-
Categories
-
Pharmaceutical Intermediates
-
Active Pharmaceutical Ingredients
-
Food Additives
- Industrial Coatings
- Agrochemicals
- Dyes and Pigments
- Surfactant
- Flavors and Fragrances
- Chemical Reagents
- Catalyst and Auxiliary
- Natural Products
- Inorganic Chemistry
-
Organic Chemistry
-
Biochemical Engineering
- Analytical Chemistry
- Cosmetic Ingredient
-
Pharmaceutical Intermediates
Promotion
ECHEMI Mall
Wholesale
Weekly Price
Exhibition
News
-
Trade Service
Life is a process of development of genetic result of genes and environment of mutual integration of various types of development.
In the process of human development, development, and decline, the human brain is always accompanied by the pruning of brain structure and the continuous reorganization of functions.
Not to mention the comparison between people with different family backgrounds or different educational backgrounds, even for people with the same high education, the individual differences in the aging process are extremely obvious, including various abilities such as exercise, mood, and memory (Figure 1).
For example, in the same 70-year-old group, some people can clearly derive mathematical formulas, and some people's logic and memory may have declined by more than half.
The quantitative measurement technology of brain cognition differences between individuals plays an important role in guiding individualized interventions such as individual development and aging process monitoring, clinical individualized precision treatment, and neuromodulation.
In the process of human development, development, and decline, the human brain is always accompanied by the pruning of brain structure and the continuous reorganization of functions.
Not to mention the comparison between people with different family backgrounds or different educational backgrounds, even for people with the same high education, the individual differences in the aging process are extremely obvious, including various abilities such as exercise, mood, and memory (Figure 1).
For example, in the same 70-year-old group, some people can clearly derive mathematical formulas, and some people's logic and memory may have declined by more than half.
The quantitative measurement technology of brain cognition differences between individuals plays an important role in guiding individualized interventions such as individual development and aging process monitoring, clinical individualized precision treatment, and neuromodulation.
In view of the above-mentioned individual different social phenomena in the process of human brain aging, can this individual difference be quantitatively described based on brain imaging data? What is the neural mechanism behind this type of individual difference? Dr.
Zuo Nianming from the Brain Network Group Research Center of the Institute of Automation, Chinese Academy of Sciences and his research team conducted research on the above-mentioned problems, using magnetic resonance imaging technology to explore the development of the human brain after adulthood and the individual difference patterns and changes in the aging process.
Laws, and discovered the relationship with cognitive function.
Zuo Nianming from the Brain Network Group Research Center of the Institute of Automation, Chinese Academy of Sciences and his research team conducted research on the above-mentioned problems, using magnetic resonance imaging technology to explore the development of the human brain after adulthood and the individual difference patterns and changes in the aging process.
Laws, and discovered the relationship with cognitive function.
Do individual differences in the aging process behave the same in different brain regions?
Based on a large data set of nearly 600 people (including multimodal magnetic resonance imaging and behavior measurement), combined with medical image processing and pattern recognition methods, the study found that functional connectivity features based on brain imaging can describe individuals who grow older with age The development trend of differences, but also found that the differences between different brain regions within individuals become smaller with age.
Comparing individual differences in different brain regions with age on the whole brain scale, the researchers further found that the primary cortex and the higher cortex have two different patterns of change: the individual differences in the higher cortex have always been at a high level, while the primary cortex has changed from adulthood.
The initial low level has been changing towards the trend of increasing individual differences (Figure 2).
This confirms that the primary need for human beings as a general animal brain to adapt to the environment is based on the basic adaptability to the environment (primary cortical function) such as vision and movement; individual differences between people are mainly manifested in advanced cognitive thinking functions (advanced) Cortical function), and this difference is reflected in the entire life cycle.
Comparing individual differences in different brain regions with age on the whole brain scale, the researchers further found that the primary cortex and the higher cortex have two different patterns of change: the individual differences in the higher cortex have always been at a high level, while the primary cortex has changed from adulthood.
The initial low level has been changing towards the trend of increasing individual differences (Figure 2).
This confirms that the primary need for human beings as a general animal brain to adapt to the environment is based on the basic adaptability to the environment (primary cortical function) such as vision and movement; individual differences between people are mainly manifested in advanced cognitive thinking functions (advanced) Cortical function), and this difference is reflected in the entire life cycle.
How does the functional connection of different anatomical distances affect individual differences?
In order to study the neural function basis of the above-mentioned individual differences, the researchers divided the functional areas of the whole brain into three types of anatomical distances according to short, medium and long, and studied the contribution of functional connections of different lengths and short anatomical distances to individual differences.
The study found that the functional connections of the three distances all contribute significantly to individual differences, but comparatively speaking, long-range connections contribute the most to the functional individual differences (p(z-test)<0.
005) (Figure 3).
Neuroscience generally believes that long-range connections can effectively integrate computing resources in different areas of the brain.
This kind of long-range connections increases significantly during the development of children; during the aging process, the study found that the changes in the above-mentioned long-range connections can best reflect the development of individual differences trend.
