Do pre-school teachers need to know about the brain?

Neuromyths are misconceptions about the brain. Although they typically have factual origins, neuromyths arise from the over-generalisation, misquotation or misunderstanding of these facts. The concern is that should neuromyths take hold, they will be used to guide teaching practices, with potentially detrimental consequences.

The prevalence of neuromyths amongst teachers has been looked at in a number of countries, but never specifically amongst pre-school teachers. Because the pre-school years can produce long-term effects in a child’s development, and pre-school teachers are important shapers of children’s cognitive growth, the authors of this study surveyed over 200 pre-school teachers in Argentina as to their beliefs in 24 brain-related statements (Table 1 in the article).

On the whole, teachers were able to choose the correct answer to most statements (labelling statements as either “correct, “incorrect” or “don’t know”). The statements most often wrongly interpreted were the myth that we only use 10% of our brain (only 26% of respondents choosing the correct answer), the myth that human memories are stored in a tiny portion of the brain, similar to a computer (20% correct), and the truth that sustained practice of mental processes can change brain structure (35% correct).

The authors noted that the surveyed teachers’ conceptions of memory and plasticity were generally weaker than, for example, their knowledge of the mind-brain relationship. Furthermore, they note that teachers used anecdotal evidence to support their incorrect beliefs, rather than any empirical data. The authors therefore recommend that teacher training incorporate some basic neuroscience content, particularly around concepts of memory and plasticity.

Hermida et al. (2016) Conceptions and misconceptions about neuroscience in preschool teachers: a study from Argentina. Educational Research 58(4):457-472

Genetics and educational attainment

Educational attainment – the number of years of formal education – is positively associated with economic and health indicators. Genetic studies have shown over 150 common genetic variants that are linked to educational attainment. These are variants that occur frequently in the population and have small individual effects. There are also rare genetic variants that can have a larger effect, such as in genes associated with psychiatric and neurodevelopmental disorders.

In a study of over 14,000 northern Europeans, researchers tested whether extremely rare variants affected educational attainment. As might be expected, rare variants in people with psychiatric or neurodevelopmental disorders were associated with decreased time spent in education. But surprisingly, a similar decrease in educational attainment was seen in the general population – those with the same genetic variant but without a brain disorder. The study adds to a body of evidence for a genetic contribution to educational achievement, intelligence and cognitive function.

Ganna et al. (2016) Ultra-rare disruptive and damaging mutations influence educational attainment in the general population. Nature Neuroscience (Advance Online Publication) doi: 10.1038/nn.4404

How learning modifies the neural code

Understanding how the brain encodes information is a major priority in neuroscience. During learning, that representation is changed in some way. In this paper, Takaki Komiyama and colleagues from the University of California, San Diego show that the characteristics of the task being learned dictate how the code is modified.

Mice were trained to discriminate between two odors, which varied in their similarity, to obtain a water reward. Distinguishing between similar odors is a difficult task that should require considerable neural resources, whereas differentiating very different odors is simple and can be accomplished rapidly to obtain a reward. The researchers tracked neural activity as the mice performed the task, letting them compare how neural representations of odors changed during learning, and how that changed differed depending on task difficulty.

For odors that were easy to discriminate, the mouse brain learns to prioritise efficiency – training reduced the number of cells activated upon odor presentation, while the proportion of cells that discriminated between the odors stayed the same. In contrast, for odors with high similarity, the priority was correct discrimination – more resources were devoted to the task, as training increased the proportion of cells used to distinguish the odors.

The study shows that even for the same learning task, different strategies are implemented in the neural code when prioritising efficiency versus robustness.

Chu et al. (2016) Balancing the robustness and efficiency of odor representations during learning. Neuron 92(1): 174-186

A common hippocampal code for space and time

The hippocampus stores our episodic memories and is also crucially involved in how our brains navigate space. To test whether similar mechanisms are involved in these disparate functions, participants’ brains were imaged with fMRI before and after learning to navigate along a specific path in a virtual world. Objects were placed at various locations as memory prompts, and the study design allowed any two objects to be linked either in time only, space only, in time and space, or not at all.

Comparing the neural activity evoked by two objects encountered close together in time or space, the researchers observed more similarity after learning than before. This indicates that the two objects were linked in memory, and was taken as evidence that the hippocampus represents memories in both temporal and spatial dimensions. Moreover, objects that were encountered close together in both time and space evoked even greater neural similarity in the hippocampus. The results are some of the first evidence that the human hippocampus uses a similar representation for spatial and temporal memories, linking the two major functions of the hippocampus – space representation and episodic memory.

Deuker et al. (2016) An event map of memory space in the hippocampus. eLife 5:e16534