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MEART: The Semi-Living Artist.

Bakkum DJ, Gamblen PM, Ben-Ary G, Chao ZC, Potter SM - Front Neurorobot (2007)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Laboratory for Neuroengineering, School of Mechanical Engineering, Georgia Institute of Technology USA.

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.

No MeSH data available.


Related in: MedlinePlus

Plastic changes in MEART and animat behavior. Unsuccessful and successful training of goal-directed animat behavior. MEART. Training with predetermined PTS caused a shift in the probability distribution of commanded movement directions in two experiments (circles, bottom row), but in an uncontrolled manner. Marks first accumulated on a side of the drawing's workspace (CCD camera image of the drawing and pixelized feedback), but successful PTS training should shift the markings back toward the center (red arrow middle row; black arc bottom row). The probability distribution of movement directions during 10 minute at the start of 2 hour experiments was subtracted from that during the final 10 minute, thus allowing negative values (red). Simulated animat. Iteratively updating the probability of selecting a given PTS for training allowed an animat to learn to move in multiple directions (circles; see Methods: Making the Semi-Living Artist). Desired angles of 0, 90, and −45 degrees (black arcs) were applied in consecutive 2 hour periods. Successful behavior was considered to be movement within the desired angle ±30 degree. Notice the changes in probability distribution of movement direction were now more likely to be in the appropriate direction and more focused than for MEART.
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Figure 7: Plastic changes in MEART and animat behavior. Unsuccessful and successful training of goal-directed animat behavior. MEART. Training with predetermined PTS caused a shift in the probability distribution of commanded movement directions in two experiments (circles, bottom row), but in an uncontrolled manner. Marks first accumulated on a side of the drawing's workspace (CCD camera image of the drawing and pixelized feedback), but successful PTS training should shift the markings back toward the center (red arrow middle row; black arc bottom row). The probability distribution of movement directions during 10 minute at the start of 2 hour experiments was subtracted from that during the final 10 minute, thus allowing negative values (red). Simulated animat. Iteratively updating the probability of selecting a given PTS for training allowed an animat to learn to move in multiple directions (circles; see Methods: Making the Semi-Living Artist). Desired angles of 0, 90, and −45 degrees (black arcs) were applied in consecutive 2 hour periods. Successful behavior was considered to be movement within the desired angle ±30 degree. Notice the changes in probability distribution of movement direction were now more likely to be in the appropriate direction and more focused than for MEART.

Mentions: While successful behavior did not occur (Figure 7), neural plasticity did (Figures 7 and 8), suggesting training stimuli had the potential to modify behavior. Normalized plasticity was defined as the difference in distribution of movement-controlling output (the CAs) in a given 10-minute period (CAPost) to those of the first 10 minute (CAPre) as:(3)Normalized change=Mean{‖CA⃑Post−CA⃑¯Pre‖2}Variance{CA⃑Pre}=∑Post‖CA⃑Post−CA⃑¯Pre‖2∑Pre‖CA⃑Pre−CA⃑¯Pre‖2where is a mean of CA vectors. A value of 1 indicates no change.


MEART: The Semi-Living Artist.

Bakkum DJ, Gamblen PM, Ben-Ary G, Chao ZC, Potter SM - Front Neurorobot (2007)

Plastic changes in MEART and animat behavior. Unsuccessful and successful training of goal-directed animat behavior. MEART. Training with predetermined PTS caused a shift in the probability distribution of commanded movement directions in two experiments (circles, bottom row), but in an uncontrolled manner. Marks first accumulated on a side of the drawing's workspace (CCD camera image of the drawing and pixelized feedback), but successful PTS training should shift the markings back toward the center (red arrow middle row; black arc bottom row). The probability distribution of movement directions during 10 minute at the start of 2 hour experiments was subtracted from that during the final 10 minute, thus allowing negative values (red). Simulated animat. Iteratively updating the probability of selecting a given PTS for training allowed an animat to learn to move in multiple directions (circles; see Methods: Making the Semi-Living Artist). Desired angles of 0, 90, and −45 degrees (black arcs) were applied in consecutive 2 hour periods. Successful behavior was considered to be movement within the desired angle ±30 degree. Notice the changes in probability distribution of movement direction were now more likely to be in the appropriate direction and more focused than for MEART.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2533587&req=5

Figure 7: Plastic changes in MEART and animat behavior. Unsuccessful and successful training of goal-directed animat behavior. MEART. Training with predetermined PTS caused a shift in the probability distribution of commanded movement directions in two experiments (circles, bottom row), but in an uncontrolled manner. Marks first accumulated on a side of the drawing's workspace (CCD camera image of the drawing and pixelized feedback), but successful PTS training should shift the markings back toward the center (red arrow middle row; black arc bottom row). The probability distribution of movement directions during 10 minute at the start of 2 hour experiments was subtracted from that during the final 10 minute, thus allowing negative values (red). Simulated animat. Iteratively updating the probability of selecting a given PTS for training allowed an animat to learn to move in multiple directions (circles; see Methods: Making the Semi-Living Artist). Desired angles of 0, 90, and −45 degrees (black arcs) were applied in consecutive 2 hour periods. Successful behavior was considered to be movement within the desired angle ±30 degree. Notice the changes in probability distribution of movement direction were now more likely to be in the appropriate direction and more focused than for MEART.
Mentions: While successful behavior did not occur (Figure 7), neural plasticity did (Figures 7 and 8), suggesting training stimuli had the potential to modify behavior. Normalized plasticity was defined as the difference in distribution of movement-controlling output (the CAs) in a given 10-minute period (CAPost) to those of the first 10 minute (CAPre) as:(3)Normalized change=Mean{‖CA⃑Post−CA⃑¯Pre‖2}Variance{CA⃑Pre}=∑Post‖CA⃑Post−CA⃑¯Pre‖2∑Pre‖CA⃑Pre−CA⃑¯Pre‖2where is a mean of CA vectors. A value of 1 indicates no change.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Laboratory for Neuroengineering, School of Mechanical Engineering, Georgia Institute of Technology USA.

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.

No MeSH data available.


Related in: MedlinePlus