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Mind, Body, World: Foundations of Cognitive Science
Cognitive science arose in the 1950s when it became apparent that a number of disciplines, including psychology, computer science, linguistics, and philosophy, were fragmenting. Perhaps owing to the field’s immediate origins in cybernetics, as well as to the foundational assumption that cognition is information processing, cognitive science initially seemed more unified than psychology. However, as a result of differing interpretations of the foundational assumption and dramatically divergent views of the meaning of the term information processing , three separate schools classical cognitive science, connectionist cognitive science, and embodied cognitive science. Examples, cases, and research findings taken from the wide range of phenomena studied by cognitive scientists effectively explain and explore the relationship among the three perspectives. Intended to introduce both graduate and senior undergraduate students to the foundations of cognitive science, Mind, Body, World addresses a number of questions currently being asked by those practicing in the What are the core assumptions of the three different schools? What are the relationships between these different sets of core assumptions? Is there only one cognitive science, or are there many different cognitive sciences? Giving the schools equal treatment and displaying a broad and deep understanding of the field, Dawson highlights the fundamental tensions and lines of fragmentation that exist among the schools and provides a refreshing and unifying framework for students of cognitive science.
- GenresPsychology
520 pages, Paperback
First published January 1, 2013
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Displaying 1 - 3 of 3 reviews
December 1, 2021
I was very excited about this book as I always loved cognitive science. I've read a few books about it, but I wanted to refresh the topic and get a new perspective. This also seemed to have a more philosophical and historical bent which made me more intrigued.
It indeed has a historical perspective. Many cognitive science textbooks simply present different areas of cognitive science from their respective fields without a unifying narrative. This is precisely what Dawson tries to offer here. It is less worried about specific details than the bigger picture of the field.
A large portion of the book is dedicated to the 3 approaches of cognitive science: classical, connectionist cognitive and embodied. Each has its own chapter and goes over the history of how those ideas arose and what they were trying to achieve.
Classical cognitive science, also called computational cognitive science, was inspired by symbolic logic and assumes that cognition is nothing but information processing. It's basically the view that the brain is like a computer, or at least something digital that works in a similar way to a computer. The finding that action potentials were all-or-none strengthened this view as if each state was like a truth value in Boolean logic. This view emerged in the 1950s and it's still the mainstream view today.
The second view is connectionism. While the first tried to understand the brain as a computer, this was more so the other way around. The brain was the starting point. This is where artificial neural networks came to be. Information is processed in a parallel manner like neurons in a brain and there are weighted connections that resemble synapses. It worked with networks in a decentralized manner.
Lastly, we have embodied cognitive science. While connectionism criticized the computer model for not taking into account how the actual brain works, embodied cognitive science criticized connectionism for being too concentrated on the brain itself. It emphasized that cognition is dependent not only on the brain but on our nervous system as a whole. And also that we have to take into account that we are embodied beings interacting with an environment and we can't think of the brain in isolation.
Each view presents itself as the correct way to think about the mind and tries to fix the shortcomings of the other approaches. Learning about these in-depth was fascinating, and the fact that such a historical approach is taken really gives you a unique perspective of how the field developed. Not only in terms of new developments, but the surrounding context of such developments which was influenced by the current cultural beliefs, technology, and philosophy.
The philosophical background is particularly interesting to me. For instance, the classical model was deeply inspired by Descartes. Oddly enough, in two major ways that opposite each other. One is that the mind is like a machine, which the model supports. On the other, it fights against thinking of the mind as something immaterial (that is a soul inhabiting the machine).
The connectionist model in turn is more in line with Locke and Hume since it's mostly empiricist in nature. There isn't an innate system for symbol manipulation. Rather, networks are dependent almost entirely on the environment to calibrate themselves, they learn by experience.
Lastly, embodied cognitive science has its philosophical roots in Heidegger and Merleau Ponty, and it assumes a type of processing based on action, not on symbolic manipulation or pattern recognition.
These topics are fascinated, but yet the book wasn't as enjoyable as I expected. First of all, there is a large amount of detail. While the philosophical and historical background does indeed provide an unusual and help bigger picture, there is often so much detail into that context that I felt the bigger picture fading.
Not only was the content often overly detailed, but sometimes overly hard as well. Some aspects that related to computation went fairly deep into logic and math, which for someone like me with very little knowledge in either made me completely lost.
Furthermore, while the different approaches to cognitive science took a lot of time, so other aspects were also covered. In particular, the cognitive science of music was a big topic, which to me was utterly incomprehensible and I had to skip it. Both its musical aspects and its cognitive science aspects were way too technical.
