Abstract
The human brain is a huge, complex system generating brain activity. The exploration of human brain function using functional magnetic resonance imaging (fMRI) is a promising method to understand brain activity. However, the complexity of the big data generated by fMRI facilitates the analysis of various levels of human brain activity, such as the distribution of neural representations, the interaction between different regions, and the dynamic interaction over time. These different levels can depict distinct prospects of the human brain activity, and considerable progress has been achieved. In the future, more big data analysis methods combining advances in computer science, including larger-scale computing, machine learning, and graph theory, will promote the understanding of the human brain.
| Original language | English |
|---|---|
| Pages (from-to) | 5059-5065 |
| Number of pages | 7 |
| Journal | Chinese Science Bulletin |
| Volume | 59 |
| Issue number | 35 |
| DOIs | |
| Publication status | Published - Dec 2014 |
| Externally published | Yes |
Keywords
- Big data
- Functional magnetic resonance imaging (fMRI)
- Human brain
- Neural interaction
- Neural representation
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