E35 Prediction of future evolution

Topic

Predicting the future evolution of the environment allows an organism to compensate for delays in its neural processing. Without this capability, a control system subject to significant delays could become unstable. The central nervous system maintains internal models of the dynamics of the body and environment that allow it to anticipate the consequences of its actions before receiving the corresponding sensory feedback. In this way, behavior does not depend exclusively on reacting to what has already happened, but also on estimating what will happen next.

A linear state model describes how the environment is expected to evolve from its current condition. However, every prediction accumulates uncertainty as the time since the last observation increases. As occurs in the predictive stage of a Kalman filter, as long as new information does not arrive to correct the estimate, the potential error continues to grow. There is thus a useful prediction horizon: an interval beyond which uncertainty becomes large enough for the prediction to lose practical value. The longer it takes for a new corrective observation to arrive, the greater the accumulated uncertainty.

The interception of a moving object constitutes a specific example of this predictive capacity. A frog catching a fly or a player trying to catch a ball must anticipate where the object will be in the future and act before it gets there. According to the text, the evidence suggests that the organism can directly estimate the final point of interception instead of continually reconstructing the entire trajectory. This behavior is compatible with an internal kinematic model that incorporates gravity as prior knowledge. By having this physical regularity within the model, the organism can predict the future meeting point more efficiently than if it had to infer the entire trajectory again at each instant.

The prediction also applies to the sensory consequences of the movements themselves. The shock copy principle states that each motor command simultaneously generates a prediction of the sensory signal it should produce. When actual sensory information arrives, the system compares it to the expected consequence. If both coincide, the signal can be attenuated because it corresponds to an event already predicted. This mechanism explains, according to the text, why it is difficult to tickle oneself: the sensory consequences of one's own movement have already been anticipated.

When the actual signal does not match the prediction, a prediction error appears instead, indicating that something unexpected occurred. The greater the difference between the predicted consequences of the motor command and those actually observed, the greater this error will be. This signal allows the internal model to be updated and the behavior subsequently adapted.

These mechanisms converge in model-based predictive control, which selects actions by considering their consequences over a future horizon and optimizing a cost function. Instead of correcting movement only after detecting an error, the body can anticipate constraints such as obstacles or force limits and plan an appropriate trajectory in advance. A more accurate prediction of future constraints allows for smoother and more efficient movements.

According to the text, the cerebellum participates in the forward internal model component of this system, predicting the consequences of actions in a way comparable to the principle used by a Kalman filter, while the prefrontal cortex is involved in longer-term planning.

Taken together, prediction transforms behavioral control from a purely reactive process to an anticipatory one. Internal models estimate how the body and environment will evolve; observations periodically correct these estimates; Download copy allows us to distinguish expected consequences from unexpected events, and predictive control uses these anticipations to select future actions. Thus, the organism can compensate for neural delays, intercept objects, detect deviations from what is expected and plan efficient movements before the real consequences of its actions reach its senses.

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