This volume represents the edited proceedings of the International Symposium on Mathematical Biology held in Kyoto, November 10-15, 1985. The symposium was or ganized by an international committee whose members are: E. Teramoto, M. Yamaguti, S. Amari, S.A. Levin, H. Matsuda, A. Okubo, L.M. Ricciardi, R. Rosen, and L.A. Segel. The symposium included technical sessions with a total of 11 invited papers, 49 contributed papers and a poster session where 40 papers were displayed. These Proceedings consist of selected papers from this symposium. This symposium was the second Kyoto meeting on mathematical topics in biology. The first was held in conjunction with the Sixth International Biophysics Congress in 1978. Since then this field of science has grown enormously, and the number of scientists in the field has rapidly increased. This is also the case in Japan. About 80 young japanese scientists and graduate students participated this time. . The sessions were divided into 4 ; , categories: 1) Mathematical Ecology and Population Biology, 2) Mathematical Theory of Developmental Biology and Morphogenesis, 3) Theoretical Neurosciences, and 4) Cell Kinetics and Other Topics. In every session, there were stimulating and active discussions among the participants. We are convinced that the symposium was highly successful in transmitting scientific information across disciplines and in establishing fruitful contacts among the participants. We owe this success to the cooperation of all participants.

This volume is dedicated to the memory of Professor Stavros Busenberg of Harvey Mudd College, who contributed so greatly to this field during 25 years prior to his untimely death. It contains about 60 invited papers by leading researchers in the areas of dynamical systems, mathematical studies in ecology, epidemics, and physiology, and industrial mathematics. Anyone interested in these areas will find much of value in these contributions.

This volume includes papers originally presented at the 8th annual Computational Neuroscience meeting (CNS'99) held in July of 1999 in Pittsburgh, Pennsylvania. The CNS meetings bring together computational neuroscientists representing many different fields and backgrounds as well as experimental preparations and theoretical approaches. The papers published here range across vast levels of scale from cellular mechanisms to cognitive brain studies. The subjects of the research include many different preparations from invertebrates to humans. In all cases the work described in this volume is focused on understanding how nervous systems compute. The research described includes subjects like neural coding and neuronal dendrites and reflects a trend towards forging links between cognitive research and neurobiology. Accordingly, this volume reflects the breadth and depth of current research in computational neuroscience taking place throughout the world.

Divided into two volumes, the book begins with a pedagogical presentation of some of the basic theory, with chapters on biochemical reactions, diffusion, excitability, wave propagation and cellular homeostasis. The second, more extensive part discusses particular physiological systems, with chapters on calcium dynamics, bursting oscillations and secretion, cardiac cells, muscles, intercellular communication, the circulatory system, the immune system, wound healing, the respiratory system, the visual system, hormone physiology, renal physiology, digestion, the visual system and hearing. New chapters on Calcium Dynamics, Neuroendocrine Cells and Regulation of Cell Function have been included. Reviews from first edition: Keener and Sneyd's Mathematical Physiology is the first comprehensive text of its kind that deals exclusively with the interplay between mathematics and physiology. Writing a book like this is an audacious act! -Society of Mathematical Biology Keener and Sneyd's is unique in that it attempts to present one of the most important subfields of biology and medicine, physiology, in terms of mathematical "language", rather than organizing materials around mathematical methodology. -SIAM review

From the preface by Joel E. Cohen: "A century from now humanity will live in a managed - or mismanaged - global garden. We are debating the need to preserve tropical forests. Farming of the sea is providing an increasing part of our fish supply. We are beginning to control atmospheric emissions. In 100 years, we shall use novel farming practices and genetic engineering of bacteria to manipulate the methane production of rice fields. The continental shelf will be providing food, energy, possibly even living space. To make such intensive management possible will require massive improvements in data collection and analysis, and especially in our concepts. A century hence we will live on a wired earth: the oceans and the crust of the earth will receive the same comprehensive monitoring now devoted to weather. As the peoples of currently developing countries increase their levels of wealth, the need for global management will become irresistible as impatience with the accidents of nature and intolerance of mismanagement of the environment - especially of living resources - grow. Our control of physical perturbations and chemical inputs to the environment will be judged by the consequences to living organisms and biological communities. How can we obtain the factual and theoretical foundation needed to move from our present, fragmented knowledge and limited abilities to a managed, global garden?" This problem was addressed in the lectures and workshops of a summer school on patch dynamics at Cornell University. The school emphasized the analysis and interpretation of spatial patterns in terrestrial and marine environments. This book contains the course material of this school, combining general reviews with specific applications.

