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Originally published in 1992, this work compliments and extends the theory and results of nonlinear psychophysics – an original approach created by the author. It breaks with the traditional mathematics used in the experimental psychology of sensation and draws on what is popularly known as chaos theory and its extension into neural networks. Topical and innovative in its approach, it integrates a diversity of topics previously treated separately into one framework. The properties of the mathematics used are illustrated in the context of substantive problems in psychophysics; thus, it builds strong new bridges between the dynamics of mass action in psychophysical processes and the broader phenomena of sensation. No other treatments of the topic take quite this approach; the use of systems theory, rather than traditional equations of psychophysics dating from the mid-nineteenth century, offers a striking contrast in both theory construction and data analysis.
This work compliments and extends the theory and results of nonlinear psychophysics -- an original approach created by the author. It breaks with the traditional mathematics used in the experimental psychology of sensation and draws on what is popularly known as chaos theory and its extension into neural networks. Topical and innovative in its approach, it integrates a diversity of topics previously treated separately into one framework. The properties of the mathematics used are illustrated in the context of substantive problems in psychophysics; thus, it builds strong new bridges between the dynamics of mass action in psychophysical processes and the broader phenomena of sensation. No other treatments of the topic take quite this approach; the use of systems theory, rather than traditional equations of psychophysics dating from the mid 19th century, offers a striking contrast in both theory construction and data analysis.
The pandemic, and our response to it, has shown how unpredictable, irrational, illogical, suddenly changing, and muddled human interactions can be in a time of crisis. How can we make sense of such confusing and baffling behavior? This book reveals how chaos and nonlinear dynamics can bring new understanding to everyday topics in social sciences. It brings together chapters from leaders at the intersection of psychology and chaos and complexity theories. Conceptual and user-friendly, it is built around six themes: 1) Seeing nonlinearity, 2) Finding patterns, 3) using Simple models, 4) Intervening nonlinearly, and 6) teaching a new Worldview. It takes no specialized study-although there is more sophisticated material and optional math for those wishing it. The techie will, in addition, find concepts and diagrams to ponder. The volume is engaging, at times startling-whether about the weather, Internet, organizations, family dynamics, health, evolution, or falling in love. It reveals how many social, personal, clinical, research, and life phenomena become understandable and can be modelled in the light of Nonlinear Dynamical Systems (NDS) theory. It even offers a broadening worldview, happening already in other sciences, toward a more dynamic, interconnected, and evolving picture, including process-oriented appreciation of one's own experience. The book offers those in the field of psychology and the social sciences a stunning new perspective on human behaviour.
Additional Resource Materials Human behavior would not be interesting to us if it remained the same from one moment to the next. Moreover, we tend to be sensitive to changes in people's behavior, especially when such change impacts on our own, and other's, behavior. This book describes a variety of techniques for investigating change in behavior. It employs conventional time series methods, as well as recently developed methodology using nonlinear dynamics, including chaos, a term that is not easy to define, nor to confirm. Although nonlinear methods are being used more frequently in psychology, a comprehensive coverage of methods, theory and applications, with a particular focus on human behavior, is needed. Between these covers, the reader is led through various procedures for linear and nonlinear time series analysis, including some novel procedures that allow subtle temporal aspects of human cognition to be detected. Analyses of reaction times, heart-rate, psychomotor skill, decision making, and EEG are supplemented by a contemporary review of recent dynamical research in developmental psychology, psychopathology, and human cognitive processes. A consideration of nonlinear dynamics assists our understanding of deep issues such as: Why is our short-term memory capacity limited? Why do chronic disorders, and also cognitive development, progress through stage-like transitions? Why do people make irrational decisions? This book will be of particular interest to researchers, practitioners, and advanced students in a variety of areas in psychology, particularly in human experimental and physiological psychology. Data analyses are performed using the latest nonlinear dynamics computer packages. A comprehensive WWW resource of software and supplementary information is provided to assist the reader's understanding of the novel, and potentially revolutionary, procedures described in the book.
