scholarly journals Chemical computing with reaction–diffusion processes

2015 ◽  
Vol 373 (2046) ◽  
pp. 20140219 ◽  
Author(s):  
J. Gorecki ◽  
K. Gizynski ◽  
J. Guzowski ◽  
J. N. Gorecka ◽  
P. Garstecki ◽  
...  
Keyword(s):  
Information Processing ◽  
Diffusion Processes ◽  
Reaction Diffusion ◽  
Living Organism ◽  
Chemical Information ◽  
Bz Reaction ◽  
Living Organisms ◽  
Basic Features ◽  
Maximum Reliability ◽  
The Brain

Chemical reactions are responsible for information processing in living organisms. It is believed that the basic features of biological computing activity are reflected by a reaction–diffusion medium. We illustrate the ideas of chemical information processing considering the Belousov–Zhabotinsky (BZ) reaction and its photosensitive variant. The computational universality of information processing is demonstrated. For different methods of information coding constructions of the simplest signal processing devices are described. The function performed by a particular device is determined by the geometrical structure of oscillatory (or of excitable) and non-excitable regions of the medium. In a living organism, the brain is created as a self-grown structure of interacting nonlinear elements and reaches its functionality as the result of learning. We discuss whether such a strategy can be adopted for generation of chemical information processing devices. Recent studies have shown that lipid-covered droplets containing solution of reagents of BZ reaction can be transported by a flowing oil. Therefore, structures of droplets can be spontaneously formed at specific non-equilibrium conditions, for example forced by flows in a microfluidic reactor. We describe how to introduce information to a droplet structure, track the information flow inside it and optimize medium evolution to achieve the maximum reliability. Applications of droplet structures for classification tasks are discussed.

scholarly journals Biomolecular nonlinear dynamic mechanisms as a foundation for human traits of information processing machine

2001 ◽  
Vol 6 (4) ◽  
pp. 263-279
Author(s):  
Nicholas G. Rambaidi
Keyword(s):  
Image Processing ◽  
Information Processing ◽  
Nonlinear Dynamic ◽  
Reaction Diffusion ◽  
Dynamic Mechanisms ◽  
Diffusion Media ◽  
Operational Information ◽  
Basic Features ◽  
Biological Entities ◽  
High Computational Complexity

A pseudo-biological paradigm in information processing launched by McCulloch and Pitts in the early 1940s has been advanced during the last decades. Different attempts were made based on these developments to design operational information processing devices capable of solving problems of high computational complexity.One of them was the use of nonlinear dynamic mechanisms inherent in information processing by biochemical, biomolecular, and simple biological entities. Chemical reaction–diffusion media proved to be effective tools for the implementation of these capabilities.Basic features of these information processing means and modeling of their information processing capabilities are discussed in this paper. Belousov–Zhabotinsky type reaction–diffusion media were used to simulate image processing operations and finding paths in a labyrinth.

scholarly journals DNA-based long-lived reaction-diffusion patterning in a host hydrogel

2019 ◽  
Author(s):  
Georg Urtel ◽  
André Estevez-Torres ◽  
Jean-Christophe Galas
Keyword(s):  
Dna Sequences ◽  
Reaction Diffusion ◽  
Life Time ◽  
Side Reactions ◽  
Chemical Information ◽  
Living Matter ◽  
Synthetic Material ◽  
Synthetic Life ◽  
Three Stages ◽  
Living Organisms

AbstractThe development of living organisms is a source of inspiration for the creation of synthetic life-like materials. Embryo development is divided into three stages that are inextricably linked: patterning, differentiation and growth. During patterning, sustained out-of-equilibrium molecular programs interpret underlying molecular cues to create well-defined concentration profiles. Implementing this patterning stage in an autonomous synthetic material is a challenge that at least requires a programmable and long-lasting out-of-equilibrium chemistry compatible with a host material. Here we show that DNA/enzyme reactions can create reaction-diffusion patterns that are extraordinary long-lasting both in solution and inside an autonomous hydrogel. The life-time and stability of these patterns - here traveling fronts and two-band patterns - are significantly increased by blocking parasitic side reactions and by dramatically reducing the diffusion coefficient of specific DNA sequences. Immersed in oil, hydrogels pattern autonomously with limited evaporation, but can also exchange chemical information from other gels when brought in contact. Our primitive metabolic material thus recapitulates two important properties of living matter: a certain degree of autonomy that makes each piece of material an ‘individual’ with its own metabolism and, at the same time, the capacity to interact with other ‘individuals’.

scholarly journals Applications of Information Theory Methods for Evolutionary Optimization of Chemical Computers

Entropy ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. 313 ◽  
Author(s):  
Jerzy Gorecki
Keyword(s):  
Information Theory ◽  
Information Processing ◽  
Chemical Reactions ◽  
Chemical Information ◽  
Real Numbers ◽  
Top Down ◽  
Chemical Oscillators ◽  
Living Organisms ◽  
Computing Structure ◽  
Simple Network

It is commonly believed that information processing in living organisms is based on chemical reactions. However, the human achievements in constructing chemical information processing devices demonstrate that it is difficult to design such devices using the bottom-up strategy. Here I discuss the alternative top-down design of a network of chemical oscillators that performs a selected computing task. As an example, I consider a simple network of interacting chemical oscillators that operates as a comparator of two real numbers. The information on which of the two numbers is larger is coded in the number of excitations observed on oscillators forming the network. The parameters of the network are optimized to perform this function with the maximum accuracy. I discuss how information theory methods can be applied to obtain the optimum computing structure.

