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Xinzhiyuan Report Editor: David [Xinzhiyuan Guide] The decision-making of humans and animals cannot be separated from the brain, and the brain's decision-making relies on "value information"
.
A new study reveals the detailed mechanism of such key information update and coding.
Experiments show that they are compiled into a resource library, which can be stored for a long time and be recalled for a long time
.
Each of us has to make a lot of decisions throughout our lives, ranging from "what to eat tonight", "where to go to play tomorrow on vacation", to "how to fight this battle" and "how to make this law
.
"
The results of these decisions must be determined by the decision-maker’s brain
.
Therefore, the key areas in the brain responsible for such "rules" have become the focus of attention of scientists
.
In 2019, researchers at the University of California, San Diego discovered areas of the brain that make “value decisions”
.
They discovered that this area is called the posterior splenic cortex (RSC) and is used to make "valuable choices", such as deciding which restaurant to eat tonight
.
Then, update the RSC with the latest information based on new impressions of the level of preference for the food tonight
.
After all, only by updating information in a timely manner can the brain make the most correct decision
.
Now, the team has made new progress on this issue
.
New research led by postdoctoral fellows Ryoma Hattori and Professor Takaki Komiyama in the Department of Biological Sciences at the school revealed the detailed mechanism of the brain's processing of such dynamically updated information
.
The results of a paper published recently in the Neuron journal show that the updated information in the RSC can be stored persistently, just like a callable resource library
.
These "persistent information" can most effectively represent or "encode" valuable signals that can span different areas of the brain
.
To study how brain activity represents the details of value-based decision-making, the researchers set up reinforcement learning experiments
.
Value decision-making is a key mechanism of the human brain, which is often impaired in neurological diseases such as schizophrenia, dementia, and addiction
.
In the experiment, the researcher mouse provided multiple options, rewarded the mouse's choice with a certain probability, and recorded the corresponding brain activity during the reinforcement learning process
.
The resulting data and network simulations point to the importance of continuous coding in how to represent rats and their value determination, and RSC as the link in this activity
.
The researchers explained in the paper: "These results show that although the information encoding is highly distributed, not all information represented in neural activity can be used in every area
.
These results show that context-dependent persistent information , Which promotes reliable signal coding and expands the distribution of information in the brain
.
"Researchers have found that the persistence of information allows value signals to be encoded most efficiently in different areas of the brain, especially in the posterior spleen cortex
.
Image source: Research team member of the Komiyama Laboratory at the University of California, San Diego, Hattori, one of the authors of the paper, said that as we all know, neurons will circulate in different patterns of activity, some neurons will surge in activity, while others will remain silent
.
Ryoma Hattori These brain activity patterns have been shown to be related to certain task-related information, such as value information for decision-making
.
As RSC plays a central role in connecting multiple brain networks and functions, this new discovery further strengthens the results of 2019
.
"We believe that in the mouse brain, RSC functions as a stable repository of value information.
When the mouse conducts intensive learning and decision-making, RSC will distribute the value information to other brain regions, which are essential for further processing of value signals.
.
"to further test their findings, Hattori and Komiyama used more than 100,000 mice decision-making" big data "repository they recorded during the experiment
.
Researchers programmed artificial intelligence (AI) networks to mimic the behavioral strategies in computer-based intensive experiments, and got results very similar to real-world experiments
.
Takaki Komiyama "When we train AI to do the same behavior, it uses the same strategy and the same way to represent the information in neural activity," Komiyama said.
"This shows that our findings are indeed the neural circuits that perform this behavior.
Selection strategy
.
This similarity between AI and mice is really interesting
.
"Reference: https://neurosciencenews.
com/value-decision-encoding-19695/https:// cell.
com/neuron/pdf/S0896-6273(21)00891-6.
pdf
.
A new study reveals the detailed mechanism of such key information update and coding.
Experiments show that they are compiled into a resource library, which can be stored for a long time and be recalled for a long time
.
Each of us has to make a lot of decisions throughout our lives, ranging from "what to eat tonight", "where to go to play tomorrow on vacation", to "how to fight this battle" and "how to make this law
.
"
The results of these decisions must be determined by the decision-maker’s brain
.
Therefore, the key areas in the brain responsible for such "rules" have become the focus of attention of scientists
.
In 2019, researchers at the University of California, San Diego discovered areas of the brain that make “value decisions”
.
They discovered that this area is called the posterior splenic cortex (RSC) and is used to make "valuable choices", such as deciding which restaurant to eat tonight
.
Then, update the RSC with the latest information based on new impressions of the level of preference for the food tonight
.
After all, only by updating information in a timely manner can the brain make the most correct decision
.
Now, the team has made new progress on this issue
.
New research led by postdoctoral fellows Ryoma Hattori and Professor Takaki Komiyama in the Department of Biological Sciences at the school revealed the detailed mechanism of the brain's processing of such dynamically updated information
.
The results of a paper published recently in the Neuron journal show that the updated information in the RSC can be stored persistently, just like a callable resource library
.
These "persistent information" can most effectively represent or "encode" valuable signals that can span different areas of the brain
.
To study how brain activity represents the details of value-based decision-making, the researchers set up reinforcement learning experiments
.
Value decision-making is a key mechanism of the human brain, which is often impaired in neurological diseases such as schizophrenia, dementia, and addiction
.
In the experiment, the researcher mouse provided multiple options, rewarded the mouse's choice with a certain probability, and recorded the corresponding brain activity during the reinforcement learning process
.
The resulting data and network simulations point to the importance of continuous coding in how to represent rats and their value determination, and RSC as the link in this activity
.
The researchers explained in the paper: "These results show that although the information encoding is highly distributed, not all information represented in neural activity can be used in every area
.
These results show that context-dependent persistent information , Which promotes reliable signal coding and expands the distribution of information in the brain
.
"Researchers have found that the persistence of information allows value signals to be encoded most efficiently in different areas of the brain, especially in the posterior spleen cortex
.
Image source: Research team member of the Komiyama Laboratory at the University of California, San Diego, Hattori, one of the authors of the paper, said that as we all know, neurons will circulate in different patterns of activity, some neurons will surge in activity, while others will remain silent
.
Ryoma Hattori These brain activity patterns have been shown to be related to certain task-related information, such as value information for decision-making
.
As RSC plays a central role in connecting multiple brain networks and functions, this new discovery further strengthens the results of 2019
.
"We believe that in the mouse brain, RSC functions as a stable repository of value information.
When the mouse conducts intensive learning and decision-making, RSC will distribute the value information to other brain regions, which are essential for further processing of value signals.
.
"to further test their findings, Hattori and Komiyama used more than 100,000 mice decision-making" big data "repository they recorded during the experiment
.
Researchers programmed artificial intelligence (AI) networks to mimic the behavioral strategies in computer-based intensive experiments, and got results very similar to real-world experiments
.
Takaki Komiyama "When we train AI to do the same behavior, it uses the same strategy and the same way to represent the information in neural activity," Komiyama said.
"This shows that our findings are indeed the neural circuits that perform this behavior.
Selection strategy
.
This similarity between AI and mice is really interesting
.
"Reference: https://neurosciencenews.
com/value-decision-encoding-19695/https:// cell.
com/neuron/pdf/S0896-6273(21)00891-6.
