A Neural Network model for spatial mental imagery investigation: A study with the humanoid robot platform iCub

2011 ◽  
Author(s):  
Alessandro G. Di Nuovo ◽  
Davide Marocco ◽  
Santo Di Nuovo ◽  
Angelo Cangelosi
Keyword(s):  
Neural Network ◽  
Mental Imagery ◽  
Network Model ◽  
Neural Network Model ◽  
Humanoid Robot ◽  
Robot Platform

scholarly journals CREATING NOVEL GOAL-DIRECTED ACTIONS AT CRITICALITY: A NEURO-ROBOTIC EXPERIMENT

2009 ◽  
Vol 05 (01) ◽  
pp. 307-334 ◽  
Author(s):  
HIROAKI ARIE ◽  
TETSURO ENDO ◽  
TAKAFUMI ARAKAKI ◽  
SHIGEKI SUGANO ◽  
JUN TANI
Keyword(s):  
Neural Network ◽  
Prefrontal Cortex ◽  
Network Model ◽  
Neural Network Model ◽  
Physical Environment ◽  
Humanoid Robot ◽  
Parietal Lobe ◽  
Initial State ◽  
Cognitive Behaviors ◽  
Sensory Motor

The present study examines the possible roles of cortical chaos in generating novel actions for achieving specified goals. The proposed neural network model consists of a sensory-forward model responsible for parietal lobe functions, a chaotic network model for premotor functions and prefrontal cortex model responsible for manipulating the initial state of the chaotic network. Experiments using humanoid robot were performed with the model and showed that the action plans for satisfying specific novel goals can be generated by diversely modulating and combining prior-learned behavioral patterns at critical dynamical states. Although this criticality resulted in fragile goal achievements in the physical environment of the robot, the reinforcement of the successful trials was able to provide a substantial gain with respect to the robustness. The discussion leads to the hypothesis that the consolidation of numerous sensory-motor experiences into the memory, meditating diverse imagery in the memory by cortical chaos, and repeated enaction and reinforcement of newly generated effective trials are indispensable for realizing an open-ended development of cognitive behaviors.

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