Cells are cognitive entities possessing great computational power. DNA serves as a multivalent information storage medium for these computations at various time scales. Information is stored in sequences, epigenetic modifications, and rapidly changing nucleoprotein complexes. Because DNA must operate through complexes formed with other molecules in the cell, genome functions are inherently interactive and involve two-way communication with various cellular compartments. Both coding sequences and repetitive sequences contribute to the hierarchical systemic organization of the genome. By virtue of nucleoprotein (...) complexes, epigenetic modifications, and natural genetic engineering activities, the genome can serve as a read-write storage system. An interactive informatic conceptualization of the genome allows us to understand the functional importance of DNA that does not code for protein or RNA structure, clarifies the essential multidirectional and systemic nature of genomic information transfer, and emphasizes the need to investigate how cellular computation operates in reproduction and evolution. (shrink)

Cellular Automata (CA) based simulations are widely used in a great variety of domains, fromstatistical physics to social science. They allow for spectacular displays and numerical predictions. Are they forall that a revolutionary modeling tool, allowing for “direct simulation”, or for the simulation of “the phenomenon itself”? Or are they merely models "of a phenomenological nature rather than of a fundamental one”? How do they compareto other modeling techniques? In order to answer these questions, we present a systematic exploration (...) of CA’s various uses. (shrink)

The data on the cellular mechanism of LTD that is presented in four target articles is synthesized into a new model of Purkinje cell plasticity. This model attempts to address credit assignment problems that are crucial in learning systems. Intracellular signal transduction mechanisms may provide the mechanism for a 3-factor learning rule and a trace mechanism. The latter may permit delayed information about motor error to modify the prior synaptic events that caused the error. This model may help to (...) focus future cellular studies on issues that are particularly critical for a computationally viable concept of cerebellar plasticity, [CRÉPEL et al.; HOUK et al.; KANO; LINDEN; VINCENT]. (shrink)

Cellular automata (henceforth: CA) are discrete, abstract computational systems that have proved useful both as general models of complexity and as more specific representations of non-linear dynamics in a variety of scientific fields. Firstly, CA are (typically) spatially and temporally discrete: they are composed of a finite or denumerable set of homogeneous, simple units, the atoms or cells. At each time unit, the cells instantiate one of a finite set of states. They evolve in parallel at discrete time steps, (...) following state update functions or dynamical transition rules: the update of a cell state obtains by taking into account the states of cells in its local neighborhood (there are, therefore, no actions at a distance). Secondly, CA are abstract, as they can be specified in purely mathematical terms and implemented in physical structures. Thirdly, CA are computational systems: they can compute functions and solve algorithmic problems. Despite functioning in a different way from traditional, Turing machine-like devices, CA with suitable rules can emulate a universal Turing machine, and therefore compute, given Turing's Thesis, anything computable.... (shrink)

While it is known that Euclid’s five axioms include a proposition that a line consists at least of two points, modern geometry avoid consistently any discussion on the precise definition of point, line, etc. It is our aim to clarify one of notorious question in Euclidean geometry: how many points are there in a line segment? – from discrete-cellular space (DCS) viewpoint. In retrospect, it may offer an alternative of quantum gravity, i.e. by exploring discrete gravitational theories. To elucidate (...) our propositions, in the last section we will discuss some implications of discrete cellular-space model in several areas of interest: (a) cell biology, (b) cellular computing, (c) Maxwell equations, (d) low energy fusion, and (e) cosmology modelling. (shrink)

The ability to memorize changes in the environment is present at all biological levels, from social groups and individuals, down to single cells. Trans‐generational memory is embedded subcellularly through genetic and epigenetic mechanisms. Evidence that cells process and remember features of the immediate environment using protein sensors is reviewed. It is argued that this mnemonic ability is encapsulated within the protein conformational space and lasts throughout its lifetime, which can overlap with the lifespan of the organism. Means to determine diachronic (...) changes in protein activity are presented. (shrink)

