brainwaves

Running faster changes brain rhythms associated with learning

September, 2011

A mouse study finds that gamma waves in the hippocampus, critically involved in learning, grow stronger as mice run faster.

I’ve always felt that better thinking was associated with my brain working ‘in a higher gear’ — literally working at a faster rhythm. So I was particularly intrigued by the findings of a recent mouse study that found that brainwaves associated with learning became stronger as the mice ran faster.

In the study, 12 male mice were implanted with microelectrodes that monitored gamma waves in the hippocampus, then trained to run back and forth on a linear track for a food reward. Gamma waves are thought to help synchronize neural activity in various cognitive functions, including attention, learning, temporal binding, and awareness.

We know that the hippocampus has specialized ‘place cells’ that record where we are and help us navigate. But to navigate the world, to create a map of where things are, we need to also know how fast we are moving. Having the same cells encode both speed and position could be problematic, so researchers set out to find how speed was being encoded. To their surprise and excitement, they found that the strength of the gamma rhythm grew substantially as the mice ran faster.

The results also confirmed recent claims that the gamma rhythm, which oscillates between 30 and 120 times a second, can be divided into slow and fast signals (20-45 Hz vs 45-120 Hz for mice, consistent with the 30-55 Hz vs 45-120 Hz bands found in rats) that originate from separate parts of the brain. The slow gamma waves in the CA1 region of the hippocampus were synchronized with slow gamma waves in CA3, while the fast gamma in CA1 were synchronized with fast gamma waves in the entorhinal cortex.

The two signals became increasingly separated with increasing speed, because the two bands were differentially affected by speed. While the slow waves increased linearly, the fast waves increased logarithmically. This differential effect could have to do with mechanisms in the source regions (CA3 and the medial entorhinal cortex, respectively), or to mechanisms in the different regions in CA1 where the inputs terminate (the waves coming from CA3 and the entorhinal cortex enter CA1 in different places).

In the hippocampus, gamma waves are known to interact with theta waves. Further analysis of the data revealed that the effects of speed on gamma rhythm only occurred within a narrow range of theta phases — but this ‘preferred’ theta phase also changed with running speed, more so for the slow gamma waves than the fast gamma waves (which is not inconsistent with the fact that slow gamma waves are more affected by running speed than fast gamma waves). Thus, while slow and fast gamma rhythms preferred similar phases of theta at low speeds, the two rhythms became increasingly phase-separated with increasing running speed.

What’s all this mean? Previous research has shown that if inputs from CA3 and the entorhinal cortex enter CA1 at the same time, the kind of long-term changes at the synapses that bring about learning are stronger and more likely in CA1. So at low speeds, synchronous inputs from CA3 and the entorhinal cortex at similar theta phases make them more effective at activating CA1 and inducing learning. But the faster you move, the more quickly you need to process information. The stronger gamma waves may help you do that. Moreover, the theta phase separation of slow and fast gamma that increases with running speed means that activity in CA3 (slow gamma source) increasingly anticipates activity in the medial entorhinal cortex (fast gamma source).

What does this mean at the practical level? Well at this point it can only be speculation that moving / exercising can affect learning and attention, but I personally am taking this on board. Most of us think better when we walk. This suggests that if you’re having trouble focusing and don’t have time for that, maybe walking down the hall or even jogging on the spot will help bring your brain cells into order!

Pushing speculation even further, I note that meditation by expert meditators has been associated with changes in gamma and theta rhythms. And in an intriguing comparison of the effect of spoken versus sung presentation on learning and remembering word lists, the group that sang showed greater coherence in both gamma and theta rhythms (in the frontal lobes, admittedly, but they weren’t looking elsewhere).

So, while we’re a long way from pinning any of this down, it may be that all of these — movement, meditation, music — can be useful in synchronizing your brain rhythms in a way that helps attention and learning. This exciting discovery will hopefully be the start of an exploration of these possibilities.

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Theta brainwaves improve remembering

September, 2011

New research suggests that successful retrieval depends not only on retrieval cues, but also on your preceding brain state.

