Curve and lattice

This blog has been on hiatus while I work on my Masters thesis. I’m still working on it, but I’m going to try to get in here and at least link to interesting content once in a while.

Here’s a transcription of an excellent talk by Benjamin H. Bratton at Postopolis LA. Though it doesn’t take music or cognitive science as its primary subject, it identifies some cultural currents important to the social and political positions of both fields.

And here’s coverage of some interesting but deeply problematic research regarding the universality of musical emotion. The researchers had subjects who claim never to have heard Western music classify the emotionality of songs by pointing at pictures of faces expressing one of three emotions: happiness, sadness, and fear. I have not yet read the paper, but the media coverage is characteristically enthusiastic and uncritical, using such misleading and awful headlines as Feel-Good Music Feels Good Around the World and Language Of Music Really Is Universal, Study Finds.

Update: Decent coverage of the Mafa music study at Cognitive Daily.

Sandrine Viellard and company at the Isabelle Peretz Research Laboratory recently published an interesting paper entitled Happy, sad, scary and peaceful musical excerpts for research on emotions. The primary goal of the work described in this paper is the creation of a standard set of musical stimuli for music-emotion research, something like Paul Ekman’s famous collection of photographs of facial expressions. Unlike Ekman, Viellard et al. aren’t demonstrating any kind of universality. In fact, they limited themselves to the genre of Western film music performed on a piano, and they see the primary structural determinants of “tension” in the music as whether or not it is in a major or minor mode and whether or not there is any chromaticism, so the cultural boundaries are fairly constrained indeed.

Simulation theories of emotional understanding posit the recognition of emotion necessarily involves some kind of internal simulation of that emotion. However, these internal simulations don’t necessarily have the same phenomenology as feeling (you can’t see it, but right here I am making a hand gesture to buttress my point!) elicited in a more direct way. The musical examples from Viellard’s library are a good example; they are (deliberately, rightly) cliché, boring, stripped of their expressive qualities. For the most part, I find myself recognizing the emotion I believe the music attempts to convey (with some exceptions, but as a composer I’m not an ideal candidate for this sort of thing), but experiencing nothing like emotion at all. Provisionally, I think this is a good thing. Music which elicits emotion rather than referencing it is slippery, different for different people, dependent upon context, maybe impossible to isolate and bottle. It’s nice to have a collection of musical examples which have been empirically assessed as accurately conveying a basic set of emotions, evocative sterility notwithstanding.

One fact which leaves me a little unsettled, mostly because these clips don’t cause me to experience any emotion, is that subjects performed better on the emotion identification task when they were told to focus on emotional experience instead of recognition:

“A significant effect of Instruction [i.e. the instruction to focus on experience versus recognition], F(1,37)=4.97; p=.032; h=.118, was observed, with a higher rating for the intended emotion in the experience condition (from .82 to .91 across emotional categories) than in the recognition condition (from .76 to .84 across emotional categories).”

I find that result very strange.

Another issue, somewhat less troubling, but still a bit problematic: A forced choice paradigm was used for categorization of the stimuli. For each stimulus, subjects were told to apply as many of the labels “happy”, “sad”, “scary”, and “peaceful” as they wanted, and the best label of those four was determined. Each of the stimuli were composed with one of those labels in mind, and so the intention of the composer was validated by the categorization task, but in a pretty weak way. What if, for example, an additional label had been allowed: “angry”? Would the categorization task then have clustered the stimuli into five groups, despite the compositional intention of conveying one of four emotions? It’d be nice to see a freer labeling procedure, it would make the library much more powerful.

References:

• Vieillard, S., Peretz, I., Gosselin, N., Khalfa, S., Gagnon, L. & Bouchard, B. (2008) Happy, sad, scary and peaceful musical excerpts for research on emotions. Cognition and Emotion, Vol. 22, Issue 4. 720-752.

