WI'16 and BIH'16 Joint Panel on Connecting Network and Brain with Big Data
October 14, 12:00 to 14:00
Yong Shi (University of Nebraska at Omaha, Chinese Academy of Sciences) and Ning Zhong (Maebashi Institute of Technology, Beijing University of Technology)
- Giorgio Ascoli, George Mason University
- Butler Lampson, Microsoft & MIT
- Hanchuan Peng, Allen Institute for Brain Science
- Vijay Raghavan, University of Louisiana at Lafayette
- Ivan Soltesz, Stanford University
- Leslie Valiant, Harvard University
Issues to Be Discussed
Network, in particular WisdomWeb of Things (W2T) developed recently, provides a social-cyber-physical space for all human communications and activities, in which big data are used as a bridge to connect relevant aspects of humans, computers, and things. It is a trend to integrate brain big data and human behavior big data with knowledge graph in the social-cyber-physical space for realizing the harmonious symbiosis of humans, computers and things. The key questions to be discussed include:
- How to connect network and brain with big data?
- How to understand brain from neural microcircuits to macroscale intelligence systems, supported by connecting network and brain with big data?
- How to realize human-level collective intelligence as a big data sharing mind – a harmonized collectivity of consciousness on the W2T by developing brain inspired intelligent technologies to provide wisdom services?
In the relation between the neuroscience and big-data, there are several interactions. Brain function/structure measurements generate big data in multi-scale, which could be used as open sources, and interconnected by information networks and knowledge graph. Social-media and sensor networks generate human behavior data in multi-modal, which is also big data. Both types of data offer the stimulus set for brain researches.
Since big data implicitly includes ensemble behavioral data of people in the social-cyber-physical space, the rules or structures of human behaviors can be extracted from them, which may reflect human brain functions. Behavior of complex dynamic systems has so extensively been studied in mathematics, biology, and complex system sciences, that combination of these studies to big data has provided some important insights of ensemble behavior of people. For neuroscience and cognitive science, thus, utilization of the big data as stimulus sets has now provided new ways to better understanding of human brain structure, functions and mechanisms in multi-scale.