Biological computation: hearts and flytraps

The original computers were people using algorithms to get mathematical results such as rocket trajectories. After the invention of the digital computer, brains have been widely understood through analogies with computers and now artificial neural networks, which have strengths and drawbacks. We define and examine a new kind of computation better adapted to biological systems, called biological computation, a natural adaptation of mechanistic physical computation. Nervous systems are of course biological computers, and we focus on some edge cases of biological computing, hearts and flytraps. The heart has about the computing power of a slug, and much of its computing happens outside of its forty thousand neurons. The flytrap has about the computing power of a lobster ganglion. This account advances fundamental debates in neuroscience by illustrating ways that classical computability theory can miss complexities of biology. By this reframing of computation, we make way for resolving the disconnect between human and machine learning.

     

The role of computation in modeling evolution

Artificial life uses computers and formal systems to model and explore the dynamics of evolution. A fundamental question for A-Life concerns the role of computation in these models, and how we are to interpret computer implementations that do not have actual contact with physical systems. In this paper I will discuss how models are seen to explain and predict in philosophy of science and how these ideas apply to A-Life. I will also explore how the notion of an epistemic cut, as defined by H. Pattee, can be realized in a computational model with an artificial physical world.     

The sociological critique of evolutionary psychology: Beyond mass modularity

This paper addresses evolutionary psychology's (EP's) mass modularity account of human intelligence. First, EP is located within 'naturalization of society' discourses. Secondly, the nature and weakness of mass modularity theory is examined. In the third part of the paper, the genetic reductionism of EP is challenged with reference to developmental systems theory (DST). However, in the fourth part, the danger of importing one biological theory to defuse the colonial ambitions of another is highlighted through an examination of sociological systems theory and its relationship with biological systems theory. Nevertheless, DST has stimulated valuable insights in theoretical sociology/anthropology. Modularity is also common in computer models of intelligence as algorithmic computation. EP draws parallels with computer modelling to claim confirmation of its own account. The fifth part of this article challenges the validity of this parallel, drawing upon Harry Collins's sociology of what humans and computers can do. Collins's work highlights the non-modular cultural 'rules' that today's computers cannot follow. In the light of these theoretical and empirical developments I conclude that contemporary sociology offers a valuable and systematic counter to discourses of genetic reductionism and the discourses of technological determination upon which they are parasitic.     

Methodological problems in evolutionary biology

One of the major criticisms of optimal foraging theory (OFT) is that it is not testable. In discussions of this criticism opposing parties have confused methodological concepts and used meaningless biological concepts. In this paper we discuss such misunderstandings and show that OFr has an empirically testable, and even well-confirmed, general core theory. One of our main conclusions is that specific model testing should not be aimed at proving optimality, but rather at identifying the context in which certain types of behaviour are optimal. To do this, it is necessary to be aware of the assumptions made in testing a model. The assumptions that are explicitly stated in the literature up to now do not completely cover the actual assumptions made in testing OFT models in practice. We present a more comprehensive set of assumptions. Although all the assumptions play a role in testing models, they are not of equal status. Crucial assumptions concern constraints and the relation between fitness and currency. Therefore, it is essential to make such assumptions testable in practice. We show that a more explicit relationship between OFT modelling and evolutionary theory can help with this. Specifically, phylogeny reconstruction and population dynamic modelling can and should be used to formulate assumptions concerning constraints and currencies.     

The measurement problem in artificial world models

The only epistemic relations between the world and organisms are established through evolution by natural selection, and learning by observation and measurement. In physics, measurements map an open domain of physical structure to a closed set of symbols. A basic problem in simulating evolution and measurement is that neither activity can be adequately formalized. Artificial world models based on programmable computers require a formalized domain of symbols in which the concepts of evolution and measurement are limited. The measurement problem also bears on the questions of the relation of computation to physics and to formal symbol systems and on what sense dissipationless computation is a useful concept.     