Computer simulation is shown to be philosophically interesting because it introduces a qualitatively new methodology for theory construction in science different from the conventional two components of "theory" and "experiment and/or observation". This component is "experimentation with theoretical models." Two examples from the physical sciences are presented for the purpose of demonstration but it is claimed that the biological and social sciences permit similar theoretical model experiments. Furthermore, computer simulation permits theoretical models for the evolution of physical systems which use (...) cellular automata rather than differential equations as their syntax. The great advantages of the former are indicated. (shrink)

Computational modeling plays an increasingly important explanatory role in cases where we investigate systems or problems that exceed our native epistemic capacities. One clear case where technological enhancement is indispensable involves the study of complex systems.1 However, even in contexts where the number of parameters and interactions that define a problem is small, simple systems sometimes exhibit non-linear features which computational models can illustrate and track. In recent decades, computational models have been proposed as a way to assist us in (...) understanding emergent phenomena. (shrink)

More than one researcher is currently proposing that the notion of information become an important element for defining living systems as well as for explaining conditions that make their origins possible. During the pre-biotic era, the type of compounds encountered would mainly have been very simple in nature and might have been immersed in the natural dynamic of the physical world and in processes of self-organization. It is furthermore quite possible that they formed a relationship between and among certain types (...) of processes that here we are specifically proposing as central for the emergence of cell organization. Consequently, an important initial step towards constructing a theory of biological information is to ask ourselves the question: how do biological systems process information? In this way, we will be contributing to the proposals of this paper where we seek to identify general principles that govern biological computing and that deal with biosemiotic approaches as they are defended in naturalistic normative terms. (shrink)

The central motivating idea behind the development of this work is the concept of prespace, a hypothetical structure that is postulated by some physicists to underlie the fabric of space or space-time. I consider how such a structure could relate to space and space-time, and the rest of reality as we know it, and the implications of the existence of this structure for quantum theory. Understanding how this structure could relate to space and to the rest of reality requires, I (...) believe, that we consider how space itself relates to reality, and how other so-called "spaces" used in physics relate to reality. In chapter 2, I compare space and space-time to other spaces used in physics, such as configuration space, phase space and Hilbert space. I support what is known as the "property view" of space, opposing both the traditional views of space and space-time, substantivalism and relationism. I argue that all these spaces are property spaces. After examining the relationships of these spaces to causality, I argue that configuration space has, due to its role in quantum mechanics, a special status in the microscopic world similar to the status of position space in the macroscopic world. In chapter 3, prespace itself is considered. One way of approaching this structure is through the comparison of the prespace structure with a computational system, in particular to a cellular automaton, in which space or space-time and all other physical quantities are broken down into discrete units. I suggest that one way open for a prespace metaphysics can be found if physics is made fully discrete in this way. I suggest as a heuristic principle that the physical laws of our world are such that the computational cost of implementing those laws on an arbitrary computational system is minimized, adapting a heuristic principle of this type proposed by Feynman. In chapter 4, some of the ideas of the previous chapters are applied in an examination of the physics and metaphysics of quantum theory. I first discuss the "measurement problem" of quantum mechanics: this problem and its proposed solution are the primary subjects of chapter 4. It turns out that considering how quantum theory could be made fully discrete leads naturally to a suggestion of how standard linear quantum mechanics could be modified to give rise to a solution to the measurement problem. The computational heuristic principle reinforces the same solution. I call the modified quantum mechanics Critical Complexity Quantum Mechanics (CCQM). I compare CCQM with some of the other proposed solutions to the measurement problem, in particular the spontaneous localization model of Ghirardi, Rimini and Weber. Finally, in chapters 5 and 6, I argue that the measure of complexity of quantum mechanical states I introduce in CCQM also provides a new definition of entropy for quantum mechanics, and suggests a solution to the problem of providing an objective foundation for statistical mechanics, thermodynamics, and the arrow of time. (shrink)

