Title |
MEART: the semi-living artist
|
---|---|
Published in |
Frontiers in Neurorobotics, November 2007
|
DOI | 10.3389/neuro.12.005.2007 |
Pubmed ID | |
Authors |
Douglas J Bakkum, Philip M Gamblen, Guy Ben-Ary, Zenas C Chao, Steve M Potter |
Abstract |
Here, we and others describe an unusual neurorobotic project, a merging of art and science called MEART, the semi-living artist. We built a pneumatically actuated robotic arm to create drawings, as controlled by a living network of neurons from rat cortex grown on a multi-electrode array (MEA). Such embodied cultured networks formed a real-time closed-loop system which could now behave and receive electrical stimulation as feedback on its behavior. We used MEART and simulated embodiments, or animats, to study the network mechanisms that produce adaptive, goal-directed behavior. This approach to neural interfacing will help instruct the design of other hybrid neural-robotic systems we call hybrots. The interfacing technologies and algorithms developed have potential applications in responsive deep brain stimulation systems and for motor prosthetics using sensory components. In a broader context, MEART educates the public about neuroscience, neural interfaces, and robotics. It has paved the way for critical discussions on the future of bio-art and of biotechnology. |
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Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 33% |
Spain | 1 | 33% |
Unknown | 1 | 33% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 3 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 4% |
Switzerland | 1 | 1% |
Italy | 1 | 1% |
France | 1 | 1% |
Japan | 1 | 1% |
Russia | 1 | 1% |
Unknown | 62 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 19 | 27% |
Researcher | 11 | 16% |
Student > Master | 10 | 14% |
Student > Doctoral Student | 5 | 7% |
Professor > Associate Professor | 5 | 7% |
Other | 15 | 21% |
Unknown | 5 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 19 | 27% |
Engineering | 13 | 19% |
Physics and Astronomy | 6 | 9% |
Computer Science | 5 | 7% |
Neuroscience | 5 | 7% |
Other | 13 | 19% |
Unknown | 9 | 13% |