NeuroIS is a field in Information Systems (IS) that makes use of neurophysiological knowledge and tools to better understand the development, adoption, and impact of information and communication technologies (ICT). The idea of applying cognitive neuroscience approaches in IS research appeared at the 2007 International Conference on Information Systems (ICIS) and at two pre-ICIS meetings (Sixth Annual Workshop on Human-Computer Interaction Research in Management Information Systems and OASIS Workshop 2007); a very limited number of publications on ICT and brain research were published in IS outlets before 2007. 

NeuroIS examines topics lying at the intersection of IS research and neurophysiology. Specifically, NeuroIS research comprises conceptual and empirical works, as well as theoretical and design science research. It includes research based on all types of neurophysiological tools, such as functional magnetic resonance imaging (fMRI), electroencephalograhy (EEG), fNIRS (functional near-infrared spectroscopy), electromyography (EMG), hormone assessments, or skin conductance and heart rate measurement. Moreover, it is foreseeable that quantitative and molecular genetics could play a significant role in future NeuroIS research.

Analysis of the extant NeuroIS literature shows that papers address the following topics, among others: employment of neurophysiological knowledge and tools to examine trust, technostress, website design, technology adoption, human-computer interaction, emotions in e-commerce, information behavior, IS design science, mental workload, social networks, usability, software development, and business process modeling and enterprise systems. Also, software prototypes of NeuroIS applications, which use bio-signals (e.g., EEG, skin conductance, pupil dilation) as system input, are an essential topic in the field; such systems are referred to as neuro-adaptive information systems. Methodological and ethical discussions are also critical.

Against the background of the fact that NeuroIS has been established as a research field in the IS discipline in the past decade, it is useful to have a syllabus in which the major concepts of the NeuroIS field are documented. More and more universities want to offer a NeuroIS introductory course, often at the graduate level. Based on such a course, students should be able to get an overview of the field in order to make an informed decision about whether, and if so how, they would like to get engaged in NeuroIS research (e.g., PhD thesis).

Importantly, because NeuroIS is a relatively young field, we observe an ongoing development of concepts, and hence this syllabus documents the current state of the field (as it is perceived by the authors of this document). It follows that it is possible that concepts which are considered important today will become less relevant in the future. Likewise, new topics which have not yet received attention in the NeuroIS literature will become important in the future. Thus, as a consequence of the moderate maturity level of the NeuroIS field, it is important that this syllabus is updated on a regular basis, at least up until a point of consolidation of the concepts in the NeuroIS field is reached.    

Learning Outcomes

We recommend teaching an introductory course to NeuroIS based on the book Fundamentals of NeuroIS: Information Systems and the Brain (Springer, 2016). This book provides an introduction to NeuroIS. In addition to this book, we recommend reading seminal papers (for a compilation of NeuroIS papers, both conceptual and empirical in nature, please see www.NeuroIS.org).

This introductory course provides a broad overview of NeuroIS. In essence, as indicated in a paper on the foundations of NeuroIS (Communications of the Association for Information Systems, Vol. 27, Article 15, p. 245), this field seeks to contribute to the development of new theories that make possible accurate predictions of IT-related behaviors, and to the design of IT artifacts that positively affect economic and non-economic variables (e.g., productivity, satisfaction, adoption, well-being). The course covers fundamental themes, including the following questions: 

• What is NeuroIS?
• Why NeuroIS?
• How to conduct NeuroIS studies?
• How to select the right NeuroIS measure given a specific research question?

The course takes a beginner rather than an expert approach to the material presented. As such, it should be of use to students of the Information Systems and Management disciplines interested in neuroscience. A major benefit of the course is that participants are provided with a large variety of NeuroIS topics and tools.