Biomedical subjects

Emanuel Todorov

Publications and source records attributed to Emanuel Todorov.

3 recordsLinked to original sources

PubMed2004

Optimality principles in sensorimotor control.

The sensorimotor system is a product of evolution, development, learning and adaptation-which work on different time scales to improve behavioral performance. Consequently, many theories of motor function are based on 'optimal performance': they quantify task goals as cost functions, and apply the sophisticated tools of optimal control theory to obtain detailed behavioral predictions. The resulting models, although not without limitations, have explained more empirical phenomena than any other class. Traditional emphasis has been on optimizing desired movement trajectories while ignoring sensory feedback. Recent work has redefined optimality in terms of feedback control laws, and focused on the mechanisms that generate behavior online. This approach has allowed researchers to fit previously unrelated concepts and observations into what may become a unified theoretical framework for interpreting motor function. At the heart of the framework is the relationship between high-level goals, and the real-time sensorimotor control strategies most suitable for accomplishing those goals.

Adaptation, Physiological↗

PubMed2002

Optimal feedback control as a theory of motor coordination.

A central problem in motor control is understanding how the many biomechanical degrees of freedom are coordinated to achieve a common goal. An especially puzzling aspect of coordination is that behavioral goals are achieved reliably and repeatedly with movements rarely reproducible in their detail. Existing theoretical frameworks emphasize either goal achievement or the richness of motor variability, but fail to reconcile the two. Here we propose an alternative theory based on stochastic optimal feedback control. We show that the optimal strategy in the face of uncertainty is to allow variability in redundant (task-irrelevant) dimensions. This strategy does not enforce a desired trajectory, but uses feedback more intelligently, correcting only those deviations that interfere with task goals. From this framework, task-constrained variability, goal-directed corrections, motor synergies, controlled parameters, simplifying rules and discrete coordination modes emerge naturally. We present experimental results from a range of motor tasks to support this theory.

Feedback↗

PubMed2002

Cosine tuning minimizes motor errors.

Cosine tuning is ubiquitous in the motor system, yet a satisfying explanation of its origin is lacking. Here we argue that cosine tuning minimizes expected errors in force production, which makes it a natural choice for activating muscles and neurons in the final stages of motor processing. Our results are based on the empirically observed scaling of neuromotor noise, whose standard deviation is a linear function of the mean. Such scaling predicts a reduction of net force errors when redundant actuators pull in the same direction. We confirm this prediction by comparing forces produced with one versus two hands and generalize it across directions. Under the resulting neuromotor noise model, we prove that the optimal activation profile is a (possibly truncated) cosine--for arbitrary dimensionality of the workspace, distribution of force directions, correlated or uncorrelated noise, with or without a separate cocontraction command. The model predicts a negative force bias, truncated cosine tuning at low muscle cocontraction levels, and misalignment of preferred directions and lines of action for nonuniform muscle distributions. All predictions are supported by experimental data.

Artifacts↗