A new study recently published in the "eLife" magazine is a new type of computer "brain circuit" or artificial neural network that can reflect the decision-making process of the human brain and reveal the changes in circuits in patients with mental illness. Has been developed. This model reveals the underlying mechanism of schizophrenia, which leads to impaired decision-making, which is a decrease in the activity of molecules called NDMA receptors in the brain. These results provide references for the development of future treatments for neuropsychiatric diseases. The main challenge of psychiatric research is how to link changes in brain synapses to the cognitive processes that lead to schizophrenia and other diseases. Dr. Sean Cabana explained. "The computational model of the brain circuit can fill these gaps. By modifying the circuit model at the synaptic level, experiments can be used to predict and test neural activity and behavior."
The team decided to build a model that can simulate brain behavior. The types of decisions they are interested in include merging multiple pieces of information. For example, when deciding where to go on vacation, you need to combine information about many factors, such as cost, weather, and cultural experience. Initially, the team wanted to know whether the computer model showed the same decision-making bias that healthy people showed in this choice. This is called "dispersion deviation". This explains that humans tend to choose more evidence.
Researchers first set up two Makaku decision-making tasks and recorded their behavior patterns. Two series are shown on the monkey. There are eight bar graphs in each series, and one bar graph on each side of the computer screen, and I have to determine which side has the higher average height. The monkey makes decisions based on approximately 30,000 sets of information. Researchers have studied the impact of timing and variability of evidence on monkey selection. They found that monkeys, like humans, generally prefer options with more evidence.
In order to study the brain processes that form the basis of this preference, the team built a computer-based circuit model. The model contains two groups of excitatory nerve cells assigned to the right option or the left option. The two groups of neurons are also related to inhibitory neurons, which counteract and balance the activity of excitatory neurons. The researchers then tested the circuit with the same decision-making task, and the results showed that the circuit can reproduce the same biases that monkeys use to make decisions (and the biases that humans use). To understand how these decision-making processes affect neuropsychiatric diseases such as schizophrenia, the research team discovered the activity of synaptic NMDA receptors that connect each group of excitatory and inhibitory neurons. Reduced. They found that the decision-making performance of the model depends on the balance between excitement and inhibition, and the balance is affected by the relative changes in the NDMA receptors of the two groups of neurons. Ketamine is known to block NDMA receptors and may temporarily reappear many symptoms of schizophrenia in healthy individuals. To test whether the model’s predictions are consistent with changes in behavior, the research team studied the effect of ketamine on monkeys’ decision-making. Ketamin reduced the accuracy of monkey decisions, but retained the same forward bias. In the computer model, this change in decision-making behavior is consistent with the change in neural activity. All in all, the changes in decision-making behavior in schizophrenia and other diseases may be due to the decreased activity of NMDA receptors present in excitatory neurons. The research team hopes that this insight can pave the way for the development of new therapies.