(ORDO NEWS) — The mouse brain is a neural network, the human brain is also a neural network of approximately the same neurons, it is just 1000 times larger.
But this is only a quantitative difference, and we know very well that the human brain is capable of solving qualitatively different tasks.
Neuroscientists from the Institute for Brain Research. Max Planck, Frankfurt for the first time experimentally showed how the human brain is fundamentally different from the mouse brain.
The human brain is very similar to the brain of a mouse, why does a person think differently?
At first glance, the mouse brain and the human brain are surprisingly similar: the nerve cells that make up our brain are almost the same, the molecular mechanisms of electrical excitation are practically the same, and many of the biophysical phenomena found in mice are quite applicable to the human brain.
Moritz Helmstedter, director of the research center. Institute for Brain Research. Max Planck (Frankfurt), who led the new study, published in the journal Science, talks about the obvious difference between the human brain and the mouse brain: “First of all, our brain contains 1000 times more nerve cells, which allows us to play chess and write children’s books, something mice don’t seem to be able to do.”
But size doesn’t explain much. At the very least, the mechanisms that allow a person to play chess, and which the mouse does not, remain incomprehensible.
The scientists took fragments of the human cortex, which surgeons took from patients during biopsy, and fragments of the mouse cortex and compared them under an electron microscope.
Analyzing neural networks in mice and humans, scientists have compiled a complete map of their connectomes, that is, interneuronal connections. What they saw was astonishing: they discovered a new type of neural network in the human cortex that is virtually absent in mice. It is a neural network that relies on numerous connections between inhibitory interneurons (or interneurons).
What are neurons
All neurons can be very roughly divided into two types – neurons that interact with the external environment, for example, sensory or motor neurons, and neurons that interact only with other neurons, that is, they perform internal work. Such neurons are called interneurons or interneurons.
Intercalary neurons are also of two types – excitatory and inhibitory. Exciters usually release the neurotransmitter glutamate into the synaptic cleft – and then the neuron that receives glutamate is excited and ready to transmit the signal further along the neural network.
Inhibitory neurons typically release the neurotransmitter GABA, and then the neuron that receives it “goes out” and does not transmit anything further. So, there were incomparably more inhibitory neurons in the human brain than in the mouse brain (relative to the total number).
But there are about the same number of active neurons working with the external environment in both mice and humans (also relative to the total number). It turns out that a person is some kind of complete brake! The brain seems to deliberately slow down a person’s reactions to external stimuli.
Why does a person need “neurobrakes”?
Helmstedter explains how inhibitory interneurons work: “They behave in a very peculiar way. They are very active, not to fire other neurons, but to silence them.
They are like kindergarten teachers or museum guards: their very laborious and energy-consuming activity is to keep others from getting excited. Now imagine a room full of museum guards gagging each other. This is what the human brain has developed!”
Why is this needed? There is a theory that such inhibitory networks can extend the time that recent events are stored in working memory before they are forgotten or stored in long-term memory, a kind of hard drive in our brains.
Helmstedter believes that a longer-term working memory helps to cope with more complex tasks and enhances reasoning abilities. But this is only one of the assumptions.
The scientist also draws attention to such points: “This can also be a consequence of pathological changes, and it must be studied in the context of neuropsychiatric disorders. Last but not least, none of today’s mainstream artificial intelligence methods use such inter-neural networks.”
It turns out that we are still not exactly the same as mice, artificial neural networks are not at all like us. But who would have thought that the main advantage of our brain is the ability to “slow down”.
And apparently, artificial neural networks will have to be taught this if we want them to solve problems comparable in complexity to those that a person solves.
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