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February 10, 2021 / neurograce

Models of the Mind: How Physics, Engineering and Mathematics Have Shaped Our Understanding of the Brain

I wrote a book!

As some of you may know, in summer of 2018 I signed a contract with Bloomsbury Sigma to write a book about my area of research: computational neuroscience.

Though the term has many definitions, computational neuroscience is mainly about applying mathematics to the study of the brain. The brain—a jumble of all different kinds of neurons interconnected in countless ways that somehow produce consciousness—has been described as “the most complex object in the known universe”. Physicists for centuries have turned to mathematics to properly explain some of the most seemingly simple processes in the universe—how objects fall, how water flows, how the planets move. Equations have proved crucial in these endeavors because they capture relationships and make precise predictions possible. How could we expect to understand the most complex object in the universe without turning to mathematics?

The answer is we can’t, and that is why I wrote this book. While I’ve been studying and working in the field for over a decade, most people I encounter have no idea what “computational neuroscience” is or that it even exists. Yet a desire to understand how the brain works is a common and very human interest. I wrote this book to let people in on the ways in which the brain will ultimately be understood: through mathematical and computational theories.

At the same time, I know that both mathematics and brain science are on their own intimidating topics to the average reader and may seem downright prohibitory when put together. That is why I’ve avoided (many) equations in the book and focused instead on the driving reasons why scientists have turned to mathematical modeling, what these models have taught us about the brain, and how some surprising interactions between biologists, physicists, mathematicians, and engineers over centuries have laid the groundwork for the future of neuroscience.

Each chapter of Models of the Mind covers a separate topic in neuroscience, starting from individual neurons themselves and building up to the different populations of neurons and brain regions that support memory, vision, movement and more. These chapters document the history of how mathematics has woven its way into biology and the exciting advances this collaboration has in store.

Interested yet? Here is how you can get your hands on a copy:

UK & ebook publication date: March 4th, 2021. Bloomsbury | Hive | Waterstones | Amazon

India publication date: March 18th, 2021. Bloomsbury | Amazon

USA publication date: May 4th, 2021. Bloomsbury | Powell’s | Barnes & Noble | Amazon | Bookshop

AU/NZ publication date: May 4th, 2021. Bloomsbury | Boomerang | Amazon

Outside those countries? Bloomsbury UK ships globally so you can use that link, or Amazon, or just check with your normal bookseller. You can also get the e-book through Bloomsbury or however you normally get your e-books, and the audiobook is on Audible and elsewhere!

In addition to the standard websites, of course you can always check with your local independent book store or library. If it’s not there, ask if they’ll stock it!

The paperback (with a fresh blue cover) came out in Fall 2022. Remember, paperbacks are just like hardbacks except cheaper and with fewer errors, so get yours from any of the above sellers!

If you got the book, and read it, and want to tell the world your thoughts on it, head over to Goodreads or your local Amazon page to leave a review. Five stars particularly appreciated šŸ™‚

There are also some translations (Chinese, Korean, and Arabic for now) in the works. Check back here for updates.


Leave a Comment
  1. CodeFerret / Jul 5 2021 7:14 pm

    Interesting selection of topics and researchers. Fig 22 needs fixing. Rao & Ballard 1999 missing from Chapter 12 Bibliography.

  2. Jim Rock / May 9 2022 9:06 pm

    Enjoying your book “Models of the Mind”. There is a small error on page 128 in your discussion of levels of precision. 18,231 is 1.82 x 10^4 and 18,115 is 1.81 x 10^4.

    Their difference is .01 x 10^4 or 100. However, it doesn’t effect the validity and content of your presentation.

    • neurograce / May 17 2022 5:02 pm

      Thank you! Corrected in the paperback.

  3. Grant Langdon / Sep 14 2022 6:24 pm

    Iā€™m listening on audible. Have the images been made available to people with just the audiobook or should we ignore every time it says see an image?

    • neurograce / Sep 17 2022 2:03 am

      Unfortunately for copyright reasons that I don’t fully understand, the audiobook can’t provide any of the print elements. But in the majority of cases the figures are supplemental, so you should be able to still follow along fine without them. Sorry!

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