How did “thinking” change in the Age of Enlightenment? That’s Wayne McGregor’s query in his newest ballet, FAR. This is worth several minutes of viewing:
Dave Pounds, my colleague in the Undergraduate Academic Program at UNCSA, put together a remarkable opportunity for faculty here a couple weeks ago—a symposium on “The Brain and Network Science” featuring two scholars from Wake Forest University, Dr. Jonathan Burdette and Dr. Paul Laurienti. The teaser for the talk was this:
” . . . The 20th Century was the century of Reductionism. The 21st Century will be the century of Complexity. We will present introductory concepts about complexity and chaos theory, fractals, and network science, and how these relate to nature, including the human body. We will also explain how network science is revolutionizing studies of the human brain. Given the interests of and expertise at UNCSA, we will integrate a discussion of fractals and network science in art and music. . .”
The talk delivered on these and a multitude of other points. Notable were Dr. Burdette’s initial comments regarding how, over the course of his early career, he has come to rethink and replace his fundamental assumptions about brain science, spurred on by developments in the relatively new field of “network science” and complexity theory. Burdette and Laurienti explain in one of their most recent articles that
” …Network science is a burgeoning field of scientific inquiry that has been used to better understand complex integrated systems, such as social networks, the US power grid, and gene interactions (Watts and Strogatz, 1998; Barabasi and Albert, 1999). More recently, this methodology has been applied to study the functional and structural connectivity of the human brain and is shedding new light on how the brain works as a system (Bullmore and Sporns, 2009). . . .”
Burdette explained that network science led him away from studying the brain through what he now refers to as a “reductionist” lens—i.e. conceiving of the brain as a machine with component parts, each with its specialized set of tasks—toward looking at the brain as a dynamic constellation of self-similar systems-within-systems (that’s where the fractal stuff comes in–long live Mandelbrot!).
The more I say about this, the greater the risk that I’ll badly misrepresent these fellows’ scholarship. But I have to admit, I took some comfort from the fact that some of the phenomena they were discussing weren’t entirely unfamiliar—back in 2009 at first ARTStem seminar, we read Melanie Mitchell’s Complexity: A Guided Tour. Then, as now, I was struck by the power of “network” science as an explanatory mechanism. But also, with its lexicon of ‘nodes’, ‘hubs’ and ‘links,’ network theory offers a potent and aesthetically appealing metaphorical language through which artists and scientists are destined to converge in the coming decades. It was valuable to sit in the room with UNCSA colleagues from different reaches of campus, learning of these emergent understandings of how our brains work, but also simply hearing Burdette and Laurienti wield this increasingly influential, paradigmatic (T.S. Kuhn, anyone?) vocabulary.
Network theory is already leading us to reimagine the way communities of minds work, the way ideas travel, and the value of the ‘unexpected’ things that happen within complex systems. At least in a metaphorical sense, I see ARTStem’s strategy of putting faculty from different institutions, different disciplines, and different art forms together into a new intellectual and creative community as reflective of some dimension of network thinking. Aren’t we all aware, after all, that the disciplinary divides that cut across institutions like UNCSA, and the organizational firewalls that mitigate the free flow of ideas between secondary and post-secondary educators, are themselves “reductionist” artifacts of the 19th and 20th centuries? [It's not a bad comparison, actually . . . the age of that static sort of phrenological mapping of the brain, which Burdette and Laurienti reject, largely coincided with the age in which the academy organized itself into disciplinary specializations]. The 21st century will likely reward those institutions and communities that facilitate the creative capacities of complex systems.
Anyways, thanks to Dave for bringing this enlightening event to campus, with its fortuitous connection to some of the same ideas ARTStem’s been playing with of late.
For those who attended the “Brain and Network Science” talk on campus recently, or even if you didn’t, there’s a fascinating article at SEED magazine online about how the brain works in periods of improvisation, musical or otherwise.
