Learning and memory as a cycle

'Neuroplasticity' is everywhere, but what do we really mean when we talk about the ever-changing brain? 

Let's dive deeper than the buzzword and explore the evidence with a model.

Cognitive neuroscience uses simplified network models like this to demonstrate how learning & memory might work at the network level. 

For this network model, nodes represent neurons, lines their connections (synapses), and the patterns - bits of our knowledge, i.e. concepts. 

This model highlights two key features of neuroplasticity:

 1) Existing nodes & connections can be active or inactive.

 2) Activating new patterns can sometimes forge new connections, but usually not new nodes.
Activation is, therefore, key for both our ability to re-expreience previously learned ideas, and our ability to create new patterns for future use.   

For deeper understanding, let's follow a new pattern through the phases of memory: Encoding, Consolidation, Storage, and Retrieval. 

Notice how the new pattern evolves from a "live" experience to newly-formed, then stored connections, ready for reactivation upon retrieval.

And... what happens next?

The key to neuroplasticity is the repeated transitions between inactive & active phases— these are processes that we can shape when teaching and learning. What we activate and reactivate during a learning experience directly influences what is learned, and how it's reconsolidated affects how well it's remembered.
Our ability to retrieve information in the long-term, is dependent on recurrent activation of both the patterns and their retrieval pathways (read more about it here).