Modeling of hyper-adaptability: from motor coordination to rehabilitation

Figures & data

Figure 1. Schematic diagram of motor control. (a) Humans can choose appropriate motor commands under the cost function provided by the environmental and body dynamics. (b) When the brain is damaged, cost function is changed so that humans need to choose different motor strategies. (c) Rehabilitation intervention aims to reshape the cost function and encourage the individual to hyper-adapt to learn a new motion strategy.

Table 1. Summary of weak and strong anticipation.

	Weak anticipation	Strong anticipation
Basic mechanism	Prediction of motor outcomes with internal models to estimate the body state for generation of motor commands	Synchronization of internal dynamics with body and environmental dynamics to reinforce motor commands
Normal adaptation	Updating of internal models to produce appropriate motor commands	No need to tune the parameters
Hyper adaptation	May not to be applicable	Reshaping of RNNs to find the global minimum
Examples	Optimal feedback control, MOSAIC	Anticipating synchronization, outfielder problems

Figure 2. Block diagram of the ‘parallel’ system: internal dynamics $g(\cdot )$ condition the behavior of the body $h(\cdot )$ such that it can be coupled with the target $f(\cdot )$ and predict its output such that $x(t+\tau )=y\left(t\right)$. Green elements represent intrinsic elements of the body and target, while yellow elements are added to enable anticipation.

Figure 3. Schematic illustration of the parallel model based on anticipating synchronization. Environmental dynamics drives both internal dynamics and body dynamics. Internal dynamics with the feedback loops will reinforce the original motor commands. Note that the internal dynamics is not internal models of environmental or body dynamics, just a band of oscillators. We discussed the possibility of using recurrent neural networks (RNNs) as internal dynamics.

Figure 4. Schematic illustration of the network modeling of normal state and hyper-adaptability.