A call for a new paradigm of island biogeography

MacArthur and Wilson’s equilibrium theory of island biogeography quickly became the paradigm of the field in the 1960s and has strongly influenced this and other disciplines of ecology and conservation biology for the past three decades. Recently, however, a growing number of ecologists have begun to question whether the theory remains a useful paradigm for modern ecology. We now have a much better appreciation for the complexity of nature and we study patterns that span a very broad range in spatial, temporal and ecological scales. At such scales, assumptions that communities are in equilibrium, that species, islands and intervening landscapes or seascapes are equivalent or homogeneous with respect to factors influencing immigration and extinction, and that in situ speciation can be overlooked become very tenuous. With this in mind, this and other papers of this special feature discuss the principal, conceptual shortcomings of the equilibrium theory and offer some modifications or alternatives to the theory that we hope will eventually lead to a more comprehensive understanding of the forces structuring insular communities.     

Natural selection and the maximization of fitness

The notion that natural selection is a process of fitness maximization gets a bad press in population genetics, yet in other areas of biology the view that organisms behave as if attempting to maximize their fitness remains widespread. Here I critically appraise the prospects for reconciliation. I first distinguish four varieties of fitness maximization. I then examine two recent developments that may appear to vindicate at least one of these varieties. The first is the ‘new’ interpretation of Fisher's fundamental theorem of natural selection, on which the theorem is exactly true for any evolving population that satisfies some minimal assumptions. The second is the Formal Darwinism project, which forges links between gene frequency change and optimal strategy choice. In both cases, I argue that the results fail to establish a biologically significant maximization principle. I conclude that it may be a mistake to look for universal maximization principles justified by theory alone. A more promising approach may be to find maximization principles that apply conditionally and to show that the conditions were satisfied in the evolution of particular traits.     

A sticker-based model for DNA computation.

We introduce a new model of molecular computation that we call the sticker model. Like many previous proposals it makes use of DNA strands as the physical substrate in which information is represented and of separation by hybridization as a central mechanism. However, unlike previous models, the stickers model has a random access memory that requires no strand extension and uses no enzymes; also (at least in theory), its materials are reusable. The paper describes computation under the stickers model and discusses possible means for physically implementing each operation. Finally, we go on to propose a specific machine architecture for implementing the stickers model as a microprocessor-controlled parallel robotic workstation. In the course of this development a number of previous general concerns about molecular computation (Smith, 1996; Hartmanis, 1995; Linial et al., 1995) are addressed. First, it is clear that general-purpose algorithms can be implemented by DNA-based computers, potentially solving a wide class of search problems. Second, we find that there are challenging problems, for which only modest volumes of DNA should suffice. Third, we demonstrate that the formation and breaking of covalent bonds is not intrinsic to DNA-based computation. Fourth, we show that a single essential biotechnology, sequence-specific separation, suffices for constructing a general-purpose molecular computer. Concerns about errors in this separation operation and means to reduce them are addressed elsewhere (Karp et al., 1995; Roweis and Winfree, 1999). Despite these encouraging theoretical advances, we emphasize that substantial engineering challenges remain at almost all stages and that the ultimate success or failure of DNA computing will certainly depend on whether these challenges can be met in laboratory investigations.     

Relatedness in spatially structured populations with empty sites: An approach based on spatial moment equations

Taking into account the interplay between spatial ecological dynamics and selection is a major challenge in evolutionary ecology. Although inclusive fitness theory has proven to be a very useful tool to unravel the interactions between spatial genetic structuring and selection, applications of the theory usually rely on simplifying demographic assumptions. In this paper, I attempt to bridge the gap between spatial demographic models and kin selection models by providing a method to compute approximations for relatedness coefficients in a spatial model with empty sites. Using spatial moment equations, I provide an approximation of nearest-neighbour relatedness on random regular networks, and show that this approximation performs much better than the ordinary pair approximation. I discuss the connection between the relatedness coefficients I define and those used in population genetics, and sketch some potential extensions of the theory.     