The emergence of the “4th Industrial Revolution,” i.e. the convergence of artificial intelligence, the Internet of Things, advanced materials, and bioengineering technologies, could accelerate socioeconomic insecurities and anxieties or provide beneficial alternatives to the status quo. In the post-Covid-19 era, the entities that are best positioned to capitalize on these innovations are large firms, which use digital platforms and big data to orchestrate vast ecosystems of users and extract market share across industry sectors. Nonetheless, these technologies also have the potential (...) to democratize ownership, broaden political-economic participation, and reduce environmental harms. We articulate the potential sociotechnical pathways in this high-stakes crossroads by analyzing cellular agriculture, an exemplary 4th Industrial Revolution technology that synergizes computer science, biopharma, tissue engineering, and food science to grow cultured meat, dairy, and egg products from cultured cells and/or genetically modified yeast. Our exploration of this space involved multi-sited ethnographic research in both the cellular agriculture community and alternative economic organizations devoted to open source licensing, member-owned cooperatives, social financing, and platform business models. Upon discussing how these latter approaches could potentially facilitate alternative sociotechnical pathways in cellular agriculture, we reflect upon the broader implications of this work with respect to the 4th Industrial Revolution and the enduring need for public policy reform. (shrink)

The aim of this paper is to propose an alternative behavioural definition of computation (and of a computer) based simply on whether a system is capable of reacting to the environment—the input—as reflected in a measure of programmability. This definition is intended to have relevance beyond the realm of digital computers, particularly vis-à-vis natural systems. This will be done by using an extension of a phase transition coefficient previously defined in an attempt to characterise the dynamical behaviour of cellular (...) automata and other systems. The transition coefficient measures the sensitivity of a system to external stimuli and will be used to define the susceptibility of a system to be (efficiently) programmed. (shrink)

Computational neuroscientists not only employ computer models and simulations in studying brain functions. They also view the modeled nervous system itself as computing. What does it mean to say that the brain computes? And what is the utility of the ‘brain-as-computer’ assumption in studying brain functions? In previous work, I have argued that a structural conception of computation is not adequate to address these questions. Here I outline an alternative conception of computation, which I call the analog-model. The term (...) ‘analog-model’ does not mean continuous, non-discrete or non-digital. It means that the functional performance of the system simulates mathematical relations in some other system, between what is being represented. The brain-as-computer view is invoked to demonstrate that the internal cellular activity is appropriate for the pertinent information-processing task.Keywords: Computation; Computational neuroscience; Analog computers; Representation; Simulation. (shrink)

Some years ago, Hidding et al. suggest that the emergence of intricate and pervasive weblike structure of the Universe on Megaparsec scales can be approximated by a well-known equation from fluid mechanics, the Burgers’ equation. The solution to this equation can be obtained from a geometrical formalism. The resulting Adhesion formalism provides deep insight into the dynamics and topology of the Cosmic Web. It uncovers a direct connection between the conditions in the very early Universe and the complex spatial patterns (...) that emerged out of these under the influence of gravity. In the present paper, we describe a cellular automaton model of the Burgers’ equation, which can be investigated via a fast computer simulation. In the end, this suggests a Cellular Automata Adhesion Model of the Universe. (shrink)

Neurulation, the curling of the neuroepithelium to form the neural tube, is an essential component of the development of animal embryos. Defects of neural tube formation, which occur with an overall frequency of one in 500 human births, are the cause of severe and distressing congenital abnormalities. However, despite the fact that there is increasing information from animal experiments about the mechanisms which effect neural tube formation, much less is known about the fundamental causes of neural tube defects (NTD). The (...) use of computer models provides one way of gaining clues about the ways in which neurulation may be compromised. Here we employ one computer model to examine the robustness of different cellular mechanisms which are thought to contribute to neurulation. The model, modified from that of Odell et al (Odell, G.M., Oster, G., Alberch, P. and Burnside, B., (1981)) mimics neurulation by laterally propagating a wave of apical contraction along an active zone within a ring of cells. We link the results to experimental evidence gained from studies of embryos in which neurulation has been perturbed. The results indicate that alteration of one of the properties of non-neural tissue can delay or inhibit neurulation, supporting the idea, gained from observation of embryos bearing genes which predispose to NTD, that the tissue underlying the neuroepithelium may contribute to the elevation of the neural folds. The results also show that reduction of the contractile properties of a small proportion of the neuroepithelial cell population may have a profound effect on overall tissue profiling. The results suggest that the elevation of the neural folds, and hence successful neurulation, may be vulnerable to relatively minor deficiencies in cell properties. (shrink)

