Ask a scientist what memory is, and you'll probably get long-term potentiation (LTP) as an answer.
To understand what LTP is, you need a little basic nerve cell (neuron) anatomy. Neurons have a nucleus and internal structures like other cells, but they also have fibrous projections called axons and dendrites. Axons carry messages (impulses—something like electrical charges) away from the cell body. Dendrites receive information from the axons of other neurons. But neurons do not touch, so nerve impulses must "jump the gap" from axon to dendrite. They do this chemically, by way of neurotransmitters that act as chemical messengers.
The axon of one neuron, a dendrite of another, and the gap between them are collectively called a synapse. LTP is the idea that synapses that are used often grow strong. That is learning. The action goes something like this: When a nerve impulse reaches the end of an axon, it triggers the release of a neurotransmitter into the gap of the synapse. When the neurotransmitter attaches to the dendrite of the next neuron, it starts an impulse in the second cell. If this happens many times, the signal is strengthened, maybe permanently. In this way, neurons become conditioned to respond strongly to signals they have received many times before.
LTP is a good explanation for the neural basis of learning, but researchers are constantly refining the idea. This week, UCLA neurophysicists report that there is an optimal brain "rhythm," or frequency, for changing synaptic strength. And further, like stations on a radio dial, each synapse is tuned to a different optimal frequency for learning.
Mayank R. Mehta and Arvind Kumar, researchers at UCLA, have found that stimulating neurons at high frequencies is not the best way to increase synaptic strength. For example, in these experiments, synapses stimulated with 10 impulses at a frequency of 30 per second achieved greater LTP than did synapses stimulated with the same number of impulses at a higher frequency (say, 100 per second). Thus, a synapse has a natural, preferred frequency for optimal learning.
That conclusion led the researchers to compare optimal frequencies based on the location of the synapse on a neuron. Mehta and Kumar found that the optimal frequency for inducing synaptic learning changed depending on where the synapse was located. The farther the synapse lay from the neuron's cell body, the higher its optimal frequency.
"Incredibly, when it comes to learning, the neuron behaves like a giant antenna, with different branches of dendrites tuned to different frequencies for maximal learning," Mehta said.
The researchers found that not only does each synapse have a preferred frequency for achieving optimal learning, but for the best effect, the frequency needs to be perfectly rhythmic—timed at exact intervals. Even at the optimal frequency, if the rhythm was thrown off, synaptic learning was substantially diminished.
Their research also showed that once a synapse learns, its optimal frequency changes. In other words, if the optimal frequency for a naïve synapse—one that has not learned anything yet—was 30 impulses per second, after learning, that very same synapse would learn optimally at a lower frequency, perhaps 24 per second. Thus, learning itself changes the optimal frequency for a synapse.
"Our work suggests that some problems with learning and memory are caused by synapses not being tuned to the right frequency," said Mehta. If that's true, the findings may lead to new therapies for treating learning disabilities. Perhaps drugs can be developed to "retune" the brain rhythms of people with learning or memory disorders. "We already know there are drugs and electrical stimuli that can alter brain rhythms," Mehta said. "Our findings suggest that we can use these tools to deliver the optimal brain rhythm to targeted connections to enhance learning."
Arvind Kumar and Mayank R. Mehta, Frequency-dependent changes in NMDAR-dependent synaptic plasticity. Frontiers in Computational Neuroscience, September 29, 2011.