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Recently, a technical result of the cooperation between Chinese and foreign researchers was published in the top journal of neurobiology, "Nature Neuroscienc.
Brain imaging technology is an important field in the development of neuroscience, which can directly observe the neurochemical changes of the brain during information processing and response to stimuli, thus providing an important reference for the diagnosis and treatment of diseas.
A real problem is that although there are large-scale human neuroscience datasets such as the UK Biobank, small-scale data samples of dozens to hundreds of people are still the norm when studying clinical populations or solving key neuroscience proble.
In the latest research results released this time, the researchers proposed for the first time to use meta-learning in the field of machine learning to solve the above proble.
Analyzing previous small samples of data, the researchers found an intrinsic correlation between an individual's representational characteristics, such as cognition, mental health, demographics and other health attributes, and brain imaging da.
At present, this new method has been evaluated on the datasets of the UK Biobank and the Human Connectome Project, and the evaluation results show that the new method reflects a higher accuracy rate than the traditional meth.
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