54,444 research outputs found
On Bioelectric Algorithms
Cellular bioelectricity describes the biological phenomenon in which cells in living tissue generate and maintain patterns of voltage gradients across their membranes induced by differing concentrations of charged ions. A growing body of research suggests that bioelectric patterns represent an ancient system that plays a key role in guiding many important developmental processes including tissue regeneration, tumor suppression, and embryogenesis. This paper applies techniques from distributed algorithm theory to help better understand how cells work together to form these patterns. To do so, we present the cellular bioelectric model (CBM), a new computational model that captures the primary capabilities and constraints of bioelectric interactions between cells and their environment. We use this model to investigate several important topics from the relevant biology research literature. We begin with symmetry breaking, analyzing a simple cell definition that when combined in single hop or multihop topologies, efficiently solves leader election and the maximal independent set problem, respectively - indicating that these classical symmetry breaking tasks are well-matched to bioelectric mechanisms. We then turn our attention to the information processing ability of bioelectric cells, exploring upper and lower bounds for approximate solutions to threshold and majority detection, and then proving that these systems are in fact Turing complete - resolving an open question about the computational power of bioelectric interactions
Complexity, BioComplexity, the Connectionist Conjecture and Ontology of Complexity\ud
This paper develops and integrates major ideas and concepts on complexity and biocomplexity - the connectionist conjecture, universal ontology of complexity, irreducible complexity of totality & inherent randomness, perpetual evolution of information, emergence of criticality and equivalence of symmetry & complexity. This paper introduces the Connectionist Conjecture which states that the one and only representation of Totality is the connectionist one i.e. in terms of nodes and edges. This paper also introduces an idea of Universal Ontology of Complexity and develops concepts in that direction. The paper also develops ideas and concepts on the perpetual evolution of information, irreducibility and computability of totality, all in the context of the Connectionist Conjecture. The paper indicates that the control and communication are the prime functionals that are responsible for the symmetry and complexity of complex phenomenon. The paper takes the stand that the phenomenon of life (including its evolution) is probably the nearest to what we can describe with the term “complexity”. The paper also assumes that signaling and communication within the living world and of the living world with the environment creates the connectionist structure of the biocomplexity. With life and its evolution as the substrate, the paper develops ideas towards the ontology of complexity. The paper introduces new complexity theoretic interpretations of fundamental biomolecular parameters. The paper also develops ideas on the methodology to determine the complexity of “true” complex phenomena.\u
Walking dynamics are symmetric (enough)
Many biological phenomena such as locomotion, circadian cycles, and breathing
are rhythmic in nature and can be modeled as rhythmic dynamical systems.
Dynamical systems modeling often involves neglecting certain characteristics of
a physical system as a modeling convenience. For example, human locomotion is
frequently treated as symmetric about the sagittal plane. In this work, we test
this assumption by examining human walking dynamics around the steady-state
(limit-cycle). Here we adapt statistical cross validation in order to examine
whether there are statistically significant asymmetries, and even if so, test
the consequences of assuming bilateral symmetry anyway. Indeed, we identify
significant asymmetries in the dynamics of human walking, but nevertheless show
that ignoring these asymmetries results in a more consistent and predictive
model. In general, neglecting evident characteristics of a system can be more
than a modeling convenience---it can produce a better model.Comment: Draft submitted to Journal of the Royal Society Interfac
System Size Stochastic Resonance: General Nonequilibrium Potential Framework
We study the phenomenon of system size stochastic resonance within the
nonequilibrium potential's framework. We analyze three different cases of
spatially extended systems, exploiting the knowledge of their nonequilibrium
potential, showing that through the analysis of that potential we can obtain a
clear physical interpretation of this phenomenon in wide classes of extended
systems. Depending on the characteristics of the system, the phenomenon results
to be associated to a breaking of the symmetry of the nonequilibrium potential
or to a deepening of the potential minima yielding an effective scaling of the
noise intensity with the system size.Comment: LaTex, 24 pages and 9 figures, submitted to Phys. Rev.
No entailing laws, but enablement in the evolution of the biosphere
Biological evolution is a complex blend of ever changing structural
stability, variability and emergence of new phenotypes, niches, ecosystems. We
wish to argue that the evolution of life marks the end of a physics world view
of law entailed dynamics. Our considerations depend upon discussing the
variability of the very "contexts of life": the interactions between organisms,
biological niches and ecosystems. These are ever changing, intrinsically
indeterminate and even unprestatable: we do not know ahead of time the "niches"
which constitute the boundary conditions on selection. More generally, by the
mathematical unprestatability of the "phase space" (space of possibilities), no
laws of motion can be formulated for evolution. We call this radical emergence,
from life to life. The purpose of this paper is the integration of variation
and diversity in a sound conceptual frame and situate unpredictability at a
novel theoretical level, that of the very phase space. Our argument will be
carried on in close comparisons with physics and the mathematical constructions
of phase spaces in that discipline. The role of (theoretical) symmetries as
invariant preserving transformations will allow us to understand the nature of
physical phase spaces and to stress the differences required for a sound
biological theoretizing. In this frame, we discuss the novel notion of
"enablement". This will restrict causal analyses to differential cases (a
difference that causes a difference). Mutations or other causal differences
will allow us to stress that "non conservation principles" are at the core of
evolution, in contrast to physical dynamics, largely based on conservation
principles as symmetries. Critical transitions, the main locus of symmetry
changes in physics, will be discussed, and lead to "extended criticality" as a
conceptual frame for a better understanding of the living state of matter
Generative models versus underlying symmetries to explain biological pattern
Mathematical models play an increasingly important role in the interpretation
of biological experiments. Studies often present a model that generates the
observations, connecting hypothesized process to an observed pattern. Such
generative models confirm the plausibility of an explanation and make testable
hypotheses for further experiments. However, studies rarely consider the broad
family of alternative models that match the same observed pattern. The
symmetries that define the broad class of matching models are in fact the only
aspects of information truly revealed by observed pattern. Commonly observed
patterns derive from simple underlying symmetries. This article illustrates the
problem by showing the symmetry associated with the observed rate of increase
in fitness in a constant environment. That underlying symmetry reveals how each
particular generative model defines a single example within the broad class of
matching models. Further progress on the relation between pattern and process
requires deeper consideration of the underlying symmetries
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