What is Cognitive Science?
A book review of Cognitive Science by José Luis Bermúdez
I’ve become increasingly fascinated by cognitive science, largely influenced by John Vervaeke. I wanted to pick up a textbook about it so I could get an introduction, and among the reputable ones, this was the shortest. When I first opened it I was a bit baffled. Crazy complex graphs that looked indecipherable. Thankful, I was mistaken. While difficult, most of them are quite accessible within the context of the book and the foundation it provides.
The first part starts with the pre-history of cognitive science. The reaction against behaviourism in psychology, due to some experiments showing learning without any reinforcement. Later studies showed that rats had “cognitive maps”, which led to several studies in spatial learning that pointed out to minds having representations, in which the mind could no longer be ignored within the behaviourist paradigm. It laters explains the theory of computation and algorithms based on Turing machines, and how that laid the foundation to cognitive science, along with Chomsky’s contribution to the structure of language. It finishes with how mental images are representations and the interdisciplinary model of vision, which is a good example of how cognitive science works (or ought to work).
The second part is all about the integration challenge. Cognitive science at its heart is an interdisciplinary endeavour, involving psychology, philosophy, linguistics, anthropology, neuroscience and artificial intelligence. But this creates the problem of lacking a unified theoretical framework that encompasses everything. It illustrates two ways of local integrations, the psychology of reasoning with evolutionary biology and game theory, and the connections between two different tools for studying brain activity (microelectrode recordings and functional neuroimaging).
The third part is about information-processing models of the mind. It starts with the physical symbolic system hypothesis, which claims a physical symbolic system is sufficient for general intention action (symbols being physical patterns). Then touches on the language of thought hypothesis from Jerry Fodor on how the physical symbolic system hypothesis deals with mental architecture — the syntax and semantics in a formal system. Next, it covers how it applies to the symbolic paradigm, touching on machine learning and several classic robots that ran on algorithms by manipulating physical symbol structures until a solution is found. One by using decisions trees, and the other with imagistic symbols. Then moves on to several types of neural networks (single-layer and multi-layer) and how they operate, including how they can be models of cognitive processes, like learning a language and object permanence in children.
The fourth part is about how the mind is organized. It covers in in-depth Fodor’s modularity of the mind (that cognition is done by specific and independent modules), touching on its characteristics and how it frames cognitive science. Other hypotheses are covered, like the massive modularity hypothesis and hybrid architectures (where the mind uses both modular and non-modular processing). This is followed by strategies for brain mapping, an introduction to neuroscience and how it has helped cognitive science progress and confirm or disprove hypotheses.
The last part is about currently growing topics in cognitive science. It touches on dynamical systems — systems that evolve over time in a law dependent manner (like Newtonian mechanics), and how it can be used in cognitive science, illustrating how it can be applied to child development in how they learn to walk and expectations of missing objects. Later it explored the situated cognition movement largely inspired by insects, given they have to solve very complex problems and yet they are a very basic organism. Neither dynamical systems nor situated cognition fits in the typical information-processing paradigm of mainstream cognitive science.
Finally, it touches on consciousness. It starts from a philosophical standpoint about the hard problem of consciousness and then illustrates some of the proposed approaches to tackling the problem (mostly by focusing on the so-called “easy” problems of consciousness instead). They’re generally categorized as either studying the phenomenology of consciousness (what is it like to be conscious of something) and what one is conscious or not (in a sort of Freudian manner).
Overall, I really enjoyed reading the book. I thought I was fairly familiar with the science of mind, but I was very wrong. While psychology gives a very solid foundation, cognitive science is another beast altogether. It’s truly the future to understand ourselves and what made me read the book. It’s fairly dense and difficult, I can’t say otherwise. Particularly when it ties to logic, mathematics or AI. But most topics I found accessible, and even if one does not understand all the details it nevertheless provides a lot of insight.
If you truly want to understand the mind, you need to learn about cognitive science, no way around it. This book provides a good introduction for it. It explains new concepts as they arise and contains helpful summaries at the end of each chapter.
This is likely not a super helpful review and maybe a bit confusing if one is not familiar with the topic, but it’s very difficult to summarize given both the complexity and the amount of information it contains.
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