Neural Networks and Neural Pruning
What are neural networks?
- Neural networks are a group (a network) of neurons that are interlinked and connected which combine to produce a specific neurological function or process e.g. learning a new language; spatial navigation
- Neural pathways form when a new behaviour is learned, and these pathways become stronger and more embedded over time and with practice e.g. perfecting an figure-skating move; becoming more fluent in a language
- Neural pathways and networks that are not frequently used may eventually cease functioning altogether e.g. forgetting how to speak French once a person leaves school; not being able to hit a hole-in-one without sufficient golf practice
What is neural pruning?
- Neural pruning refers to the process carried out by the brain in order to increase its efficiency
- Synapses and neurons that are no longer used or needed are eliminated by the brain
- Neural pruning is a key function of neuroplasticity as it is involved in the pruning of neural networks and neurons that may once have been learned (increased grey matter) but are now no longer used (decreased grey matter)
The brain: more networks than social media!
Which research studies support neural networks and neural pruning?
- Maguire (2000) showed that years spent as a black cab driver in London may result in increased grey matter in the posterior hippocampus – evidence of neuroplasticity and by extension the neural networks involved in spatial navigation
- Draganski et al. (2004) found that learning to juggle led to neuroplasticity (increased grey matter in the mid-temporal cortex) but that this then decreased significantly when the participants stopped juggling (evidence of neural pruning)
- Gotgay et al. (2004) found that neural pruning occurs frequently and rapidly in children from birth, as their more spontaneous, impulsive behaviours are replaced by increasingly sophisticated cognitions
Maguire and Draganski’s studies are available as separate Key Studies – just navigate the Brain and Behaviour section of this topic to find them.
Jugglers have more grey matter – but only if they don’t stop juggling…
Exam Tip
Remember that when you answer a question on neural networks or neural pruning you do not need to evaluate the study or include any critical thinking into your response. These two key terms will only appear on Paper 1 Section A therefore you only need to outline/describe/explain the theory or study. Adding evaluation will not increase your mark for any SAQ.
Evaluation of neural networks and neural pruning research:
Maguire (2000)
- Strength: The choice of sample is suitable in terms of their experience of spatial navigation
- Limitation: There may be other explanations for the increased grey matter in the taxi drivers’ posterior hippocampi
Draganski et al. (2004)
- Strength: The findings have a useful application as they can be used to inform possible interventions and therapies to offset degenerative brain conditions such as Alzheimer’s
- Limitation: This was a self-selecting sample which means that it is not representative of a wider population as self-selecting samples often share characteristics e.g. helpful, interested, extrovert
Gotgay et al. (2004)
- Strength: The use of a longitudinal design means that the researchers could measure changes in grey matter over time
- Limitation: The findings do not explain why neural pruning occurs, only that brain development appears to follow the same pattern across the sample
Exam Tip
As part of your revision of this topic you may read about 'neural branching' so be careful not to confuse this with neural pruning. Remember that neural pruning occurs when the brain gets rid of neurons and connections that it no longer requires, whereas neural branching occurs when new synaptic connections are made (it is the opposite of neural pruning).
TIP: Think of branching as 'branching out' - so new synaptic connections; think of pruning as 'reducing' (or like a wrinkly prune!) - so synaptic connections are removed/reduced