The study found that the functional connections of the three distances all contribute significantly to individual differences, but comparatively speaking, long-range connections contribute the most to the functional individual differences (p(z-test)<0.
005) (Figure 3).
Neuroscience generally believes that long-range connections can effectively integrate computing resources in different areas of the brain.
This kind of long-range connections increases significantly during the development of children; during the aging process, the study found that the changes in the above-mentioned long-range connections can best reflect the development of individual differences trend.
Can imaging calculations reflect individual differences in cognitive abilities?
Have the above findings based on brain imaging calculations been verified in cognitive behavior? In order to answer this question, the researchers further used the most conventional motor function (including strength perception, exercise plan synthesis, etc.
) evaluation to demonstrate the imaging findings.
The results confirmed that cognitive function (exercise ability) increases with age and individual differences increase; this individual difference is significantly related to individual differences in imaging expression (Figure 4).
This shows that the above-mentioned findings based on brain imaging are consistent with cognitive behavioral capabilities.
) evaluation to demonstrate the imaging findings.
The results confirmed that cognitive function (exercise ability) increases with age and individual differences increase; this individual difference is significantly related to individual differences in imaging expression (Figure 4).
This shows that the above-mentioned findings based on brain imaging are consistent with cognitive behavioral capabilities.
The research provides a quantitative calculation and neuroscience explanation based on brain imaging for the phenomenon that individual differences increase with age, and will provide a neuroscience basis for individualized education, individualized diagnosis and treatment of clinical diseases, and neuromodulation intervention.
Physically-based neuromodulation technologies (such as transcranial electrical stimulation, etc.
) can quantitatively regulate the neural activity of the target area, opening up a new way to study the neural activity of the brain, the mechanism of disease, and the neural basis of cognitive intelligence.
However, this technology is in clinical practice.
It has not yet been fully popularized, and the fundamental reason lies in the inconsistent efficacy caused by individual differences.
The above-mentioned calculation and measurement research on individual differences will promote the accurate clinical implementation of neuroregulation from various aspects such as the formulation of regulation plans and the evaluation of curative effects.
Physically-based neuromodulation technologies (such as transcranial electrical stimulation, etc.
) can quantitatively regulate the neural activity of the target area, opening up a new way to study the neural activity of the brain, the mechanism of disease, and the neural basis of cognitive intelligence.
However, this technology is in clinical practice.
It has not yet been fully popularized, and the fundamental reason lies in the inconsistent efficacy caused by individual differences.
The above-mentioned calculation and measurement research on individual differences will promote the accurate clinical implementation of neuroregulation from various aspects such as the formulation of regulation plans and the evaluation of curative effects.
Related research results were published online on Cerebral Cortex, and the research work was supported by the National Natural Science Foundation of China and the Beijing Brain Project.
(Bioon.
com)
(Bioon.
com)
Life is a process of development of genetic result of genes and environment of mutual integration of various types of development.
In the process of human development, development, and decline, the human brain is always accompanied by the pruning of brain structure and the continuous reorganization of functions.
Not to mention the comparison between people with different family backgrounds or different educational backgrounds, even for people with the same high education, the individual differences in the aging process are extremely obvious, including various abilities such as exercise, mood, and memory (Figure 1).
For example, in the same 70-year-old group, some people can clearly derive mathematical formulas, and some people's logic and memory may have declined by more than half.
The quantitative measurement technology of brain cognition differences between individuals plays an important role in guiding individualized interventions such as individual development and aging process monitoring, clinical individualized precision treatment, and neuromodulation.
GeneticIn the process of human development, development, and decline, the human brain is always accompanied by the pruning of brain structure and the continuous reorganization of functions.
Not to mention the comparison between people with different family backgrounds or different educational backgrounds, even for people with the same high education, the individual differences in the aging process are extremely obvious, including various abilities such as exercise, mood, and memory (Figure 1).
For example, in the same 70-year-old group, some people can clearly derive mathematical formulas, and some people's logic and memory may have declined by more than half.
The quantitative measurement technology of brain cognition differences between individuals plays an important role in guiding individualized interventions such as individual development and aging process monitoring, clinical individualized precision treatment, and neuromodulation.
In view of the above-mentioned individual different social phenomena in the process of human brain aging, can this individual difference be quantitatively described based on brain imaging data? What is the neural mechanism behind this type of individual difference? Dr.
Zuo Nianming from the Brain Network Group Research Center of the Institute of Automation, Chinese Academy of Sciences and his research team conducted research on the above-mentioned problems, using magnetic resonance imaging technology to explore the development of the human brain after adulthood and the individual difference patterns and changes in the aging process.
Laws, and discovered the relationship with cognitive function.
Zuo Nianming from the Brain Network Group Research Center of the Institute of Automation, Chinese Academy of Sciences and his research team conducted research on the above-mentioned problems, using magnetic resonance imaging technology to explore the development of the human brain after adulthood and the individual difference patterns and changes in the aging process.
Laws, and discovered the relationship with cognitive function.
Do individual differences in the aging process behave the same in different brain regions?
