April 2020 research round-up

Research highlights in learning and education from around the world I 2 min 40 sec read
Published in Neuroscience
April 2020 research round-up

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Explaining, between study, to help learning

Explaining what you have learned to another person can help consolidate the information in your memory and identify gaps in your knowledge. Although these benefits are well-established, one factor that hasn’t received much attention is when the explanation should be given. Typically, research has only considered explanations given after completing a study block – for example after reading an entire chapter of a textbook.

In this study, the authors compared the learning benefits of post-study explanations with between-study explanations. When studying texts requiring conceptual knowledge (such as the workings of a combustion engine), students showed greater learning if asked to give explanations of the content between study phases, compared to at the end of the study block. The authors suggest that between-study explanations force the learner to identify knowledge gaps, which can then be addressed during later study.

Lachner et al. (2020) Timing matters! Explaining between study phases enhances students’ learning. Journal of Educational Psychology 112(4): 841-853 DOI: https://dx.doi.org/10.1037/edu...

Disentangling the brain activities underlying working memory

To store information in working memory – a trait that predicts a person’s intelligence and academic achievement – we need to prioritize the important material while suppressing what is irrelevant.

In this study, researchers show that prioritization and suppression rely on different rhythmic brain activities – oscillations – occurring in different brain regions. Moreover, by applying transcranial magnetic stimulation (TMS) to these areas, the researchers could artificially improve working memory capacity. For this artificial enhancement to work, the frequency of the TMS needed to match the oscillation frequency in the target brain region, which caused the prioritization and suppression effects to be amplified.

Thus the study offers causal evidence that specific oscillations (at theta and alpha frequency) in specific brain regions (frontal and parietal cortex) affect distinct aspects of working memory (prioritization and suppression).

Riddle et al. (2020) Causal evidence for a role of theta and alpha oscillations in the control of working memory. Current Biology 30(9): P1748-1754.E4 DOI: https://doi.org/10.1016/j.cub....

Cell populations underlying memory generalization and discrimination

To learn, we sometimes need to generalize across similar memories – this helps us learn that dogs bark and have four legs, for example. At other times, we need to discriminate amongst several similar memories – for example identifying your pet dog from amongst many others. How does the brain achieve this?

In this study, researchers show that distinct populations of cells within the dentate gyrus are involved in generalizing or discriminating memories. The two cell populations belong to distinct neural circuits, and the particular properties of those circuits favor the cells’ involvement in either generalization or discrimination.

Sun et al. (2020) Functionally distinct neuronal ensembles within the memory engram. Cell 181(2): P410-423.E17 DOI: https://doi.org/10.1016/j.cell.2020.02.055

Boosting recall by limiting memory interference

We have all had difficulty recalling a particular memory from a host of similar, overlapping memories. These memories interfere with each other, making specific recall more challenging.

One way to reduce this interference – and make recall more reliable – is to recall the “old” memory at the same time you are storing the “new” memory. However, it isn’t clear why this strategy works.

Now, using functional magnetic resonance imaging as people undertook memory tasks, researchers show that if the old memory is “in mind” when encoding the new, similar memory, the two are integrated or linked together. This contextualizes the memories and helps distinguish between them, thus reducing interference.

Chanales et al. (2019) Interference between overlapping memories is predicted by neural states during learning. Nature Communications 10: 5363 DOI: https://doi.org/10.1038/s41467-019-13377-x

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