Embodying cultured networks with a robotic drawing arm.
The advanced and robust computational power of the brain is shown by the complex behaviors it produces. By embodying living cultured neuronal networks with a robotic or simulated animal (animat) and situating them within an environment, we study how the basic principles of neuronal network communication can culminate into adaptive goal-directed behavior. We engineered a closed-loop biological-robotic drawing machine and explored sensory-motor mappings and training. Preliminary results suggest that real-time performance-based feedback allowed an animat to draw in desired directions. This approach may help instruct the future design of artificial neural systems and of the algorithms to interface sensory and motor prostheses with the brain.
Bakkum
Douglas J
DJ
Department of Biomedical Engineering, Georgia Tech and Emory Univ., USA.
Chao
Zenas C
ZC
Gamblen
Phil
P
Ben-Ary
Guy
G
Shkolnik
Alec G
AG
DeMarse
Thomas B
TB
Potter
Steve M
SM
D000818:Animals; D001132:Arm / Q000502:physiology*; D001185:Artificial Intelligence; D032701:Biomimetics / Q000295:instrumentation* / Q000379:methods; D001701:Bionics / Q000295:instrumentation* / Q000379:methods; D018929:Cell Culture Techniques / Q000295:instrumentation* / Q000379:methods; D002478:Cells, Cultured; D003491:Cybernetics / Q000295:instrumentation / Q000379:methods; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D009415:Nerve Net / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods; D051381:Rats; D012371:Robotics / Q000295:instrumentation* / Q000379:methods; D018511:Systems Integration