Recent developments in neuroscience and brain-inspired artificial intelligence have opened up new possibilities in understanding intelligence. Now, a research team led by Tianzi Jiang at the Institute of Automation of the Chinese Academy of Sciences has outlined the key components and properties of an innovative platform called the Digital Twin Brain, which could bridge the gap between biological and artificial intelligence and provide new insights into both. This research was published Sept. 22 in Intelligent Computing, a Science Partner Journal.
Network structure is something that biological and artificial intelligence have in common. Since the brain consists of biological networks, a digital model or “twin” of the brain built using artificial networks would allow researchers to feed knowledge about biological intelligence into the model. The ultimate goal is to “propel the development of artificial general intelligence and facilitate precision mental healthcare,” a feat calling for joint efforts from interdisciplinary scientists worldwide.
Using the Digital Twin Brain, researchers could explore the working mechanisms of the human brain by simulating and modulating the brain in different states for various cognitive tasks. For example, they could simulate how the brain functions properly in a resting state and how it malfunctions in disorders, or develop methods to shift it away from an undesirable state by modulating its activity.
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