Abstract
To interact successfully with an uncertain environment, organisms must be able to respond to both unanticipated and anticipated events. For unanticipated events, organisms have evolved stereotyped motor behaviors mapped to the statistical regularities of the environment, which can be trigged by specific sensory stimuli. These “reflexive” responses are more or less hardwired to prevent falls and represent, maybe, the best available solution to maintaining posture given limited available time and information. With the gift of foresight, however, motor behaviors can be tuned or prepared in advance, improving the ability of the organism to compensate for, and interact with, the changing environment. Indeed, foresight's improvement of our interactive capacity occurs through several means, such as better action selection, processing, and conduction delay compensation and by providing a prediction with which to compare our actual behaviors to, thereby facilitating error identification and learning. Here we review the various roles foresight (prediction) plays in maintaining our postural equilibrium. We start by describing some of the more recent findings related to the prediction of instability. Specifically, we cover recent advancements in the understanding of anticipatory postural behaviors that are used broadly to stabilize volitional movement and compensate for impending postural disturbances. We also describe anticipatory changes in the state, or set, of the nervous system that may facilitate anticipatory behaviors. From changes in central set, we briefly discuss prediction of postural instability online before moving into a discussion of how predictive mechanisms, such as internal models, permit us to tune, perhaps our highest level predictive behaviors, namely the priming associated with motor affordances. Lastly, we explore methods best suited to expose the contribution of prediction to postural equilibrium control across a variety of contexts.
Highlights
The world is full of obstacles, opportunities and distractions with which we must interact
Some of the ways in which prediction contributes to balance are well understood, in cases where self-initiated movement needs to be stabilized or when we need to counter a known perturbation originating from an external source
Both of these instances hinge on past-experience and learning to match postural adjustments with an internal representation of the forthcoming disruption to equilibrium
Summary
The world is full of obstacles, opportunities and distractions with which we must interact. Given the capacity of these “cognitive” networks to process current and historical information, they are ideally suited to recognize current context in the light of previous experience for the purpose of dynamically anticipating and preparing for action Such flexibility is important as we move through the world because the actions that are ideal for maintaining postural equilibrium will change with the constraints and opportunities afforded by a particular environment. The additional need to select the most appropriate response from an array of options, while simultaneously suppressing unsuitable, yet potentially automated actions, implies a need for higher-level supervision It raises the question of how we combine the utility of rapid, stereotyped compensatory reactions with the need to match our actions to what is permitted by a given environment at a particular moment in time? Specific cross-discipline concepts such as predictive modeling (internals models), affordances for action, and associative learning each have important implications for adapting our movements to maintain postural equilibrium in challenging environments, and provide a way to overcome conflicting demands for goal-directed action at high speed
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