Neuroscience on effective learning

By Tanjim Sayeeda

Memory and learning lie in the heart of evolution, particularly for humans. Organisms have evolved by experiencing challenges that teach them about how to adapt behaviours in order to overcome the same challenges in the future. Thus, species survival has depended on the process of learning, storing and retrieving information. Attempts to explain these critical processes have been made by ancient philosophers, cognitive psychologists and neuroscientists alike, but we still do not have a complete understanding of the mechanisms that underly memory and learning (Stern, 2017). Research into educational neuroscience is critical today, especially as we live in an advancing innovative landscape where humans are facing increasingly complex challenges that require optimal problem solving skills. A key question being asked in neuroscience is: how can humans use their brains to the best of its ability?

In order the optimise brain performance, the mechanisms behind the learning brain need to be understood. Neuroscientists believe that our neural pathways may play a role in the learning process. The strengthening and weakening of synapses between neurons in our brain is termed synaptic plasticity, a concept first articulated by the psychologist Donald Olding Hebb. In simple terms, Hebb explains that “neurons that fire together, wire together” and “neurons that fire apart, wire apart”. Whether adjacent neurons are activated simultaneously or not determines if the synapse is strengthened or weakened respectively. Hebb’s theory gained precedence when in vivo and in vitro experiments revealed processes known as long-term potentiation (LTP) and long term depression (LTD) in synapses. LTP and LTD refer to the respective increase or decrease in voltage change induced within the postsynaptic neuron by the presynaptic neuron (Abraham, Jones & Glanzman, 2019). LTP will occur if the presynaptic neuron fires 20 ms before the postsynaptic neuron, whereas LTD is generated if the firing occurs 20 ms after; this is known as spike-timing dependence (Feldman, 2012). 

Neuroplasticity teaches that learning creates new neural pathways in the brain. Learning a new language and musical instrument has the potential to form new neuronal connections and thus change the way the brain is operating (Abraham, Jones & Glanzman, 2019). The brain is thus analogous to muscles: exercising muscles strengthens them while neglecting muscles weaken them. In short, the strength of the brain depends on the utilisation of it. However, despite numerous evidence on neuroplasticity and LTP contributing to learning and memory, it cannot be conclusively stated that memory resides in the synapses. To consolidate current theories, new techniques and methods are needed in order to better visualise the manipulation of synaptic strength in in vivo experiments (Humeau & Choquet, 2019). 

Neuroscience may be able to explain how connections are made in the brain, however there is less understanding on how stored memory traces can be retrieved. Studies have found increased activity in the globus pallidus, thalamus, anterior cingulate gyrus and cerebellum during recall (Hu, Eskandar & Williams, 2009). Despite the lack of awareness, findings can confidently conclude that retrieval-based learning is the most effective strategy to maintaining our memories (Karpicke, Blunt & Smith, 2016). Psychology explains that recalling previously learned information strengthens the memory trace and the likelihood that it gets stored in the long term memory. In a study where students were required to memorise a list of foreign words in a learning session, the results demonstrated that the condition which utilised spaced retrieval practices performed better than conditions that did not attempt recall at all or recalled repeatedly without spacing (Balota et al., 2006). Retrieval is an underappreciated learning strategy as surveys on college students indicate that the most used revision strategy is re-reading notes. Abundant research indicates that passive reading provides little to not benefit for learning and memory (Karpicke, Butler & Roediger III, 2009).

Another benefit to enhanced learning is metacognition, the process of reflecting on how we think. Metacognition is essentially having self-awareness as it involves deep planning, observing, assessing and processing our own performance. Exercising metacognition gives meaning to the learning experience by allowing learners to recognise their weaknesses and strengths so amendments can be made where necessary. Additionally, knowledge can also be contextualised in different settings because a deeper level of awareness for the subject matter is gained. Experiments using functional magnetic resonance imaging (fMRI) on participants undergoing decision making activities found that the metacognition neural system composes of a monitoring system and a control system. These systems contain the dorsal anterior cingulate cortex, anterior insular cortex and lateral frontopolar cortex. The monitoring system processes the uncertainties from the decision while the control system implements cognitive control such as strategy and attention depending on the task. Thus, metacognition works in conjunction with decision making to adapt and control behaviours geared towards specific goals (Bang & Fleming, 2018). 

In conclusion, the human brain has a remarkable ability to learn and adapt from its environment. Neuroscientific research provides integral insight into the mechanisms of the learning brain, so humans can use their brains to its full potential and thus continue to make ground-breaking strides as we move into the future. 


Abraham, W. C., Jones, O. D. & Glanzman, D. L. (2019) Is plasticity of synapses the mechanism of long-term memory storage? NPJ Science of Learning. 4 (1), 9-10. Available from: Available from: doi: 10.1038/s41539-019-0048-y.

Balota, D. A., Duchek, J. M., Sergent-Marshall, S. D. & Roediger, H. L. (2006) Does Expanded Retrieval Produce Benefits Over Equal-Interval Spacing? Explorations of Spacing Effects in Healthy Aging and Early Stage Alzheimer’s Disease. Psychology and Aging. 21 (1), 19-31. Available from: Available from: doi: 10.1037/0882-7974.21.1.19.

Bang, D. & Fleming, S. M. (2018) Distinct encoding of decision confidence in human medial prefrontal cortex. Available from: .

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Hu, R., Eskandar, E. & Williams, Z. (2009) Role of deep brain stimulation in modulating memory formation and recall. Neurosurgical Focus. 27 (1), E3. Available from: Available from: doi: 10.3171/2009.4.FOCUS0975.

Humeau, Y. & Choquet, D. (2019) The next generation of approaches to investigate the link between synaptic plasticity and learning. Nature Neuroscience. 22 (10), 1536-1543. Available from: Available from: doi: 10.1038/s41593-019-0480-6.

Karpicke, J. D., Blunt, J. R. & Smith, M. A. (2016) Retrieval-Based Learning: Positive Effects of Retrieval Practice in Elementary School Children. Frontiers in Psychology. 7 350. Available from: Available from: doi: 10.3389/fpsyg.2016.00350.

Karpicke, J. D., Butler, A. C. & Roediger III, H. L. (2009) Metacognitive strategies in student learning: Do students practise retrieval when they study on their own? Memory (Hove). 17 (4), 471-479. Available from: Available from: doi: 10.1080/09658210802647009.

Rodrigues, A. C., Loureiro, M. A. & Caramelli, P. (2010) Musical training, neuroplasticity and cognition. Dementia & Neuropsychologia. 4 (4), 277-286. Available from: Available from: doi: 10.1590/S1980-57642010DN40400005.

Stern, E. (2017) Individual differences in the learning potential of human beings. NPJ Science of Learning. 2 (1), 2-7. Available from: Available from: doi: 10.1038/s41539-016-0003-0.

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