Just read the free executive summary of a report entitled “Emerging Cognitive Neuroscience and Related Technologies” prepared by the National Research Council for the Department of Defense. Mostly predictable, but a couple of things stuck out. First is the burgeoning military interest in “culture studies”. It’s a relief to see, even in this roundabout way, the US military’s failure to communicate across cultures acknowledged or addressed. I hope the motive for cross-cultural research isn’t merely tactical, but strategic, foundational and systematic. If the military sees understanding of cross-cultural unversality and difference as simply means to the end of, say, more effective mind-reading, that would miss the point. A glimmer of light: “Conventional social science models based primarily on Western ideas may be challenged by invisible biases.”

Second, the report seems pretty naïve about AI. It jumps from a paragraph about expert systems directly to speculation about “an intelligent machine that uses the Internet to train itself”. The internet, of course, is “by far the closest we have come to a total database of knowledge”. Whoa there, guys.

More coverage at Wired and MetaFilter.

Long week; didn’t get a chance to post anything. As penance, I’m going to write something every day until the sloth is washed away.

Melissa Saenz and Christof Koch at Caltech offer up the first lab-tested reports of visual-audio synesthesia. They’ve found four people who hear sound when they see motion or flashes of light. The sounds they hear are “simple” (I’m not sure what that means) beeps, taps, and whirrs. No sound is perceived due to eye movement, so it really does seem to be triggered by the perception of stuff-tagged-as-motion, and not something lower-level, right off the retina.

To validate the claims of synesthesia, pairs of short rhythms were played to subjects, either as visual flashes or auditory beeps. Subjects reported whether they thought the rhythms in each pair were the same or different. Typically people are quite good at identifying auditory rhythms and bad with visual ones. As expected, everybody did well on the auditory task, but only the synesthetes could accurately compare the visual rhythms, presumably because they could hear them. Interestingly, over the course of the experiment, the synesthetes reported that the synesthetic sounds they heard along with the visuals changed to match the real sounds played during the auditory tests.

A neat direction to go with this would be to play various visual stimuli for the synesthetes and collect phenomenological descriptions of the sounds heard, with the aim of mapping the visual-audio mapping. Are the sounds similar in dynamic profile to the visuals which trigger them? What causes the sounds to change even as the visuals stay the same, as they did during the experiment? What are the intersubjective differences in the synesthetic sounds?

References:

• Saenz, M.; Koch, C. The sound of change: visually-induced auditory synesthesia. Current Biology (2008) vol. 18 (15) pp. R650-R651

In my previous entry I discussed a talk at Neukom ‘08 by Daniel Dennett where he revises his model of consciousness to account for recent thought regarding competition for resources within the brain. He refers us to a paper by Tecumseh Fitch which both provides a detailed explanation of how this competition came about and offers a defense of intrinsic intentionality—the possibility of things being intrinsically directed toward other things.

Fitch begins by providing his interpretation of Dennett’s thought in The Intentional Stance. He sees Dennett’s work as a full-force attack on the possibility of intrinsic intentionality (all citations Fitch 2007):

The thrust of Dennett’s argument is that this “something” (which he terms variously “original” and “intrinsic” intentionality) is an illusion, a deep philosophical mistake that derives from our unwillingness to fully bite the bullet and accept natural selection (and its products, especially ourselves) for the blind and goal-less process that it is. Dennett criticizes intrinsic intentionality with arguments that need to be taken seriously, arguments which seem to force us into a corner where we must choose between the following propositions: either accept that all intentionality, including our own, is derivative (and then admit that a thermostat has a little bit of intentionality, too), or we retreat from this unpalatable option into a mysterian, outmoded belief in “original/intrinsic intentionality”, a concept that under close scrutiny leads to contradiction and paradox at every turn.

At Neukom, Dennett says Fitch misinterpreted his work on intentionality, but doesn’t explain exactly how. Regardless, he thinks Fitch is right, and he’s on board with nano-intentionality and its implications.