It's a book that gives me a lot of mixed feelings. In one way I felt that it didn't deliver a lot of what it promised and it brings to mind a lot of frustration trying to understand some of the content, most of which I eventually gave up. Yet, the parts I did enjoy, most of the ones I described here, were utterly fascinating.
Furthermore, I'm always sceptical of my own judgement about labelling a book bad when I make a lot of notes. My notes for this book were almost twice as long as normal, and I skipped close to half of the entire book.
I also found the book very helpful for references, which perhaps for the layman reader is completely useless, but for people that are more seriously into the topic and may want to reference certain ideas and when they developed, this was a fantastic resource for that purpose.
It indeed has a historical perspective. Many cognitive science textbooks simply present different areas of cognitive science from their respective fields without a unifying narrative. This is precisely what Dawson tries to offer here. It is less worried about specific details than the bigger picture of the field.
A large portion of the book is dedicated to the 3 approaches of cognitive science: classical, connectionist cognitive and embodied. Each has its own chapter and goes over the history of how those ideas arose and what they were trying to achieve.
Classical cognitive science, also called computational cognitive science, was inspired by symbolic logic and assumes that cognition is nothing but information processing. It's basically the view that the brain is like a computer, or at least something digital that works in a similar way to a computer. The finding that action potentials were all-or-none strengthened this view as if each state was like a truth value in Boolean logic. This view emerged in the 1950s and it's still the mainstream view today.
The second view is connectionism. While the first tried to understand the brain as a computer, this was more so the other way around. The brain was the starting point. This is where artificial neural networks came to be. Information is processed in a parallel manner like neurons in a brain and there are weighted connections that resemble synapses. It worked with networks in a decentralized manner.
Lastly, we have embodied cognitive science. While connectionism criticized the computer model for not taking into account how the actual brain works, embodied cognitive science criticized connectionism for being too concentrated on the brain itself. It emphasized that cognition is dependent not only on the brain but on our nervous system as a whole. And also that we have to take into account that we are embodied beings interacting with an environment and we can't think of the brain in isolation.
Each view presents itself as the correct way to think about the mind and tries to fix the shortcomings of the other approaches. Learning about these in-depth was fascinating, and the fact that such a historical approach is taken really gives you a unique perspective of how the field developed. Not only in terms of new developments, but the surrounding context of such developments which was influenced by the current cultural beliefs, technology, and philosophy.
The philosophical background is particularly interesting to me. For instance, the classical model was deeply inspired by Descartes. Oddly enough, in two major ways that opposite each other. One is that the mind is like a machine, which the model supports. On the other, it fights against thinking of the mind as something immaterial (that is a soul inhabiting the machine).
The connectionist model in turn is more in line with Locke and Hume since it's mostly empiricist in nature. There isn't an innate system for symbol manipulation. Rather, networks are dependent almost entirely on the environment to calibrate themselves, they learn by experience.
Lastly, embodied cognitive science has its philosophical roots in Heidegger and Merleau Ponty, and it assumes a type of processing based on action, not on symbolic manipulation or pattern recognition.
These topics are fascinated, but yet the book wasn't as enjoyable as I expected. First of all, there is a large amount of detail. While the philosophical and historical background does indeed provide an unusual and help bigger picture, there is often so much detail into that context that I felt the bigger picture fading.
Not only was the content often overly detailed, but sometimes overly hard as well. Some aspects that related to computation went fairly deep into logic and math, which for someone like me with very little knowledge in either made me completely lost.
Furthermore, while the different approaches to cognitive science took a lot of time, so other aspects were also covered. In particular, the cognitive science of music was a big topic, which to me was utterly incomprehensible and I had to skip it. Both its musical aspects and its cognitive science aspects were way too technical.
It's a book that gives me a lot of mixed feelings. In one way I felt that it didn't deliver a lot of what it promised and it brings to mind a lot of frustration trying to understand some of the content, most of which I eventually gave up. Yet, the parts I did enjoy, most of the ones I described here, were utterly fascinating.
Furthermore, I'm always sceptical of my own judgement about labelling a book bad when I make a lot of notes. My notes for this book were almost twice as long as normal, and I skipped close to half of the entire book.
I also found the book very helpful for references, which perhaps for the layman reader is completely useless, but for people that are more seriously into the topic and may want to reference certain ideas and when they developed, this was a fantastic resource for that purpose.
January 9, 2024
Excellent introduction to core ideas in cognitive science
December 24, 2023
Really excellent overview of the different approaches to cognitive science. I learned a lot from this. I would have loved to take a class where this was the textbook.
Not sure I'm convinced of his synthesis argument, but it's at least an intriguing possibility that I hadn't considered before.
Not sure I'm convinced of his synthesis argument, but it's at least an intriguing possibility that I hadn't considered before.
Displaying 1 - 3 of 3 reviews