant nervous oscillations to amplify and propagate towards far apart brain areas. Paraphrasing the BPT’s definition, we could state that: when a few components of a self-similar nervous oscillation are moved and rotated throughout the cortical connectome, two self-similar oscillations are achieved instead of the original one. Furthermore, based on topological structures, we illustrate how, counterintuitively, the amplification of scale-free oscillations does not require information transfer.

Neuropeptides in Alzheimer’s Disease: An Update

2019 ◽  
Vol 16 (6) ◽  
pp. 544-558 ◽  
Author(s):  
Carla Petrella ◽  
Maria Grazia Di Certo ◽  
Christian Barbato ◽  
Francesca Gabanella ◽  
Massimo Ralli ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Animal Models ◽  
Potential Role ◽  
Brain Distribution ◽  
Brain Areas ◽  
Small Proteins ◽  
Current Review ◽  
The Central Nervous System ◽  
Available Information

Neuropeptides are small proteins broadly expressed throughout the central nervous system, which act as neurotransmitters, neuromodulators and neuroregulators. Growing evidence has demonstrated the involvement of many neuropeptides in both neurophysiological functions and neuropathological conditions, among which is Alzheimer’s disease (AD). The role exerted by neuropeptides in AD is endorsed by the evidence that they are mainly neuroprotective and widely distributed in brain areas responsible for learning and memory processes. Confirming this point, it has been demonstrated that numerous neuropeptide-containing neurons are pathologically altered in brain areas of both AD patients and AD animal models. Furthermore, the levels of various neuropeptides have been found altered in both Cerebrospinal Fluid (CSF) and blood of AD patients, getting insights into their potential role in the pathophysiology of AD and offering the possibility to identify novel additional biomarkers for this pathology. We summarized the available information about brain distribution, neuroprotective and cognitive functions of some neuropeptides involved in AD. The main focus of the current review was directed towards the description of clinical data reporting alterations in neuropeptides content in both AD patients and AD pre-clinical animal models. In particular, we explored the involvement in the AD of Thyrotropin-Releasing Hormone (TRH), Cocaine- and Amphetamine-Regulated Transcript (CART), Cholecystokinin (CCK), bradykinin and chromogranin/secretogranin family, discussing their potential role as a biomarker or therapeutic target, leaving the dissertation of other neuropeptides to previous reviews.

scholarly journals Limbic Expression of mRNA Coding for Chemoreceptors in Human Brain—Lessons from Brain Atlases

2021 ◽  
Vol 22 (13) ◽  
pp. 6858
Author(s):  
Fanny Gaudel ◽  
Gaëlle Guiraudie-Capraz ◽  
François Féron
Keyword(s):  
G Proteins ◽  
The Body ◽  
Trace Amines ◽  
Chemical Senses ◽  
Brain Areas ◽  
Genes Encoding ◽  
The Central Nervous System ◽  
Human Brains ◽  
The Brain ◽  
Brain Atlases

Animals strongly rely on chemical senses to uncover the outside world and adjust their behaviour. Chemical signals are perceived by facial sensitive chemosensors that can be clustered into three families, namely the gustatory (TASR), olfactory (OR, TAAR) and pheromonal (VNR, FPR) receptors. Over recent decades, chemoreceptors were identified in non-facial parts of the body, including the brain. In order to map chemoreceptors within the encephalon, we performed a study based on four brain atlases. The transcript expression of selected members of the three chemoreceptor families and their canonical partners was analysed in major areas of healthy and demented human brains. Genes encoding all studied chemoreceptors are transcribed in the central nervous system, particularly in the limbic system. RNA of their canonical transduction partners (G proteins, ion channels) are also observed in all studied brain areas, reinforcing the suggestion that cerebral chemoreceptors are functional. In addition, we noticed that: (i) bitterness-associated receptors display an enriched expression, (ii) the brain is equipped to sense trace amines and pheromonal cues and (iii) chemoreceptor RNA expression varies with age, but not dementia or brain trauma. Extensive studies are now required to further understand how the brain makes sense of endogenous chemicals.

scholarly journals Evidence for a pervasive ‘idling-mode’ activity template in flying and pedestrian insects

