January 2017 research round-up

Research highlights in learning and education from around the world

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Jan 31, 2017
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Shared memories mean shared brain activity

Previous research has shown that two people who experience the same event also show similar patterns of brain activity. Furthermore, in a single individual, the patterns of activity observed during perception of an event are reactivated during recall. The question posed in this study was whether a person’s brain activity during recall of an experience was more similar to the experience itself (experience–recall similarity), or more similar to a second person’s brain activity during recall of the same material (recall–recall similarity).

To test this, participants viewed a TV show and were later asked to verbally describe as much of the show as possible. Their brains were scanned with fMRI while they watched the show, and again while they recalled the show’s events. Perhaps surprisingly, recall–recall similarity was greater between two people than experience–recall similarity in a single individual, indicating that the neural transformations that occur from experience to recall are shared across people. Moreover, the greater the transformation from experience to recall, the better the event was remembered, suggesting that extrapolating the gist of a scene from its details may help memory formation. This finding may be analogous to well-established learning concepts like summarization and content transformation, which re-frame information to aid memory consolidation.

Chen et al. (2017) Shared memories reveal shared structure in neural activity across individuals. Nature Neuroscience 20:115-125.


Two-way interaction between attention and learning

A major motivator in learning is the reward associated with it. This type of reward-incentivized learning, in which some decisions have a bigger payoff than others, is called reinforcement learning. Studied frequently in the laboratory using simple tasks, reinforcement learning becomes unwieldy in complex environments, where there are many sources of potential reward – the brain needs to identify which components are rewarding and weight them according to their payoff. How is this achieved?

In this paper, researchers show that the answer is selective attention. Participants viewed a series of nine images, each of which had a reward value unknown to the participant. The task was to identify which image(s) offered the greatest reward. The authors used fMRI to identify which image a participant focussed on, and were thus able to discern how attention interacted with learning. As participants learned which images were rewarded, their attentional focus narrowed onto the most rewarding images. The results suggest a ‘two-way street’ between attention and learning, in which focused attention allows learning of environmental complexities, and in which learning promotes more focused attention.

Leong et al. (2017) Dynamic interaction between reinforcement learning and attention in multidimensional environments. Neuron 93(2):451-563.


A new player in memory consolidation?

The hippocampus encodes episodic memories about our past experiences, which are inevitably closely associated with our physical location at the time. During sleep or rest, the same pattern of activity seen during an experience is replayed many times, helping to consolidate the memory. This neural replay was thought to occur only in the hippocampus, consistent with its central role in memory storage. Now, researchers show that replay also occurs in the medial entorhinal cortex (MEC), a brain region closely connected to the hippocampus, and which like the hippocampus is also important in encoding our physical location. Importantly, the replay in the MEC occurs even when the hippocampus is not replaying events, showing that the two phenomena are independent. The work suggests that critical memory consolidation processes aren’t limited to the hippocampus. Future studies should begin to unravel which memories prioritise hippocampal over MEC replay, and vice versa.

O’Neill et al. (2017) Superficial layers of the medial entorhinal cortex replay independently of hippocampus. Science 355(6321):184-188.


Neurostimulation enhances working memory

The use of non-invasive brain stimulation devices to improve cognition is contentious, with much conflicting data existing as to its efficacy. In the case of working memory, previous research using either transcranial direct current stimulation (tDCS) or transcranial magnetic stimulation (TMS) has found, at best, only small effects of neurostimulation. In this study, researchers tested whether a type of TMS that more closely mimics the brain’s natural activity patterns could robustly enhance working memory when delivered to the dorsolateral prefrontal cortex. The authors showed that performance on the less taxing of the two cognitive tasks improved relative to a control group, an effect that was largest after the stimulation had finished, rather than during the stimulation. Performance on the more difficult task showed no benefit.

Hoy et al. (2016) Enhancement of working memory and task-related oscillatory activity following intermittent theta-burst stimulation in healthy controls. Cerebral Cortex 26(12)4563-4573.


Physical activity in the classroom helps learning

Physical activity produces cognitive benefits alongside its health benefits. In educational settings, supervised exercise programs are normally separate from classroom learning opportunities. Some have thought that this separation may be inefficient, in that the time spent exercising is time not spent learning. To counter this, researchers have sought to integrate physical activity into classroom lessons.

In this study, preschool children learned to associate animals with the continents to which they belonged. Children were placed into three groups: no physical activity, integrated physical activity (in which the physical activity was relevant to the learning material), and non-integrated physical activity (no relation between type of physical activity and the learning material). Both groups that performed physical activity showed improved learning compared to the no activity control group, an effect that persisted at 5-weeks post-training. The type of physical activity did not influence learning. Whether the improvement was directly due to exercise-related factors or is secondary to changes in cognitive factors (e.g. attention, motivation) is, however, unclear, particularly given the children’s self-reported increase in enjoyment when performing the physical activity versions of the task. Nevertheless, the results show that integrating physical activity into the classroom can aid learning.

Mavilidi et al. (2016) Infusing physical activities into the classroom: Effects on preschool children’s geography learning. Mind, Brain, and Education 10(4):256-263.

Go to the profile of Alan Woodruff

Alan Woodruff

Community Editor, Queensland Brain Institute

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