Non-invasive Brain Stimulation as a Set of Research Tools in NeuroIS: Opportunities and Methodological Considerations

Laurence Dumont, Sofia El Mouderrib, Hugo Théoret, Sylvain Sénécal, Pierre-Majorique Léger
2018 Communications of the Association for Information Systems  
NeuroIS is a growing field that builds on neuroscience to improve the understanding of human interaction with information technologies and information systems. One can investigate causal relationships between brain activity patterns, cognitive processes, and behavior in a non-invasive way via using non-invasive brain stimulation (NIBS) tools, but researchers in the neuroIS community have yet to do so. We introduce NIBS, show how it can address caveats found in current research, describe the
more » ... ementation of a NIBS protocol, and assess what these tools can bring to the neuroIS field. Communications of the Association for Information Systems 80 Volume 43 10.17705/1CAIS.04305 Paper 5 the second and first conditions for causality, the direction of the impact is clearer and points to a causal link. Third, no explanation should be able to explain the effect other than its presumed cause. Other variables could also influence A and B in a related or unrelated fashion and, thus, lead to a faulty impression of causality. Confounding variables, moderation, and mediation (among other factors) can cause one to mistake correlation for causation (Schlesselman, 1978) . Research based on self-reported measures has discussed the conditions under which it is reasonable to presume causality (Freedman, 2010) and has partially resolved this issue with analytical methods such as structural equation models (SEM) (Kline, 2015) or Granger causality analyses (Kostelecki, 2013) . However, the neuroIS field's young age means we need to bring forward statistical and design methods that will allow researchers to achieve stronger conclusions. Even if one fulfills all three conditions for causality, a causal relationship still may not exist. In situations where behavior follows brain activity (e.g., motor commands come from brain activity), it seems logical to infer causality. However, one needs to determine what is specific to a particular behavior and rule out unrelated activity that may occur simultaneously in the brain. While statistical and experimental design can improve the plausibility of a causal link, NIBS-induced changes in neuronal excitability or oscillatory activity allow experimental manipulations from which one can draw stronger conclusions on the links between brain activity and interactions with information systems. This type of manipulation also strengthens the plausibility of a causal link and helps validate associations between brain and behavior.
doi:10.17705/1cais.04305 fatcat:5u4cusdnszbblf3zlvvxhflgbu