Motor Learning Theories: How Movement is Controlled and Adapted

As we gear up for the Vet Rehab Summit, we’re diving into Motor Learning. This week, we explore motor learning theories and how they can help us more deeply understand movement assessment and therapy in our canine and equine patients.

 

Let’s dive into the theory.

 

Theories in Behavioural Science

A theory within the scientific construct is a well-substantiated explanation of an observable phenomenon, based on facts that have been repeatedly confirmed through observation and experimentation.

Motor learning falls under the umbrella of the Behavioural Sciences, and the theories we discuss here relate to understanding behaviour, specifically, how it changes through skill acquisition. While these theories draw on neuroscience and biomechanics, their core focus is on the behavioural processes underpinning movement.

So, a motor learning theory is a set of interrelated ideas used to explain, describe, and predict movement behaviour. These theories guide our clinical reasoning by offering frameworks that help us interpret what we observe and make more informed decisions in practice.

In this article, we’ll explore two of the most influential motor learning theories:

1. Schmidt’s Schema Theory – a central control theory
2. Dynamical Systems Theory – a systems-based, self-organising theory

 

Each offers a different lens through which to understand movement acquisition, variability, and adaptability.

 

 

Schmidt’s Schema Theory – The Generalized Motor Program

This theory falls under the category of central control theories, which suggests that the nervous system uses stored memory representations to control movement. The core concept is the Generalized Motor Program (GMP). It provides allowance for adaptations to a GMP to produce coordinated movement.

 

What is a Generalized Motor Program?

A GMP is a memory structure that contains the essential information needed to produce a class of movements – not just one specific action, but a set of actions that share common features.

Example: Think of walking. Whether the surface is grass, sand, or water, the core pattern remains the same. It’s adapted for the terrain using movement-specific parameters, but the GMP remains intact.

 

Key Components of GMP:

• Invariant Features: These are the characteristics of a movement that remain constant each time it is performed. The most commonly cited is relative timing – how long each phase of a movement lasts in proportion to the whole.
• Parameters: These are the features that can be adjusted depending on the situation. This includes movement duration, force output, or which limbs or muscles are involved.

 

The Role of Schema

Schmidt extended this theory with the concept of a schema, which is a set of rules created through experience. Every time a movement is executed, the nervous system stores:

1. Initial conditions
2. Movement parameters used
3. Sensory feedback received
4. Movement outcome

Over time, these experiences form schemas – abstract rules used to generate movement in novel situations.

 

Clinical Example:

A dog recovering from TPLO surgery relearns how to transition from sit to stand. The GMP for rising exists, but the parameters (e.g., muscle force, joint angles) must adapt due to changes in strength, proprioception, and pain. As repetitions increase, the schema becomes more accurate, and the task becomes more efficient and consistent.

 

Why It Matters

Schmidt’s theory helps us explain:

• How animals can adapt a known movement pattern to a new context
• Why repetition with variability is essential in rehab
• How we can progressively load and challenge a movement while preserving the core structure

It also attempts to solve the Degrees of Freedom Problem by proposing that movement is governed by higher-level programs, reducing the complexity of controlling each joint or muscle individually.

 

Dynamical Systems Theory: Movement Emerges, It’s Not Pre-Planned

In contrast to the idea of pre-programmed control, Dynamical Systems Theory (DST) views movement as an emergent property of a complex system. It draws on principles from physics, biology, chemistry, and mathematics to explain motor behaviour.

Here, movement is not centrally commanded, but rather emerges from the interaction of the individual, the task, and the environment. The system is self-organising.

 

Key Concepts in DST include:

 

Nonlinear Dynamics

A small change in one variable (like speed or load) can result in a sudden, qualitative shift in movement behaviour.

Example: A transition from walk to trot occurs when the control variable – speed – increases past a certain point. Instead of the transition being conscious, it occurs spontaneously in response to the increase in speed. Think of a horse or dog on a treadmill.

 

Stability and Attractors

• Stability: Refers to how resistant a movement pattern is to disruption or changes.
• Attractors: A preferred, energy-efficient movement pattern. These are the default states the system returns to when perturbed.

 

Example: Walking and trotting are attractor states. At different speeds, one becomes more stable and efficient than the other.

 

Order and Control Parameters

• Order Parameters: Variables that define the movement pattern (e.g., gait phases, limb coordination).
• Control Parameters: External or internal variables (e.g., incline, speed, fatigue) that influence or shift the order parameter.

Example in Rehab: Adding incline during treadmill walking may act as a control parameter, leading to a spontaneous change in stride length or cadence.

 

Coordinative Structures (Muscle Synergies)

Muscles and joints don’t work in isolation, instead they are grouped into coordinative structures that act as functional units. This allows the central nervous system to recruit a functional unit to perform a task instead of coordinating and recruiting muscles individually.

These can:

• Exist naturally (e.g., in locomotion)
• Be developed through practice or rehab to perform new or asymmetrical tasks

Example: Teaching a dog to perform lateral stepping involves developing new coordinative structures that differ from the default forward gait synergy.

 

Perception-Action Coupling

Movement is tightly linked to how the animal perceives its environment. Sensory inputs – visual, tactile, proprioceptive – are continuously integrated to guide movement in real time.

Example: A horse approaching a raised pole adjusts its stride based on visual cues, not by executing a stored “pole-crossing” plan, but by actively adapting the movement in response to the environment.

 

Why It Matters

DST explains:

• How movement can adapt spontaneously
• Why variability in practice is valuable
• How environmental and task constraints can be used as tools in rehab
• The importance of creating conditions that allow movement to emerge, rather than trying to force it

It also provides a compelling solution to the coordination problem: using synergies and self-organisation to reduce the computational burden on the nervous system.

 

Final Thoughts

Both Schema Theory and Dynamical Systems Theory offer powerful tools to understand and guide motor learning. One is top-down (planned control), the other bottom-up (emergent control). Both acknowledge the complexity, adaptability, and intelligence of the motor system.

In practice, most movement therapy integrates elements of both.

 

What’s Next?

In our next article, we’ll explore the OPTIMAL Theory of Motor Learning, which combines motivation, attention, and neuroplasticity to enhance how we teach and learn movement.

I’m incredibly excited about what this one means to us as animal rehabilitation therapists, so stay tuned!

 

References

 1. Watson-van Zyl, J. 2025. Motor learning: Motor Control Theories [Lecture to PTS216]. Equine-librium College, Plettenberg Bay, 08 April 2025. 

2. OpenAI. (2025). ChatGPT [Large language model]. https://chat.openai.com/chat