Based on a large data set of nearly 600 people (including multimodal magnetic resonance imaging and behavior measurement), combined with medical image processing and pattern recognition methods, the study found that functional connectivity features based on brain imaging can describe individuals who grow older with age The development trend of differences, but also found that the differences between different brain regions within individuals become smaller with age.
Comparing individual differences in different brain regions with age on the whole brain scale, the researchers further found that the primary cortex and the higher cortex have two different patterns of change: the individual differences in the higher cortex have always been at a high level, while the primary cortex has changed from adulthood.
The initial low level has been changing towards the trend of increasing individual differences (Figure 2).
This confirms that the primary need for human beings as a general animal brain to adapt to the environment is based on the basic adaptability to the environment (primary cortical function) such as vision and movement; individual differences between people are mainly manifested in advanced cognitive thinking functions (advanced) Cortical function), and this difference is reflected in the entire life cycle.
Big DataComparing individual differences in different brain regions with age on the whole brain scale, the researchers further found that the primary cortex and the higher cortex have two different patterns of change: the individual differences in the higher cortex have always been at a high level, while the primary cortex has changed from adulthood.
The initial low level has been changing towards the trend of increasing individual differences (Figure 2).
This confirms that the primary need for human beings as a general animal brain to adapt to the environment is based on the basic adaptability to the environment (primary cortical function) such as vision and movement; individual differences between people are mainly manifested in advanced cognitive thinking functions (advanced) Cortical function), and this difference is reflected in the entire life cycle.
How does the functional connection of different anatomical distances affect individual differences?
In order to study the neural function basis of the above-mentioned individual differences, the researchers divided the functional areas of the whole brain into three types of anatomical distances according to short, medium and long, and studied the contribution of functional connections of different lengths and short anatomical distances to individual differences.
The study found that the functional connections of the three distances all contribute significantly to individual differences, but comparatively speaking, long-range connections contribute the most to the functional individual differences (p(z-test)<0.
005) (Figure 3).
Neuroscience generally believes that long-range connections can effectively integrate computing resources in different areas of the brain.
This kind of long-range connections increases significantly during the development of children; during the aging process, the study found that the changes in the above-mentioned long-range connections can best reflect the development of individual differences trend.
The study found that the functional connections of the three distances all contribute significantly to individual differences, but comparatively speaking, long-range connections contribute the most to the functional individual differences (p(z-test)<0.
005) (Figure 3).
Neuroscience generally believes that long-range connections can effectively integrate computing resources in different areas of the brain.
This kind of long-range connections increases significantly during the development of children; during the aging process, the study found that the changes in the above-mentioned long-range connections can best reflect the development of individual differences trend.
Can imaging calculations reflect individual differences in cognitive abilities?
Have the above findings based on brain imaging calculations been verified in cognitive behavior? In order to answer this question, the researchers further used the most conventional motor function (including strength perception, exercise plan synthesis, etc.
) evaluation to demonstrate the imaging findings.
The results confirmed that cognitive function (exercise ability) increases with age and individual differences increase; this individual difference is significantly related to individual differences in imaging expression (Figure 4).
This shows that the above-mentioned findings based on brain imaging are consistent with cognitive behavioral capabilities.
) evaluation to demonstrate the imaging findings.
The results confirmed that cognitive function (exercise ability) increases with age and individual differences increase; this individual difference is significantly related to individual differences in imaging expression (Figure 4).
This shows that the above-mentioned findings based on brain imaging are consistent with cognitive behavioral capabilities.
The research provides a quantitative calculation and neuroscience explanation based on brain imaging for the phenomenon that individual differences increase with age, and will provide a neuroscience basis for individualized education, individualized diagnosis and treatment of clinical diseases, and neuromodulation intervention.
Physically-based neuromodulation technologies (such as transcranial electrical stimulation, etc.
) can quantitatively regulate the neural activity of the target area, opening up a new way to study the neural activity of the brain, the mechanism of disease, and the neural basis of cognitive intelligence.
However, this technology is in clinical practice.
It has not yet been fully popularized, and the fundamental reason lies in the inconsistent efficacy caused by individual differences.
The above-mentioned calculation and measurement research on individual differences will promote the accurate clinical implementation of neuroregulation from various aspects such as the formulation of regulation plans and the evaluation of curative effects.
Physically-based neuromodulation technologies (such as transcranial electrical stimulation, etc.
) can quantitatively regulate the neural activity of the target area, opening up a new way to study the neural activity of the brain, the mechanism of disease, and the neural basis of cognitive intelligence.
However, this technology is in clinical practice.
It has not yet been fully popularized, and the fundamental reason lies in the inconsistent efficacy caused by individual differences.
The above-mentioned calculation and measurement research on individual differences will promote the accurate clinical implementation of neuroregulation from various aspects such as the formulation of regulation plans and the evaluation of curative effects.
Related research results were published online on Cerebral Cortex, and the research work was supported by the National Natural Science Foundation of China and the Beijing Brain Project.
(Bioon.
com)
(Bioon.
com)
