Memory and the Computational Brain

by Charles R. Gallistel, Adam Philip King

Memory and the Computational Brain offers a provocative argument that goes to the heart of neuroscience, proposing that the field can and should benefit from the recent advances of cognitive science and the development of information theory over the course of the last several decades.
A provocative argument that impacts across the fields of linguistics, cognitive science, and neuroscience, suggesting new perspectives on learning mechanisms in the brain Proposes that the field of neuroscience can and should benefit from the recent advances of cognitive science and the development of information theory Suggests that the architecture of the brain is structured precisely for learning and for memory, and integrates the concept of an addressable read/write memory mechanism into the foundations of neuroscience Based on lectures in the prestigious Blackwell-Maryland Lectures in Language and Cognition, and now significantly reworked and expanded to make it ideal for students and faculty

Genres: Science, Nonfiction, Neuroscience, Philosophy, Psychology, Linguistics, Brain

336 pages, Paperback

First published January 1, 2009

Reviews

[Hessam Akhlaghpour · Rating 5 out of 5]

The first 9 chapters just explain basic concepts in computer science. I skipped most of them and only read their two paragraph summaries. The rest of the book is extraordinary, as it challenges some of the most well-accepted paradigms in neuroscience, e.g. that long term memories are stored as changes in synaptic conductance rates. I found this book to be very enlightening and highly recommend it to anyone that is interested in doing research in neuroscience. If you are not a neuroscientist, you won't have difficulty understanding the book but you might not realize the significance of his claims and why they are considered so controversial.

[Romann Weber · Rating 2 out of 5]

Given the passion and thoroughness with which Gallistel and King tackle their subject, I am almost embarrassed to give this book such a low rating. The subject matter is, in itself, hugely interesting, and the authors' main thesis—which challenges the dominant connectionist orthodoxy—is a valuable contribution to the cognitive science literature. The thesis is also a simple one: "If the computational theory of mind, the core assumption of cognitive science, is correct, then brains must possess a mechanism for carrying information forward in time in a computationally accessible form" [p. 287]. The authors stress that neural plasticity, well accepted as a mechanism for learning, is unrealistically assumed to also be responsible for memory's "carrying information forward" and cannot possibly do the job it's claimed to do.

Sadly, for me at least, the authors' painstaking approach to establishing their case, complete with thorough analyses of Turing machines and detailed, protracted explanations of various toy implementations of a variety of tasks—from simple arithmetic to dead reckoning of location—made for often painfully dull reading. The book is not without its good passages, and it is at least equipped with chapter-ending summaries to refresh the memory of those rendered punch-drunk or finding themselves dragging their eyes over the material more than actually reading it. Chapter 16 serves as a nice closer to the book, and the reader pressed for time may do well to read it, the introduction, and the end-of-chapter summaries to more than adequately get the book's message.

[DJ]

Musings on memory and its role in computation from a man who is very unhappy with neuroscientists' collective assumption that memory amounts to jiggling synaptic variables

[Ogi Ogas · Rating 3 out of 5]

My ratings of books on Goodreads are solely a crude ranking of their utility to me, and not an evaluation of literary merit, entertainment value, social importance, humor, insightfulness, scientific accuracy, creative vigor, suspensefulness of plot, depth of characters, vitality of theme, excitement of climax, satisfaction of ending, or any other combination of dimensions of value which we are expected to boil down through some fabulous alchemy into a single digit.

[Billie Pritchett · Rating 4 out of 5]

Honestly, I put off this review for so long that I can barely remember the contents of Charles Gallistel's book Memory and the Computational Brain. It was primarily a book about how learning in the brain works according to a set of specific evolutionary problems we have to solve. So that means that the brain devotes itself to certain big problem areas, like visual processing and linguistic processing. Memory, on the other hand, is a different sort of system, according to Gallistel. It's a mechanism that can retrieve information from each independent system (like the visual system or linguistic system) and package it so as to bring the information to mind. That's all I remember from the book. Would like to read it again.

[Chase Mackey · Rating 5 out of 5]

This book lives up to its subtitle. Gallistel and King go to town on the current undeveloped explanation of how the brain has memory, and learns. They succeed in my opinion.