To make the interface design of computer application system better, meet the psychological and emotional needs of users, and be more humanized, the emotional factor is increasingly valued by interface designers. In the design of human-computer interaction graphical interfaces, the designer attaches great importance to the emotional design of the interface, and enhances the humanized design of the interface, which cannot only improve the comfort of the interface, but also improve the fun of the interface, to ensure the psychological and (...) emotional needs of users can be better satisfied. It may acquire information that is favorable to innovative design by utilizing cluster analysis algorithm to tackle the problem of complicated cultural information, and then utilize cellular genetic algorithm to carry out creative design of cultural items. It increases the availability of cultural and creative goods. The classic cluster analysis technique offers the maximum data clustering effect of 53.3%, according to the findings of this paper’s experiments. While the improved cluster analysis algorithm has the highest data clustering effect of 90%. It can be seen that the improved cluster analysis algorithm can effectively perform cluster analysis on a large amount of data in cultural and creative products. It thus finds out the most suitable designer’s creative information, which helps designers create better products. (shrink)

This book is an introduction, entirely by example, to the possibilities of using computer models as tools in phosophical research in general and in philosophical logic in particular. Topics include chaos, fractals, and the semantics of paradox; epistemic dynamics; fractal images of formal systems; the evolution of generosity; real-valued game theory; and computation and undecidability in the spatialized Prisoner's Dilemma.

The bookModeling Reality covers a wide range of fascinating subjects, accessible to anyone who wants to learn about the use of computer modeling to solve a diverse range of problems, but who does not possess a specialized training in mathematics or computer science. The material presented is pitched at the level of high-school graduates, even though it covers some advanced topics (cellular automata, Shannon's measure of information, deterministic chaos, fractals, game theory, neural networks, genetic algorithms, and Turing machines). These (...) advanced topics are explained in terms of well known simple concepts: Cellular automata - Game of Life, Shannon's formula - Game of twenty questions, Game theory - Television quiz, etc. The book is unique in explaining in a straightforward, yet complete, fashion many important ideas, related to various models of reality and their applications. Twenty-five programs, written especially for this book, are provided on an accompanying CD. They greatly enhance its pedagogical value and make learning of even the more complex topics an enjoyable pleasure. (shrink)

Almost all biomedical research to date has relied upon mean measurements from cell populations, however it is well established that what it is observed at this macroscopic level can be the result of many interactions of several different single cells. Thus, the observable macroscopic ‘average’ cannot outright be used as representative of the ‘average cell’. Rather, it is the resulting emerging behaviour of the actions and interactions of many different cells. Single‐cell RNA sequencing (scRNA‐Seq) enables the comparison of the transcriptomes (...) of individual cells. This provides high‐resolution maps of the dynamic cellular programmes allowing us to answer fundamental biological questions on their function and evolution. It also allows to address medical questions such as the role of rare cell populations contributing to disease progression and therapeutic resistance. Furthermore, it provides an understanding of context‐specific dependencies, namely the behaviour and function that a cell has in a specific context, which can be crucial to understand some complex diseases, such as diabetes, cardiovascular disease and cancer. Here, we provide an overview of scRNA‐Seq, including a comparative review of emerging technologies and computational pipelines. We discuss the current and emerging applications and focus on tumour heterogeneity a clear example of how scRNA‐Seq can provide new understanding of a complex disease. Additionally, we review the limitations and highlight the need of powerful computational pipelines and reproducible protocols for the broader acceptance of this technique in basic and clinical research. (shrink)

The counterfactual account of physical computation is simple and, for the most part, very attractive. However, it is usually thought to trivialize the notion of physical computation insofar as it implies ‘limited pancomputationalism’, this being the doctrine that every deterministic physical system computes some function. Should we bite the bullet and accept limited pancomputationalism, or reject the counterfactual account as untenable? Jack Copeland would have us do neither of the above. He attempts to thread a path between the two horns (...) of the dilemma by buttressing the counterfactual account with extra conditions intended to block certain classes of deterministic physical systems from qualifying as physical computers. His theory is called the ‘algorithm execution account’. Here we show that the algorithm execution account entails limited pancomputationalism, despite Copeland’s argument to the contrary. We suggest, partly on this basis, that the counterfactual account should be accepted as it stands, pancomputationalist warts and all. (shrink)