Economic and ecological views on climate change mitigation with bioenergy and negative emissions

Climate stabilization scenarios emphasize the importance of land‐based mitigation to achieve ambitious mitigation goals. The stabilization scenarios informing the recent IPCC's Fifth Assessment Report suggest that bioenergy could contribute anywhere between 10 and 245 EJ to climate change mitigation in 2100. High deployment of bioenergy with low life cycle GHG emissions would enable ambitious climate stabilization futures and reduce demands on other sectors and options. Bioenergy with carbon capture and storage (BECCS) would even enable so‐called negative emissions, possibly in the order of magnitude of 50% of today's annual gross emissions. Here, I discuss key assumptions that differ between economic and ecological perspectives. I find that high future yield assumptions, plausible in stabilization scenarios, look less realistic when evaluated in biophysical metrics. Yield assumptions also determine the magnitude of counterfactual land carbon stock development and partially determine the potential of BECCS. High fertilizer input required for high yields would likely hasten ecosystem degradation. I conclude that land‐based mitigation strategies remain highly speculative; a constant iteration between synoptic integrated assessment models and more particularistic and fine‐grained approaches is a crucial precondition for capturing complex dynamics and biophysical constraints that are essential for comprehensive assessments.     

Representations of Nature on the Mongolian Steppe: An Investigation of Scientific Knowledge Construction

Extensive land degradation across the Mongolian steppe has prompted a variety of multinational and multidisciplinary research projects over recent years. The situation provides an important opportunity to investigate and illuminate some of the international, national, and local dimensions of scientific practice that critically condition the production of environmental knowledge. In this article I juxtapose the competing knowledge bases and assumptions of various relevant groups (including natural vs. social scientists, nationalist Chinese vs. ethnic Mongolians, and urban intellectuals vs. indigenous herders) to develop the argument that multiple ideological and institutional boundaries work together to circumscribe scientific inquiry and data collection. The situated construction of knowledge undermines prospects for improving incremental objectivity and impedes more comprehensive understanding of serious environmental problems. [Chinese grasslands, land degradation, indigenous knowledge, sociology of science, interdisciplinary research]     

Levels and loops: the future of artificial intelligence and neuroscience

In discussing artificial intelligence and neuroscience, I will focus on two themes. The first is the universality of cycles (or loops): sets of variables that affect each other in such a way that any feed-forward account of causality and control, while informative, is misleading. The second theme is based around the observation that a computer is an intrinsically dualistic entity, with its physical set-up designed so as not to interfere with its logical set-up, which executes the computation. The brain is different. When analysed empirically at several different levels (cellular, molecular), it appears that there is no satisfactory way to separate a physical brain model (or algorithm, or representation), from a physical implementational substrate. When program and implementation are inseparable and thus interfere with each other, a dualistic point-of-view is impossible. Forced by empiricism into a monistic perspective, the brain-mind appears as neither embodied by or embedded in physical reality, but rather as identical to physical reality. This perspective has implications for the future of science and society. I will approach these from a negative point-of-view, by critiquing some of our millennial culture's popular projected futures.     

Buffon, Darwin, and the Non-Individuality of Species – A Reply to Jean Gayon

Gayon's recent claim that Buffon developed a concept of species as physical individuals is critically examined and rejected. Also critically examined and rejected is Gayon's more central thesis that as a consequence of his analysis of Buffon's species concept, and also of Darwin's species concept, it is clear that modern evolutionary theory does not require species to be physical individuals. While I agree with Gayon's conclusion that modern evolutionary theory does not require species to be physical individuals, I disagree with his reasons and instead provide logical rather than historical reasons for the same conclusion.     

Survey of research in the theory of homogeneous structures and their applications

This work presents some of the author's reflections, the purpose of which is to give an orientation on the present stage and recent developments in the investigations of the theory of homogeneous structures and their applications. This survey appears to be desirable at this time because a number of research workers in mathematical and theoretical biology are becoming interested in making contributions in the theory of homogeneous structures and their applications. It is hoped that this survey will provide a stimulus and some introduction to the subject. The choice of topics is dictated largely by my predilections, and in no way shall I attempt to illustrate the vast and rapidly increasing field of applications of mathematical techniques or even, more generally, the mathematical mode of thinking in the enormous variety of problems in the theory of homogeneous structures and its applications, including biology. Indeed, to present anything like a comprehensive picture would require bulky and manifold volumes of very heterogeneous contributions. However, I shall list a number of biological and engineering fields where techniques of homogeneous structures have been employed and give the reader a short indication of selected bibliographic aids.     

