Sunday, March 20, 2011

#CCK11: Earning a Place in the Network

I continue to revel in Olaf Sporns' wonderful book about neural networks: Networks of the Brain. In Chapter 8: Dynamic Patterns in Spontaneous Neural Activity, Sporns examines the dominant model in brain studies that says brains are mainly structures for receiving, processing, and then responding to sensory impressions from outside the brain (eyes, ears, skin, etc.). As Sporns says, "This theoretical framework treats the brain as a system in which the essential neural process is the transformation of inputs into outputs" (149). If I understand Sporns correctly, then this view of the brain borrows heavily from computer information theory: signals from keyboard and mouse are input to the CPU, which then processes the signals and outputs a result in the form of another signal, or: I press the A key on my Macintosh PowerBook Pro's keyboard, then the internal 2.53 GHz Intel Core i5 chip processes that signal, and finally it outputs signals to the screen to display the letter A. In the view of traditional neuroscience, then, my brain is like the Intel Core i5 chip: a more or less efficient processor of sensory input into motor output.

This is a simple view of brain activity, and it is consistent with a Newtonian worldview that sees reality as a machine: a collection of parts with regular, reliable, and highly predictable interactions in which cause and effect are necessarily linked. If I press the A key on my computer keyboard, then the CPU will process that signal and it will cause A to appear on my screen. If this doesn't happen, then the machine is malfunctioning and requires repair. Or … if I teach (input) the technique for handling in-text citations according to the MLA Style Manual, then my students (CPUs) will process that input, and they will necessarily output papers that properly handle in-text citations according to the Modern Language Association's authoritative guide. If they don't, then their machines (brains) are malfunctioning and require repair (further teaching). If I'm a particularly sensitive and liberal teacher, then I might suspect that the teaching/learning process could be broken elsewhere—say, with my teaching technique—but I will not likely suspect that the entire mechanistic process itself does not adequately capture the reality of how students might learn to do in-text citations according to the MLA.

For two hundred years, both neuroscience and teaching have focused on a mechanistic model of input -> processing -> output, and this model has, indeed, taught us much about both brains and learning, but in the end, this model is too limiting. As Sporns says, "Until now, much of the interest in theoretical neuroscience has focused on stimulus-driven or task-related computation, and considerably less attention has been given to the brain as a dynamic, spontaneously active, and recurrently connected system" (149, 150). So what happens if we begin to consider students as dynamic, spontaneously active, recurrently connected systems?

Sporns explains why, despite its huge and continuing contributions to neuroscience, this mechanistic view does not adequately capture the reality of brains and, by my extension, the reality of students learning MLA techniques. Sporns provides strong research that suggests that the majority of neural activity is not in response to external input through eyes, ears, nose, tongue, and skin or output through motor and cognitive functions. As he says, "Whether considering individual neurons or entire brain regions, one finds that the vast majority of the structural connections that are made and received among network elements cannot be definitively associated with either input or output" (150). This raises at least the possibility that, similarly, most learning is not in response to either input through instruction or output through homework and papers.

Rather, the brain seems to spend much of its time self-organizing, partly in response to external inputs (nurture) and partly in response to internal physical structures (nature) but, perhaps, mostly through its own processes of maintenance and tweaking. As Sporns says, "Spontaneously generated network states form an internal functional repertoire. The observation and modeling of endogenous or spontaneous brain activity provide a unique window on patterns of self-organized brain dynamics—an intrinsic mode of neural processing that may have a central role in cognition" (151). The brain does not merely and automatically intake and process external inputs (say, teaching about MLA); rather, external inputs must "earn representation via their impact upon the pre-existing functional disposition of the brain" (151, Sporns quoting Rodolfo LlinĂ¡s).

I like that: external stimuli don't just automatically find a place within our brains; rather, they have to earn a place among the stuff that is already there. Thus, merely showing up in class and lecturing about how MLA handles in-text citations does NOT guarantee a place for my lecture in any student's mind. It doesn't even suggest a place. Rather, my lecture must "earn representation via [its] impact upon the pre-existing functional disposition of the [student's] brain." What's more, while the relationship between my lecture and one student brain is complex and dynamic enough, I likely have thirty students, all with differing "pre-existing functional dispositions" in their brains. Now, we're really beginning to appreciate the complication and complexity of learning. How does one teacher awaken in the different minds of thirty people even so simple a concept as in-text citations according to the MLA? Does it even make sense to ask that question, putting the onus of learning simply on the teacher as if she can stamp out knowledge from brain to brain?

Well, it's Sunday morning, and I'm just getting to the essential questions for me, but I'm also in the middle of repainting the guest bathroom, a task my wife really wants me to finish. Her desires are definitely earning representation via their impact upon the pre-existing functional disposition of my brain.

I will, of course, talk more about neural networks and education later.
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