Learning, Unlearning, and Relearning

How Our Brain Adapts and Why It Matters in Rehabilitation

Introduction

Learning, unlearning, and relearning are essential parts of how we acquire, refine, and restore skills—whether it’s mastering a new hobby, breaking an old habit, or recovering from an injury. These processes bring about profound changes in the brain, including the strengthening of synapses, the growth of new neurons, and the reorganization of neural networks.

However, many conventional rehabilitation approaches were developed based on ideas that don’t quite fit with what we now know about how the brain changes. As research into brain plasticity—the brain’s ability to change and adapt—evolves, it’s becoming clear that some older methods may not fully leverage these natural processes. This post explores the neurophysiology behind learning, unlearning, and relearning, highlighting how these processes shape the brain and how rehabilitation approaches can either support or hinder them. We’ll also explore how newer, more task-oriented methods align better with how our brain naturally learns and relearns.

1. Neurophysiology of Learning

Learning refers to acquiring new information or skills, and it engages multiple neural processes.

• Synaptic Level Changes:

  • Long-Term Potentiation (LTP): When a neuron is repeatedly stimulated, the connection between synapses becomes stronger, a phenomenon known as LTP. This is driven by increased neurotransmitter release, the insertion of additional receptors (e.g., AMPA receptors), and increased synaptic efficacy.

  • Synaptic Plasticity: Learning involves strengthening of existing synapses and the formation of new synapses, enhancing connectivity within neural networks. Synaptogenesis ensures long-lasting retention of new skills.

Neurons that fires together, wires together - Donald Hebb

• Neuronal Level Changes:

  • Dendritic Growth: Neurons sprout new dendritic spines to enhance connectivity with other neurons. The hippocampus, motor cortex, and prefrontal cortex exhibit significant dendritic changes during learning.

  • Neurogenesis: New neurons are generated, especially in the hippocampus, to support memory and learning.

  • Functional Reorganization: Brain regions may dynamically reconfigure their connections to integrate newly learned information. For example, motor learning can induce plasticity in both primary motor cortex and supplementary motor areas.

2. Neurophysiology of Unlearning

Unlearning refers to the process by which previously learned behaviors or skills are weakened or forgotten, often necessary for behavioral adaptation.

• Synaptic Level Changes:

  • Long-Term Depression (LTD): This is the opposite of LTP. Synaptic efficacy decreases when certain pathways are not frequently used. LTD involves a reduction in neurotransmitter release and removal of AMPA receptors, leading to weaker synaptic connections.

  • Pruning of Synapses: Unused synaptic connections are eliminated over time. This pruning allows the brain to allocate resources more efficiently and remove redundant information.

• Neuronal Level Changes:

  • Reduction in Dendritic Spines: Neurons retract some dendritic spines that are no longer needed, reducing connectivity.

  • Functional Reorganization: The brain undergoes a functional reconfiguration where underused neural networks are weakened, and resources are reallocated to more relevant tasks. For instance, if a person stops practicing a skill, the brain regions associated with that skill show reduced activation.

3. Neurophysiology of Relearning

Relearning refers to the reacquisition of skills or knowledge that were previously lost, often seen in recovery from neurological conditions or after extended disuse.

• Synaptic Level Changes:

  • Reactive Synaptogenesis: Synapses that were weakened during unlearning are re-established. Some synapses may also be newly formed to compensate for those lost during the unlearning process.

  • LTP Reactivation: Previous synaptic pathways can regain strength more rapidly due to residual plasticity (referred to as "savings").

• Neuronal Level Changes:

  • Increased Plasticity in Multiple Regions: Relearning engages plasticity in multiple areas of the brain beyond the original site. For example, in stroke recovery, motor skills may be relearned by recruiting areas adjacent to or even remote from the damaged regions.

  • Neurogenesis and Circuit Remodeling: The hippocampus and motor cortex play key roles in relearning. Neurons undergo remodeling, including re-formation of dendritic spines, to reestablish previously acquired skills.

  • Compensatory Pathways: If the original neural pathway is not available, new circuits are recruited for the task. This adaptability is an essential feature of relearning, especially in rehabilitation contexts.

Functional Implications

• Behavioral Adaptation: Learning, unlearning, and relearning reflect the brain’s flexibility and adaptability, which allow us to learn new skills, let go of outdated behaviors, and reestablish lost capabilities.

• Neural Efficiency: Through these processes, the brain optimizes its functions by retaining relevant skills, discarding redundant information, and restructuring circuits when needed.

• Clinical Relevance: Understanding these neurophysiological processes is crucial in rehabilitation sciences. For example, stroke rehabilitation involves unlearning maladaptive behaviors and relearning functional movements, aided by task-specific and context-specific neuroplasticity.

How Bobath (NDT) and Task-Oriented Training Conceptualize Learning, Unlearning, and Relearning

While conventional models like Bobath therapy(NDT) focus on passive facilitation and the inhibition of abnormal movements, modern approaches such as task-oriented functional training actively engage patients in meaningful tasks, leveraging the brain’s plasticity. Understanding how interventions align—or misalign—with these neurophysiological processes is critical to designing effective rehabilitation strategies. In the following section, I compare these two approaches, highlighting their assumptions and how they engage with the brain's ability to learn, unlearn, and relearn.

