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. 

Nodes represent neurons, lines their connections (synapses), and the patterns - bits of our knowledge.

This model highlights two key features of neuroplasticity:

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

 2) Activating new patterns can sometimes forge new connections (but generally not new nodes).

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 reactivate influences what is learned, and how it's reconsolidated affects how well it's remembered.