Tuesday, June 25, 2013

Cursive Writing and the Extended Mind

Recently, National Post columnist Andrew Coyne gave his personal reaction to children not being taught cursive writing in school. This is a growing trend in North American schools, a trend that Coyne finds alarming. Why? Because Coyne recognizes that writing is not just done ’in the head’, but is an activity that involves interacting with particular external media.  He writes, “How we write, in other words, affects what we write. You compose in a different way using pen and ink than you do on a computer.”

I must admit that I do not find myself in agreement with some of Coyne’s specific claims about why writing cursively is different than composing at a keyboard. For instance, he describes typing as ‘file retrieval’, because you have to remember where a particular letter is on the keyboard. In contrast, “With handwriting, you create the letters anew each time, using much more complex motor skills. Whether it’s the flowing motion of the arm, or the feel of the page under your hand, or the aesthetic satisfaction of a well-turned ‘f’, it seems to engage the more intuitive, right-brain aspects of cognition.” As a cognitive scientist, I am reluctant to appeal to intuition or to right-brain processing.

As an embodied cognitive scientist, though, I am in complete agreement with Coyne’s view that how we write affects what we write. The extended mind hypothesis makes the claim that the external world is a fundamental component of our mentality; change that world and you change the mind. Coyne provide some wonderful examples of how his own writing processes are affected by constraints imposed by external media, and I see these as compelling examples of the extended mind hypothesis in action. For instance, Coyne takes advantage of the extended mind to deal with writer’s block: “Often when I am stuck at the keyboard, unable to find my way out of whatever mental cul-de-sac I have put myself in, I will pick up a pen and start writing — and the words start to come again.”

My own experience with the physical act of writing complements Coyne’s. In my final year of high school, I took a typing class as an option, and have long since thought that it was the most important part of my high school education. But as an undergraduate student, and as a graduate student, typing was never my first line of attack. Instead, I would take lecture notes by hand, and would later study for exams by typing my notes up. The first draft of any paper that I wrote was created in longhand. I would then edit that handwritten manuscript, and only when I was happy with it would I type the final version. It wasn’t until my last year as a PhD student that I learned to compose at the keyboard because of the newfound pressure of ‘publish or perish’. Cursive drafts simply took too long to produce.

I am now quite expert in composing manuscripts at the keyboard; most of my current writing is done on a laptop, sitting in a reclining chair in my living room with my dog sleeping on my legs. When I encounter writer’s block, I -- like Coyne -- deal with it by changing the medium. But I don’t go back to longhand. Instead, I’m more likely to activate my speech recognition software and dictate to my computer. (I used this software to compose this very post.)This approach does make me think about writing in a different way, but one more important thing that I’ve noticed is that it changes my writing style. Coyne’s column makes me wonder what would happen to my writing style if I went back to my old ways and pulled out pencil and paper.
 
Coyne’s column also makes me wonder about the research that has been conducted on the effects of writing medium on writing ability. In a recent post, I suggested that the embodied experimental psychologists involved with the Canadian Society for Brain, Behavior, and Cognitive Science were missing the key implications of the extended mind hypothesis. Does removing cursive writing from the school curriculum impact the thought processes involved in converting our thoughts into text? I think that I’m going to explore the existing literature on this issue; this seems exactly like the sort of applied problem that is crying out for extensive contributions from embodied cognitive science.

Wednesday, June 12, 2013

Health And Postsecondary Education

With respect to the Alberta government’s health file, the past two days have been turbulent.  Yesterday the Minister of Health, Fred Horne, instructed the board of Alberta Health Services (AHS) to cancel bonus payments to its executives.  These bonus payments – called ‘pay at risk’ – involve paying a certain portion of an executive’s salary, but only if the executive has met some performance target.  Apparently, pay at risk is part of the contract of about 100 AHS executives, and for the fiscal year 2012-13 amounts to a total of $3.2M.  Pay at risk will not be included in future contracts.

The AHS board voted to ignore the health minister’s directive.  They defended this decision on two grounds: the sanctity of contracts, and board autonomy.  The AHS viewed itself as functioning at arm’s length from the government.  Horne dismissed the entire AHS board earlier today.

Currently, executive bonuses at AHS are politically ugly.  Some front-line health care workers are losing their jobs, which sets an awkward context for highly paid executives receiving large bonuses.  After the recent (austere) provincial budget, the health minister expressed displeasure with these bonuses, because they were out of step with the budget’s theme of ‘living within our means’.  However, with respect to eliminating pay at risk, “Horne insisted the decision rests with the AHS board, adding: ‘I don’t have the authority to interfere with someone’s contract of employment.’”  Of course, he had the authority to direct the AHS board to interfere with these contracts, as well as the authority to remove the board when they refused.

Regardless of one’s view of pay at risk, it apparently is part of a contractual agreement administered by an arm’s length board.  The government’s action suggests that it has no interest in honouring such agreements, and feels no hesitation about directing arm’s length boards to violate them to keep in step with government policy.  Jen Gerson’s column in the National Post – accompanied by the headline “Don’t Mess With The Boss Lady” – points out that Horne’s action sends a strong message to other arm’s length boards.  What is the message?  Do not defy the government!

