Author: Fontaine Gibbs
Editors: Erin Vinson, Raayan Dhar
In this article, I give a brief overview of findings from three fields of neuroscience which provide insights on how to enhance learning, neuroplasticity, memory and stress responses. The conclusions found are applied to the learning experiences of individuals in the COVID-19 pandemic, during which lockdown and staying at home may change an individual’s learning environment.
Neuroplasticity
Neuroplasticity is an umbrella term for the brain’s ability to change and adapt in response to changing environments or stimuli (Voss, 2017). On a micro scale, individual synapses adjust the amount of neurotransmitters released and/or the axon’s sensitivity depending on the frequency of action potentials. For example, if you repeatedly practice a new badminton trick, the synapses for that movement will be strengthened, allowing you to learn and remember the move. In terms of macro structure, neural pathways that are frequently stimulated, like a pathway corresponding to new material you are learning at school, may grow more dendritic branches. However, pathways which are rarely used may lose branches and even whole neurons.
It was previously believed that neurogenesis, the formation of new neurons, was only found in developing individuals, such as newborns and adolescents. Now, it has been well-established that adults can also have continuously changing brains when provided with a new and stimulating environment (Sapolsky, 2020). This provides hope that individuals of any age are capable of development and learning.
What sort of stimuli?
What kind of stimuli is ideal for neuroplasticity? It has been found that enriched environments at critical periods can prolong one’s duration of neuroplasticity by triggering the growth of dendrites (Greifzu et al., 2014). However, too much stimulation is not helpful; overload of stimuli, such as a noisy environment, tends to result in neurons remaining in an immature state and an exaggerated incorporation of that memory in the sensory map (Sengpiel et al., 1999). Furthermore, the quality of stimuli can make or break critical periods, as windows of high neuroplasticity are experienced in early childhood and adolescence. Poor quality environments, such as unpredictable noise levels (experimentally simulated with white noise) can cause a critical period to end early, while stable environments (stimulated by constant white noise that blurs out any other inputs) can prolong it (Chang and Merzenich, 2003).
Thus, lack of new stimulation during something such as a lockdown could raise more concerns beyond boredom, as may also make it more difficult for individuals to learn new content or skills. However, an advantage may be that individuals have greater control over their home environments, and may be able to enforce more stable levels of noise and stimulation to increase the quality of their learning.
Memory
Skill Learning and Non-Declarative Memories
Skill learning is a type of learning that is highly kinesthetic- involving learning by doing. For instance, practicing guitar chords to learn a new song. These involve non-declarative memory, which is implicit and does not rely on conscious memory, as opposed to declarative memory, which involves conscious recollection of semantic facts and events, although both are dependent on the same regions of the brain: the medial temporal lobe of the hippocampus and the midline nuclei of the thalamus.
There are various forms of non-declarative memory. Firstly, associative non-declarative memories involve classical conditioning where an individual learns to associate a stimulus and task with a reward. For instance, if someone receives a reminder about an upcoming paper, completes the paper, and is awarded chocolate in return, over time they will become accustomed to completing their papers upon receiving reminders, even if the chocolate is no longer awarded. This is because they have associated reminders with completing papers, and thus develop an automatic response to that trigger (Cheung, 2007).
The habit loop of stimulus, task, and reward has long been utilised as a productivity tool (Duhigg, 2012), however, how is it used during the pandemic? Arguably, the inherent social rewards of many tasks have been removed or reduced as a result of lockdown, and therefore isolation. For example, the reward of being able to play a piece with bandmates to produce a satisfying sound, being able to socialise with a lab partner while learning through experiments, or eating with friends during lunch after a morning full of classes. Thus, learners may find it helpful to find new rewards for previously socially satisfying activities, or actively reintroduce social rewards through social interaction online.
Another common form of non-declarative memory used in learning is repetition priming. This involves presenting a stimulus to learners briefly. The special thing about this technique is that it does not involve conscious recognition; when the learner is primed with the stimulus, it is merely looked over briefly and not studied in detail. Despite its rather indirect nature, recognition priming has been found to improve individuals’ ability to detect words or objects after exposure (Squire and Kandel, 2000). Learners in lockdown may thus find it helpful to stimulate the repeated exposure to learning material that would be common in a classroom setting by continuously going over class material or using active recall tools at home.
Stress: Helpful or harmful?
In neuroscience, stress is most quickly associated with the fight or flight response: activation of the autonomic nervous system, the hypothalamus-pituitary-adrenal axis, and the subsequent release of stress hormones such as adrenaline and cortisol. This triggers ATP production, which makes individuals more alert, and suppresses less urgent bodily functions such as digestion, helping them deal with the stressor at hand (Harvard Health Publishing, 2011). However, as is emerging with the phenomenon of chronic stress, the stress response can be exhausting and damaging if it is always ‘on’ (Sapolsky, 2004).
However, it’s not entirely clear-cut whether these harms extend to learning and memory. In some studies, administering the stress hormone cortisol directly before learning improves memory retention and recognition of what was learned. This may be because cortisol and the adrenaline that follows it are both crucial for the formation of emotional memories, which are more likely to be recalled than ‘bland’ ones. On the other hand, studies have also found that cortisol is unhelpful for learning new material when administered longer before, even by thirty minutes. A likely explanation for this is that cortisol levels spike 20-30 minutes after a stress response begins, activating the hippocampus and amygdala, which are key players in memory formation. Thus, excitement of these regions too long before learning may inhibit rather than enhance retention (Vogel and Schwabe, 2016).
We can infer from these findings that stress associated with the pressure of learning or meeting a deadline may be helpful for learning, but chronic stress unrelated to learning can hinder it. This is an important takeaway to apply to COVID-19 lockdowns, as many students may be stressed by drastic changes to their lifestyle and learning habits, especially being deprived of familiar classroom environments. Recognising and reducing this form of stress may not only be beneficial to their physical and mental health, but also their performance academically, and recreating some positive stressors of a classroom environment such as time pressure or exams may be helpful.
References
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Cheung, Vincent CK. “Skill Memory: Learning by Doing Part I.” Neural Basis of Learning and Memory, MIT OpenCourseware, 2007, ocw.mit.edu/courses/brain-and-cognitive-sciences/9-03-neural-basis-of-learning-and-memory-fall-2007/lecture-notes/lecture04.pdf.
Greifzu, F., et al. “Environmental Enrichment Extends Ocular Dominance Plasticity into Adulthood and Protects from Stroke-Induced Impairments of Plasticity.” Proceedings of the National Academy of Sciences, vol. 111, no. 3, 2014, pp. 1150–1155., doi:10.1073/pnas.1313385111.
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