This collective volume is the first to discuss systematically what are the possibilities to model different aspects of brain and mind functioning with the formal means of fractal geometry and deterministic chaos. At stake here is not an approximation to the way of actual performance, but the possibility of brain and mind to implement nonlinear dynamic patterns in their functioning. The contributions discuss the following topics (among others): the edge-of-chaos dynamics in recursively organized neural systems and in intersensory interaction, the fractal timing of the neural functioning on different scales of brain networking, aspects of fractal neurodynamics and quantum chaos in novel biophysics, the fractal maximum-power evolution of brain and mind, the chaotic dynamics in the development of consciousness, etc. It is suggested that the ‘margins’ of our capacity for phenomenal experience, are ‘fractal-limit phenomena’. Here the possibilities to prove the plausibility of fractal modeling with appropriate experimentation and rational reconstruction are also discussed. A conjecture is made that the brain vs. mind differentiation becomes possible, most probably, only with the imposition of appropriate symmetry groups implementing a flowing interface of features of local vs. global brain dynamics. (Series B)
This book is a series of case studies with a common theme. Some refer closely to previous work by the author, but contrast with how they have been treated before, and some are new. Comparisons are drawn using various sorts of psychological and psychophysiological data that characteristically are particularly nonlinear, non-stationary, far from equilibrium and even chaotic, exhibiting abrupt transitions that are both reversible and irreversible, and failing to meet metric properties. A core idea is that both the human organism and the data analysis procedures used are filters, that may variously preserve, transform, distort or even destroy information of significance.
Relational Psychophysics in Humans and Animals offers a comprehensive and integrated overview of the often fragmented field of psychophysics. It introduces key concepts in psychophysics and clearly summarises and illustrates the central issues through telling examples. It combines empirical research and theoretical approaches from general psychophysics, animal psychophysics and human-infant psychophysics, to create a systematic comparison of these three key areas. Through out, Viktor Sarris makes a strong case for more comparative psychophysical research across different species and across different stages of development. He presents original research and examines frame-of-reference models, behavioural psychophysics, developmental psychophysics, perceptual-cognitive psychophysics and evolutionary perspectives, to create an integrated framework for the direction of new research. The book will be an invaluable aid for researchers in the fields of perception and psychophysics.
Although its roots can be traced to the 19th century, progress in the study of nonlinear dynamical systems has taken off in the last 30 years. While pertinent source material exists, it is strewn about the literature in mathematics, physics, biology, economics, and psychology at varying levels of accessibility. A compendium research methods reflect
Psychophysics is by definition mappings between events in the environment and levels of human sensory responses. In this text the methods of nonlinear dynamics, employing trajectories developed for simpler sensory modelling, are extended to classes of problems which lie at the interface between sensation and perception. A diversity of topics for which extensive empirical evidence exists are reformulated by writing their dynamics in terms of complex trajectories put into coupled lattices and into cascades of such lattices. Fundamental relationships between core processes of psychophysics in time and space, and recurrent quantitative or topological distortions of the physical world which arise in perception, are given a treatment which contrasts fundamentally with traditional linear equations in use since the 19th century.
Social (psychological and sociological) systems present considerable difficulties for modellers due to their complexity, multidimensionality, uncertainty and irreducibility. The book proposes that response functions (MRF) be used as a method of constructing purposeful, credible and integrated social systems' models from data and prior knowledge or information. A semi-empirical, or "grey-box", MRF model may be regarded as a trade-off between a knowledge-based model and a "black-box" (empirical) model. It may embody all the existing knowledge on the process (or a part thereof) and, in addition, it relies on parameterised functions, whose parameters are determined from measurements. Observations contain hidden information on the processes under consideration and one of the main purposes of the proposed method is to "extract" and describe these hidden relationships. Parameterisation offers ways to couple qualitative with quantitative analysis. This combination makes it possible to take into account all the phenomena that are not modelled with the required accuracy through prior knowledge. Although only a simplified picture of the processes is modelled, a "grey box" system model provides some insight into the system processes. These processes are featured by chains of causality, highlighting stressors and variables responsive to stressors. The method of response functions is a nonlinear regression method that implies credible models in the sense that they are identifiable and, hopefully, explain system output behaviour satisfactorily. For case studies the authors have selected the problems usually studied by psychologists and sociologists with statistical procedures, such as investigation of variance and discriminant analysis based on the general linear model or one of its multivariate generalisations (structural equation models, etc.); disordered eating and obesity; subjective well-being and alexithymia. An accompanying CD-ROM contains the demonstration versions of three models that are discussed in the various chapters.The Method of Response Functions in Psychology and Sociology is aimed at Mathematical Psychologists; Mathematical Sociologists; Applied Psychologists; Sociologists and Social Practitioners. It will also be suitable for use on undergraduate as well as graduate and postgraduate courses specializing in these areas.