Neuroscientists have long pondered the mechanism behind learning and memory formation in the human brain. On the cellular level, it's generally agreed that we learn when stimuli are repeated frequently enough that our synapses - the gap-connections between neurons - respond and become stronger. Now, a team of UCLA neuro-physicists has discovered that this change in synaptic strength actually has an optimal "rhythm," or frequency, a finding that could one day lead to new strategies for treating learning disabilities.
"Many people have learning and memory disorders, and beyond that group, most of us are not Einstein or Mozart," said Mayank R. Mehta, one of the study's co-investigators. "Our work suggests that some problems with learning and memory are caused by synapses not being tuned to the right frequency."
The tendency for connections between neurons to grow stronger in response to repeated stimuli is known as synaptic plasticity. The series of signals one neuron gets from the others to which it's connected, dubbed "spike trains," arrive with variable frequencies and timing, and it's these trains that induce formation of stronger synapses- the very basis for "practice makes perfect."
In previous studies, it was shown that very high frequency neuronal stimulation (about 100 spikes per second) led to stronger connecting synapses, while stimulation at a much lower frequency (one spike per second) actually reduced synaptic strength. But real-life neurons, performing routine behavioral tasks, only fire 10 or so consecutive spikes, not hundreds, and they do this at a far lower frequency - around 50 spikes per second.
Achieving experimental spike rates that more closely approximate real life has proved rather elusive, however. Mehta explains one of the variables they encountered: "Spike frequency refers to how fast the spikes come. Ten spikes could be delivered at a frequency of 100 spikes a second or at a frequency of one spike per second."
But Mehta and his co-investigator, Arvind Kumar, didn't let that hurdle stop them. Instead, they worked out a complex mathematical model and validated it with actual data from their experiments. Now able to generate spike patterns closer to those that occur naturally, the team discovered that, contrary to their predictions, neuron stimulation at the highest frequencies wasn't the ideal way to bolster synaptic strength.
"The expectation, based on previous studies, was that if you drove the synapse at a higher frequency, the effect on synaptic strengthening, or learning, would be at least as good as, if not better than, the naturally occurring lower frequency," Mehta said. "To our surprise, we found that beyond the optimal frequency, synaptic strengthening actually declined as the frequencies got higher."
The realization that synapses have optimal frequencies for learning prompted Mehta and Kumar to determine whether synapse location on a neuron had any specific role. They discovered that the more distant the synapse was from the neuron's bulbous main body, the higher the frequency it required for optimal strengthening. "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 team also revealed that aside from having optimal frequencies at which maximal learning occurs, synapses also strengthen best when those frequencies are exactly-timed in perfect rhythms. Take away the beat, they found, and even with the ideal frequency, synaptic strengthening is appreciably compromised.
The image shows a neuron with a tree trunk-like dendrite. Each triangular shape touching the dendrite represents a synapse, where inputs from other neurons, called spikes, arrive (the squiggly shapes). Synapses that are further away on the dendritic tree from the cell body require a higher spike frequency (spikes that come closer together in time) and spikes that arrive with perfect timing to generate maximal learning (Image: UCLA Newsroom)
As if these remarkable revelations weren't enough, they also discovered that a synapse's optimal frequency changes once it learns. The researchers feel that understanding of this fundamental could yield insight into treatments for conditions related to memory dysfunction (or the need to forget), such as post-traumatic stress disorder.
With additional study, these findings could possibly lead to the development of new drugs capable of "re-calibrating" faulty brain rhythms in people with memory or learning 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."
The research paper entitled Frequency-dependent changes in NMDAR-dependent synaptic plasticity is available online at Frontiers in Computational Neuroscience.
Source: UCLA
