Neuroplasticity

• Neuroplasticity is the brain's ability to adapt to change, whether it be from injury and illness, or changes due to learning and experience. It can be split into structural plasticity and functional plasticity.
• Structural plasticity refers to changes in brain structures like the hippocampus that occur due to learning experienced over time. In other words, it doesn't happen immediately but over time.
• Functional plasticity refers to the brain's ability to replace lost or damaged functions by using existing brain regions in their place.
• Plasticity simply means the brain is not a static, concrete mass, but a flexible organ that responds and adapts to environmental stressors
• Someone who had half their brain removed via a hemispherectomy to control their epilepsy, may still be able to function normally as the remaining hemisphere takes over the tasks of the removed hemisphere
• An example of neuroplasticity is Maguire (2000) in which London black cab taxi drivers who spent years navigating and learning routes through central London, had increased gray matter in the posterior hippocampus (linked to spatial navigation).
• Neural networks are a network of neurons and neural pathways that are interlinked to produce a specific neurological function or process, such as learning a new skill or spatial navigation.
• Neural pathways form whenever a new behavior is learned. They grow stronger, become embedded over time and with practice. Ex. perfecting muscle memory when performing a sport, or becoming more fluent at a language
• Neural pathways and networks that aren't frequently used may ultimately stop functioning altogether. This is why we forget how to speak a foreign language like Spanish or French once we stop taking classes.
• Neural pruning refers to the process in which the brain attempts to increase its efficiency by eliminating synapses and neurons that are no longer used or needed.
• Neural pruning is a key part of neuroplasticity since it involves "pruning" neural networks and neurons that was once learned (increased gray matter) but is now no longer used (decreased gray matter).
• Maguire (2000) is an example of neural networks as it is evidence of neuroplasticity and the neural networks involved in spatial navigation.
• Draganski et al (2004) is an example of neural pruning because learning to juggle increased gray matter in the mid-temporal cortex (neuroplasticity) which decreased when participants stopped juggling.