Signals that make a difference

A causal approach to biological information is outlined. There are two aspects to this approach: information as determining a choice between a set of alternative objects, and information as determining the construction of a single object. The first aspect has been developed in earlier work to yield a quantitative measure of biological information that can be used to analyse biological networks. This paper explores the prospects for a measure based on the second aspect, and suggests some applications for such a measure. These two aspects are not suggested to exhaust all the facets of biological information.

progress in biophysics and molecular biology, 2012

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: http://www.elsevier.com/copyright a b s t r a c t In the last century, jointly with the advent of computers, mathematical theories of information were developed. Shortly thereafter, during the ascent of molecular biology, the concept of information was rapidly transferred into biology at large. Several philosophers and biologists have argued against adopting this concept based on epistemological and ontological arguments, and also, because it encouraged genetic determinism. While the theories of elaboration and transmission of information are valid mathematical theories, their own logic and implicit causal structure make them inimical to biology, and because of it, their applications have and are hindering the development of a sound theory of organisms. Our analysis concentrates on the development of information theories in mathematics and on the differences between these theories regarding the relationship among complexity, information and entropy.

Causality in the Sciences, 2011

Forthcoming in Phyllis McKay Illari, Federica Russo, and Jon Williamson, eds., Causality in the Sciences, Oxford University Press.) i. Introduction. Since the middle of the 20 th century neuroscientists, evolutionary theorists, molecular geneticists and other biologists, have talked as though information and information flow are important explanatory notions. However, some influential recent literature in philosophy of science disagrees. Paul Griffiths says that although

Journal for General Philosophy of Science, 2021

Download available at https://rdcu.be/cl0vS. Applied Evolutionary Epistemology is a scientific-philosophical theory that defines evolution as the set of phenomena whereby units evolve at levels of ontological hierarchies by mechanisms and processes. This theory also provides a methodology to study evolution, namely, studying evolution involves identifying the units that evolve, the levels at which they evolve, and the mechanisms and processes whereby they evolve. Identifying units and levels of evolution in turn requires the development of ontological hierarchy theories, and examining mechanisms and processes necessitates theorizing about causality. Together, hierarchy and causality theories explain how biorealities form and diversify with time. This paper analyzes how Applied EE redefines both hierarchy and causality theories in the light of the recent explosion of network approaches to causal reasoning associated with studies on reticulate and macroevolution. Causality theories have often been framed from within a rigid, ladder-like hierarchy theory where the rungs of the ladder represent the different levels, and the elements on the rungs represent the evolving units. Causality then is either defined reductionistically as an upward movement along the strands of a singular hierarchy, or holistically as a downward movement along that same hierarchy. Upward causation theories thereby analyze causal processes in time, i.e. over the course of natural history or phylogenetically, as Darwin and the founders of the Modern Synthesis intended. Downward causation theories analyze causal processes in space, ontogenetically or ecologically, as the current eco-evo-devo schools are evidencing. This work demonstrates how macroevolution and reticulate evolution theories add to the complexity by examining reticulate causal processes in space–time, and the interactional hierarchies that such studies bring forth introduce a new form of causation that is here called reticulate causation. Reticulate causation occurs between units and levels belonging to different as well as to the same ontological hierarchies. This article concludes that beyond recognizing the existence of multiple units, levels, and mechanisms or processes of evolution, also the existence of multiple kinds of evolutionary causation as well as the existence of multiple evolutionary hierarchies needs to be acknowledged. This furthermore implies that evolution is a pluralistic process divisible into different kinds.

Acta Biotheoretica, 2019

This paper aims to provide a philosophical and theoretical account of biological communication grounded in the notion of organisation. The organisational approach characterises living systems as organised in such a way that they are capable to self-produce and self-maintain while in constant interaction with the environment. To apply this theoretical framework to the study of biological communication, we focus on a specific approach, based on the notion of influence, according to which communication takes place when a signal emitted by a sender triggers a change in the behaviour of the receiver that is functional for the sender itself. We critically analyse the current formulations of this account, that interpret what is functional for the sender in terms of evolutionary adaptations. Specifically, the adoption of this etiological functional framework may lead to the exclusion of several phenomena usually studied as instances of communication, and possibly even of entire fields of investigation such as synthetic biology. As an alternative, we reframe the influence approach in organisational terms, characterising functions in terms of contributions to the current organisation of a biological system. We develop a theoretical account of biological communication in which communicative functions are distinguished from other types of biological functions described by the organisational account (e.g. metabolic, ecological, etc.). The resulting organisational-influence approach allows to carry out causal analyses of current instances of phenomena of communication, without the need to provide etiological explanations. In such a way it makes it possible to understand in terms of communication those phenomena which realise interactive patterns typical of signalling interactions – and are usually studied as such in scientific practice – despite not being the result of evolutionary adaptations. Moreover, this approach provides operational tools to design and study communicative interactions in experimental fields such as synthetic biology.

Philosophical Studies, 2010

Both the quantity of information and the informational content of a signal are defined in the context of signaling games. Informational content is a generalization of standard philosophical notions of propositional content. It is shown how signals that initially carry no information may spontaneously acquire informational content by evolutionary or learning dynamics. It is shown how information can flow through signaling chains or signaling networks. Keywords Information Á Signals Á Content Á Evolution Á Learning Á Signaling networks In the beginning was information. The word came later. Dretske (1981) 1 Epistemology Dretske was calling for a reorientation in epistemology. He did not think that epistemologists should spend their time on little puzzles or on rehashing ancient arguments about skepticism. Rather, he held that epistemology by would be better served by studying the flow of information. I think so too. Other pioneers of this naturalistic point of view, in somewhat different ways, are Millikan (1984) and Harms (2004). Information is carried by signals. It flows through signaling networks.

Current Biology, 2007

Is it possible to untangle the ‘entangled bank’ — Darwin’s metaphor for the complexity and connectedness of species in the natural world? Studies on webs of species interactions suggest so, but a major question remains unanswered: how specialized are different ecological networks? By considering how strongly species interact with each other, information theory may give the answer.

Disputatio. Philosophical Research Bulletin, 2017

In this article I present a proposal for a new epistemic paradigm for the interpretation of complex reticular phenomena: the information network. Starting from an analysis of the concept of network in different contexts, such as in the case of an artificial neuronal network, the signal network of a swarm intelligence or the synaptic network in the brain, the present work has the ambition to identify the common features of all this kinds of net and to start delineating a general epistemic paradigm. The strongest idea of this essay is that the most important thing in a net in not its architecture, but the information content it conveys: any information is here presented as a set of signs, hence, any information network constitutes a semiotic system (which is particularly evident in a swarm intelligence). The nodes of a net can be seen as the agents of a system: each agent locally manipulates signs, modifying in this way its environment (the very semiotic system it belongs to, the information network). Therefore, I argue that the very information structure influences local responses of the individual agents, feedbacks the system and self–organize.

Literature's progress has always come from between words, from between signs & signifiers, from between statements and actions, between characters, between dramas, between epics—as though fiction were a fabric that clothes one thing in order to undress another.