Brain link mining system based on document analysis and functional nuclear magnetic resonance imaging analysis

Abstract

The invention relates to a brain link mining system and method based on document analysis and functional nuclear magnetic resonance imaging analysis, and belongs to the fields of computer technologies and cognitive neuroscience technologies. The system comprises a dynamic causal model module, an activation analysis module, a document link analysis module, a seeking sub-network module, a document database and a brain network link database. The method comprises the steps of firstly, by calculating the activated probabilities of all brain coordinates in all documents, figuring out the activated probabilities of corresponding anatomical areas to obtain activated brain areas, mining modes which frequently appear in the brain areas through the association rules algorithm, calculating confidence coefficients to obtain a trusted brain function network, establishing the corresponding documents to generate a brain network database, then collecting corresponding functional nuclear magnetic resonance imaging data by utilizing a functional nuclear magnetic resonance imaging system, and verifying the actual link direction and weight numbers of a network edge by utilizing the dynamic causal model module. In this way, the problem that calculating is overlong in time and low in accuracy in the brain link analysis process is solved.

Description

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AI Technical Summary

Benefits of technology

This patented method helps analyze past data on how well different parts or individuals have interacted with each other during their lifetime. By identifying which connections occur most frequently at specific points within these segments, we aim to improve our understanding about complex systems like biological networks.

Problems solved by technology

Technological Problem addressed in this patented technical problem described in the patents describes how to efficiently study neural activity within neurons during learning processes related to memory systems. Existing techniques involve analyzing behavior patterns over multiple locations called hypotheses, but they only provide limited insight about what happens inside the brain itself. However, we found out that previous attempts were either unsuccessful or resulted in incorrect inferences made. Additionally, conventional approaches require extensive training sessions involving trial design and testing, leading to long waiting periods before final conclusions drawn up.

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