Over the last few decades, neuroscience has begun to confirm or refute certain hypotheses we had about how the brain works, in addition to leading us down new paths of knowledge. Given the complexity of this fascinating organ, we are only at the beginning of this promising exploration. However, thanks to brain imaging, we know a little more about some of its particularities at different stages of life and their links with learning. Here they are!

Throughout life: a flexible brain

Brain plasticity. For a long time, it was thought that brain development took place mainly before birth, in the womb, and during infancy and that genetic factors largely governed it. This was before the discovery of brain plasticity, the extraordinary capacity of the brain to evolve and adapt at any age. At the neuronal level, this translates into connections created or strengthened, others that are weakened or eliminated, thus modifying the brain’s architecture and functioning. The driving force behind this dynamic process is a cognitive activity, particularly learning. Thus, even in adulthood, learning would be the best way to improve or maintain our cognitive abilities or slow down their decline.

Of course, plasticity is not the only factor that comes into play in the development and performance of the brain. Genetic factors over which we have either no or limited control are also to be taken into account. In this respect, the contribution of neuroscience is welcomed, whether it is to help identify, diagnose, understand, and, if possible, intervene on them. Dyslexia, dyscalculia and dementia, commonly referred to as the “3 D’s”, are the known neurological problems that impact learning or cognition and for which neuroscience has so far contributed the most in terms of diagnosis or remediation.

Automation and cognitive inhibition. Automation and cognitive inhibition are two complementary neurocognitive learning mechanisms (see Neuroscience: learning in 4 steps and The 3 speeds of thought). Brain imaging has revealed that they are present not only in adults but also in children. Automation is the outcome of the learning process, the fact that, through repetition and practice, our knowledge passes from conscious processing to automatic processing. And once a learning element is automated, the brain is free to move on to the next.

Cognitive inhibition is sometimes called “de-automatization” since the brain dynamics behind it are in the opposite direction of automation. As described by Quebec neuroscientist Steve Masson, inhibition is the “brain’s ability to control spontaneous intuitions, strategies or habits by releasing inhibitory neurotransmitters that interfere with the activation of the neural networks responsible for these intuitions, strategies or habits.” This capacity is essential to allow learning that, at first glance, goes against what seems logical to us. This is because some of the learning that occurs earlier in life is so firmly imprinted in our brains that if it cannot be erased must be inhibited. A study by Masson and colleagues (2014) showed that the brains of science students used this inhibitory mechanism to give scientifically valid answers to questions about non-scientific notions that were commonly conveyed.

Childhood: a time of firsts

A “sensitive” period for some learning. Although the brain changes throughout life, childhood is when it is most efficient for some learning. This is the case in early childhood for learning involving sensory stimuli, including sounds and language, and specific emotionally and cognitively rich experiences.

Neural recycling. Later, the acquisition of new “cultural” skills, such as arithmetic or reading, will begin to result in “neural recycling” in the young child’s head, a process by which the pre-existing architecture of specific brain regions is altered during learning so that the new skills can take hold. For example, the young brain uses the existing architectures of object recognition, oral comprehension, speech production, and word meaning networks when learning to read. However, neural connections related to object recognition will have to be modified since letters and words are “objects” that have not yet been processed. Then, for the child to eventually understand the meaning of words, connections will have to be made between the “recycled” object recognition networks and the region corresponding to word meaning that he or she began to acquire when learning to speak.

Early constraints. The first constraints also appear in the learning process. While the young brain that has not yet learned to read does not consider the orientation of objects in its recognition of objects, it will take extra effort to distinguish between the letters b, d, p and q. Neural recycling also applies to learning numbers. Even if a baby already has a number sense that allows him to intuitively evaluate quantities — knowing the difference between, for example, two objects or a dozen — in order to learn Arabic numerals and eventually geometry, the child’s brain will have to engage in neural recycling.