2015 ◽  
Vol 2 (5) ◽  
pp. 150085 ◽  
Author(s):  
Andrew M. Reynolds ◽  
Hayley B. C. Jones ◽  
Jane K. Hill ◽  
Aislinn J. Pearson ◽  
Kenneth Wilson ◽  
...  
Keyword(s):  
Activity Patterns ◽  
Movement Ecology ◽  
Movement Patterns ◽  
Environmental Cues ◽  
Natural Environments ◽  
Scale Invariant ◽  
Scale Free ◽  
Flight Mills ◽  
Innate Behaviour ◽  
Multiple Species

Understanding the complex movement patterns of animals in natural environments is a key objective of ‘movement ecology’. Complexity results from behavioural responses to external stimuli but can also arise spontaneously in their absence. Drawing on theoretical arguments about decision-making circuitry, we predict that the spontaneous patterns will be scale-free and universal, being independent of taxon and mode of locomotion. To test this hypothesis, we examined the activity patterns of the European honeybee, and multiple species of noctuid moth, tethered to flight mills and exposed to minimal external cues. We also reanalysed pre-existing data for Drosophila flies walking in featureless environments. Across these species, we found evidence of common scale-invariant properties in their movement patterns; pause and movement durations were typically power law distributed over a range of scales and characterized by exponents close to 3/2. Our analyses are suggestive of the presence of a pervasive scale-invariant template for locomotion which, when acted on by environmental cues, produces the movements with characteristic scales observed in nature. Our results indicate that scale-finite complexity as embodied, for instance, in correlated random walk models, may be the result of environmental cues overriding innate behaviour, and that scale-free movements may be intrinsic and not limited to ‘blind’ foragers as previously thought.

SMALL-WORLD AND SCALE-FREE PROPERTIES OF FRACTAL NETWORKS MODELED ON n-DIMENSIONAL SIERPINSKI PYRAMID

Fractals ◽  
2017 ◽  
Vol 25 (06) ◽  
pp. 1750057 ◽  
Author(s):  
CHENG ZENG ◽  
MENG ZHOU
Keyword(s):  
Small World ◽  
The Self ◽  
Scale Free ◽  
Evolving Networks ◽  
Self Similar

In this paper, we construct evolving networks based on the construction of the [Formula: see text]-dimensional Sierpinski pyramid by the self-similar structure. We show that such networks have scale-free and small-world effects.

scholarly journals Elucidating the Neuropathologic Mechanisms of SARS-CoV-2 Infection

2021 ◽  
Vol 12 ◽  
Author(s):  
Mar Pacheco-Herrero ◽  
Luis O. Soto-Rojas ◽  
Charles R. Harrington ◽  
Yazmin M. Flores-Martinez ◽  
Marcos M. Villegas-Rojas ◽  
...  
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Molecular Mechanisms ◽  
Cell Types ◽  
Public Health Emergency ◽  
Converting Enzyme ◽  
Neurological Manifestations ◽  
Brain Areas ◽  
Angiotensin Converting Enzyme 2 ◽  
The Central Nervous System

The current pandemic caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a public health emergency. To date, March 1, 2021, coronavirus disease 2019 (COVID-19) has caused about 114 million accumulated cases and 2.53 million deaths worldwide. Previous pieces of evidence suggest that SARS-CoV-2 may affect the central nervous system (CNS) and cause neurological symptoms in COVID-19 patients. It is also known that angiotensin-converting enzyme-2 (ACE2), the primary receptor for SARS-CoV-2 infection, is expressed in different brain areas and cell types. Thus, it is hypothesized that infection by this virus could generate or exacerbate neuropathological alterations. However, the molecular mechanisms that link COVID-19 disease and nerve damage are unclear. In this review, we describe the routes of SARS-CoV-2 invasion into the central nervous system. We also analyze the neuropathologic mechanisms underlying this viral infection, and their potential relationship with the neurological manifestations described in patients with COVID-19, and the appearance or exacerbation of some neurodegenerative diseases.

scholarly journals Fractal fluctuations in the cardiovascular dynamical system : from the autonomic control to the central nervous system influence