The seven deadly sins of comparative analysis

Phylogenetic comparative methods are extremely commonly used in evolutionary biology. In this paper, I highlight some of the problems that are frequently encountered in comparative analyses and review how they can be fixed. In broad terms, the problems boil down to a lack of appreciation of the underlying assumptions of comparative methods, as well as problems with implementing methods in a manner akin to more familiar statistical approaches. I highlight that the advent of more flexible computing environments should improve matters and allow researchers greater scope to explore methods and data.     

One equation to rule them all: a philosophical analysis of the Price equation

This paper provides a philosophical analysis of the Price equation and its role in evolutionary theory. Traditional models in population genetics postulate simplifying assumptions in order to make the models mathematically tractable. On the contrary, the Price equation implies a very specific way of theorizing, starting with assumptions that we think are true and then deriving from them the mathematical rules of the system. I argue that the Price equation is a generalization-sketch, whose main purpose is to provide a unifying framework for researchers, helping them to develop specific models. The Price equation plays this role because, like other scientific principles, shows features as abstractness, unification and invariance. By underwriting this special role for the Price equation some recent disputes about it could be diverted.     

Bearing Witness: Assumptions, Realities, and the Otherizing of Katrina

As post-Katrina rebuilding of Louisiana and Mississippi proceeds, we should heed the lessons from anthropologists and others studying aid and development in other parts of the world who point out that aid is often predicated on poorly examined assumptions about beneficiaries and local conditions. Hence, as the recovery after Katrina continues, assumptions about the U.S. South and about poverty, race, and class in the United States must be exposed and examined as well as assumptions about disaster victims and relief. Drawing on personal experiences, I examine here some of the assumptions with which I operated as a small group of friends and I organized an unofficial relief team to provide whatever aid we could to people on the Mississippi Gulf coast in the first few weeks after Hurricane Katrina. I recount the disconnections between my assumptions and the local conditions as relayed by Katrina survivors or that members of the team and I witnessed firsthand.     

Human attention: the exclusion of distracting information as a function of real and apparent separation of relevant and irrelevant events

A leading theory suggests that human vision operates by separate and parallel analysis of each of the simple features of the visual scene; but computation of the identity of objects, which needs combination of these features, is undertaken selectively and only for some parts of the incoming information. It is known that the identity of distracting events affects reaction time only for distractors spatially close to the reaction signal. This suggests that the selection is spatially based; perhaps taking place in the projection areas. Experiments on this topic have, however, normally considered events only at a fixed viewing distance; in this study different viewing distances were employed. It was found that, over the range of conditions used, the ability to exclude irrelevant distractors depended upon the true physical separation and not on the angular separation at the eye of the observer. Hence the 'attention' system must operate at a point later than the computation of true physical location, rather than at the very early stage where angular separation only is available.     

DNA computing using single-molecule hybridization detection

DNA computing aims at using nucleic acids for computing. Since micromolar DNA solutions can act as billions of parallel nanoprocessors, DNA computers can in theory solve optimization problems that require vast search spaces. However, the actual parallelism currently being achieved is at least a hundred million-fold lower than the number of DNA molecules used. This is due to the quantity of DNA molecules of one species that is required to produce a detectable output to the computations. In order to miniaturize the computation and considerably reduce the amount of DNA needed, we have combined DNA computing with single-molecule detection. Reliable hybridization detection was achieved at the level of single DNA molecules with fluorescence cross-correlation spectroscopy. To illustrate the use of this approach, we implemented a DNA-based computation and solved a 4-variable 4-clause instance of the computationally hard Satisfiability (SAT) problem.