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Models of the Mind: How Physics, Engineering and Mathematics Have Shaped Our Understanding of the Brain Hardcover – May 4, 2021

4.5 out of 5 stars 215 ratings

Grace Lindsay reveals the value of describing the machinery of neuroscience using the elegant language of mathematics.

The brain is made up of 85 billion neurons, which are connected by over 100 trillion synapses. For over a century, a diverse array of researchers have been trying to find a language that can be used to capture the essence of what these neurons do and how they communicate – and how those communications create thoughts, perceptions and actions. The language they were looking for was mathematics, and we would not be able to understand the brain as we do today without it.

In
Models of the Mind, author and computational neuroscientist Grace Lindsay explains how mathematical models have allowed scientists to understand and describe many of the brain's processes, including decision-making, sensory processing, quantifying memory, and more. She introduces readers to the most important concepts in modern neuroscience, and highlights the tensions that arise when bringing the abstract world of mathematical modelling into contact with the messy details of biology.

Each chapter focuses on mathematical tools that have been applied in a particular area of neuroscience, progressing from the simplest building block of the brain – the individual neuron – through to circuits of interacting neurons, whole brain areas and even the behaviors that brains command. Throughout Grace will look at the history of the field, starting with experiments done on neurons in frog legs at the turn of the twentieth century and building to the large models of artificial neural networks that form the basis of modern artificial intelligence. She demonstrates the value of describing the machinery of neuroscience using the elegant language of mathematics, and reveals in full the remarkable fruits of this endeavor.

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Editorial Reviews

Review

“Grace Lindsay provides a masterful tour of this important frontier, tackling intimidating topics with verve and wit.” - Sean Carroll

“This is a remarkable book … an excellent introduction to an area that few of us probably know anything about, and all the more fascinating because of that.” -
Popular Science

Models of the Mind is a grand tour through the history of computational neuroscience, from its humble beginnings in information theory and neuron structure up to its modern manifestations harnessing supercomputers to run large scale convolutional neural networks that model important brain systems.” - Women You Should Know

“The book is not only wide-ranging in its choice of topics but is also a lively journey through the history of these efforts and traces the lives of the eccentric and fascinating scientists who were instrumental in figuring out the brain’s working by using tools ranging from information theory and graph theory to Bayesian modeling and neural networks.” -
3 Quarks Daily

“‘Enthralling, erudite and accessible … an engrossing history of science and an enlightening guide to neuroscience’s current frontiers.’” -
Liam Drew, Neurobiologist and author of I, Mammal: The Story of What Makes Us Mammals

“‘This book is an anthology of the scientific poetry that has illuminated our studies and conceptions of the brain.’” -
Professor Larry Abbott, Center for Theoretical Neuroscience, Columbia University

About the Author

Grace Lindsay is an Assistant Professor of Psychology and Data Science at New York University.

After completing her PhD in 2018 at the Center for Theoretical Neuroscience at Columbia University, she went on to a postdoctoral fellowship at University College London, where her research focused on building mathematical models exploring sensory processing. Before that, she earned a bachelor's degree in Neuroscience from the University of Pittsburgh, and received a research fellowship to study at the Bernstein Center for Computational Neuroscience in Freiburg, Germany. She was awarded a Google PhD Fellowship in Computational Neuroscience in 2016 and has spoken at several international conferences.

Product details

  • Publisher ‏ : ‎ Bloomsbury Sigma
  • Publication date ‏ : ‎ May 4, 2021
  • Language ‏ : ‎ English
  • Print length ‏ : ‎ 400 pages
  • ISBN-10 ‏ : ‎ 1472966422
  • ISBN-13 ‏ : ‎ 978-1472966421
  • Item Weight ‏ : ‎ 1.16 pounds
  • Dimensions ‏ : ‎ 6.02 x 1.39 x 8.72 inches
  • Customer Reviews:
    4.5 out of 5 stars 215 ratings

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4.5 out of 5 stars
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Top reviews from the United States

  • Reviewed in the United States on October 1, 2023
    No one should start reading this book thinking there will be a final equation at the end of the book that explains everything. This field is very much a work in progress.

    Having said that, the author does a great job explaining progress to date: The author explains how the brain works, from chemistry, to individual neurons, to groups of neurons to the brain as a whole. Although "mathematics" is in the title, a reader does not need to be able to solve a partial differential equation to understand the material. And, it is full of great tidbits of knowledge, like memory is not stored in neurons (neurons either fire or don't fire based on their inputs per a simple equation), memory is stored in the strength of the synapses between neurons.

