Degrees of freedom problem
The motor equivalence problem was first formulated by the Russian neurophysiologist Nikolai Bernstein: "It is clear that the basic difficulties for co-ordination consist precisely in the extreme abundance of degrees of freedom, with which the [nervous] centre is not at first in a position to deal.
The latter has become predominant in motor control, as Bernstein's theories have held up well and are considered founding principles of the field as it exists today.
Animal models, though, remain relevant in motor control and spinal cord reflexes and central pattern generators are still a topic of study.
In Bernstein's formulation, the problem results from infinite redundancy, yet flexibility between movements; thus, the nervous system apparently must choose a particular motor solution every time it acts.
Bernstein's rational understanding of movement and prediction of motor learning via what we now call "plasticity" was revolutionary for his time.
Thus, Bernstein was one of the first to understand movement as a closed circle of interaction between the nervous system and the sensory environment, rather than a simple arc toward a goal.
Not only is the problem itself exceedingly difficult to tackle, but the vastness of the field of study makes synthesis of theories a challenge.
One of the largest difficulties in motor control is quantifying the exact number of DOFs in the complex neuromuscular system of the human body.
[3] Studies of limb mechanics focus on the peripheral motor system as a filter which converts patterns of muscle activation into purposeful movement.
In this paradigm, the building block is a motor unit (a neuron and all the muscle fibers it innervates) and complex models are built to understand the multitude of biological factors influencing motion.
Traditionally, neurophysiological studies have used animal models with electrophysiological recordings and stimulation to better understand human motor control.
The motor system has been shown to adapt to changes in its mechanical environment on relatively short timescales while simultaneously producing smooth movements; these studies investigate how this remarkable feedback takes place.
Common paradigms of study include voluntary reaching tasks and perturbations of standing balance in humans.
[11] A component of these adjustable gains might be a "minimum intervention principle" where the nervous system only performs selective error correction rather than heavily modulating the entirety of a movement.
A mix of cost variables such as minimum energy expenditure and a "smoothness" function is the most likely choice for a common performance criterion.
It has been shown that adaptation in a visuomotor reaching task becomes optimally tuned so that the cost of movement trajectories decreases over trials.
The theory must have certain information provided before it can make a behavioral prediction: what the costs and rewards of a movement are, what the constraints on the task are, and how state estimation takes place.
[9] Multiple operational time-scales complicate the process, including sensory delays, muscle fatigue, changing of the external environment, and cost-learning.
[15] Evidence for this structure comes from electromyographical (EMG) data in frogs, cats, and humans, where various mathematical methods such as principal components analysis and non-negative matrix factorization are used to "extract" synergies from muscle activation patterns.
[9] A nervous system which controls force must generate torques based on predicted kinematics, a process called inverse dynamics.
For example, during a sit-to-stand task, head and center-of-mass position in the horizontal plane are more tightly controlled than other variables such as hand motion.
Most of these theories also incorporate some sort of hierarchical neural control scheme, usually with cortical areas at the top and peripheral outputs at the lowest level.
