2024 Hardcover Reprint of Original 1959 Edition. Exact facsimile of the original edition, not reproduced with Optical Recognition Software. This book by one of the world's foremost philosophers of science presented a striking new picture of the logical character of scientific discovery--a picture which does full justice to the liberating effect of the Einsteinian revolution in physics and its immense impact upon scientific thought in general. For this new English edition Dr. Popper did his own translation and has written 150 pages of entirely new text. Ernest Nagel considered this work "a first rate contribution to the logic of scientific method. The book contains a very interesting chapter on quantum mechanics, which performs one of the few sensible analyses of the Indeterminacy Principle which I have seen in print... The book is highly stimulating and contains much that is bed-rock for future work."--From the Dusk Jacket.

Methods in Neuronal Modeling is the first technical handbook on computational neuroscience. Written for researchers and theoreticians alike, it outlines methods and techniques used for simulating on digital computers the functional properties of single neurons from synapses, dendrites, single cells; and small invertebrate networks to large scale neural networks in the mammalian nervous system. The use of new experimental tools such as selective staining methods, membrane patch electrodes, voltage and calcium-dependent dyes, and multielectrode recordings, together with the, advent of universally available powerful computing, makes it possible to construct detailed and realistic models of neuronal systems. Methods in Neuronal Modeling addresses such questions as what can and should be simulated and what techniques should be used; what experimental parameters are crucial for such simulations, and whether these models may be verified experimentally. Chapters cover simulation of passive dendritic trees, compartmental models of single cells including neurons with a number of different ionic channels, calcium current dynamics, simulations of small invertebrate networks, simulations of the mammalian cortex, connectionists' models, and the use of parallel computers in modeling neural networks. Although the chapters were written by several authors, they are uniform in structure and notation. Detailed examples are given to clarify the different approaches. Each chapter concludes with a description of the model discussed and the details of its implementation on the computer. Christof Koch is an Assistant Professor of Computation and Neural Systems at the California Institute of Technology. Idan Segev is a Lecturer in Neurobiology at the Institute of Life Science, Hebrew University of Jerusalem. Methods in Neuronal Modeling inaugurates the new series in Computational Neuroscience, edited by Terrence J. Sejnowski and Tomaso Poggio. A Bradford Book.