Neurons in the brain communicate with each other by transmitting sequences of electrical spikes or action potentials. One of the major challenges in neuroscience is to understand the basic physiological mechanisms underlying the complex spatiotemporal patterns of spiking activity observed during normal brain functioning, and to determine the origins of pathological dynamical states, such as epileptic seizures and Parkinsonian tremors. A second major challenge is to understand how the patterns of spiking activity provide a substrate for the encoding and transmission of information, that is, how do neurons compute with spikes? It is likely that an important element of both the dynamical and computational properties of neurons is that they can exhibit bursting, which is a relatively slow rhythmic alternation between an active phase of rapid spiking and a quiescent phase without spiking. This book provides a detailed overview of the current state-of-the-art in the mathematical and computational modelling of bursting, with contributions from many of the leading researchers in the field.

This volume includes papers presented at the Sixth Annual Computational Neurosci ence meeting (CNS*97) held in Big Sky, Montana, July 6-10, 1997. This collection includes 103 of the 196 papers presented at the meeting. Acceptance for meeting presentation was based on the peer review of preliminary papers originally submitted in January of 1997. The papers in this volume represent final versions of this work submitted in January of 1998. Taken together they provide a cross section of computational neuroscience and represent well the continued vitality and growth of this field. The meeting in Montana was unusual in several respects. First, to our knowledge it was the first international scientific meeting with opening ceremonies on horseback. Second, after five days of rigorous scientific discussion and debate, meeting participants were able to resolve all remaining conflicts in barrel race competitions. Otherwise the magnificence of Montana and the Big Sky Ski Resort assured that the meeting will not soon be forgotten. Scientifically, this volume once again represents the remarkable breadth of subjects that can be approached with computational tools. This volume and the continuing CNS meet ings make it clear that there is almost no subject or area of modem neuroscience research that is not appropriate for computational studies.

What every neuroscientist should know about the mathematical modeling of excitable cells, presented at an introductory level.

In August 1988. the Sixth International Coral Reef Symposium was held in Townsville resulting in an influx of most of the world's coral reef sCientists to the city. We seized this opportunity at the Australian Institute of Marine Science to run a small workshop immediately before the symposium on the outbreaks of the crown-of-thorns starfish. Aeanthaster planei. We invited that small band of mathematicians who had been modelling the phenomenon, (and who may not have normally attended an international meeting so thoroughly dedicated to natural science) to meet with those SCientists who had been been actively working on the phenomenon in the field. John Casti notes in his delightful new book Alternate Realities (Wiley, 1989): 'If the natural role of the experimenter is to generate new observables by which we know the processes of Nature, and the natural role of the mathematician is to generate new formal structures by which we can represent these processes. then the system SCientist finds his niche by serving as a broker between the two. ' I think our book shows the fruits of that brokerage through the wide range of models explored within its pages. the high level of collaboration and interaction across disciplines evident in the individual papers, and in the emerging synthesis that reflects a far deeper understanding of this complex phenomenon than was possible even a few years ago.

The "raison d'etre" of hierarchical dustering theory stems from one basic phe nomenon: This is the notorious non-transitivity of similarity relations. In spite of the fact that very often two objects may be quite similar to a third without being that similar to each other, one still wants to dassify objects according to their similarity. This should be achieved by grouping them into a hierarchy of non-overlapping dusters such that any two objects in ~ne duster appear to be more related to each other than they are to objects outside this duster. In everyday life, as well as in essentially every field of scientific investigation, there is an urge to reduce complexity by recognizing and establishing reasonable das sification schemes. Unfortunately, this is counterbalanced by the experience of seemingly unavoidable deadlocks caused by the existence of sequences of objects, each comparatively similar to the next, but the last rather different from the first.