The ability to manipulate complex networks requires full knowledge of the system. All complex networks work under this rule. And one of the most important complex neural networks is our nervous system.
Researchers are trying to make complex models of the work and interaction of our neurons in individual and entirety states for finding the point, where consciousness begins. We know that somewhere in our brain or nervous system is a key to consciousness but the question is, how deep and how small is the thing that makes our nervous system work as it works?
This information might be crucial when we are making new AI systems that are hybrid entireties between hardware and software. Those systems might use living neurons for thinking, or they use quantum computer platforms. And that means we must realize that if we make something wrong the system reaches consciousness. The neurons have a self-organized ability to learn things.
The new optical methods to make those models make it possible to see how our neurons operate. The system can use blood cells as arrays that transmit information forward.
"Complex-domain neural network empowers large-scale coherent imaging". Credit: Xuyang Chang" (ScitechDaily.com/Revolutionizing Optical Imaging With Complex-Domain Neural Networks)
Things like quantum mechanics give us the tools and models for modeling. How information scales across the brain and nervous system. Researchers took those models for that thing like from the free energy models. The idea is that the energy acts like information in our brains. The free energy model is simple.
Energy fills the space if it cannot go into some particles. The energy will not vanish, it just changes its form. In some dark energy models free energy known as dark energy forms when energy hits ball-shaped particles. When that energy falls in the middle of those particles it jumps back. And the spin of those particles is the thing that increases the energy level of that radiation.
An international team of researchers has discovered that the self-organization of neurons during learning aligns with the mathematical theory known as the free energy principle. (ScitechDaily.com/ Free Energy Principle Predicts Self-Organized Learning in Real Neurons)
Just like muscular cells require moving. Neurons require new things to handle. Like human feet made for moving. Neurons and brains are made for learning. If that model is right, we can make a decision. That neurons need to learn new things. So, just like in muscles, where muscle cells require motion and action, neurons require new things to learn to keep themselves in good shape and condition.
The experimental setup. Cultured neurons grew on top of electrodes. Patterns of electrical stimulation trained the neurons to reorganize so that they could distinguish two hidden sources. Waveforms at the bottom represent the spiking responses to a sensory stimulus (red line). Credit: RIKEN (ScitechDaily.com/ Free Energy Principle Predicts Self-Organized Learning in Real Neurons)
This means the mathematical models made for physics and quantum systems like quantum mechanics can use for modeling how information behaves in the brain and how the neurons interact. When neurons interact they must make a similar process with quantum entanglement.
They must adjust their energy levels so that information can travel between neurons. Also, neurotransmitters must load their information when they travel through synapsis. If the energy level of those neurotransmitters is too low neurons cannot receive that information.
Then we must ask what this thing makes with neurology. The answer is that the information or thoughts scale over our brain like energy travels in the universe. Most of our thoughts are hidden from our social network. But some of our thoughts are hidden from ourselves. So we can use dark energy and dark matter model to model consciousness and functions of the brain.
If we want to use the energy model for the thinking process we can make the next kind of decisions.
1) The visible matter is thoughts that we share with others.
2) Dark matter is thoughts that we don't share.
3) Dark energy is thoughts and visions that don't reach consciousness.
If we use energy as the model of thinking. We must realize, that information cannot ever vanish. Also, we must understand that the brain doesn't form information. Brains just connect memories and observations to the new entirety. That means brains are not creating information from nothingness. The brain just turns one form of information into another. So when brains are working with information or thinking shape of information changes when the brain connects observations with memories.
Only a small part of thoughts are shared with other people. Those thoughts that we tell are the same as visible material. Then dark matter of consciousness are things that we think, but what we don't share with other people. Those dark thoughts are things that we keep in our minds. And then finally dark energy of thoughts can be thoughts that ever come to consciousness. Those things are seen in dreams. We cannot remember what we saw during sleep time. That brain function is hidden from us. And maybe there are the things that make us humans.
https://scitechdaily.com/revolutionizing-optical-imaging-with-complex-domain-neural-networks/?expand_article=1
https://scitechdaily.com/free-energy-principle-predicts-self-organized-learning-in-real-neurons/?expand_article=1
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