Using a reverse-engineering method similar to that of the Blue Brain Project, Jenn-Kang Hwang and her team at the National Tsing Hua University in Taiwan have engineered a computer-simulated  fruit fly brain with single-cell precision.

The researchers stained (using green-fluorescent protein) and imaged tens of thousands of neurons in the fly brain and used complex gene-marking procedures to find out which cells interacted with one another.

These methods helped them elucidate the architecture of specific networks of cells, and that information allowed for a reconstruction of the pathways of functional brain regions, and ultimately the full structure of the brain.  The authors compare their model of interacting neurons to a city highway system, writing:

Each unit is like a city containing local intersected streets and avenues linked to other cities through multi-lane highways without cross-traffic.  Sometimes, several geographically closed units form a family working together for a specific function requiring intensive information processing.

The researchers also address the age-old brain/computer comparison, pithily stating:

It seems that a fly brain is smarter and more complicated than any computer built thus far.

However, their work by no means represents a full understanding of the workings of the fruit fly brain and the translation of neural network to behavior (that level of understanding is a ways away); rather, it’s a useful visual tool for testing hypotheses about specific neural interactions in the fruit fly brain, and locating neurons of interest.  It’s akin to navigating on a road trip – why use a glove compartment full of small, unconnected state maps when you can use a nice, big road atlas?

The Hwang team has published the results of their brain-mapping project online for free and open access, just like the Human Genome Project did in 2003.  To see the exciting images and videos, go here.

h/t sciencedaily.com

We are very proud to present the world premiere of BLUEBRAIN – Year One, a documentary short which previews director Noah Hutton’s 10-year film-in-the-making that will chronicle the progress of The Blue Brain Project, Henry Markram’s attempt to reverse-engineer a human brain. Enjoy the piece and let us know what you think.

The film is being produced by Noah Hutton’s production company, Couple 3 Films.

Color-opponent cells in the primate visual cortex (Margaret Livingstone).

In an essay I wrote to coincide with the first Beautiful Brain podcast, I discussed some of the current trends in neuroaesthetics research as presented at the 2009 Copenhagen Neuroaesthics Conference. I did not mention some of the heavyweights in the field who have shaped much of the current conversation between the arts and the brain sciences— figures whose work is alternatingly insightful and reductive, microcosms of where we currently stand in this attempt at Consilience.

The names Ramachandran, Zeki, and Livingstone are among the top tier of art and brain researchers, each of whom have made and are continuing to make important contributions to the field from a variety of approaches. Harvard neurobiologist Margaret Livingstone’s achievements are in the realm of visual perception, based mostly on electrode recordings from primate visual cortex. Her work has demonstrated the building blocks of color perception—something we share with primates—where individual cells are tuned to fire action potentials in response to certain parts of the spectrum, and are organized in a system where color opposites, such as red and green, arise from the excitation and inhibition of these neighboring color-opponent cells.

The cellular basis of luminosity is another of Livingstone’s contributions to understanding our basic systems of visual perception; one of her favorite examples of the luminosity phenomenon is Monet’s “Impression Sunrise” of 1872.

Impression Sunrise, Claude Monet, 1872.

In this painting, the orange sun seems to glow against the darker sky for two reasons: first, the orange-blue color-opponent nature of our visual system sets the sun and sky apart in our color perception; second, the lack of any change in luminance between the sun and the sky activates our perception of the orange of the sun more intensely, and we perceive this wonderful glowing of the sun (if the image were grayscale, as below, we could not see the sun as well—thus, with luminance almost the same between sun and sky, our visual system seizes on differences in color, and the sun seems to pop out).

Impression Sunrise, grayscale.

Livingstone’s work presents some of the most exciting evidence we have for understanding the very basic phenomena of visual perception—yet because we’re talking about primates, it’s hard to get beyond these essential properties of color perception and optical illusions and move to an explanatory framework that could handle more of the complex subjectivity of human art. Knowing these visual basics can explain why Monet’s sun glows like it does, but this gets us only so far—the human brain quickly moves beyond base visual tricks and involves a much more subjective world of mood and memory.

