Understanding How Intelligence can Emerge from a Network of Neurons

This book aims to explain how intelligence can emerge from the operation of a network of neurons, whether biological or artificial. It incorporates in particular some concepts from the field of artificial intelligence, especially Deep Learning, to explain how the neural representation of an object can be independent of its distance, orientation, position in the visual field, etc. Essentially, this book begins with a model representing a network of highly interconnected neurons, then continues with the examination of each of the basic functions of our thought process (categorisation, recognition, mental representation, etc.), which lead to the further development of the architecture and characteristics of the original network at each stage. In this book we aim to help the reader construct, brick by brick, a simple model that, once completed, will make it possible for them to understand how our neurons can generate intelligence. No specialised knowledge is required to read this book. It has no mathematical or chemical formulas, no computer algorithms, and uses clear and simple language illustrated with a large number of diagrams. This book will provide: neurobiology with a compass to navigate the maze of the brain, cognitive psychology with the missing link between neural networks and basic psychology, and artificial intelligence with a model to give robots a foot-hold in the real world. This book is for PhD students and researchers, and we hope it will give them a lot of ideas for discussion.