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CIP record for this book is available from the British Library

      ISBN 978-1-78630-472-8

      Acknowledgments

      I wish to thank my colleagues, Virginie Hoel, Christophe Loyez, François Danneville, Kevin Carpentier and Ilias Sourikopoulos, who have accompanied my work on neuro-inspired information processing. This book would not have been possible without our numerous discussions on this new research theme.

      I would also like to thank Marie-Renée Friscourt for her diligent and efficient proofreading of the manuscript, and for the many insightful remarks made for the benefit of its improvement.

      Introduction

      The invention of the junction transistor in 1947 was undoubtedly the most significant innovation of the 20th Century, with our day-to-day lives coming to entirely depend on it. Since this date, which we will come back to later, the world has “gone digital”, with virtually all information processed in binary form by microprocessors.

      The exploit was thus essentially based on “human” or “cortical” processing of information: processing power, too often advanced today, is not always the sine qua non condition for success!

      This remarkable evolution was only made possible by the existence of a universal model of information processing machines, the Turing machine, and a technology capable of physically implementing these machines, that of semiconductor devices. More specifically, the “binary coding/Von Neumann architecture/CMOS technology” triplet has been the dominant model of information processing systems since the early 1970s.

      Yet two limits have been reached at present: that of miniaturization, with devices not exceeding several nanometers in size, and that of power dissipated, with a barrier of the order of 100 Watts when the processor is working intensely.

      Associating neuroscience, information technology, semiconductor physics and circuit design as well as mathematics and information theory, the subject matter addressed covers a wide variety of fields.

      To enable the reader to progress uninterrupted through this book, they are regularly reminded of the basic concepts, or referred to the list of reference documents provided. Wherever possible, mathematical models of the phenomena studied are proposed, in order to enable an analysis that while simplified, offers a quantitative picture of the influence of the various parameters. This thinking aid using analytical formulations is, we believe, the condition for sound understanding of the physics of the phenomena involved.

      This book is organized into four essentially independent chapters:

       – Chapter 1 introduces the basic concepts of electronic information processing, in particular coding, memorization, machine architecture and CMOS technology, which constitutes the hardware support for such processing. As one of the objectives of this book is to expand on the link between information processing and energy consumption, various ways of improving the performance of current systems are presented – particularly neuro-inspired processing, the central topic of this book. A fairly general comparison of the operating principles and performance of a modern microprocessor and of the brain is also presented in this chapter.

       – Chapter 2 is dedicated to the known principles of the functioning of the brain, and in particular those of the cerebral cortex, also known as “gray matter”. In this part, the approach is top-down, i.e. the cortex is first looked at from a global, functional perspective before we then study its organization as a basic processing unit, the cortical columns. An emblematic example, vision and the visual cortex, is also described to illustrate these different functional aspects.

       – Chapter 3 offers a detailed exploration of neurons and synapses, which are the building blocks of information processing in the cortex. Based on an in-depth analysis of the physical principles governing the properties of biological membranes, different mathematical models of neurons are described, ranging from the most complex to the simplest phenomenological models. Based on these models, the response of neurons and synapses to various stimuli is also described. This chapter also explores the principles of propagation of action potentials, or spike, along the axon, and examines

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