An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent (...) explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993. (shrink)

In this book, Newell makes the case for unified theories by setting forth a candidate.

What enables individually simple insects like ants to act with such precision and purpose as a group? How do trillions of individual neurons produce something as extraordinarily complex as consciousness? What is it that guides self-organizing structures like the immune system, the World Wide Web, the global economy, and the human genome? These are just a few of the fascinating and elusive questions that the science of complexity seeks to answer. In this remarkably accessible and companionable book, leading complex systems (...) scientist Melanie Mitchell provides an intimate, detailed tour of the sciences of complexity, a broad set of efforts that seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals. Comprehending such systems requires a wholly new approach, one that goes beyond traditional scientific reductionism and that re-maps long-standing disciplinary boundaries. Based on her work at the Santa Fe Institute and drawing on its interdisciplinary strategies, Mitchell brings clarity to the workings of complexity across a broad range of biological, technological, and social phenomena, seeking out the general principles or laws that apply to all of them. She explores as well the relationship between complexity and evolution, artificial intelligence, computation, genetics, information processing, and many other fields. Richly illustrated and vividly written, Complexity : A Guided Tour offers a comprehensive and eminently comprehensible overview of the ideas underlying complex systems science, the current research at the forefront of this field, and the prospects for the field's contribution to solving some of the most important scientific questions of our time. (shrink)

NOW IN PAPERBACK"€"Starting from a collection of simple computer experiments"€"illustrated in the book by striking computer graphics"€"Stephen Wolfram shows how their unexpected results force a whole new way of looking at the operation of our universe.

People coordinate body postures and gaze patterns during conversation. We review literature showing that (1) action embodies cognition, (2) postural coordination emerges spontaneously when two people converse, (3) gaze patterns influence postural coordination, (4) gaze coordination is a function of common ground knowledge and visual information that conversants believe they share, and (5) gaze coordination is causally related to mutual understanding. We then consider how coordination, generally, can be understood as temporarily coupled neuromuscular components that function as a collective unit (...) known as a coordinative structure in the motor control literature. We speculate that the coordination of gaze and body sway found in conversation may be understood as a cross‐person coordinative structure that embodies the goals of the joint action system. (shrink)

We investigated the coupling between a speaker's and a listener's eye movements. Some participants talked extemporaneously about a television show whose cast members they were viewing on a screen in front of them. Later, other participants listened to these monologues while viewing the same screen. Eye movements were recorded for all speakers and listeners. According to cross‐recurrence analysis, a listener's eye movements most closely matched a speaker's eye movements at a delay of 2 sec. Indeed, the more closely a listener's (...) eye movements were coupled with a speaker's, the better the listener did on a comprehension test. In a second experiment, low‐level visual cues were used to manipulate the listeners' eye movements, and these, in turn, influenced their latencies to comprehension questions. Just as eye movements reflect the mental state of an individual, the coupling between a speaker's and a listener's eye movements reflects the success of their communication. (shrink)

The theory of the organism-environment system starts with the proposition that in any functional sense organism and environment are inseparable and form only one unitary system. The organism cannot exist without the environment and the environment has descriptive properties only if it is connected to the organism. Although for practical purposes we do separate organism and environment, this common-sense starting point leads in psychological theory to problems which cannot be solved. Therefore, separation of organism and environment cannot be the basis (...) of any scientific explanation of human behavior. The theory leads to a reinterpretation of basic problems in many fields of inquiry and makes possible the definition of mental phenomena without their reduction either to neural or biological activity or to separate mental functions. According to the theory, mental activity is activity of the whole organism-environment system, and the traditional psychological concepts describe only different aspects of organisation of this system. Therefore, mental activity cannot be separated from the nervous system, but the nervous system is only one part of the organism­environment system. This problem will be dealt with in detail in the second part of the article. (shrink)

