Subverting and being subverted are different levels of competition

Collect the microprobabilities of quantum and accumulate them to become the network center node with high connectivity. Pen ~ fun ~ pavilion www.biquge.info

Information exchange is the foundation of the network.

Tags: Divide the hierarchy, simplicity, energy minimization balance; Extreme: focus, high differentiation of the network, to rise to the top, improve the irreplaceable degree, that is, to achieve the ultimate;Pain points: use the distribution of the network, grasp one end of the distribution function, and concentrate the customer group (love of love, hate of hate);**Silk thinking: natural index e is a use of quantum characteristics in limited resources to grab the maximum benefit of the multiple (the silk gets the world, Alipay), in essence, the waste of resources collected. Set the armpits into a fur;

Thinking is the premise of reading, and then there is the mode of reading. Reading ability is a selective expression of the brain, that is, a relatively independent module, and the next step is to explore the relationship between the structure and function of the nervous system

The accumulation of experience is like increasing the number of decimal places after a number, and when precise enough, it can be done at a point of a strictly 1m length, and the transformation of its measurement results can carry an infinite amount of information.

The construction of neural network structures is a physical prerequisite for brain functions such as memory. The construction of neural network connections is a new combination of networks, and its power is not 1+1, but increases exponentially as the number increases.

Levels are relatively independent modules, and the formation of patterns is the counterpart of this structure.

The brain is a network that is constantly combining, can show a certain adaptability to the environment, can form a certain pattern (when the number of repetitions is too much, the paths will merge), change the internal connection pattern according to external stimuli (using the plasticity of neurons), and the network structure according to multi-level coupling is the basis for the reflection of external information. At the same time, the characteristics of neural networks also determine our cognitive patterns of the external world, that is, we need to meet certain characteristics in order to be recognized, which in turn has a certain impact on the environment (the correlation between the evolution of culture and the structure of the human brain)

The education of the network structure is the formation of the connection pattern.

Brain activities such as reading are essentially external stimuli mapped to the human brain so that the internal network structure is patterned to activate or inhibit, and the expression of the network structure formed is a specific pattern, such as thinking, movement, emotional fluctuations, and so on. Reuse of neural networks.

Neural connections are basic one-dimensional structures, pathway formation is two-dimensional structures, pathway coupling is three-dimensional structures, module formation and module movement are high-dimensional structures, i.e., networks.

The neural network structure of the brain has no definite purpose, but may have relative patterns that allow it to adapt to the current environment. Any function is a pattern that has been developed after countless attempts, and the partitioning of the brain is a manifestation of the formation of relatively independent modules, but it is only a differentiation, not a special design. The web itself is its own creator.

There is a limit to the plasticity of the network, which is the inevitable convergence. The convergence range of hierarchical formation does not mean that it is limited, but that it is the optimal allocation of local resources. It is like the division of labor at the social level. At the same time, with the help of inter-level communication, we continue to expand the cognitive boundaries of the human population

If the distribution of these measures to minimize energy and optimize the allocation of resources makes the formation of equipotential irrational, the equipotential is the most primitive assumption, and it is time for us to move forward. The general structure conforms to the basic physiological structure of the human brain, and only a few parts can form new neural circuits, and it is the latter that determines the uniqueness of the individual

Genes do not evolve the ability to read, but they can determine the way neurons are connected, i.e., the underlying laws. Then the construction of the Euclidean system is to be expected. There are many steps to connect between different functions, and we can only ensure a high probability of connection between adjacent quantities, that is, a relatively large degree of correlation. You can't use recursion, because the correlation drops dramatically as the distance increases. For example, 80% to the power of 10 is 10. 7%。 Although the structure of the network makes attenuation not so simple, the speed is really fast.

As a resistance to change, memory, perhaps, is the source of civilization.

The intake of various stimuli may be a reshaping of neural networks, such as exercise, which can improve brain function to a certain extent

The formation of neural networks is closely related to the Fourier transform of signal processing: such as convolution, central limit law, Gaussian distribution

Exercise accelerates the communication of nerves, and our nerves aging is due to the increase in the average distance of nerve connections, when we form a certain resistance to changes through external movements, it can help to maintain normal thinking and avoid various cognitive disorders. In fact, the introduction of various stimuli and the mapping in the brain can play a similar role.