‘I saw it with my own eyes!’ We tend to believe what we see with our eyes is real and accurate. What we often do not realize is that our eyes register only a reflection of the outside world. To reconstruct reality from this reflection we have to rely on inferences and assumptions. It is like putting together the pieces of a puzzle without any knowledge about the whole picture. Our brain does this without our conscious awareness. In a split second it organizes and interprets incoming visual information to form a stable and meaningful image of the world around us. The brain does not analyze all the incoming information in detail, though. Only the most relevant or interesting part is permitted through the ‘gateway to consciousness’. The rest of the information you are not aware of. For example, when you concentrate on your television set you will not see the painting hanging above it on the wall. Every individual also has internal neural factors, such as memory, that influence the brain’s interpretation of information. For example, when you have experienced something before, it is hard to see things ‘differently’ on a second encounter. The information registered by your eyes intermingles with a blueprint of the previous encounter you have stored in your memory. Your image of the outside world thus is a mixture of incoming visual information and internal neural factors. Therefore, it is a personal experience unique to you. ‘You look with your eyes, but you see with your brain!’ Short explanation of the video: Our video explains the basics of how the brain analyzes visual information. You see a man (‘the observer’) watching a movie-clip on his laptop. The visual information presented on his laptop is registered by his eyes and translated into neural signals that enter his brain. Through dance we portray what happens inside the observer’s brain. The leading dancer in the video, who can be recognized by the brain depicted on his clothing, represents the observer’s internal neural factors, such as his goals and experiences. The dancers with an information-icon depicted on their clothing (‘the i-dancers’) represent the incoming visual information. In the observer’s brain the visual information is organized and features that belong together are grouped (the leading dancer puts the i-dancers in the correct positions). Then, one piece of the visual information is selected for detailed neural analysis (in the foreground the leading dancer examines one of the i-dancers). The neural processing of the other information is suppressed (the other i-dancers make slower movements in the background). When the observer is interrupted by a phone call the neural analysis of the visual information dies out (all dancers fall on the ground). After the phone call the observer looks at his laptop again. He now remembers the movie-clip on his laptop. The organization of the visual information inside his brain is more efficient than before (the leading dancer groups the i-dancers fast and deliberately). Also, the visual information has become predictable (the leading dancer knows the choreography of the i-dancers). For detailed neural processing the observer’s brain easily selects the same piece of visual information as before (the leading dancer guides his favorite i-dancer to the foreground again), which now interacts with the internally stored blueprint (the leading dancer and the favorite i-dancer dance together). ‘The eye sees only what the mind is prepared to comprehend.’ Henri-Louis Bergson 1859-1941. French philosopher and Literature Nobel Prize winner in 1927 see http://www.maartjedejong.com/Pictures/dance/dancephotos.htm for a visual explanation, news and extras about this video. ‘Dance Your Ph.D.’ Finalists Announced – ScienceNOW.
“ . . . ‘We’ve always done ourselves a big disservice in dance by saying that it isn’t an intellectual art form, but one of instinct,’ he tells me. ‘Of course, instinct plays into the way we generate and perform choreography, but I’ve always been fascinated by what’s going on with the physical thinking; not only when performing, but in actually creating movement. What are the models by which imagination is constrained? What is this relationship between the brain and the body? And what would happen if you corrupted the messages from the brain to the body, to try and make somebody dis-coordinated, un-coordinated; the antithesis of what you usually do with choreography, which is all body-perfect, body-beautiful?’ . . .
. . . For the scientists’ part, the collaboration seems to be proving equally fruitful. Barnard, whose speciality is clinical depression, suggests that the tools being developed to help dancers free themselves from mental traps may influence how depressive patients are treated in future. . . “
This is remarkable. Composer and flutist Finn Peters is working with technology that translates his brainwaves directly into the music he is “thinking.” Read more.
” . . . These concepts haven’t just influenced my scientific work—they have also affected my playing. For example, musical patterns that are not intuitive melodically can arise because they lie comfortably under the hands. Physical logic can be used to generate musical ideas. You can hear this happen in Chopin, whose music is very ‘pianistic’—that is, it lies well under the fingers. . .”