Most models of response time (RT) in elementary cognitive tasks implicitly assume that the speed-accuracy trade-off is continuous: When payoffs or instructions gradually increase the level of speed stress, people are assumed to gradually sacrifice response accuracy in exchange for gradual increases in response speed. This trade-off presumably operates over the entire range from accurate but slow responding to fast but chance-level responding (i.e., guessing). In this article, we challenge the assumption of continuity and propose a phase transition model for (...) RTs and accuracy. Analogous to the fast guess model (Ollman, 1966), our model postulates two modes of processing: a guess mode and a stimulus-controlled mode. From catastrophe theory, we derive two important predictions that allow us to test our model against the fast guess model and against the popular class of sequential sampling models. The first prediction—hysteresis in the transitions between guessing and stimulus-controlled behavior—was confirmed in an experiment that gradually changed the reward for speed versus accuracy. The second prediction—bimodal RT distributions—was confirmed in an experiment that required participants to respond in a way that is intermediate between guessing and accurate responding. (shrink)

Where Medicine Went Wrong explores how the idea of an average value has been misapplied to medical phenomena, distorted understanding and lead to flawed medical ...

Residual fluctuations produced in typical experimental methodologies are examined as correlated noises. The effective range of the correlations was assessed by determining whether the decay over look‐back time is better described as a power law or exponential. Both of these decay laws contain free parameters and it is argued that it is not possible to distinguish their models on the basis of simple measures of goodness‐of‐fit. Global analyses that evaluate models on the basis of how well they generalize are conducted. (...) The models are examined in terms of three constructs that all bear on generalization: cross‐validity, flexibility, and representativeness. Quantitative assessment of a large ensemble of data suggests that the correlations decay over time as a power law. The conclusion is that human residual fluctuation is a correlated fractal. (shrink)

The temporal granularity of consciousness may be far less fine than the real-time information processing mechanisms that underlie our sensitivity to small temporal differences. It is suggested that conscious time perception, like space perception, is subject to errors that belie a unitary underlying representation. E. R. Clay's concept of the “specious present,” an extended moment represented in consciousness, is suggested as an alternative to the more common notion of instantaneous experience that underlies much reasoning based on the “time of arrival” (...) in consciousness. (shrink)

Observations of ultrafast cognition in human performance challenge intuitive information processing and computation metaphors of cognitive processing. Instances of ultrafast cognition are marked by ultrafast response times of reliable, accurate responses to a relatively complex stimulus. Ultrafast means response times that are as fast as a single feedforward burst of activity across the nervous system connecting eye to hand. Thus the information processing and computation metaphors in question are those in which some amount of time is required to decide and (...) initiate a response, over and above the minimum time required, physiologically, for the eye-hand chain of action potentials—these are metaphors in which the brain does work that has a measurable duration in time. Ultrafast cognition can be explained by synergies spanning the mind and body. Synergies are temporary dynamical structures that anticipate context-appropriate behaviour. An anticipatory state poises the mind and body in symmetry among equivalent options for behaviour, and only a minimal change in context, favouring one option over any other, is sufficient to break symmetry and enact an ultrafast cognitive response. (shrink)

Many previous treatments of voluntary behavior have viewed intentions as causes of behavior. This has resulted in several dilemmas, including a dilemma concerning the origin of intentions. The present article circumvents traditional dilemmas by treating intentions as constraints that restrict degrees of freedom for behavior. Constraints self-organize as temporary dynamic structures that span the mind-body divide. This treatment of intentions and voluntary behavior yields a theory of intentionality that is consistent with existing findings and supported by current research.

Does a concurrent cognitive task affect the dynamics of bimanual rhythmic coordination? In‐phase coordination was performed under manipulations of phase detuning and movement frequency and either singly or in combination with an arithmetic task. Predicted direction‐specific shifts in stable relative phase from 0° due to detuning and movement frequency were amplified by the cognitive task. Nonlinear cross‐recurrence analysis suggested that this cognitive influence on the locations of the stable points or attractors of coordination entailed a magnification of attractor noise without (...) a reduction in attractor strength. An approximation to these findings was achieved through parameter changes in a motion equation in relative phase. Results are discussed in terms of dual‐task performance as limited resources, dynamics rather than chronometrics, and reparameterization rather than degradation. (shrink)