We used computer simulations to study the possible role of the dispersion of cellular coupling, refractoriness or both, in the mechanisms underlying cardiac arrhythmias. Local ischemia was first assumed to induce cell to cell dispersion of the coupling resistance (Case 1), refractory period (Case 2), or both of them (Case 3). Our numerical experiments based on the van Capelle and Durrer model showed that vortices could not be induced by cell to cell variations. With cellular properties dispersed in (...) a patchy way within the ischemic zone, a single activation wave could give rise to abnormal activities. This demonstrates the stability of the wave front under small inhomogeneities. Probabilities of reentry, estimated for the three cases cited above showed that a severe alteration of the coupling resistance may be an important factor in the genesis of reentry. Moreover, use of isochronal maps revealed that vortices were both stable and sustained with an alteration of the coupling alone or combined with a reduction of the action potential duration. Conversely, simulations with reduction of the refractoriness alone, inducing only transient patterns, could exhibit functionally determined reentries. (shrink)

Philosophical modeling has a long and distinguished history, but the computer offers new and powerful prospects for the creation and manipulation of models. It seems inevitable that the computer will become a major tool in future philosophical research. Here I offer an overview of explorations in philosophical computer modeling that we in the Group for Logic and Formal Semantics at SUNY Stony Brook have undertaken: explorations regarding (1) the potential emergence of cooperation in a society of egoists, (2) self‐reference and (...) paradox in fuzzy logic, (3) a fractal approach to formal systems, and (4) on‐going explorations with models for the emergence of communication. The attempt is not to give a detailed report on any of these but to give a bird s‐eye view of them all, emphasizing the general form that the models take, the philosophical motivations behind them, and the kinds of philosophical results that they may have to offer. (shrink)

Mathematical models of tumour invasion appear as interesting tools for connecting the information extracted from medical imaging techniques and the large amount of data collected at the cellular and molecular levels. Most of the recent studies have used stochastic models of cell translocation for the comparison of computer simulations with histological solid tumour sections in order to discriminate and characterise expansive growth and active cell movements during host tissue invasion. This paper describes how a deterministic approach based on reaction-diffusion (...) models and their generalisation in the mechano-chemical framework developed in the study of biological morphogenesis can be an alternative for analysing tumour morphological patterns. We support these considerations by reviewing two studies. In the first example, successful comparison of simulated brain tumour growth with a time sequence of computerised tomography (CT) scans leads to a quantification of the clinical parameters describing the invasion process and the therapy. The second example considers minimal hypotheses relating cell motility and cell traction forces. Using this model, we can simulate the bifurcation from an homogeneous distribution of cells at the tumour surface toward a nonhomogeneous density pattern which could characterise a pre-invasive stage at the tumour-host tissue interface. (shrink)

Attempts to formalize the diagnostic process are by no means a recent undertaking; what is new is the availability of an engine to process these formalizations. The digital computer has therefore been increasingly turned to in the expectation of developing systems which will assist or replace the physician in diagnosis. Such efforts involve a number of assumptions regarding the nature of the diagnostic process: e.g. where it begins, and where it ends. ‘Diagnosis’ appears to include a number of quite different (...) cognitive processes, some of which seem more subject to formalization than others. Underlying the difficulties inherent in these efforts at formalization, is the hierarchical structure of medical knowledge including that of diseases. (By ‘hierarchical structure’, I mean no more than that our descriptions of clinical objects necessarily refer to different levels of organization; atomic, molecular, cellular, physiological system, entire patient.) Since diagnosis is in part a form of classification, measures of similarity between the clinical findings of a particular patient and a potential disease, are needed. This is complicated by the fact that some diseases are described using the vocabularies of physics and chemistry, others with the vocabulary of psychology, and most, with terms taken from a number of different hierarchical levels. The differences between the descriptions made using these vocabularies will be seen to exert systematic (if not uniform) influences upon the diagnostic process. CiteULike Connotea Del.icio.us What's this? (shrink)