V.S. Ramachandran is best known for both his work on synesthesia and his controversial “principles” to explain trends in art over millennia. While his synesthesia work is largely fMRI based, the “principles” combine fMRI data with predictions for what we may see on a cellular level during the perception of art. One of the principles Ramachandran most often uses as an example is that of the peak-shift phenomenon: he claims that across cultures and across art forms, pleasurable features of objects and figures are accentuated (such as the curves in a feminine figure) which target reward mechanisms in our brain, and could, in part, explain why we find certain art beautiful. In more modernist work, he argues that artists intuitively used techniques that played into the peak-shift phenomenon, such as Picasso’s faces, which present multiple perspectives of the same object to our visual system at the same moment, leading to a stronger activation of a category-specific “face cell” at the top of a hierarchy in the cortex, and thus a more pleasurable reaction. His principles feel exciting in their speculation into specific cellular mechanisms at hand during the perception of art, yet highly reductive in their lack of attention to the vast worlds of personal and cultural memory we bring to each viewing experience. As in Livingstone’s work, we can find starting points in these principles, but can never assume we are explaining the totality of the perceptive experience.

Lastly, Semir Zeki takes a similar bottom-up approach to cognitive science and aesthetics— studying, like Livingstone, the neural basis of color perception. His search has taken him from work on retinal cells to the visual cortex to the study of the neural correlates of the subjective states of love, beauty, and more recently, hate, mostly through fMRI work. “Perceiving something as ugly or beautiful involves activation of the medial orbito-frontal cortex,” he explained in a recent interview. “The [electrical] activity measured in these areas through scanning is much more pronounced when pictures considered to be beautiful are perceived.”

Zeki claims that artists are instinctive neuroscientists, innately understanding fundamental perceptual processes in the brain and exploring them in their art. Zeki’s writing gives much credit to artists who in reality, at the time they were working, had no idea of the actual physical properties of the brains they were using to create their art. This is neuro-revisionism, and it pervades much of the art/brain conversation in popular media—Virginia Woolf on consciousness, Monet on color processing, Stravinsky on cognitive dissonance—take your pick. Any art that anyone has ever produced can be mined for neuroscientific implications—it is more a product of the neuro-craze we live in at this juncture in the 21^st century than any sort of real or even metaphorical “prediction” these artists had about future scientific findings. One will find predictions about what’s inside wherever you want to find them—humans have brains, and we use them for everything. Is it such a wonder that our art has reflected fundamental principles of the thing that made it?

The artist as a portal (and only a portal—none living before modern neuroscience truly predicted any cellular findings) is an interesting way to approach brain science, especially for those unfamiliar with the science of cells and synapses. But it is dangerous in the evolution of this conversation between art and neuroscience because it has stopped, for the time being, in the aforementioned fMRI studies of individuals’ brains while they create and perceive art. These studies have lent important insights into the locations and role of brain regions, and could thus be used to generate hypotheses for future research at the cellular level—but because of the need to remain noninvasive with human subjects, we may be working with fMRI data combined with primate-based cellular speculation for many years to come. One hope to move beyond the delayed magnetic traces of blood-transported iron that fMRI machines detect is a modeling endeavor such as The Blue Brain Project, which seeks to simulate an entire human brain on IBM supercomputers, neuron by neuron, within ten years. If we have a functioning model of a brain, filled out with a life’s worth of experience, then perhaps we could really see what is happening in the dark jungle when art is made or seen.

We’re approaching a time in modern neuroscience where we can move beyond the fascination in correlating artistic output with cognitive neuroscience, beyond the loose association of an artist’s work with a modern fMRI study about a function of the brain that happens to have something to do with the art at hand. As some scientists—such as Livingstone and Ramachandran—have already began, we can start talking about cells and synapses, the most fundamental language we have, and appreciate the beauty of the brain by tracking the movement of a work of art through its dense networks that feedforward, feedback, and always associate, beginning to populate our understanding of art in the brain with higher and higher degrees of complexity.