Conventional Approach: Bobath Concept

The Bobath concept is a widely known neurorehabilitation approach developed in the mid-20th century. It focuses on inhibiting abnormal movement patterns and muscle tone through passive handling and facilitation by the therapist. The underlying premise is that normal movement patterns must be restored before functional activities can occur. The emphasis is on suppressing abnormal postures, movements and tone to prevent maladaptive behaviors.

• Example of Application:
  In Bobath therapy, a patient with stroke with spasticity in the arm might undergo passive movements and guided handling by the therapist to reduce muscle tone. The goal is to inhibit spasticity and "normalize" movement patterns before encouraging the patient to engage in tasks. Compensatory movements (e.g., shoulder elevation or trunk flexion) are discouraged because they are thought to interfere with functional recovery.

• Neurophysiological Critique:
  The Bobath concept focuses primarily on blocking (‘inhibition’) maladaptive pathways but neglects active engagement that promotes plasticity. For example:

  • Synaptic Plasticity: Passive and therapist guided movements may not be sufficient to trigger long-term potentiation (LTP)—the strengthening of synaptic connections critical for learning. Without active practice, the pathways responsible for motor recovery remain underutilized.

  • Dendritic Spine Growth: Minimal active engagement reduces the opportunity for dendritic spines to grow, which limits the formation of new connections.

  • Neurogenesis: Passive interventions are unlikely to stimulate the generation of new neurons in regions like the hippocampus, which is essential for learning and memory.

  • Non-Task, Blocked Practice and Limited Variability: Repeating non-task related movement patterns without variability do not effectively promote long-term potentiation (LTP) or synaptogenesis, both of which are essential for forming new neural connections and solidifying learned movements. Lack of variability in these movements also means that the brain's neuronal are not sufficiently challenged across different scenarios, reducing the likelihood of generalization.

Modern Approach: Task-Oriented Functional Training

Task-oriented functional training aligns with modern neuroscience by emphasizing active participation, problem-solving, and variability in real-world tasks. It leverages the brain's ability to reorganize itself—known as neuroplasticity—by engaging multiple neural circuits through meaningful tasks.

• Example of Application:
  In task-oriented training, the same patient with stroke would engage in functional activities, such as reaching for objects on a shelf or pouring water into a glass. The therapist encourages the patient to try different ways of completing the task, even if the movements are not perfect. For example, the patient might initially compensate with trunk movements while improving hand control over time. Practicing these tasks in varying contexts (e.g., reaching for objects of different sizes and weights) reinforces skill acquisition through active learning and variability.

• Neurophysiological Alignment:
  Task-oriented training aligns with the brain’s natural plasticity mechanisms:

  • LTP and Synaptogenesis: Repeated, meaningful task practice strengthens synaptic connections (LTP) and promotes the formation of new synapses (synaptogenesis), enabling the reacquisition of motor skills.

  • Dendritic Spine Growth: Active engagement promotes the growth of new dendritic spines, improving connectivity between neurons.

  • Reactive Synaptogenesis: In cases of injury, task practice encourages the formation of compensatory synaptic connections to restore function.

  • Neurogenesis: Learning through active participation promotes neurogenesis, particularly in the hippocampus, improving memory for motor tasks.

  • Functional Reorganization: By encouraging patients to explore and adapt, the brain reorganizes itself by recruiting new circuits to support functional recovery. For example, in stroke rehabilitation, motor control may shift to adjacent regions or involve other compensatory pathways.

• Error-Based Learning and Variability:
  Task-oriented training integrates error-based learning, where the patient learns from mistakes, refining movements through trial and error. Practicing tasks in variable contexts helps to engage multiple brain regions, facilitating skill generalization and retention. This variability enhances plasticity by challenging the brain to adapt across different scenarios.

Conclusion

The comparison between the Bobath approach and task-oriented functional training demonstrates how modern neurophysiotherapy interventions align more effectively with neuroplasticity principles. Task-oriented training encourages active engagement, variability, and problem-solving, which are essential for promoting LTP, synaptogenesis, and functional reorganization. It leverages the brain’s ability to adapt through dendritic spine growth, neurogenesis, and compensatory plasticity, ultimately leading to better skill acquisition and retention. In contrast, the Bobath approach(NDT), while historically influential, limits active participation and the variability needed to engage these neurophysiological processes fully.

As neuroscience continues to reveal the dynamic nature of brain plasticity, rehabilitation strategies must evolve toward interventions that foster task-specific learning, variability, and real-world problem-solving. These principles provide the foundation for functional recovery by facilitating learning, unlearning maladaptive patterns, and relearning lost abilities in ways that align with how the brain naturally adapts to change.

This shift ensures that patients receive interventions grounded in modern neurophysiological insights, maximizing their potential for meaningful and lasting recovery