The first aim of simulation in virtual environment is to help biologists to have a better understanding of the simulated system. The cost of such simulation is significantly reduced compared to that of in vivo simulation. However, the inherent complexity of biological system makes it hard to simulate these systems on non-parallel architectures: models might be made of sub-models and take several scales into account; the number of simulated entities may be quite large. Today, graphics cards are used for general (...) purpose computing which has been made easier thanks to frameworks like CUDA or OpenCL. Parallelization of models may however not be easy: parallel computer programing skills are often required; several hardware architectures may be used to execute models. In this paper, we present the software architecture we built in order to implement various models able to simulate multi-cellular system. This architecture is modular and it implements data structures adapted for graphics processing units architectures. It allows efficient simulation of biological mechanisms. (shrink)

The basic reproduction number R0\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_0$$\end{document} is the average number of new infections produced by a typical infective individual in the early stage of an infectious disease, following the introduction of few infective individuals in a completely susceptible population. If R0 1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_0>1$$\end{document} the infection can invade the host population and persist. This threshold quantity is well studied for SIR compartmental or mean field models (...) based on ordinary differential equations, and a general method for its computation has been proposed by van den Driessche and Watmough. We concentrate here on SIR epidemiological models that take into account the contact network N underlying the transmission of the disease. In this context, it is generally admitted that R0\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{0}$$\end{document} can be approximated by the average number R2,3\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{2,3}$$\end{document} of infective individuals of generation three produced by an infective of generation two. We give here a simple analytic formula of R2,3\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{2,3}$$\end{document} for SIR cellular networks. Simulations on two-dimensional cellular networks with von Neumann and Moore neighborhoods show that R2,3\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{2,3}$$\end{document} can be used to capture a threshold phenomenon related the dynamics of SIR cellular network and confirm the good quality of the simple approach proposed recently by Aparicio and Pascual for the particular case of Moore neighborhood. (shrink)

The aim of this paper is to propose an alternative behavioural definition of computation based simply on whether a system is capable of reacting to the environment—the input—as reflected in a measure of programmability. This definition is intended to have relevance beyond the realm of digital computers, particularly vis-à-vis natural systems. This will be done by using an extension of a phase transition coefficient previously defined in an attempt to characterise the dynamical behaviour of cellular automata and other systems. (...) The transition coefficient measures the sensitivity of a system to external stimuli and will be used to define the susceptibility of a system to be programmed. (shrink)

We explore the possibility of teaching philosophy through the teaching of computer programming. It is pedagogically useful to use programming because it is extremely popular (especially due to the recent breakthroughs in machine learning), and it can provide a novel, interesting, and clear introduction to a variety of classic philosophical issues. We discuss two examples. The first is using programming to solve digital image manipulation tasks as a way of introducing and clarifying debates over external world skepticism. The second is (...) programming a simulation of a simple 2-D cellular automaton as a way of introducing and clarifying debates over determinism and free will. (shrink)

Computational neuroscience attributes coloured areas and other perceptual qualia to calculations that are realizable in multiple cellular forms. This faces serious issues in explaining how the various qualia arise and how they bind to form overall perceptions. Qualia may instead be neuroelectrical. Growing evidence indicates that perceptions correlate with neuroelectrical activity spotted by locally activated EEGs, the different qualia correlate with the different electrochemistries of unique detector cells, a unified neural-electromagnetic field binds this activity to form overall perceptions, and (...) this field interacts with sensory circuits to help attentively guide perception. The coloured areas in images may thus be seated in the electrochemistry of unique cells, while constancy mechanisms and other multiply realizable computations just help refine these images behind the scenes. This theory is ultimately testable. (shrink)

Varela, Thompson, and Rosch illustrated their original presentation of the enactive theory of cognition with the example of a simple cellular automaton. Their theory was paradigmatically anti-computational, and yet automata similar to the one that they describe have typically been used to illustrate theories of computation, and are usually treated as abstract computational systems. Their use of this example is therefore puzzling, especially as they do not seem to acknowledge the discrepancy. The solution to this tension lies in recognizing (...) a hidden background assumption, shared by both Varela, Thompson, and Rosch and the computational theories of mind which they were responding to. This assumption is that computation requires representation, and that computational states must bear representational content. For Varela, Thompson, and Rosch, representational content is incompatible with cognition, and so from their perspective the automaton that they describe cannot, despite appearances, be computational. However, there now exist several accounts of computation that do not make this assumption, and do not characterize computation in terms of representational content. In light of these recent developments, we will argue that it is quite straightforward to characterize the enactive automaton as a non-representational computing mechanism, one that we do not think they should have any objections to. (shrink)