    The only problem I noticed was not with this book, but the blinders that the scientists seem to have. They seem to be ignoring millennia of experience about human consciousness that has been documented. Great thinkers like Plato and Buddha, and more recently B.K.S. Iyengar and Thich Nhat Hanh, have been explaining how consciousness works from a human perspective for a very long time. But, the scientists described in this book seem to be starting from scratch, exploring consciousness in a much more shallow way, almost like how a thermostat is aware. I believe, if scientists are going to understand human consciousness, they need to explore biology of what these great thinkers describe as real/deep consciousness, rather than what they have described as superficial consciousness. I read a book by Giulio Tononi (cited in this book) and came to the same conclusion. Let's get below the surface.
    2 people found this helpful
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  • Reviewed in the United States on July 25, 2021
    A very readable discussion of the cosmic issues confronting our understanding of the mind. I will take two picky issues with what I thought were omitted from an otherwise perfect discussion: Keffer Hartline’s work on lateral inhibition (that won him a Nobel) and the neglect of significant instruments such as the negative capacitance amplifier that permitted physiologists to truly “see” the neuron. An excellent reference.
    13 people found this helpful
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  • Reviewed in the United States on May 21, 2021
    The book is a good overview of the existing modeling approaches to the brain. The author almost avoids writing down a single equation! The details about the various scientists involved are also very interesting. And the author is a very clear writer. I think the book is a good jumping off point for people who want to delve into the field.
    11 people found this helpful
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  • Reviewed in the United States on January 14, 2022
    I am an undergraduate student of math and CS, interested in AI and the brain. Very informative and understandable to me. A new favorite.
    5 people found this helpful
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  • Reviewed in the United States on June 15, 2021
    Great review of major discoveries in computational neuroscience
    3 people found this helpful
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  • Reviewed in the United States on January 3, 2024
    I've only just started the book, and I like the content a lot so far. This review is about print quality of the paperback version.

    The copy I received is printed on low-quality paper, similar to newsprint, making it hard to read. You can also notice the low quality when holding the book -- it's very light.
  • Reviewed in the United States on September 14, 2021
    I’ve been interested in neuroscience for a while, but sometimes, books on the topic aren’t written for the average person. I’ve heard a lot of talk about this book from Grace Lindsay, so I decided to check it out even though I’m not much of a math guy, which scared me even more. Fortunately, Grace did an incredible job of making this book accessible to the average reader like myself. Throughout the book, the author not only breaks down complex topics, but you also learn the history of neuroscience as well as how mathematics and models have helped us understand the brain. There were still a few parts that I didn’t quite grasp, but for the most part, I was able to keep up, so I think many people would enjoy this book if they’re interested in the brain. Some of my favorite chapters were in the realm of topics I’m more familiar with such as reward-based learning, decision making, and some others. So, if you like this topic at all or are curious to get into it, I’m sure you’ll enjoy this book.
    8 people found this helpful
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  • Reviewed in the United States on May 17, 2021
    Was hoping this book was gonna be more about deriving a mathematical theory of the mind, however it was more of a history lesson of different tools used in model building like little bios of the people that invented the techniques instead of going over in detail how they worked. Was also expecting the author to share an attempt to model something about the brain but nope. Disappointed
    24 people found this helpful
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Top reviews from other countries

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  • Peter
    5.0 out of 5 stars A very clear journey through the history of modelling the brain
    Reviewed in Italy on October 27, 2023
    Il libro affronta in maniera chiara le tappe nello sviluppo di modelli per capire il funzionamento del cervello.
    Il linguaggio usato è abbastanza semplice e può essere letto anche da non esperti di neuroscience. Personalmente, ho trovato estremamente interessanti alcuni passaggi del libro. Lo consiglio vivamente a chi è interessato ad approfondire la nostra attuale comprensione del cervello animale.
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  • Geronimo Ordoñez
    5.0 out of 5 stars Perfect for starters.
    Reviewed in Mexico on September 5, 2023
    I'm a mechatronics engineer getting specialized on neural sciences. I say this to all STEM people who want to dive into the neuro world: this is the way.
  • Amazon Customer
    5.0 out of 5 stars Very good introduction to computational neuroscience
    Reviewed in Canada on December 21, 2023
    ....
  • CHICHA Marc
    5.0 out of 5 stars Indispensable❗️
    Reviewed in France on August 20, 2021
    Pour tous ceux qui s’intéressent à l’intelligence artificielle dite “forte” [AGI, et veulent comprendre pourquoi il semble que la communauté des chercheurs s’apprête à célébrer la venue d’un nouvel “hiver” dans ce domaine,
    À force, semble-t-il, de confusion “médiatiquement entretenue” entre ML et IA,
    Ce livre est une mine : Accessible, clair et simple, sans artifices, snobisme, ni formalisme mathématique pédant, enfin un ouvrage de vulgarisation scientifique ... intelligent, sur ... l’intelligence❗️🙏😉

    Un vrai plaisir, avec en prime une foule de références et de pistes à suivre pour approfondir le sujet, dans toutes les directions de la recherche...

    Un grand merci à Grace Lindsay.🙏
  • Joseph Thomas
    5.0 out of 5 stars Brilliant book - covers all the essential developments
    Reviewed in India on May 4, 2023
    Want to know more about computational neuroscience in a relatively non-technical and historical way? Then this is your go-to book for sure! Lindsay has done the field a great service! Wish this book was around when I pursued my MSc degree in this particular area more than a decade ago.