Title :
Learning of spatial relationships between observed and imitated actions allows invariant inverse computation in the frontal mirror neuron system
Author :
Oh, Hyuk ; Gentili, Rodolphe J. ; Reggia, James A. ; Contreras-Vidal, José L.
Author_Institution :
Neurosci. & Cognitive Sci. Program, Univ. of Maryland, College Park, MD, USA
fDate :
Aug. 30 2011-Sept. 3 2011
Abstract :
It has been suggested that the human mirror neuron system can facilitate learning by imitation through coupling of observation and action execution. During imitation of observed actions, the functional relationship between and within the inferior frontal cortex, the posterior parietal cortex, and the superior temporal sulcus can be modeled within the internal model framework. The proposed biologically plausible mirror neuron system model extends currently available models by explicitly modeling the intraparietal sulcus and the superior parietal lobule in implementing the function of a frame of reference transformation during imitation. Moreover, the model posits the ventral premotor cortex as performing an inverse computation. The simulations reveal that: i) the transformation system can learn and represent the changes in extrinsic to intrinsic coordinates when an imitator observes a demonstrator; ii) the inverse model of the imitator´s frontal mirror neuron system can be trained to provide the motor plans for the imitated actions.
Keywords :
neurophysiology; action execution; biologically plausible mirror neuron system model; frontal mirror neuron system; imitated action; inferior frontal cortex; internal model framework; invariant inverse computation; inverse model; learning; observed action; posterior parietal cortex; spatial relationship; superior temporal sulcus; ventral premotor cortex; Adaptation models; Biological system modeling; Brain modeling; Computational modeling; Mirrors; Neurons; Visualization; Humans; Imitative Behavior; Models, Biological; Neurons;
Conference_Titel :
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-4121-1
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2011.6091038