Assimilation and plasticity help to shape the brain

MA Education
Tuesday, May 2, 2017

In this article, we look at established pedagogy, including Piaget's theory of equilibration, through a lens of current neuroscience research, to find out what it reveals and where collaboration might take us.

Assimilation and plasticity help to shape the brain
Assimilation and plasticity help to shape the brain

Piaget initiated the systematic study of cognitive development, highlighting how differently children thought from adults and proposing a ‘stage theory’ of intellectual development of progressive reorganisation of mental processes from childhood to adulthood. Children, he proposed, build a representation of their world through the building blocks of schemas or units of knowledge relating to aspects of the world.

Equilibrium occurs when a child's schemas can deal with most new information through assimilation (using existing schemata or prior mental structures to deal with new situations). However, a state of disequilibrium occurs when assimilation is not possible, here equilibration drives the learning process as we seek balance by accommodation (existing schema needs to be changed or new ones created to deal with new information).

Increase in quantity and complexity of schemata led to the development of a child's mental processes and this, Piaget thought, developed in four stages: Sensorimotor Stage (Birth-two), object permanence via mental representations occurs here; Preoperational Stage (two to seven), with egocentric and symbolic thought; Concrete Operational Stage (seven to 11), the beginning of logical or operational thought and conservation of number; Formal Operational Stage (11 and over), with abstract concepts, and logically tested hypotheses.

Piaget felt that active or discovery learning, through manipulation of objects, processes and concepts was the best way for children to learn to construct their own truths from their experiences. Rather than shallow imitation, exploration would create disequilibrium, which would need equilibration, thus driving learning.

Vygotsky, Bruner and other theorists questioned the idea of stages, seeing learning as a continuous process and placing more emphasis on culture and language. Vygotsky felt children's learning occurred in social contexts where children collaborated, using language, with the ‘more knowledgeable other’. For Piaget, thought precedes language; for Vygotsky thought is linked to our ability to communicate (Conkbayir, 2017).

Neuroscience and the developing brain

Human infants have a long period of immaturity, a protected time to learn about their environment, a capacity to learn, high levels of neurochemicals making synapse connection changes easier. The brain region called the prefrontal cortex, with its focus on planning and action, takes an especially long time to mature, allowing infants an unrestrained sense of exploration and imagination unhindered by excessive formal thinking. Throughout these processes, wellbeing and cognition are closely linked and adverse stress will affect learning.

The majority of our neurons are formed in the womb – the connections between neurons become stronger and more extensive during infancy through our developing communication skills, behaviours and emotional attachments. Myelination, the insulation of axons in the brain by a fatty-substance called myelin, increases the speed of sensory information flow along an axon. Myelin thickness changes in response to the environment, learning and skills practice.

Synapses, formed fast in infancy, allow messages to be passed between neurons and contributes to brain ‘plasticity’; its ability to change. Synaptic ‘pruning’ (removing unused synaptic connections and making room for new ones) is linked to plasticity. Pruning helps us to specialise and to adapt to our environment and makes rich early experiences critical so that a wide range of abilities remain possible. Sensitive (formerly critical) periods are windows of growth, which correspond with various domains of development, such as language, movement, and emotions (Abbott and Burkitt, 2015).

Learning from mistakes is linked with brain plasticity, with new synapses forming when we make mistakes – more electrical activity occurring when a person makes a mistake than when they give a correct response or is instructed. Critically, ‘it is a time of struggle; the brain is challenged and the challenge results in growth’ (Boaler, 2015); this reflects Piaget's theories on disequilibrium. Those with a growth mindset embraced mistakes more readily and experienced greater brain activity than those with a fixed mindset.

Learning from mistakes is linked with brain plasticity, with new synapses forming – more activity occurring when a person makes a mistake than when they give a correct response or is instructed.

Caution when using neuroscience to influence pedagogy

Neuroscience has the potential to deal with diverse concerns, such as the effect of domestic violence or autistic spectrum disorder on the child's brain. There is need for caution, however.:

  • Reductionist approaches to the question of mind to purely observable data, ignoring the question of consciousness or emotions, meaning-making, free will, autonomy or our interaction with our environment. We might then ignore the wider picture, the philosophical debate, the fact that an infant's power to imitate is not simply to learn, but also to connect.