From the beginning of his paper, Fitch focuses on a key difference between living things and machines: the ability of living things, especially small ones like cells and neurons, to adapt to local circumstances by changing their shape. Formal changes act as both a kind of memory and a way in which the cell is “about” its environment. This inherent, formal aboutness is nano-intentionality. Fitch argues that the kind of inherent intentionality we attribute to minds is a consequence of the nano-intentionality of cells and neurons. “When combined properly into large interconnected systems, this combined mass-action of cellular nano-intentionality yields intrinsic intentionality in the typical philosopher’s sense, as well as both consciousness and the efficacy of our subjectively sensed self to move the body and perform other acts of will (‘intentionality’ in its general English sense), just as the mass and velocity of gas molecules contained in a volume are constitutive of its temperature, pressure and weight.”

Here is how the argument evolves: Start with an amoeba. We understand much of how amoebas work on a mechanical level, and we know they came to behave this way because of natural selection. This is Fitch’s “prototypical example of [...] nano-intentionality”. The “purpose” of an ameoba is “realized via its physical form: it is a complex arrangement of matter serving to do useful things like find food and avoid toxins”, etc. Critically, an ameoba can deal with novelty using trial and error, “remembering” successful strategies by modifying its form. In contrast, a thermostat can only interact with what it was designed to interact with; it is only “about” what it was designed to be “about”. But an ameoba is about its whole environment, a world of things.

In multi-celluar organisms, groups of specialized nano-intentional cells cooperate, creating intentional subsystems which are “about” different things. Fitch’s example is the sponge. Each subsystem in the sponge is “about” something different, like creating efficient water flows or digesting. Fitch argues that the intentionality of these groups allows the sponge to be intentional itself, independent of an observer taking Dennett’s intentional stance. A sponge is “about” filter-feeding because its constituant parts allow it to filter feed, because the sponge evolved that way. “The aboutness of the sponge is reflected in its structure, but is constituted by its evolutionary history: the story of sponge-kind.” I.e., the way in which individual cells are “about” their environment changes when their environment contains other, collaborating cells: a kind of group intentionality emerges. The same is true on the next level of abstraction: collaborating groups of groups of cells like a sponge.

Next Fitch looks at jellyfish. They have a basic nervous system, a nano-intentional subsystem which is about information processing. In the nervous system, neurons don’t just collaborate with other neurons to perform a simple task like flaggellation, they interact with each other, such that structural changes in one cell are changes in the environment of the others. Indeed, a change in the nervous system of an organism is a change in the environment of many other cells in that organism, neurons or not. Neurons are “‘about’ amplification of information into locally adaptive patterns of action”. Neuronal events, however, are about whatever environmental change triggered the event. The organism as a whole can now react to the world around it. Fitch calls systems with this capacity “proto-mental.”

Fitch goes all the way up. The nervous system evolves from simply reacting to environmental changes, to representing those changes, and eventually to acting as a generative model, a source of ideas about “possible worlds”. Neuronal assemblages which are successful, i.e. whose representations correspond to actions actually taken by the organism in the world, are “tagged” by other neuronal assemblages, and from this emerges the serial experience of consciousness. Here we have intentionality in the philosopher’s sense, and a theory about how it arises. Fitch concludes that any system which has this kind of possible-world-tagging system must have some subjective experience, some awareness:

“To the extent that this argument is correct, awareness is the intrinsic subjective side of an objectively-verifiable capability of some types of nervous system to both entertain multiple hypothesis at a given time, and to later learn from their mistakes and successes. This leads to a rather strong and surprising thesis: that any nervous system objectively capable of considering and choosing among mental options, and of learning from its past decisions, will have at least a little bit of awareness as it does so: a little bit of (serial) consciousness.”

Fitch is, essentially, biting the natural-selection bullet offered by Dennett. But rather than looking for ways in which some internal mind could interface with an external world, he shows us how mind and world are inextricably related, and how directedness emerges from this relation.

The paper also includes an interesting discussion of how this way of thinking will affect artificial intelligence research, among other things.

References:

Dennett, D. How Mindless Algorithms Build Minds. May 9, 2008. Online video clip, accessed on July 21, 2008. http://neukominstitute.com/index.php/site/feature/dennett_talk/symposia/49/symposium08

Dennett, D. (1987) The Intentional Stance. MIT Press.

Fitch, W.T. (2007) Nano-Intentionality: A Defense of Intrinsic Intentionality. Biology & Philosophy, Vol. 23: 157-177.