Investigation of Control and Coordination Strategies of Multi-Joint Reaching Movements

My PhD research is focused on understanding how our central nervous system (CNS) tackles the problem of motor redundancy in order to plan and execute multi-joint reaching movements. One could think of human body as a machine consisting of several effectors (Arms, Legs, Torso and Head) which are controlled by a central processor, the brain and the spinal chord. The research revolves around how our brain takes advantage of the biomechanical structure of the corresponding effectors to produce goal directed movements. In order to do that, the brain needs to have a clear understanding of the relationship between the descending motor commands and the consequent response that it elicits on its effectors.

This research investigation is approached in three different ways -

1) By observing the structure of control and co-ordination at the level of joints and muscles during the reaching movement.

2) By building a computational model of the dynamics of the arm to predict the control structure.

3) By manipulating the sensory motor association between the motor commands and the arm dynamics to study the effects of motor learning through supervised and reinforcement learning paradigms.

Motor Redundancy

In human beings, behavior largely manifests with the production of multi-joint movements. This involves controlling individual effectors as well as spatiotemporal coordination between them (Latash, 2008). Common daily activities such as reaching for an object, walking, typing on a keyboard, and so on utilize multi-joint movements. These seemingly easy tasks are quite involved and computationally challenging for our central nervous system (CNS). Specifically, our limbs are bestowed with multiple degrees of freedom (DoFs) in order to accomplish a variety of complex tasks, while an individual task would pose fewer constraints. For example, reaching a point in space would impose 3 constraints (X, Y, Z positions in Cartesian coordinates) while our upper arm consists of 7 degrees of freedom at shoulder, elbow, and wrist joints (ignoring the 21 DoFs of hand). The problem for CNS is to solve this under constraint system to arrive at a single solution among infinitely many possible theoretical solutions. This is known as the problem of motor redundancy (Bernstein, 1967). Bernstein had proposed the computations in terms of coordination among individual effectors as a means to solve this problem (Bernstein, 1967; Bongaardt and Meijer, 2000). Gelfand and Latash restated this problem as the problem of motor abundance by stating that the system exploits among the many equally achievable solutions and establishes an advantageous flexible control strategy (Gelfand and Latash, 1998; Latash et al., 2000).

Leading Joint Hypothesis

One mechanism that has been postulated to deal with the problem of motor-abundancy is advocated by Dounskaia and her team who have suggested for the leading joint hypothesis (LJH). The LJH states that any multi-joint reaching movement consists of a leading joint which contributes to the majority of the active muscle torque which drives the movement while the other subordinate joints utilize interaction torques caused due to mechanical linkage and also actively compensate for any endpoint error during the movement (Dounskaia, 2010; Kim et al., 2009; Ambike and Schmiedeler, 2013). In the context of this hypothesis, a major goal of the CNS is to choose the leading and subordinate joints through the process of learning.

References -

• Latash, Mark. Synergy. Oxford University Press, 2008.

• Bernshteĭn, N. A. The Co-Ordination and Regulation of Movements. Pergamon Press, 1967.

• Bongaardt, Rob, and Onno G. Meijer. “Bernstein’s Theory of Movement Behavior: Historical Development and Contemporary Relevance.” Journal of Motor Behavior, vol. 32, no. 1, Mar. 2000.

• Gelfand IM, Latash ML. On the problem of adequate language in motor control. Motor Control. 1998

• Latash, M. “There Is No Motor Redundancy in Human Movements. There Is Motor Abundance.” Motor Control, vol. 4, no. 3, July 2000.

• Dounskaia, Natalia. “Control of Human Limb Movements: The Leading Joint Hypothesis and Its Practical Applications.” Exercise and Sport Sciences Reviews, vol. 38, no. 4, Oct. 2010, p. 201.

• Kim, Young-Kwan, et al. “Multicomponent Control Strategy Underlying Production of Maximal Hand Velocity during Horizontal Arm Swing.” Journal of Neurophysiology, vol. 102, no. 5, Nov. 2009, pp. 2889–99.

• Ambike, Satyajit, and James P. Schmiedeler. “The Leading Joint Hypothesis for Spatial Reaching Arm Motions.” Experimental Brain Research, vol. 224, no. 4, Feb. 2013, pp. 591–603.

Coursework during PhD (Cumulative Grade Point - 8.4/10) -

1. Fundamentals of Systems and Cognitive Neuroscience

2. Fundamentals of Molecular and Cellular Neuroscience

3. Topics in Systems and Cognitive Neuroscience

4. Neural Signal Processing

5. Applied Probability and Statistics

6. Dynamics and Control of Mechanical Systems

© Niranjan Chakrabhavi