  • ‘Neurobunk’ or overly simplistic messages relayed via the media about ‘research shows’-type soundbites, such as the amygdala's only function is as the ‘fear centre’, or the potentially overzealous interpretation of mirror neurons.

  • Neuroscientific research does not always incorporate the idea of culture, a construct valued by Vygotsky.

  • The ethics of imaging or investigating children or the use of newer processes, such as neurofeedback (use of mild electrical stimulation to improve brain functioning) without fully understanding the brain.

  • Research is relatively new, often not replicated, and open to misinterpretation, particularly when linking a correlation of observations with causation, without regard to other variables.

  • ‘Blobology’, or the danger of simply mapping functions to precise areas of the brain by monitoring brain activity without fully understanding function (like seeing lights on in houses at night but not knowing what is going on inside).

  • Little application to what is valuable in the classroom, or indeed parenting, coupled with high expectations. ‘Neuroscience is not yet at the point where it can help educators pick out particular sub processes for intensive remediation of a struggling child’ (Hruby, Goswami, Frederiksen and Perfetti; in Abbott and Burkitt, 2011).

  • Reluctance by the scientific community to apply findings, possibly to protect its integrity and avoid overgeneralisations.

  • Some of the research tells us little new; much of what we learn is that it is largely ordinary, everyday experiences and age-old intuitive interactions, such as ‘motherese’ that best shape the infants mind.

  • Neuroscience and early brain development is not rigorously taught on courses but could complement theory.

  • The ‘two cultures’ of the sciences and humanities must work together to consider the wider issues inherent in this field.

  • There are thousands of papers, largely unorganised, often adopting non-theoretical data-driven perspectives, or that use adult cognitive models.

  • Failure to remember that everything we do is in the context of something else, such as affect, behaviour and cognition.

Advances in neuroscience

In the mid-1980s and through the 1990s, scientists discovered that children, rather than being ‘blank slates’, know more about the world than we believed. Far beyond simply understanding the immediate, concrete world, researchers found that infants could decipher abstract concepts from a confusing sensory mess. The central idea of cognitive science was that the brain is a kind of computer designed by evolution and programmed by experience. Using mathematical ideas, such as probabilistic models, computer scientists and philosophers began to unravel complex gene expression problems and how the computer-like hypotheses-forming and complex reasoning in children's heads might work (Gopnik, 2010).


Piaget developed his theory, a century ago, without the benefit of current neuroscience. He worked with the abstract concept of the mind rather than with the anatomy and functions of the brain. Brain imaging (neuroimaging) was invented in the 1880s by Mosso, who devised a technique to assess how blood was redistributed through the brain during task execution or while experiencing an emotion.

Later, computed tomography (CT) scans emerged, followed by the development of the magnetic resonance imaging in the seventies. Functional neuroimaging can measure brain responses of children undertaking cognitive tasks, but the methods and interpretations of data rest with the researchers, often fitting with funding priorities.

Non-invasive neuroimaging such as magnetic resonance imaging (MRI), functional MRI (magnets monitor changes in oxygen levels in the blood), electroencephalography (EEG; electrodes detect electrical signals), and event-related potentials (ERP) have helped map brain activity during typical and atypical development.

Diffusion tensor imaging (DTI) examines brain images and the diffusion of water molecules in the brain to track active pathways in the brain. Positron Emission Tomography (PET) locates synapses by circulating a radioactive tracker. Functional near-infrared spectroscopy (fNIRS) helps monitor face-to-face interactions between adults and infants via monitoring of haemoglobin levels (Finnegan, 2016).

What can neuroscience tell us?

Developments in neuroscience could help to verify or refute earlier theorists ideas on learning and development. For example, maturational changes (say, in the prefrontal cortex) might account for Piaget's observations on object permanence, which he felt linked with cognitive functions. This link is not universally recognised, with object permanence perhaps linked with working memory and other processes (Abbott and Burkitt, op cit).

Vygotsky understood the role of biology, studying medicine and neuropsychology, and through his clinical work on aphasia and Parkinson's disease. He researched the development of higher mental functions as well as cerebral injury at different periods of development. His ‘more knowledgeable other’, ‘scaffolding’, and his ‘zone of proximal development’ are based on these experiences.