In his classic paper On Computable Numbers Turing analyzed what can be done by a human computor in a routine, “mechanical” way. He argued that mechanical op-erations obey locality conditions and are carried out on configurations satisfying boundedness conditions. Processes meeting these restrictive conditions can be shown to be computable by a Turing machine. Turing viewed memory limitations of computors as the ultimate reason for the restrictive conditions. In contrast, Gandy analyzed in his paper Church’s Thesis and Principles for Mechanisms (...) what can be done by “discrete deterministic mechanical devices” and appealed to physical considerations to motivate restrictive principles. These devices include, crucially, ones that carry out parallel processes, e.g., cellular automata. Following Turing’s methodological ways and guided by Conway’s “Game of Life” as a paradigm, Gandy formulated four restrictive principles and proved that devices satisfying them are computationally equivalent to Turing machines. (shrink)

What is reality for an agent? What is minimal cognition? How does the morphology of a cognitive agent affect cognition? These are still open questions among scientists and philosophers. In this chapter we propose the idea of info-computational nature as a framework for answering those questions. Within the info-computational framework, information is defined as a structure, and computation as the dynamics of information. To an agent, nature therefore appears as an informational structure with computational dynamics. Both information and computation in (...) this context have broader meaning than in everyday use, and both are necessarily grounded in physical implementation. Evolution of increasingly complex living agents is understood as a process of morphological computation driven by agents’ interactions with the environment. It is a process much more complex than random variation; instead the mechanisms of change are morphological computational processes of self-organisation. Reality for an agent emerges as a result of interactions with the environment together with internal information processing. Following Maturana and Varela, we take cognition to be the process of living of an organism, and thus it appears on different levels of complexity, from cellular via organismic to social. The simpler the agent, the simpler its “reality” defined by the network of networks of info-computational processes, which constitute its cognition. The debated topic of consciousness takes its natural place in this framework, as a process of information integration that we suggest naturally evolved in organisms with a nervous system. Computing nature/pancomputationalism is sometimes confused with panpsychism or claimed to necessarily imply panpsychism, which we show is not the case. Even though we focus on natural systems in this chapter, the info-computational approach is general and can be used to model both biological and artifactual cognitive agents. (shrink)

Even the simplest known living organisms are complex chemical processing systems. But how sophisticated is the behaviour that arises from this? We present a framework in which even bacteria can be identified as capable of representing information in arbitrary signal molecules, to facilitate altering their behaviour to optimise their food supplies, for example. Known asion/Representation theory, this framework makes precise the relationship between physical systems and abstract concepts. Originally developed to answer the question of when a physical system is (...) class='Hi'>computing, AR theory naturally extends to the realm of biological systems to bring clarity to questions of computation at the cellular level. (shrink)

Church's and Turing's theses dogmatically assert that an informal notion of effective calculability is adequately captured by a particular mathematical concept of computability. I present an analysis of calculability that is embedded in a rich historical and philosophical context, leads to precise concepts, but dispenses with theses. To investigate effective calculability is to analyze symbolic processes that can in principle be carried out by calculators. This is a philosophical lesson we owe to Turing. Drawing on that lesson and recasting work (...) of Gandy, I formulate boundedness and locality conditions for two types of calculators, namely, human computing agents and mechanical computing devices (discrete machines). The distinctive feature of the latter is that they can carry out parallel computations. The analysis leads to axioms for discrete dynamical systems (representing human and machine computations) and allows the reduction of models of these axioms to Turing machines. Cellular automata and a variety of artificial neural nets can be shown to satisfy the axioms for machine computations. (shrink)

