Descartes Lived Here

My wife Nancy and I have just returned from Stockholm, where we attended the European Congress of Psychology.  As part of our trip we did a fair amount of walking around the oldest part of the city, Gamla Stan, which dates back to 1200.  On our first journey into this area, we emerged from the metro and decided to walk around this small island, which houses the Royal Palace and the Nobel Museum.

Shortly after our walk began, Nancy noticed an elegant old doorway which drew us near.  At the time, we had been marvelling at the narrow alleyways, cobblestone roads, and ornate old buildings; this doorway (shown below) was another amazing sight on our walking tour.

However, a plaque by the doorway heightened our interest in it.  This was the location of the house in which philosopher Rene Descartes lived in the final year of his life.  Descartes had come to Stockholm in 1649 to be the philosophical mentor of Queen Christina.  However, to fit her schedule, Descartes (a notorious late riser) found himself walking from here to the palace (a few minutes away) for 5 am philosophical discussions.  The chilly walk, and cold castle, led to pneumonia which killed Descartes in 1650, only a few months after his arrival in Sweden.  (An alternative theory provided by Cartesian scholar Theodor Ebert is that Descartes was poisoned by a Catholic priest who used a communion wafer laced with arsenic.)

This surprising plaque provided a delightful historical context for our walk – Descartes lived here! – but, later, made me reflect upon Descartes’ impact on cognitive science in general, and on my own training in particular.

Classical cognitive science, which views cognition as the rule-governed manipulation of symbols, is largely the modern face of Cartesian philosophy.  Descartes’ view that one acquires new knowledge via reasoning from axiomatic knowledge is completely consistent with the classical view that cognition is computation.  In my new book (which will be released within the next few weeks), I suggest that the critical difference between classical cognitive science and Cartesian philosophy is that the former replaces the latter’s dualism with materialism.

As a PhD student I was steeped in the classical approach while being trained in the fabulous environment created by my supervisor, Zenon Pylyshyn.  My thesis concerned computational vision, and I spent a fair amount of time working through mathematical proofs concerning natural constraints that could be used to solve certain problems facing human motion perception.  Such computational investigations are clearly consistent with the spirit of Cartesian philosophy.

When I arrived at the University of Alberta in 1987, I was faced with the task of developing my own research program.  To pay the bills, I continued with some work on computational vision.  However, I also began to steep myself in connectionist cognitive science, primarily with the goal of critiquing it.  To my surprise, I made a handful of discoveries that made me more sympathetic to it.  In some sense, I was replacing the influence of Rene Descartes with that of John Locke!  Later work on interpreting artificial neural networks permitted me to flesh out some key similarities between classical and connectionist cognitive science, similarities that served as the foundation of my first book.  Artificial neural networks are involved in the majority of my publications; they reflect an empiricist philosophy that is difficult to reconcile with Cartesian rationality.  Interestingly, though, I am reluctant to think of myself as a connectionist.

More recently I have become very interested in the central ideas of another school, embodied cognitive science.  In terms of the era of Descartes and Locke, embodied cognitive science has roots in the philosophy of Giambattista Vico.  My students and I explored embodied cognitive science using some simple LEGO robots.  One result of this has been my openness to considering the virtues of situation and embodiment.

It would seem that my development as a cognitive scientist has taken me a long distance from my classical training; the phrase “Descartes lived here” describes the evolution of my own beliefs about cognitive science.

However, I have not completely abandoned my classical roots.  I still see a great deal of merit in the core assumptions of classical cognitive science.  My soon-to-be released book makes an effort to find links amongst the foundations of classical, connectionist, and embodied cognitive science.  I argue that these three approaches are not as incommensurable as one might imagine.  To the extent that my personal cognitive science can be represented as the cobblestone alleys of Gamla Stan, Descartes still walks there – perhaps softly.

Brain, Behaviour, and Cognitive Science

This past weekend I participated in the 23^rd annual meeting of the Canadian Society for Brain, Behaviour, and Cognitive Science (CSBBCS), held on the University of Calgary campus.  As far as my lab is concerned, the conference was a moderate success.  My PhD student Brian Dupuis was extremely busy at his poster, and throughout the conference had many research-related conversations with researchers from around the country.  I was less busy at my own posters, but was not surprised at this, because I was not reporting experimental results – and this is a very experimentally oriented society.  I did have a handful of detailed discussions about naïve Bayes and modern perceptrons, as well as about strange circles and the Coltrane changes, which helped pass the time!