What governs whether or not you’ll retrieve a memory? I’ve talked about the importance of retrieval cues, of the match between the cue and the memory code you’re trying to retrieve, of the strength of the connections leading to the code. But these all have to do with the memory code.

Theta brainwaves, in the hippocampus especially, have been shown to be particularly important in memory function. It has been suggested that theta waves before an item is presented for processing lead to better encoding. Now a new study reveals that, when volunteers had to memorize words with a related context, they were better at later remembering the context of the word if high theta waves were evident in their brains immediately before being prompted to remember the item.

In the study, 17 students made pleasantness or animacy judgments about a series of words. Shortly afterwards, they were presented with both new and studied words, and asked to indicate whether the word was old or new, and if old, whether the word had been encountered in the context of “pleasant” or “alive”. Each trial began with a 1000 ms presentation of a simple mark for the student to focus on. Theta activity during this fixation period correlated with successful retrieval of the episodic memory relating to that item, and larger theta waves were associated with better source memory accuracy (memory for the context).

Theta activity has not been found to be particularly associated with greater attention (the reverse, if anything). It seems more likely that theta activity reflects a state of mind that is oriented toward evaluating retrieval cues (“retrieval mode”), or that it reflects reinstatement of the contextual state employed during study.

The researchers are currently investigating whether you can deliberately put your brain into a better state for memory recall.

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[2333] Addante, R. J., Watrous A. J., Yonelinas A. P., Ekstrom A. D., & Ranganath C.
(2011).  Prestimulus theta activity predicts correct source memory retrieval.
Proceedings of the National Academy of Sciences. 108(26), 10702 - 10707.

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Mindfulness meditation may help attention through better control of alpha rhythms

May, 2011

New research suggests that meditation can improve your ability to control alpha brainwaves, thus helping you block out distraction.

As I’ve discussed on many occasions, a critical part of attention (and working memory capacity) is being able to ignore distraction. There has been growing evidence that mindfulness meditation training helps develop attentional control. Now a new study helps fill out the picture of why it might do so.

The alpha rhythm is particularly active in neurons that process sensory information. When you expect a touch, sight or sound, the focusing of attention toward the expected stimulus induces a lower alpha wave height in neurons that would handle the expected sensation, making them more receptive to that information. At the same time the height of the alpha wave in neurons that would handle irrelevant or distracting information increases, making those cells less receptive to that information. In other words, alpha rhythm helps screen out distractions.

In this study, six participants who completed an eight-week mindfulness meditation program (MBSR) were found to generate larger alpha waves, and generate them faster, than the six in the control group. Alpha wave activity in the somatosensory cortex was measured while participants directed their attention to either their left hand or foot. This was done on three occasions: before training, at three weeks of the program, and after the program.

The MBSR program involves an initial two-and-a-half-hour training session, followed by daily 45-minute meditation sessions guided by a CD recording. The program is focused on training participants first to pay close attention to body sensations, then to focus on body sensations in a specific area, then being able to disengage and shifting the focus to another body area.

Apart from helping us understand why mindfulness meditation training seems to improve attention, the findings may also explain why this meditation can help sufferers of chronic pain.

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Brain implant reveals the neural patterns of attention

February, 2010

A paralyzed patient implanted with a brain-computer interface device has allowed scientists to determine the relationship between brain waves and attention.

A paralyzed patient implanted with a brain-computer interface device has allowed scientists to determine the relationship between brain waves and attention. Recordings found a characteristic pattern of activity as the subject paid close attention to the task. High-frequency beta oscillations increased in strength as the subject waited for the relevant instruction, with peaks of activity occurring just before each instructional cue. After receiving the relevant instruction and before the subject moved the cursor, the beta oscillation intensity fell dramatically to lower levels through the remaining, irrelevant instructions. On the other hand, the slower delta oscillation adjusted its frequency to mirror the timing of each instructional cue. The authors suggest that this "internal metronome" function may help fine-tune beta oscillations, so that maximum attention is paid at the appropriate time.

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