The Computational Brain

Abstract

Before this book was published in 1992, conceptual frameworks for brain function were based on the behavior of single neurons, applied globally. This book developed a different conceptual framework, based on large populations of neurons. This was done by showing that patterns of activities among the units in trained artificial neural network models had properties that resembled those recorded from populations of neurons recorded one at a time. It is one of the first books to bring together computational concepts and behavioral data within a neurobiological framework. Aimed at a broad audience of neuroscientists, computer scientists, cognitive scientists, and philosophers, the book is written for both expert and novice. This anniversary edition offers a new preface by the authors that puts the book in the context of current research. This approach influenced a generation of researchers in the field of neuroscience. Even today, when neuroscientists can routinely record from hundreds of neurons using optics rather than electricity, and the 2013 White House BRAIN initiative heralded a new era in innovative neurotechnologies, the main message of this book is still relevant.

A neurociência computacional no estudo dos processos cognitivos

“…Churchland and Sejnowski (1992) reformulate this question as follows: "When can a physical system be called a computer?" Among cautious considerations, the question is answered by indicating that a computer is a system that receives one type of signal (a set of data), which is converted and represented by means of a code; it then performs finite and definite operations related to that code, changing its physical configurations, and at the end, it generates a result that can be associated with the original signal.…”

“…It has been a fertile and heuristic approach to consider the nervous system a system that computes information (Churchland & Sejnowski, 1988, 1992Eliasmith, 2007). To perform its operations, the nervous system has to convert the signals from the environment into its own internal code, which is structured into changes in the electrical potential of neurons through ionic flows.…”

“…The general question is clear: how do such circuits lead to cognition? To answer this question, contributions from areas such as physiology and computer science must be taken into account (Churchland & Sejnowski, 1992).…”

Methods and Techniques of Complex Systems Science: An Overview

“…24. It is certainly legitimate to regard any dynamical process as also a computational process, [284][285][286]195], so one could argue that the data is produced by some kind of program. But even so, this computational process generally does not resemble that of the minimal, Kolmogorov program at all.…”

A hybrid model for rodent spatial learning and localization

“…A vast body of data from lesion studies and cellular recordings directly implicates the hippocampal formation in rodent spatial learning [l4]. The present model is based on the anatomy and physiology of the rodent hippocampus [5]. We draw inspiration the locale hypothesis, which argues for the association of configurations of landmarks in the scene to the animal's own position estimates at different places in the environment as suggested by O'Keefe and Nadel.…”