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1 Neurobiology, Hebrew University, Jerusalem, Israel; Interdisciplinary Center for Neural Computation, Hebrew University, Jerusalem, Israel
2 Neurobiology, Hebrew University, Jerusalem, Israel
3 Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
* To whom correspondence should be addressed. E-mail: yoramkt{at}shum.cc.huji.ac.il.
The dynamic model of the octopus arm described in paper I (Yekutieli et al. 2005) was used here to investigate the neural strategies employed for controlling the reaching movements of the octopus arm. These are stereotypical extension movements used to reach towards an object. In the dynamic model, sending a simple propagating neural activation signal to contract all muscles along the arm produced an arm extension with kinematic properties similar to those of natural movements. Control of only two parameters fully specified the extension movement: the amplitude of the activation signal (leading to the generation of muscle force) and the activation traveling time (the time the activation wave takes to travel along the arm). We found that the same kinematics could be achieved by applying activation signals with different activation amplitudes all exceeding some minimal level. This suggests that the octopus arm could employ minimal amplitudes of activation to generate the minimal muscle forces required for the production of the desired kinematics. Larger amplitude signals would generate larger forces that increase the arm's stability against perturbations without changing the kinematic characteristics. The robustness of this phenomenon was demonstrated by examining activation signals with either a constant or a bell-shaped velocity profile. Our modeling suggests that the octopus arm biomechanics may allow independent control of kinematics and resistance to perturbation during arm extension movements.
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