Microbial systems biology has made enormous advances in relating microbial physiology to the underlying biochemistry and molecular biology. By meticulously studying model microorganisms, in particular Escherichia coli and Saccharomyces cerevisiae, increasingly comprehensive computational models predict metabolic fluxes, protein expression, and growth. The modeling rationale is that cells are constrained by a limited pool of resources that they allocate optimally to maximize fitness. As a consequence, the expression of particular proteins is at the expense of others, causing trade‐offs between cellular (...) objectives such as instantaneous growth, stress tolerance, and capacity to adapt to new environments. While current computational models are remarkably predictive for E. coli and S. cerevisiae when grown in laboratory environments, this may not hold for other growth conditions and other microorganisms. In this contribution, we therefore discuss the relationship between the instantaneous growth rate, limited resources, and long‐term fitness. We discuss uses and limitations of current computational models, in particular for rapidly changing and adverse environments, and propose to classify microbial growth strategies based on Grimes's CSR framework. (shrink)

Biological phenomena can be investigated at multiple levels, from the molecular to the cellular to the organismic to the ecological. In typical biology instruction, these levels have been segregated. Yet, it is by examining the connections between such levels that many phenomena in biology, and complex systems in general, are best explained. We describe a computation-based approach that enables students to investigate the connections between different biological levels. Using agent-based, embodied modeling tools, students model the microrules underlying a biological (...) phenomenon and observe the resultant aggregate dynamics. We describe 2 cases in which this approach was used. In both cases, students framed hypotheses, constructed multiagent models that incorporate these hypotheses, and tested these by running their models and observing the outcomes. Contrasting these cases against traditionally used, classical equation-based approaches, we argue that the embodied modeling approach connects more directly to students’ experience, enables extended investigations as well as deeper understanding, and enables “advanced” topics to be productively introduced into the high school curriculum. (shrink)

Against the opinion that DNA as program is not sufficiently explanatory, we maintain that the cellular machinery is entirely computational, and we identify the crucial notion of the interpreter that expresses the gene with the minimal gene set. Epigenetics research does not so much need paradigm shifts as the unraveling of an exceedingly complex computational machine.

This aricle discusses the similarity between the propagation of pathogens (viruses and worms) on computer networks and the proliferation of pathogens in cellular organisms (organisms with genetic material contained within a membrane-encased nucleus). It introduces several biological mechanisms which are used in these organisms to protect against such pathogens and presents security models for networked computers inspired by several biological paradigms, including genomics (RNA interference), proteomics (pathway mapping), and physiology (immune system). In addition, the study of epidemiological models for (...) disease control can inspire methods for controlling the spread of pathogens across multiple nodes of a network. It also presents results based on the authors’ research in immune system modeling. (shrink)

Any low-level processes, the sequence of chemical interactions in a living cell, muscle cellular activity, processor commands or neuron interaction, is possible only if there is a downward causality, only due to uniting and controlling power of the highest level. Therefore, there is no special “hard problem of consciousness”, i.e. the problem of relation of ostensibly purely biological materiality and non-causal mentality - we have only the single philosophical problem of relation between the upward and downward causalities, the problem (...) of interrelation between hierarchic levels of existence. It is necessary to conclude that the problem of determinacy of chemical processes by the biological ones and the problem of neuron interactions caused by consciousness are of one nature and must have one solution. (shrink)

One recursively enumerable real α dominates another one β if there are nondecreasing recursive sequences of rational numbers (a[n] : n ∈ ω) approximating α and (b[n] : n ∈ ω) approximating β and a positive constant C such that for all n, C(α − a[n]) ≥ (β − b[n]). See [R. M. Solovay, Draft of a Paper (or Series of Papers) on Chaitin’s Work, manuscript, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, 1974, p. 215] and [G. J. (...) Chaitin, IBM J. Res. Develop., 21 (1977), pp. 350–359]. We show that every recursively enumerable random real dominates all other recursively enumerable reals. We conclude that the recursively enumerable random reals are exactly the Ω-numbers [G. J. Chaitin, IBM J. Res. Develop., 21 (1977), pp. 350–359]. Second, we show that the sets in a universal Martin-Lof test for randomness have random measure, and every recursively enumerable random number is the sum of the measures represented in a universal Martin-Lof test. (shrink)