Tuning into brainwave rhythms accelerates learning in adults

Overview: Tuning into a person’s brain wave cycle before they perform a learning task can dramatically improve the rate at which cognitive skills improve.

Source: University of Cambridge

Scientists have shown for the first time that briefly tuning into a person’s individual brain wave cycle before performing a learning task dramatically increases the rate at which cognitive skills improve.

According to the team behind the study, calibrating the speed of information delivery to match our brain’s natural pace increases our ability to absorb and adapt to new information.

Researchers at the University of Cambridge say these techniques could help us maintain “neuroplasticity” much later in life and promote lifelong learning.

“Each brain has its own natural rhythm, generated by the oscillation of neurons working together,” said Prof. Zoe Kourtzi, senior author of the study from Cambridge’s Department of Psychology. “We simulated these fluctuations so that the brain is in tune with itself — and in the best condition to thrive.”

“The plasticity of our brain is the ability to restructure and learn new things, constantly building on previous patterns of neuronal interactions. By using brainwave rhythms, it may be possible to enhance flexible learning across the lifespan, from childhood to older adulthood,” Kourtzi said.

The findings, published in the journal cerebral cortexwill be researched as part of the Center for Lifelong Learning and Individualized Cognition: a research collaboration between Cambridge and Nanyang Technological University (NTU), Singapore.

The neuroscientists used electroencephalography — or EEG — sensors attached to the head to measure electrical activity in the brains of 80 study participants and measure brain wave rhythms.

The team took alpha waves. The mid-range of the brain wave spectrum, this wave frequency tends to dominate when we are awake and relaxed.

Alpha waves oscillate between eight and twelve hertz: a full cycle every 85-125 milliseconds. However, each person has their own alpha peak frequency within that range.

Scientists used these measurements to create an optical “pulse”: a white square that flickers on a dark background at the same rate as each person’s individual alpha wave.

Participants were given a personalized 1.5-second dose to get their brains to work at their natural rhythm — a technique called “entrainment” — before being given a tricky, fast-paced cognitive task: trying to identify specific shapes in a barrage. of visual clutter.

A brainwave cycle consists of a peak and a trough. Some participants received pulses that matched the peak of their waves, some with the trough, while some received rhythms that were either random or at the wrong speed (a little faster or slower). Each participant repeated more than 800 variations of the cognitive task, and the neuroscientists measured how quickly people improved.

The learning rate for those stuck in the right rhythm was at least three times faster than for all other groups. When the participants returned the next day to complete another round of tasks, those who learned much faster through entrainment had maintained their higher level of performance.

“It was exciting to discover the specific conditions you need to get this impressive boost in learning,” says first author Dr Elizabeth Michael, now at Cambridge’s Cognition and Brain Sciences Unit.

“The intervention itself is very simple, just a short flicker on a screen, but when we hit the right frequency plus the right phase alignment, it seems to have a strong and lasting effect.”

Importantly, entrainment pulses must match the nadir of a brain wave. Scientists believe this is the point in a cycle where neurons are in a state of “high receptivity.”

“We feel like we’re constantly engaged with the world, but in fact our brains are taking quick snapshots and then our neurons communicate with each other to string the information together,” said study co-author Prof. Victoria Leong, of NTU and Cambridge’s Department of Paediatrics. .

“Our hypothesis is that by tailoring information delivery to the optimal phase of a brain wave, we maximize information capture because our neurons are then at the peak of excitability.”

Previous work from Leong’s Baby-LINC lab shows that mothers’ and babies’ brain waves synchronize when they communicate. Leong believes the mechanism in this latest study is so effective because it reflects the way we learn as babies.

“We are tapping into a mechanism that allows our brain to tune in to temporal stimuli in our environment, specifically communicative cues such as speech, gaze and gestures that are naturally exchanged during parent-infant interactions,” Leong said.

This shows a person in an EEG cap
The brain wave experiment was set up in the Adaptive Brain Lab, led by Prof. Zoe Kourtzi, in the Department of Psychology at the University of Cambridge. Credit: University of Cambridge

“When adults talk to young children, they use child-directed speech – a slow and exaggerated form of speech. This study suggests that child-directed speech may be a spontaneous way to match and train children’s slower brain waves to aid learning .”

The researchers say that although the new study tested visual perception, these mechanisms are likely “domain general”: applicable to a wide variety of tasks and situations, including auditory learning.

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They argue that possible applications for brainwave entrainment may sound like science fiction, but are increasingly feasible. “While our study used complex EEG machines, there are now simple headband systems that allow you to measure brain frequencies quite easily,” Kourtzi said.

“Kids now do so much of their learning in front of screens. You can imagine using brainwave rhythms to improve aspects of learning for children who are struggling in mainstream classrooms, perhaps due to attention deficits.”

Other early applications of brainwave entrainment to drive learning may involve training in professions where rapid learning and quick decision-making are vital, such as pilots or surgeons. “Virtual reality simulations are now an effective part of training in many professions,” says Kourtzi.

“Implementing pulses that are in sync with brain waves in these virtual environments could give new learners a head start, or help those retraining later in life.”

About this learning research news

Writer: Fred Lewsey
Source: University of Cambridge
Contact: Fred Lewsey – University of Cambridge
Image: The statue is attributed to the University of Cambridge

Original research: Open access.
“Learning to the rhythm of your brain: Individualized entrainment drives learning for perceptual decisions” by Zoe Kourtzi et al. cerebral cortex


Learning to the beat of your brain: Individualized entrainment drives learning for perceptual decisions

Training is known to improve our ability to make decisions when interacting in complex environments. However, individuals differ in their ability to learn new tasks and acquire new skills in different environments. Here we test whether this variability in learning ability is related to individual brain oscillatory states.

We use a visual flicker paradigm to train individuals on their own brain rhythm (i.e., peak alpha frequency) as measured by resting-state electroencephalography (EEG). We demonstrate that this individual frequency-matched brain entrainment results in faster learning in a visual identification task (i.e., detecting targets embedded in background noise) compared to entrainment that does not match an individual’s alpha frequency.

Furthermore, we show that learning is specific to the phase relationship between the immersive flicker and the visual target stimulus. EEG during entrainment showed that individualized alpha entrainment increases alpha power, induces phase alignment in the pre-stimulus period, and results in shorter latency of early visual evoked potentials, suggesting that brain entrainment facilitates early visual processing to produce enhanced perceptual support decisions.

These findings suggest that individualized brain entrainment may drive perceptual learning by altering reinforcement control mechanisms in the visual cortex, indicating a key role for individual neural oscillatory states in learning and brain plasticity.

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