The resistance changes that can occur with muscle movement are the nerve stimulation that normally innervates muscle movement

Like the network structure of neurotransmitters such as endorphins, the coupling of brain neurotransmitters and the body's neurotransmitters such as thyroxine may have some local significance in the matrix formed by their concentration fluctuations

Do the basic connections between nerves follow the principle of use-in-and-out?

The balance between neurotransmitters is a response to various stimuli, and when certain influences are exerted by the outside world, the balance can only diffuse. Can the brain learn changes in the pattern of cell connections: there are specific brain regions

The reconstruction of the connection mode, the formation and diffusion of the balance mode, and the possibility of connection are improved

The connections of the synapses are the units of disease, like atoms, and their statistical level may have a certain property emergence, that is, the formation of patterns. This may be the mechanism of memory formation. The different modules can be considered as relatively independent levels, i.e., neural pathways. This is another level of basic units, and the different levels of traversal make the network structure formed, so as to express certain higher properties, such as various functions. That's the power of integration, and it takes extreme precision to match. This is the coupling of the structure, while the function is coupled to the mechanism of structure formation, that is, the formation of the structure is in accordance with the mechanism of natural selection. Function is the selective expression of structure, such as the flow of various ions. This is the connection of the internet. The coordination of functions and structure can make the overall structure of the network harmonious.

The substrate is the same, but the form of the network in which it is expressed is different (e.g., IQ differences between people)

The similarity between the levels, i.e., the holographic nature. This is the basis of prediction, but it is the probability that is predicted, and we can only see the expression of reality, which can only be observed on a relatively large scale

The structure and function of the brain are based on the different levels of expression of neural networks, and our thoughts, emotions, etc. are all selective expressions at different levels, which can continue to be subdivided.

Perception is the mapping of information from the outside world to the different structures of the internal neural network through frequencies (eigenvalues).

The operation of the network is a fractal dimension, the efficiency is relatively high, and at the same time, the energy consumption is 2%, and the mass needs 20% of the blood

The role of nerves is to construct logical systems, and the overall expression of nerves in different situations has its intrinsic properties

Specialization, which is a division of labor, is also the result of the overall expression of the network, which is both a cause and a result, and is a dynamic structure formed in a loop like feedback; corresponding, the convergence radius of processing, how large the region corresponds to how much function, there is a center bias, and the more important the function corresponds to the larger the region (Matthew effect), there is a power-law distribution function

The network uses the wave function to process the intrinsic features, and its frequency and intensity echo the different parts and levels of the body's neural network, and the excited nerves form a new network, and its intrinsic is a certain sensation and so on. There is a transmission of information between the echoes of the network, which is collected through information from different sensory cells

The network is a coupling of different levels, i.e., periods, which can be decomposed using Fourier series, and the time domain becomes the frequency domain

The overall movement of the MRI is strengthened and coupled with an increase in temperature and blood flow

Chimerism, the structural basis of the selective expression of the environment, and the different levels of chimerism are partial differentiation of different variables

The final generation of patterns, such as language and culture, is adapted to different environments, which is the optimal solution. Language can also be used as a level of neural networks, and it is also a network structure, which can evolve continuously (regarded as iterative), and the current stage of language is the distribution of optimized solutions and differential solutions, which is the result of probability collapse. The foxp2 gene is an eigen, derived from the median value theorem.

The existence of viable mutilated individuals suggests a certain degree of independence at the level

The individual differences between males and females are the result of the selective expression of the selective expression of the topological deformation of the network such as organs, nerves, muscles, etc., which are the expression of neural network structures of different parts and different intensities

Probabilistic Networks: Probability Theory, Information Theory, Self-Organization, Hierarchical Coupling (Fourier Series), Network Society, Chaos

The coupling of cycles, followed by a certain screening, selectively expresses from chaos (probability library) to a certain new cycle

Synergy, hierarchical similarity

Distribution function, eigenis is the property of the matrix, the central limit theorem, the law of large numbers, the principle of fixed points

1 The irreversible direction is an intrinsic of the network, which is essentially a sublayer of a larger structure

2. The linear solution of a differential equation and its period

The essence of interaction is the field, which is like a coupling of Taiji diagrams, with the basic units of mutual transformation

Gauss's theorem and the loop theorem

Mapping of data, patterns emerging through the statistical results of big data

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