The classical picture of the neurons in the brain was wrong
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The Human brain contains about 86 billion neurons. Each of these neurons connect with other cells, forming trillions of connections. The place of contact of two neurons or a neuron and a signal-receiving cells is called the synapse. Through these synapses to transmit nerve impulses.
The Science of all this has been known for a long time. Scientists over a hundred years ago found that each neuron works as a Central excited element. Inside it is first accumulate incoming electrical signals, and then, when they reach a certain threshold, the neuron generates and sends a short electrical pulse into numerous branches – the dendrites. Their ends are membranous appendages – spines. With these spines and sends a pulse. When the spines of one neuron are connected with the spines of the other, forming a synapse. But this is only one type of contact. Synapses are also formed by the contact themselves dendrites and bodies of neurons.
However a new study conducted by Israeli experts from the University of Bar-Ilan and published scientific journal nature, debunks the classical view of the neuron.
In 1907, the French neuroscientist Louis Lapik suggested a model in which the voltage in the dendritic spines of neurons increases the accumulation of electrical signals. When you reach a certain high, the neuron responds with a burst of activity, then the voltage is reset. It also meant that if a neuron has not yet "collected" a strong enough electrical signal, it will not send the impulse.
The next hundred years, neuroscientists have studied the brain cells, based on this model. However, in the framework of new types of experiments scientists have proved that Lapik was wrong.
the Old scheme of neurons as excitable units total (left image) and with sensitivity the right, left and bottom (right image)
The Researchers found that each neuron operates not as a collection of excitable elements. In fact, its dendritic spines can act differently. Roughly speaking, the "left" and "right" dendrites do not wait for accumulation of signals in order to summarize them and to generate momentum. On the contrary, each of them works in the opposite direction, creating a completely different impulses.
"We came to this conclusion using a new experimental set-up, but, in principle, these results could be detected using technologies that existed since the 1980-ies. Faith in scientific discovery a hundred years ago led to this delay," says the head of works Professor IDO Kanter.
The Researchers decided to study the nature of the neural impulse is a spike of electrical activity. In one experiment on a neuron with the different parties, and applied electric current, and in another experiment, the researchers used the effect of multiple input signals.
The Obtained results indicate that the direction of the received signal can significantly affect the response of the neuron. For example, a weak signal "left" and a weak signal right neuron does not total and does not respond pulse. However, if one of the parties received a more powerful signal, even he can start the reaction of a neuron.
According to canter, it is necessary to abandon traditional ideas and re-examine the functionality of brain cells. First and foremost it is extremely important for understanding the nature of neurodegenerative diseases. Perhaps the neurons that are not able to differentiate "left" and "right" can be the starting point for the identification of the origin of these diseases.
New experiments also questioned the method of "sorting spines" are used by hundreds of research groups around the world. Method helps measure activity from many neurons, but, like others, is based on the assumptions that, perhaps, will soon be officially deprecated.
However the priority for neuroscientists has been to understand how neurons are "sorting" incoming signals and on the basis of this form your "opinion". In addition, the authors note that they conducted experiments with only one type of nerve cells called pyramidal neurons. Although they are also pear-shaped, stellate, granular, irregular and spindle-shaped.
In Addition to medical applications, the discovery could bear significant benefits in terms of the scope of development of more sophisticated artificial neural networks, the researchers say.
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