Discover the learning mechanism of the brain

The image shows a nerve cell with a stem like a dendrite, each triangular shape touching the dendrite represents a synapse, where the input from other neurons called the thorns (scrawl shape). Further synapses in the dendritic plants of the cellular organism require a higher frequency of spikes (spikes come closer together in time) and electrical impulses to the rhythm of time at precise intervals to create maximum learning ability.

Our brain learns through changes in the power of synapses, which are connections between nerve cells, in response to stimulation.

Now, in a finding that challenges the common wisdom of the brain's learning mechanism, physicists working at UCLA, USA have discovered: a "rhythm " Optimal brain or frequency, has the effect of altering the power of synapses. And furthermore, like stations on radio frequency detectors, each synapse is adjusted to a different optimal frequency for learning.

These findings will provide a unified theory of mechanisms that underlie brain learning, which can lead to new treatments for the treatment of learning disabilities.

The results of this study will be published in Computational Neuroscience.

"Many people have learned and suffered from memory disorders, and beyond that group, most of us are not geniuses like Einstein or Mozart," said leading author Mayank R. Mehta. of the article and is an associate professor in the Faculties: Neurology, Neurology, Physics and Astronomy, UCLA University. "Our work shows that some problems with learning and memory are caused by synapses, which are not adjusted to the appropriate frequency."

A change in the strength of a synapse in response to stimulation known as synaptic plasticity is caused through the so-called "string of thorns" , a series of nerve signals that occur with frequency. different and time. Previous experiments demonstrated that when nerve cells are stimulated at a very high frequency (for example, 100 spikes per second), it will strengthen the synaptic synapses, while stimulating at low frequencies. then the power to stimulate synapses (for example, one of the branches per second) is reduced.

These experiments had previously used hundreds of continuous spikes in the very high frequency range to create ductility. However, when the brain is activated in real life behavior, nerve cells only have about 10 consecutive spikes, not a few hundred. And the researchers did so at a much lower frequency, usually within 50 spikes per second.

In other words, Mehta said: "The increase in the frequency of spikes, refers to how fast the spikes are transferred. 10 spikes can be transferred at a frequency of 100 spikes in 1 second or at the frequency of one spine per second ".

So far, researchers have not been able to conduct experiments at the level of natural simulation. But Mehta and co-author Arvind Kumar, an intern and former colleague, worked in Mehta's lab, were able to obtain measurements for the first time using a complex mathematical model that they develop and validate with test data.

Contrary to previous assumptions, Mehta and Kumar found that if it comes to stimulating synapses with naturally occurring spine models, stimulating nerve cells at the highest frequencies is not The best way to enhance synaptic strength.

For example, a synapse is stimulated with only 10 mutations at a frequency of 30 spikes per second, it causes a much greater strength increase than synaptic stimulation with 10 spikes at a frequency of 100 spikes per second.

"Expectations, based on previous research, if you regulate synapses at a higher frequency, effective for strengthening synapses, or learning, will be the best, when the frequency is low. more natural, " Mehta said. "To our surprise, we found that exceeding the optimal frequency, strengthening synapses actually rejects higher frequencies."

The knowledge that a synapse has a preferred frequency for maximum learning that researchers compare the optimal frequency based on the location of synapses on a neuron. Neurons are shaped like woods, with the base nuclei being plants, tree branches like large branches and synapses like leaves on branches.

When Mehta and Kumar compared learning-based synapses where synapses were placed in dendritic branches (branches), what they found was important: optimal frequency to attract learning of joints nervous, depending on where the synapses lie. Far from synapses is from the cell body of the nerve cell, higher than its optimal frequency.

Mehta said: "Amazingly, when it comes to learning, neurons act like a giant antenna, with different branches (branches) of tree branches adjusting different frequencies for maximum learning ".

The researchers found that not only each synapse has a preferred frequency to achieve optimal learning, but also for the best learning efficiency, this frequency needs to be completely in rhythm with time at exact time intervals. Even at the optimal frequency, if not according to the rhythm that was emitted, synapse learning is significantly reduced. Their research also shows that once a synapse is learning, it needs to change its optimal frequency. In other words, if the optimal frequency for a naive synapse - one of the synapses has not yet learned anything that says: 30 spikes in a second, after learning, the same synapse will learn optimally at a lower frequency, saying: only 24 spikes per second So learning itself changes the optimal frequency for a synapse.

This learning is due to the "deviation" process that is important for the treatment of disorders associated with forgetful symptoms, such as post-traumatic stress disorder, the researchers said.

Although more research is needed, current results suggest that: many drugs can be developed to " up " the brain rhythm of people with learning disorders or memory, or that many of us can become Einstein or Mozart if the optimal brain rhythm has been assigned to each synapse.

Mehta said: "We already know there are drugs and electrical stimuli that can change the brain rhythm."

"Our findings suggest we can use these tools to provide optimal brain rhythms to target connectivity to enhance learning ability."

Funding for this study is provided by the National Science Foundation, the National Institutes of Health, the Whitehall Foundation, and the WM Keck Foundation. The authors report no conflict of interest.