Start Date
14-12-2012 12:00 AM
Description
The integration of both neuroscience and psycho-physiological methods into Information Systems (IS) research in order to better understand how the brain operates in an IS-relevant context has gained importance. Articles highlighting the potential of NeuroIS have opened the discussion of methodological issues associated with the use of fMRI. NeuroIS research, however, must remain cognizant of the fact that the neural implementation of complex mental processes is based on activity in a network of varied brain areas. Against this background, the present article seeks to make a methodological contribution by introducing methods of connectivity analysis to IS research and by giving an overview of the basic principles. We describe different methods of connectivity analysis, discuss a concrete example, and show how connectivity analysis can inform IS research. The major objective of this paper is to contribute to a better understanding of advanced techniques for brain imaging data analysis.
Recommended Citation
Hubert, Marco; Linzmajer, Marc; Riedl, René; Kenning, Peter; and Hubert, Mirja, "Introducing Connectivity Analysis to NeuroIS Research" (2012). ICIS 2012 Proceedings. 9.
https://aisel.aisnet.org/icis2012/proceedings/ResearchMethods/9
Introducing Connectivity Analysis to NeuroIS Research
The integration of both neuroscience and psycho-physiological methods into Information Systems (IS) research in order to better understand how the brain operates in an IS-relevant context has gained importance. Articles highlighting the potential of NeuroIS have opened the discussion of methodological issues associated with the use of fMRI. NeuroIS research, however, must remain cognizant of the fact that the neural implementation of complex mental processes is based on activity in a network of varied brain areas. Against this background, the present article seeks to make a methodological contribution by introducing methods of connectivity analysis to IS research and by giving an overview of the basic principles. We describe different methods of connectivity analysis, discuss a concrete example, and show how connectivity analysis can inform IS research. The major objective of this paper is to contribute to a better understanding of advanced techniques for brain imaging data analysis.