The spontaneous emission in the human brain at the time of sleeping or without any input stimulus or sensory input indicates the presence of noise in it. Many researches show, the adding of noise enhances biological signals such as ECG and EEG to detect on a device. However, in simulation-based recognition, quality assessment, or perception of sensory signals system, the performance starts to decrease with an increase of noise level. Now, the question is, how the human brain is so robust to various conditions for the above mentioned tasks? Does noise really enhance the brain works? If yes, how?
I do not understand human physiology, but I have experience in creating and training artificial neural networks. Your question interested me, so I will allow myself to make an assumption. Maybe the noise allows the weights to have some variation? That is, thanks to him, the human neural network is not оverfitting.
There is quite a lot in your question, so I'm going to break it into sections. First is your comment regarding noise: "The spontaneous emission in the human brain at the time of sleeping or without any input stimulus or sensory input indicates the presence of noise in it "
This is an incorrect assumption; the brain activity observed during sleep, may in part be spontaneous (K-complexes/sleep spindles), but it is also still related to stimuli processing, both internal and external, as these processes still occur.
Your next line ("Many researches show, the adding of noise enhances biological signals such as ECG and EEG to detect on a device.") seemingly refers to the idea of Stochastic resonance, which is really just a manipulation of the summative properties of waves, and a very specific/selective inclusion of noise.
Finally, you asked "How the human brain is so robust to various conditions for the above mentioned tasks? Does noise really enhance the brain works? If yes, how?" The first question is enormously broad and high level, it's akin to asking how the human brain is able to process both visual and aural signals. It can be somewhat answered by the idea of function specific neural systems, but it's fair more complex and less well understood than that. As for the second part, it is somewhat debatable; there has been some recent work from Brad Voytek's group arguing the neural value of noise, and the role it may play as reset switches amongst other functions, and that may be a good place for you to start.
Thanks Ty Lees for your explanation. If you would give me some references related to your explanation, I would learn more about those issues.
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