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An exhaustive answer to this question (how the neuron works) has not yet been found. That is, of course, a lot is already known, but there is no complete understanding. And what I have written below is a very gross simplification.
As for the example of information , I think that the question is put very incorrectly. And if you answer head-on, then the neuron contains pieces of information about different parts of a phenomenon – in other words, the phenomenon is divided into parts(aspects, signs), and there is information about each part of this phenomenon. A piece is taken from each such information, and one piece from each part is added to one neuron. For this reason, each neuron separately stores something faceless, and only when they connect all these pieces in one rhythm (in one pulse), they can reflect certain properties of some phenomenon. For example, the response to light or the smell of food is decomposed into signs – light intensity, color, direction, maybe flicker frequency, polarization, etc. And about each of these signs” piece by piece ” is laid in each of the neurons (neurons can be duplicated many times in this case) belonging to the same network. This network should control, for example, a muscle, i.e. the movement of the body. And neurons reading information about light, or rather, each neuron will receive part of the information about the intensity of light, part about color, part about direction, and then, based on its memory, it will give out impulses… these impulses, combined with the impulses from the neighbors, will control a SINGLE movement of the muscle. From this we can say that the neuron stores in itself how to respond to those “pieces” that come to it from other receptors or neurons. And this determines the so-called gollographic nature of neural networks – each neuron stores pieces of information about EACH sign of a phenomenon.
Read about Fourier transforms. This is an analogy. But any first-year student can understand the Fourier transform. Understand the question of how the time-amplitude function is transformed into a frequency-amplitude function. And you will see that each point of the frequency-amplitude graph contains a fraction of information about EACH point of the time-amplitude graph.