What does all of this have to do with Alberta’s postsecondary education system?  Arm’s length boards govern Alberta’s universities and colleges.  Their autonomy became an issue when the Minister of Enterprise and Advanced Education delivered mandate letters to them shortly after the provincial budget.  The same minister later asked all institutions to institute a wage freeze over the next three years.  An obvious concern to anyone employed in postsecondary education is that the government’s approach to AHS and its contracts is the model for upcoming interactions with university boards.

How binding is a university employee’s contract?  How autonomous is a university’s Board of Governors?  We will find answers to these questions in the not-too-distant future.

Monday, June 10, 2013

Brain, Behaviour, and Cognitive Science

This past weekend I participated in the 23rd 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 na├»ve 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.

Thursday, June 06, 2013

Strange Circles That Map Coltrane Changes

One of my collaborators notes that my last few blogs are very political in nature.  I thought that I would change that up by writing about some artificial neural networks and jazz research that we have been conducting, research to be presented this weekend at a conference in Calgary.  Of course, this assumes that jazz is not political, which is probably a dangerous move.

Most jazz pieces are essentially song structures in which musicians play sequences of chords called chord progressions.  Certain chord progressions are popular because the transition from chord to chord is musically pleasing, and because the progression permits moving from one musical key to another, permitting flexibility and providing musical variety.

One particularly important chord progression is the II-V-I., in the key of C major this progression starts by first playing the D minor seventh chord (Dm7), then by playing the G dominant seventh chord (G7), and ends by playing the C major seventh chord (Cmaj7).  In the key of C this is a II-V-I progression because D, the root note of Dm7, is the second note of the C major scale; G, the root note of G7, is the fifth note of the C major scale; and C, the root note of Cmaj7, is the first note of the C major scale.

The II-V-I has evolved into more complex chord progressions.  For instance, John Coltrane introduced the chord progression now known as the Coltrane changes on his seminal 1960 album Giant Steps, where it is central to two pieces, “Giant Steps” and “Countdown”.  The Coltrane changes are an elaboration of the II-V-I; it includes the three chords of this older progression, but adds four more chords.  Two of these are lead-in chords to the V, and the other two are lead-in chords to the I.  The table below provides the Coltrane changes for the key of C major.


Last summer we were interested in training artificial neural networks to generate chord progressions: when presented a chord, a network would generate the next chord in the progression.  To do this for the Coltrane changes, we had to determine the chord progression for any major key.  However, this is not easy: accounts of the Coltrane changes on the web are opaque.

In a previous blog entry, I described some ‘strange circles’ – arrangements of notes in a circle, so that adjacent notes in the circle are a constant musical interval apart – that we had extracted from other musical networks that we trained.  For our Coltrane project, we found that combining these circles into more complex diagrams provided a map that let us build our training set.

In particular, all of the tonic notes of the Coltrane changes are represented in a ‘rose diagram’ that attaches a ‘strange circle’ of major thirds to every note around the more traditional circle of fifths.  Here is the complete ‘rose diagram’:
 


The inner circle provides the tonic notes for the II-V-I skeleton of this progression, and the outer circles provide the tonic notes for the lead in chords.  To use this map, you start with a chord from the inner circle, you then play four chords related to the outer circle, and you end with two chords from the inner circle.  The figure below shows how the Coltrane changes falls out of the ‘rose diagram’ for the key of C major.  In this figure I extended the lines ending in G# and B so that the chords are mapped in the proper order.  The dotted arrows take you chord by chord through the changes; compare their order with the table above.  If you follow this pattern starting at any other inside note, then you will generate the Coltrane changes for some other key.

 We found that a very simple network – one with no hidden units – could learn the Coltrane progression if we presented inverted chords.  Inverted chords are the same chords (i.e. the same set of notes), but the notes are arranged in a different order.  When we examined the internal structure of the trained network, we found another easily mapped regularity.

The connection weights revealed that the network had learned that a key aspect of the Coltrane changes involved the relationships between the different base notes used in the seven (inverted) chords for the changes.  These relationships only involve four different musical intervals: unison, the major second, the minor 7th, and the major 7th.  A unique connection weight defined each of these intervals.  These relationships could be plotted as a map of movements about the vertices of a triangle, where each vertex is the lowest note of an inverted chord.

 One such map is shown below.  It starts with a chord that has F as its lowest note, then moves to play four different chords, each having Eb as a low note.  It returns to F, and then ends with a chord whose lowest note is E:

 

Interestingly, to start the same sequence in the next key the first note is the Eb; the last arrow in this map is a pointer to the first chord in the next key.  If you fill out the remaining triangles then another elegant map of the Coltrane changes is produced:



The interesting thing about this final map is that its outer wheel of notes, and its inner wheel of notes, are two other ‘strange circles’: the two circles of major seconds.  In short, it seems that whenever we train networks on tasks that involve musical chords, we find the networks represent chord regularities with these strange circles.