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Abstrak :
In the late 1960s and early 1970s David Marr produced three astonishing papers in which he gave a detailed account of how the fine structure and known cell types of the cerebellum, hippocampus and neocortex perform the functions that they do. He later went on to be one of the main founders of Computational Neuroscience. In his book on Vision he distinguished between the computational, algorithmic and implementational levels, and the three early theories concerned implementation. However, they were produced when Neuroscience was in its infancy. Now that so much more is known it is time to revisit these early theories to see to what extent they are still valid and what needs to be altered to produce viable theories that stand up to current evidence. This book has gathered some of the most distinguished international contributors to do this. After a general introduction there are three chapters on the cerebellum, three on the hippocampus and two on the neocortex. The book ends with an appreciation of the life of David Marr by Lucia Vaina.

Abstrak :
This book investigates the fascinating concept of a continuum between human memory and memory of materials. The first part provides state-of-the-art information on shape memory alloys and outlines a brief history of memory from the ancient Greeks to the present day, describing phenomenological, philosophical, and technical approaches such as neuroscience. Then, using a wealth of anecdotes, data from academic literature, and original research, this short book discusses the concepts of post-memory, memristors and forgiveness, highlights the analogies between materials defects and memory traces in the human brain. Lastly, it tackles questions of how human memory and memory of materials work together and interact. With insights from materials mechanics, neuroscience and philosophy, it enables readers to understand and continue this open debate on human memory.

Abstrak :
Neuronal noise combines experimental, theoretical and computational results to show how noise is inherent to neuronal activity, and how noise can be important for neuronal computations. The book covers many aspects of noise in neurons, with an emphasis on the largest source of noise : synaptic noise. It also provides the specialist with a summary of the large body of sometimes contrasting experimental data, and different theories proposed to explore the computational power that various forms of "noise" can confer to neurons.

Abstrak :
Inspired by response to a workshop at the 2008 OCNS meeting, this book tracks advances in the application of phase response (PR) analysis to the study of electrically excitable cells, focusing on applications of PR analysis in the computational neurosciences.

Abstrak :
Calculus of thought : neuromorphic logistic regression in cognitive machines is a must-read for all scientists about a very simple computation method designed to simulate big-data neural processing. This book is inspired by the Calculus ratiocinator idea of Gottfried Leibniz, which is that machine computation should be developed to simulate human cognitive processes, thus avoiding problematic subjective bias in analytic solutions to practical and scientific problems. The reduced error logistic regression (RELR) method is proposed as such a "Calculus of thought." This book reviews how RELR's completely automated processing may parallel important aspects of explicit and implicit learning in neural processes. It emphasizes the fact that RELR is really just a simple adjustment to already widely used logistic regression, along with RELR's new applications that go well beyond standard logistic regression in prediction and explanation. Readers will learn how RELR solves some of the most basic problems in today’s big and small data related to high dimensionality, multi-colinearity, and cognitive bias in capricious outcomes commonly involving human behavior.

Abstrak :
This book describes the torrent of data generated through research on the neurobiology and psychology of drug addiction, and discusses the role of mathematical and computational modeling in the development of more testable and rigorous models of addiction.