2021 ◽  
Author(s):  
Asif Hasan Sharif
Keyword(s):  
Central Nervous System ◽  
Heart Rate ◽  
Nervous System ◽  
Autonomic Nervous System ◽  
Dynamic Feature ◽  
Scale Free ◽  
Autonomic Nervous ◽  
Factorization Technique ◽  
The Central Nervous System

The fractal component in the complex fluctuations of the human heart rate represents a dynamic feature that is widely observed in diverse fields of natural and artificial systems. It is also of clinical significance as the diminishing of the fractal dynamics appears to correlate with heart disease processes and adverse cardiac events in old age. While the autonomic nervous system directly controls the pacemaker cells of the heart, it does not provide an immediate characterization of the complex heart rate variability (HRV). The central nervous system (CNS) is known to be an important modulator for various cardiac functions. However, its role in the fractal HRV is largely unclear. In this research, human experiments were conducted to study the influence of the central nervous system on fractal dynamics of healthy human HRV. The head up tilt (HUT) maneuver is used to provide a perturbation to the autonomic nervous system. The subsequent fractal effect in the simultaneously recorded electroencephalography and beat-to-beat heart rate data was examined. Using the recently developed multifractal factorization technique, the common multifractality in the data fluctuation was analyzed. An empirical relationship was uncovered which shows the increase (decrease) in HRV multifractality is associated with the increase (decrease) in multifractal correlation between scale-free HRV and the cortical expression of the brain dynamics in 8 out of 11 healthy subjects. This observation is further supported using surrogate analysis. The present findings imply that there is an integrated central-autonomic component underlying the cortical expression of the HRV fractal dynamics. It is proposed that the central element should be incorporated in the fractal HRV analysis to gain a more comprehensive and better characterization of the scale-free HRV dynamics. This study provides the first contribution to the HRV multifractal dynamics analysis in HUT. The multivariate fractal analysis using factorization technique is also new and can be applied in the more general context in complex dynamics research.

scholarly journals On the fractal nature of complex syntax and the timescale problem

2020 ◽  
Vol 10 (4) ◽  
pp. 697-721
Author(s):  
D. Reid Evans
Keyword(s):  
Complex Systems ◽  
Dynamic Systems Theory ◽  
Self Similarity ◽  
Scale Invariant ◽  
Complex Dynamic Systems ◽  
Complex Syntax ◽  
Dynamic Relationship ◽  
Self Similar ◽  
Multiple Component ◽  
Dynamic Relationships

Fundamental to complex dynamic systems theory is the assumption that the recursive behavior of complex systems results in the generation of physical forms and dynamic processes that are self-similar and scale-invariant. Such fractal-like structures and the organismic benefit that they engender has been widely noted in physiology, biology, and medicine, yet discussions of the fractal-like nature of language have remained at the level of metaphor in applied linguistics. Motivated by the lack of empirical evidence supporting this assumption, the present study examines the extent to which the use and development of complex syntax in a learner of English as a second language demonstrate the characteristics of self-similarity and scale invariance at nested timescales. Findings suggest that the use and development of syntactic complexity are governed by fractal scaling as the dynamic relationship among the subconstructs of syntax maintain their complexity and variability across multiple temporal scales. Overall, fractal analysis appears to be a fruitful analytic tool when attempting to discern the dynamic relationships among the multiple component parts of complex systems as they interact over time.

scholarly journals Vesicular Transport of Encapsulated microRNA between Glial and Neuronal Cells

2020 ◽  
Vol 21 (14) ◽  
pp. 5078 ◽  
Author(s):  
Walter J. Lukiw ◽  
Aileen I. Pogue
Keyword(s):  
Information Transfer ◽  
Biological Information ◽  
Messenger Rnas ◽  
Innate Immune Signaling ◽  
Cells Of Origin ◽  
Metabolic Products ◽  
Inflammatory Phenotype ◽  
The Central Nervous System ◽  
Neuro Inflammation ◽  
End Stage

