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Research Interests 

Physiology - Psychophysics - Theoretical models - Action observation - Somatics


A word about me

Everything about human movement is interesting to me.  I like the way we ‘live’ in our bodies and take them for granted, hardly ever really stopping to notice them until they remind us of their presence with pain.  I like the wisdom and insight we can gain by simply choosing to pay attention to our bodies, their subtle spontaneous movements and the experience of using them in every day life.  I like the beauty of athletes and dancers (and others) for whom moving their body is a way of life and a living.  It is natural, then, that as a scientist I've chosen to study movement, control of movement, and motor learning.  That is, I study how voluntary movements are controlled and how new skills are learned.  

My interest in this area interacts with my own experiences of moving -- as an athlete, or a martial artist, or a dancer.  I am working to integrate my scientific work with a more lived experience of the body, and I am very open to students who are interested in pursuing projects in this direction.

Past direction and current research

My scientific background is a collection of variations on the theme of motor control. In my PhD, under the direction of Prof. Eilon Vaadia (Hebrew Univesrity, Jerusalem) I studied the activity of single units in motor cortex of awake behaving primates. The monkeys performed movements with one arm alone or both arms together, and I asked how the two different sides of the cortex were involved in control of these movements.  I followed this with postdoctoral research with Prof. Reza Shadmehr (Johns Hopkins University, Baltimore, MD) using psychophysical techniques and computer modeling of human behavior.  While I was involved in a number of projects during my post doc, the main focus was a study of the representation of forces experienced during simple reaching movements. Please see my list of publications for background on that research.

I am currently pursuing research in a number of complementary directions including physiological research, behavioral research, theoretical modeling and other more abstract approaches to the study of movement.  Below I include a brief summary of each project.

Physiology

Perturbed reaching

The perturbed reaching task is one of the most intensively studied paradigms in the field of motor control and motor learning.  It has been enormously succesful as a tool for studying how movements are represented, how they are learned and consolidated, how feedforward and feedback control interact in the control of movement, and many other aspectsof motor control.  Understandably, there is considerable interest in understanding how the brain learns this task.  While some researchers have studied the role of motor cortex in the learning of this task, significant evidence suggests that the cerebellum plays a key role in perturbed reaching.  We have trained cats to perform the perturbed reaching task and are currently working on chronic implantation of recording electrodes into the cerebellum to explore the how Purkinje cells behave during this task.

Bistability of Purkinje cells

The bistability of Purkinje cell membranes represents a serious challenge to current models of cerebellar function. Evidence from our lab (Yartsev et al., 2009) suggests that this bistability has a profound effect on the firing rate of Purkinje cells in the awake cat, but leaves open the question of its functional role.  We are continuing this line of research by investigating the bistability of simultaneously recorded Purkinje cells in the awake and anaesthetized cat.

Psychophysics

In collaboration with Prof. Dagmar Timmann of  Essen University, we have been exploring the functional roles of different areas associated with arm movements in the cerebellar cortex. We believe that by better understanding the mapping of specific functions on the cerebellar cortex, we will gain a better understanding both of how the cerebellar cortex is organized and also about how the motor system itself is organized to perform different tasks.  Some of this work has been published (Rabe et al., 2009), and a second article is currently under review.

Theoretical models

Behavior of people learning the perturbed reaching paradigm has been succesfully modeled.  While many aspects of the task remain unmodeled, the basic models that have been developed have been remarkably succesful in capturing the trial-to-trial variance in human movement.  For instance, the simple state space model below
State space model of learning
says that y, a 2x1 vector representing the error on movement n, is the difference between F, the force applied on movement n, and z, the expectation of force generated by an internal model the subject maintains of the task dynamics. This internal model exists for all possible directions of movement, so z is a 2Mx1 vector (where M is the number of possible targets) and K is a 2Mx2 matrix that selects the expectation appropriate to the current direction. The second equations stipulates that this internal model is updated after each movement by an amount proportional to the error.  K now assigns the error to the dimensions within the 2M vector that are appropriate for the current movement direction.  The 2Mx2M parameter B is the generalization matrix which says how much movements in one direction should affect other directions. The 2x2 parameter D is a compliance matrix and describes how far the hand moves as a result of a unit force different directions.  This simple model is capable of describing up to 80% of the variance from movement to movement of individual subjects and more than 90% of the variance of data averaged across subjects.

My current modeling work is going in two opposite directions from this starting point.On the one hand, we have developed a model of the cerebellum (based on the model of Schweighofer from 1998) which is capable of learning in the way described by the state space model above. On the other hand, we are developing models of the entire motor system based on the underlying ideas of control systems.

Observation

We can learn through the observation of others. It has recently been suggested that this process results from activation of motor areas, and that motor learning through action observation uses much the same mechanisms as actual motor practice. We have tested this and discovered that a number of predictions that result from this hypothesis are violated in a complex motor learning task where people learn skils like juggling and devil sticks.  We are continuing these investigations in hopes of discovering what precisely is learned through observation of this task, and during what stages of learning this occurs.

Embodiment

I am very interested in the possibility of combining approaches to motor learning that arise from the somatic methods -- such as Feldenkrais, Alexander, Pilates, Yoga, and others -- with the scientific approach to understanding.  I am actively engaged in a project to determine whether motor practice can influence cognitive and emotional behavior, and to test the hypothesis that the mechanism of this effect is revealed in specific oscillations in the EEG.

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Last Updated: January 31, 2010
Maintained by donchin@bgu.ac.il