When I go to a conference like CSBBCS, I am interested in seeing the kinds of topics that are ‘hot’, and I enjoy watching students present their posters and their talks.  This conference is  a particularly good one for students to work on such skills.  I saw many excellent student presentations at the (nicely organized) poster sessions.  I enjoyed a particularly enthusiastic account of different types of cuing presented by Shelby Siroski from the University of Regina.  I watched some fine student oral presentations  as well.  I was very impressed by a talk on the bouba/kiki effect delivered by David Michael Sidhu of the University of Calgary.

 

Of course, I also enjoyed bumping into former students and mentors whose professional lives have intersected mine throughout my career!

In terms of ‘hot’ topics, what surprised me about CSBBCS 2013? Several talks and posters expressed sympathy with embodied cognitive science.  This included the Donald O. Hebb Distinguished Contribution Award Address delivered by James Enns of UBC.  His address, “Human Perception: A science of synergy”, made calls to increase the ecological validity of experimental cognitive psychology, to consider the role of action and interaction, and to take seriously the notion of ‘cognition in the wild’.  There was also a full symposium on embodied cognition, which included an excellent talk by my former graduate student Paul Siakaluk who has established his own productive lab at UNBC.  References to action and to ecological validity were sprinkled liberally throughout all of the poster sessions.

However, what struck me about most of the CSBBCS nod to embodied cognitive science was that it was so … classical … in nature.  Much of the research aimed to provide representational accounts of phenomena that involved actions or bodies.  A popular citation that situated this approach (pardon the pun) was Barsalou’s (2009) approach to simulation theory.

What I did not see was any recognition of the fact that a key implication of embodied cognitive science involves removing mental representation.  I have been grappling with the tension between embodied and classical cognitive science over the last few years (Dawson, 2013; Dawson, Dupuis & Wilson, 2010).  What happens to classical cognitive science when notions like the extended mind and stigmergy assail it?  Representationalists might be surprised at the implications, discussed for instance by Clark (2008).  When Hutchins (1995) studies cognition in the wild, he discovers cognitive scaffolds in the world that externalize both representation and computation, and support group cognition.  Hutchings notes that we do less (cognition) because the world does more.  At the extreme, Chemero (2009) argues that cognitive science’s big mistake was to appeal to representations.

 

This radical critique of representationalism has not yet received any traction at CSBBCS.  Intrigued by the apparent lack of concern about the tension between representational and embodied cognitive science at this conference, I tried to explore it in more detail.  At the Hebb address, I asked Enns about what he thought about the future of representation in cognitive science.  He seemed to respond (once he parsed my question, which apparently puzzled him) that introspection indicates that we have representations, so there will always be a place for them in cognitive theory.  I had a more fruitful exchange with Michael Masson from the University of Victoria, who pointed out that it was a reasonable research strategy to explore representations of action, and that it was interesting to consider the cognitive neuroscience of such representations.

 

Of course, others – like myself – find it equally interesting to consider how much cognition can be accomplished in the absence of representation!  What happens when you find inspiration in Chemero instead of Barsalou?  Perhaps we will find out at future meetings of this society!

References

 

• Barsalou, L. W. (2009). Simulation, situated conceptualization, and prediction. Philosophical Transactions of the Royal Society B-Biological Sciences, 364(1521), 1281-1289.
• Chemero, A. (2009). Radical Embodied Cognitive Science. Cambridge, Mass.: MIT Press.
• Clark, A. (2008). Supersizing The Mind: Embodiment, Action, And Cognitive Extension. Oxford ; New York: Oxford University Press.
• Dawson, M. R. W. (2013). Mind, Body, World: Foundations Of Cognitive Science. Edmonton, AB: Athabasca University Press.
• Dawson, M. R. W., Dupuis, B., & Wilson, M. (2010). From Bricks To Brains: The Embodied Cognitive Science Of LEGO Robots. Edmonton, AB: Athabasca University Press.
• Hutchins, E. (1995). Cognition in the Wild. Cambridge, Mass.: MIT Press.

Desert Island Books For Cognitive Scientists

Teaching the foundations of cognitive science requires providing students a sense of its historical and philosophical roots.  My lectures try to accomplish this by providing heavy doses of quotes from, and pictures of, pioneering cognitive scientists.  (I gathered enough of this material to launch a gallery of cognitive scientists.)

Last term, as part of my mission to expose students to the roots of cognitive science, I found myself describing various pioneering works as ‘desert island books’.  I told my class that these were classic texts that any marooned cognitive scientist would be content to have by their side when facing a lengthy wait for rescue.  I am not expecting to be in that situation myself, but after 25 years at the University of Alberta I can comfortably imagine retiring to my retreat at Hastings Lake, Alberta to spend some serious time reading classics of cognitive science.  In addition, I am long enough in the tooth to be able to suggest a few foundational texts for budding cognitive scientists.