Adolescence: Full power, but lack of control

Increased connectedness. A period of dramatic physical and psychological change, adolescence is a time when the brain reaches a high cognitive potential under the microscope of neuroscience. “Connectedness” increases while the white matter composed of axons, the communication cables linking neurons, grows in volume.

Immature prefrontal cortex. However, alongside this unfolding brain potential, the prefrontal cortex — the seat of executive control, reasoning and decision making — is far from mature, which does not occur until around age 30. Add to this lack of control the increased amount of hormones in the brain, and it is easy to see why this period of life, as exciting as it is, has its share of instability (see The importance of emotions in learning).

Adulthood: more control… and mistakes

Mature prefrontal cortex. The prefrontal cortex is one of the last brain regions to mature. As a result, adults have more control over their learning than children and adolescents.

Well-established connections. In adulthood, neural connections are well established. In other words, neurons analyze, transmit and store information in memory while structuring appropriate responses. Compared to children, whose connections are not yet as strong and defined, adults are more cognitively efficient. On the other hand, since their habits are well established, their errors are more difficult to correct.

Reduced brain activity. Mastery of a task resulting from well-established neural connections goes hand in hand with a lower level of brain activity. The problem is that when the brain is less activated, it tends to decline, a factor that is added to its normal decline — or accelerated by neurological pathologies in particular — linked to ageing. Let’s remember that learning seems to be the best antidote to maintain our cognitive faculties as long as possible or at least to limit their decline.

Noémie DUFORT, Les neurosciences en éducation [Dossier thématique], Réseau d’information pour la réussite éducative, 2020.
Olivier HOUDÉ, Mieux connaître le développement de l’intelligence chez l’enfant. Le rôle clé de l’inhibition cognitive, Le Réseau EdCan, 2015.
Steve MASSON, Mieux connaître le cerveau peut-il nous aider à mieux enseigner?, Le Réseau EdCan, 2014.
Masson et al., Differences in Brain Activation Between Novices and Experts in Science During a Task Involving a Common Misconception in Electricity, 2014.
OCDE, Comprendre le cerveau : naissance d’une science de l’apprentissage : Nouveaux éclairages sur l’apprentissage apportés par les sciences cognitives et la recherche sur le cerveau, Éditions de l’OCDE, Paris, 2007.
Vinita SRIVASTAVA, Comment les neurosciences peuvent améliorer l’éducation, The Conversation, 2015.

Neuroscientific limitations and possibilities

Some clarification is needed about the limitations of neuroscience, particularly its preferred technology, functional brain imaging (fMRI). Although fMRI has shown that learning does indeed modify the brain by showing us that it becomes active when cognitive tasks are in progress, fMRI does not explicitly tell us how skills are developed, nor does it currently predict or diagnose a learning disability.

We must therefore be wary of simplistic approaches that, under a neuroscientific label, actually convey neuromyths, including learning styles, multiple intelligences, left or right brain dominance, the idea that we only use 10% of our brain, etc. (see Education through the lens of neuroscience and 3 Myths That Prevent You from Learning).

That said, the methods used in neuroscience — which are, by the way, constantly evolving — allow us to observe inter-individual differences in the anatomy and functioning of the brain. And if they do not provide all the keys to the learning process, by revealing specific cerebral mechanisms at play, they make it possible to establish the causality of intuitions on subjects already known in education and participate in the development of effective approaches including those aimed at learning disabilities. In particular, neuroscientists are trying to understand with more finesse the best times to make different types of learning, the processing of language and mathematics, the influence of the environment and tools, and the development and regulation of emotions.

Catherine Meilleur

Catherine Meilleur

Creative Content Writer @KnowledgeOne. Questioner of questions. Hyperflexible stubborn. Contemplative yogi.

Catherine Meilleur has over 15 years of experience in research and writing. Having worked as a journalist and educational designer, she is interested in everything related to learning: from educational psychology to neuroscience, and the latest innovations that can serve learners, such as virtual and augmented reality. She is also passionate about issues related to the future of education at a time when a real revolution is taking place, propelled by digital technology and artificial intelligence.