Active learning, however, in accordance with the theories of Vygotsky, Piaget and Bruner, among others, has been shown to be beneficial, creating neural networks in the orbitofrontal cortex as well as increased synaptic connections. In Bruner's spiral progression approach, memory is an important factor. Additionally, in accordance with Vygotsky's beliefs, neuroscientists believe that the human brain is constructed socially. These ideas are reflected in the Characteristics of Effective Learning.

Play is an essential tool for infants; improving social competence, adaptivity, rule-adherence and emotional regulation, and promoting the neocortical executive control regions to control other neural systems. Recent studies reveal that problem-solving strategies can enchance learning and operational thought, and have progressed our thinking about metacognition. Neuroscientific investigation and imaging has revealed which brain area are involved in metacognition, with potentially separable systems for prospective and retrospective judgements of performance. Metacognition is distinct from task performance itself and involves suppressing inappropriate responses, as well as the executive functions involved in metacognition (Abbott and Burkitt, op cit).

We understand that caregivers, through securely-attached relationships, reciprocity and emotional availability with their infants, activate growth in the brain – for example, Meanye's study in Conkbayir, 2017. Brain imaging has investigated differences in interdependence and in theory of mind across cultures. We understand the effects of trauma, the social engagement system of the brainstem, the fight-flight response of the amygdala, mirror neurons, bonding hormones, and many other concepts.

‘Nature versus nurture is dead, long live nature versus nurture’ (Ridley, in Conkbayir, op cit). This age-old debate is complex and might now be void. The somewhat controversial area of molecular epigenetics describes how gene expression may embed in the organism traces of social experiences and transient environmental factors, especially at sensitive periods, through the modification of neural circuits, and then be transmitted across generations without changes in the DNA sequence. This presents challenges for social sciences and biology to reconsider their relationship with one another (Conkbayir, op cit).


Developmental cognitive neuroscience embraces a range of disciplines. Vygotsky drew from constructs and explanations from psychology, history, linguistics, philosophy, and anthropology, to form a multi-disciplinary approach to ‘mind’. Developmental cognitive neuroscience as a discipline began at a conference in Philadelphia in 1989 organised by Adele Diamond; the first formal collaboration of developmental psychologists, cognitive scientists, and neuroscientists, unaware of the crossovers of their work and facilitating translations to bridge the conceptual divides and to recognise the importance of early brain development, especially the prefrontal cortex.

Mind, Brain and Education is a holistic academic discipline and collaboration between psychologists, neuroscientists, and educators attempting to contextualise data in the classroom in approaches, such as neuropedagogy. With academic courses available, this area looks at executive brain functions, motivation, sleep, bilingualism, dyslexia, stress and emotions, among other areas, and their effect on learners, attempting to build the educational neuroscience community through ‘bidirectional’ research work by interdisciplinary researchers to reduce discrimination and to better inform educational policy (Knox, 2016).

Calls for theoretical frameworks

Application of developmental cognitive neuroscientific data could be driven by better theory-guided data interpretation, such as constructivist developmental theories of cognition, to help draw more consistent conclusions from neuroimaging. This might help draw theory-based hypotheses from data on a range of areas – mental/executive attentional capacity; cortical thickness; domain versus material/content processes; hemispheric involvement in cognition; structural maturation.

Neo-Piagetians attempted to address problems with Piaget's theories, organising a great deal of empirical data by using theory-guided, testable, constructivist models, in an effort to explain transitions within cognitive developmental growth and from one stage to the next.

Various neo-Piagetian theories could guide neuroscience research and neuroimaging when examining speed of processing, better understanding of the progressive reorganisation of developmental schemas during childhood, or cognitive-complexity constraints on mental attentional capacity, language, or levels of processing abstraction and individual differences between cognition and affect.

The future

There will undoubtedly be advances in neuroimaging, particularly in combining imaging types (BRAIN, 2014). Neuroimaging is already helping us to understand various areas, such as the effort involved for infants in processing new words or phonetic discrimination, the complexity of reading and dyslexia, and has confirmed that babies prefer prosodic sounds (high-pitched and slower speech) and motherese (Conkbayir, op cit).

We could benefit from a better understanding of emotions, the multiple systems in the brain controlling language, the central question of whether language is innate or learned, or how it links with other functions, such as movement, as well as collaborative learning and theory of mind. Neuroscience adds another dimension to our knowledge, along with pedagogy and our observations.

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