Exosomes (EXs) and extracellular microvesicles (EMVs) represent a diverse assortment of plasma membrane-derived nanovesicles, 30–1000 nm in diameter, released by all cell lineages of the central nervous system (CNS). They are examples of a very active and dynamic form of extracellular communication and the conveyance of biological information transfer essential to maintain homeostatic neurological functions and contain complex molecular cargoes representative of the cytoplasm of their cells of origin. These molecular cargoes include various mixtures of proteins, lipids, proteolipids, cytokines, chemokines, carbohydrates, microRNAs (miRNA) and messenger RNAs (mRNA) and other components, including end-stage neurotoxic and pathogenic metabolic products, such as amyloid beta (Aβ) peptides. Brain microglia, for example, respond to both acute CNS injuries and degenerative diseases with complex reactions via the induction of a pro-inflammatory phenotype, and secrete EXs and EMVs enriched in selective pathogenic microRNAs (miRNAs) such as miRNA-34a, miRNA-125b, miRNA-146a, miRNA-155, and others that are known to promote neuro-inflammation, induce complement activation, disrupt innate–immune signaling and deregulate the expression of neuron-specific phosphoproteins involved in neurotropism and synaptic signaling. This communication will review our current understanding of the trafficking of miRNA-containing EXs and EMVs from astrocytes and “activated pro-inflammatory” microglia to target neurons in neurodegenerative diseases with an emphasis on Alzheimer’s disease wherever possible.

scholarly journals Scale-free, programmable design of morphable chain loops of kilobots and colloidal motors

2020 ◽  
Vol 117 (16) ◽  
pp. 8700-8710
Author(s):  
Mayank Agrawal ◽  
Sharon C. Glotzer
Keyword(s):  
Brownian Dynamics ◽  
Colloidal Particles ◽  
Autonomous Robots ◽  
Design Strategy ◽  
Dynamics Simulation ◽  
Design Parameters ◽  
Brownian Dynamics Simulation ◽  
Scale Invariant ◽  
Scale Free ◽  
Mechanical Constraints

Micron-scale robots require systems that can morph into arbitrary target configurations controlled by external agents such as heat, light, electricity, and chemical environment. Achieving this behavior using conventional approaches is challenging because the available materials at these scales are not programmable like their macroscopic counterparts. To overcome this challenge, we propose a design strategy to make a robotic machine that is both programmable and compatible with colloidal-scale physics. Our strategy uses motors in the form of active colloidal particles that constantly propel forward. We sequence these motors end-to-end in a closed chain forming a two-dimensional loop that folds under its mechanical constraints. We encode the target loop shape and its motion by regulating six design parameters, each scale-invariant and achievable at the colloidal scale. We demonstrate the plausibility of our design strategy using centimeter-scale robots called kilobots. We use Brownian dynamics simulation to explore the large design space beyond that possible with kilobots, and present an analytical theory to aid the design process. Multiple loops can also be fused together to achieve several complex shapes and robotic behaviors, demonstrated by folding a letter shape “M,” a dynamic gripper, and a dynamic pacman. The material-agnostic, scale-free, and programmable nature of our design enables building a variety of reconfigurable and autonomous robots at both colloidal scales and macroscales.

Application of Fractal Geometry to Fracture Forensics, Research and Production

2006 ◽  
Vol 45 ◽  
pp. 1646-1651 ◽  
Author(s):  
J.J. Mecholsky Jr.
Keyword(s):  
Fractal Analysis ◽  
Fractal Geometry ◽  
Crack Size ◽  
Structural Parameter ◽  
New Materials ◽  
Scale Invariant ◽  
Prepared Material ◽  
Reasonable Approach ◽  
Self Similar ◽  
Production Problems

The fracture surface records past events that occur during the fracture process by leaving characteristic markings. The application of fractal geometry aids in the interpretation and understanding of these events. Quantitative fractographic analysis of brittle fracture surfaces shows that these characteristic markings are self-similar and scale invariant, thus implying that fractal analysis is a reasonable approach to analyzing these surfaces. The fractal dimensional increment, D*, is directly proportional to the fracture energy, γ, during fracture for many brittle materials, i.e., γ = ½ E a0 D* where E is the elastic modulus and a0 is a structural parameter. Also, D* is equal to the crack-size-to-mirror-radius ratio. Using this information can aid in identifying toughening mechanisms in new materials, distinguishing poorly fabricated from well prepared material and identifying stress at fracture for field failures. Examples of the application of fractal analysis in research, fracture forensics and solving production problems are discussed.

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