What books would provide me contentment on a desert island?

I generated the list below to answer this question.  I constrained it in two ways.  First, I limited it to thirteen books.  Second, I tried to give equal representation to the three major approaches to cognitive science (classical, connectionist, and embodied).

Classical Cognitive Science

Miller, G. A., Galanter, E., & Pribram, K. H. (1960). Plans and the Structure Of Behavior. New York:  Henry Holt & Co.

Newell, A., & Simon, H. A. (1972). Human Problem Solving. Englewood Cliffs, NJ: Prentice-Hall.

Pylyshyn, Z. W. (1984). Computation and Cognition. Cambridge, MA.: MIT Press.

Simon, H. A. (1969). The Sciences of the Artificial. Cambridge, MA: MIT Press.

About 25 years ago I rescued my copy of Miller, Galanter and Pribram from a discard pile; after my first reading of it I was amazed at how current this pioneering book still managed to be.  A recent look through it reminded me of its attempt to bridge cognitivism with cybernetics.  Newell and Simon provide an incredible manifesto of modeling in a classic book that introduces production systems, physical symbol systems, and protocol analysis.  Pylyshyn’s book offers a rich theoretical account of the implications of assuming that cognition is computation, including a deep discussion of what is involved in validating models of cognition.  Simon’s masterpiece provides a link between the science of cognition and the science of design, and is a continuous source of inspiration about how to think like a cognitive scientist.

Connectionist Cognitive Science

McCulloch, W. S. (1988). Embodiments of Mind. Cambridge, MA: MIT Press.

Minsky, M. L., & Papert, S. (1969). Perceptrons: An Introduction To Computational Geometry (1st ed.). Cambridge, Mass.,: MIT Press.

Rosenblatt, F. (1962). Principles of Neurodynamics. Washington: Spartan Books.

Rumelhart, D. E., & McClelland, J. L. (1986). Parallel Distributed Processing, V.1. Cambridge, MA: MIT Press.

The McCulloch book is a collection of his important papers, primarily from the 1940s into the 1960s, many of which are classics.  It is not an easy read, but it is fun, and it is also incredible to see the breadth of topics covered – links from the abstract to the physical abound.  Minsky and Papert provide a wonderfully challenging read that illustrates how computational analyses of artificial neural networks should proceed.  Rosenblatt’s magnum opus introduces the perceptron, but is far deeper than some might expect, and foresees aspects of the New Connectionism.  The Rumelhart and McClelland book heralded New Connectionism; this first volume of a pair of books gives the reader a lot of dangerous information about how to carry out connectionist research. (It is largely responsible for my developing my own skills in this field; I suspect that many connectionists taught themselves from reading it in the late 1980s.)

Embodied Cognitive Science

Braitenberg, V. (1984). Vehicles: Explorations in Synthetic Psychology. Cambridge, MA: MIT Press.

Gibson, J. J. (1979). The Ecological Approach To Visual Perception. Boston, MA: Houghton Mifflin.

Neisser, U. (1976). Cognition and Reality: Principles And Implications Of Cognitive Psychology. San Francisco: W. H. Freeman.

Winograd, T., & Flores, F. (1987). Understanding Computers and Cognition. New York: Addison-Wesley.

This is quite a mixed bag of selections, which is only proper, because the embodied approach is fairly fragmented.  Braitenberg provides a collection of thought experiments that illustrate the importance of realizing that an agent is embedded in its environment.  It ties in nicely with the Simon book mentioned earlier.  Gibson’s theory of perception is a foundational example of the key elements of embodied cognitive science, and Gibson’s work inspired Neisser’s embodied treatment of cognition.  Winograd and Flores offer a fascinating critique of classical cognitive science, and suggest embodied solutions to these problems.  I read both Neisser and Winograd and Flores when I was a student and missed the point of both books; 25 years later I was astounded with how prescient both were, and was amazed at my inability to understand them properly on the first read!

Combining Elements Of All Three Approaches

Marr, D. (1982). Vision. San Francisco, Ca.: W.H. Freeman.

The last book on my list is such a seminal work that it really stands on its own.  Furthermore, Marr’s theory combines strong elements of all of the different schools of cognitive science: he is clearly concerned with constructing representations in the classical sense, but develops algorithms that are essentially connectionist, and his proofs concern properties of the world (i.e. natural constraints).  His ability to move from mathematical proofs to single cell recordings of visual neurons is astonishing; for me, this was one of the two most influential books that I have ever read (the other being Pylyshyn’s, cited above).