Infochemistry and the Future of Chemical Information Processing

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Nikolay V. Ryzhkov ◽  
Konstantin G. Nikolaev ◽  
Artemii S. Ivanov ◽  
Ekaterina V. Skorb
Keyword(s):  
Information Processing ◽  
Annual Review ◽  
Chemical Information ◽  
Publication Date ◽  
Chemical Systems ◽  
Silicon Devices ◽  
Molecular Logic ◽  
Living Organisms ◽  
Diverse Data ◽  
Unconventional Methods

Nowadays, information processing is based on semiconductor (e.g., silicon) devices. Unfortunately, the performance of such devices has natural limitations owing to the physics of semiconductors. Therefore, the problem of finding new strategies for storing and processing an ever-increasing amount of diverse data is very urgent. To solve this problem, scientists have found inspiration in nature, because living organisms have developed uniquely productive and efficient mechanisms for processing and storing information. We address several biological aspects of information and artificial models mimicking corresponding bioprocesses. For instance, we review the formation of synchronization patterns and the emergence of order out of chaos in model chemical systems. We also consider molecular logic and ion fluxes as information carriers. Finally, we consider recent progress in infochemistry, a new direction at the interface of chemistry, biology, and computer science, considering unconventional methods of information processing. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering, Volume 12 is June 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

From many to one: Meditation and the plasticity of the predictive mind

2020 ◽  
Author(s):  
Ruben Laukkonen ◽  
Heleen A Slagter
Keyword(s):  
Cognitive Enhancement ◽  
The Self ◽  
Predictive Processing ◽  
Focused Attention ◽  
Conceptual Processing ◽  
Current State ◽  
Contemplative Science ◽  
Open Monitoring ◽  
Living Organisms ◽  
The Brain

How profoundly can humans change their own minds? In this paper we offer a unifying account of meditation under the predictive processing view of living organisms. We start from relatively simple axioms. First, the brain is an organ that serves to predict based on past experience, both phylogenetic and ontogenetic. Second, meditation serves to bring one closer to the here and now by disengaging from anticipatory processes. We propose that practicing meditation therefore gradually reduces predictive processing, in particular counterfactual cognition—the tendency to construct abstract and temporally deep representations—until all conceptual processing falls away. Our Many- to-One account also places three main styles of meditation (focused attention, open monitoring, and non-dual meditation) on a single continuum, where each technique progressively relinquishes increasingly engrained habits of prediction, including the self. This deconstruction can also make the above processes available to introspection, permitting certain insights into one’s mind. Our review suggests that our framework is consistent with the current state of empirical and (neuro)phenomenological evidence in contemplative science, and is ultimately illuminating about the plasticity of the predictive mind. It also serves to highlight that contemplative science can fruitfully go beyond cognitive enhancement, attention, and emotion regulation, to its more traditional goal of removing past conditioning and creating conditions for potentially profound insights. Experimental rigor, neurophenomenology, and no-report paradigms combined with neuroimaging are needed to further our understanding of how different styles of meditation affect predictive processing and the self, and the plasticity of the predictive mind more generally.

scholarly journals Power Failure of Mitochondria and Oxidative Stress in Neurodegeneration and Its Computational Models

Antioxidants ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 229
Author(s):  
JunHyuk Woo ◽  
Hyesun Cho ◽  
YunHee Seol ◽  
Soon Ho Kim ◽  
Chanhyeok Park ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Mitochondrial Dysfunction ◽  
Computational Models ◽  
Neuronal Damage ◽  
Living Organism ◽  
The Body ◽  
Mitochondrial Functions ◽  
A Cell ◽  
The Brain ◽  
And Oxidative Stress

The brain needs more energy than other organs in the body. Mitochondria are the generator of vital power in the living organism. Not only do mitochondria sense signals from the outside of a cell, but they also orchestrate the cascade of subcellular events by supplying adenosine-5′-triphosphate (ATP), the biochemical energy. It is known that impaired mitochondrial function and oxidative stress contribute or lead to neuronal damage and degeneration of the brain. This mini-review focuses on addressing how mitochondrial dysfunction and oxidative stress are associated with the pathogenesis of neurodegenerative disorders including Alzheimer’s disease, amyotrophic lateral sclerosis, Huntington’s disease, and Parkinson’s disease. In addition, we discuss state-of-the-art computational models of mitochondrial functions in relation to oxidative stress and neurodegeneration. Together, a better understanding of brain disease-specific mitochondrial dysfunction and oxidative stress can pave the way to developing antioxidant therapeutic strategies to ameliorate neuronal activity and prevent neurodegeneration.

Event-Related Potentials in Psychiatry: Approaches to Research and Clinical Applications

1983 ◽  
Vol 17 (4) ◽  
pp. 307-318 ◽  
Author(s):  
H. G. Stampfer
Keyword(s):  
Information Processing ◽  
Psychiatric Disorders ◽  
Rapid Development ◽  
Event Related Potentials ◽  
Clinical Applications ◽  
Direct Access ◽  
Practical Application ◽  
Clinical Methods ◽  
Related Potentials ◽  
The Brain

This article suggests that the potential usefulness of event-related potentials in psychiatry has not been fully explored because of the limitations of various approaches to research adopted to date, and because the field is still undergoing rapid development. Newer approaches to data acquisition and methods of analysis, combined with closer co-operation between medical and physical scientists, will help to establish the practical application of these signals in psychiatric disorders and assist our understanding of psychophysiological information processing in the brain. Finally, it is suggested that psychiatrists should seek to understand these techniques and the data they generate, since they provide more direct access to measures of complex cerebral processes than current clinical methods.

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