For several years, there has been an increased application of neuroscientific approaches in the North American Information Systems (IS) discipline. Theories and methods from neuroscience contribute to a better understanding of human behavior. Since IS tries to explain human behavior in the use of information systems, neuroscientific approaches can also contribute to a growth of knowledge. In this regard, Dimoka et al. (2007, p. 13) stated in one of the first publications on this matter: “It is just hard to believe that a better understanding of brain functioning will not lead to better IS theories.” Against the background of the increasing internationalization of business and information systems engineering (BISE), the following discussion deals with the issue of “NeuroIS”. The need for a discussion on NeuroIS is reinforced by the fact that neuroscientific approaches also gain in importance in other business and social sciences (e.g., neuroeconomics, Camerer et al. 2005). In the years 2009 and 2010, there have already been two relevant scientific symposia in Austria which explicitly focused on NeuroIS. At this year’s conference “Gmunden Retreat on Advances in NeuroIS” (see http:// www.NeuroIS.org), which was attended by a number of experts from the German-speaking BISE, opportunities and challenges of NeuroIS were discussed. Here, both methodical and theory-related issues were on the agenda. A central conclusion of the conference was that neuroscientific approaches can help not only to explain human behavior in dealing with information, but are also relevant for design-oriented BISE scientists. This circumstance is of particular interest for BISE researchers in the German-speaking area as one of their strengths is the design and concept of new innovative technologies. In order to achieve a broad perspective on the issue in the course of this discussion, both North American scientists as well as representatives of the Germanspeaking BISE were invited to comment on the topic. The following authors accepted my invitation to this discussion (in alphabetical order): Prof. Rajiv D. Banker, Merves Chair in Accounting and Information Technology, Fox School of Business and Management, Temple University, USA; Prof. Jan vom Brocke, Hilti Chair in Business Process Management, University of Liechtenstein; Prof. Fred D. Davis, David D. Glass Chair in Information Systems, Sam M. Walton College of Business, University of Arkansas, USA; Prof. Pierre-Majorique Leger, Associate Professor am Department of Information Technologies, HEC Montreal, Canada; Prof. Gernot R. Muller-Putz, Associate Professor at Institute of Knowledge Discovery, Laboratory of BrainComputer Interfaces, Graz University of Technology, Austria; Prof. Rene Riedl, Associate Professor at Department of Business Informatics – Information Engineering, University of Linz, Austria. The six authors comment on various facets of NeuroIS that appear relevant and important for BISE in four contributions. Rene Riedl and Gernot R. Muller-Putz illustrate that neuroscientific approaches may be used to explain BISE-related phenomena as well as for the design of innovative information systems, based on three specific examples. For instance, the authors report on a laboratory experiment based on eBay websites. In addition, the authors refer to research and development projects in the IT industry which were presented to the public as prototypes in recent years. Jan vom Brocke comments on the role of neuroscience in design-oriented BISE research, arguing that neuroscientific approaches can not only be used in behavioral research. Building on the potentials of design-oriented research, vom Brocke distinguishes two major research streams: research by design and research on design. As to the former, he discusses the role of neuroscientific methods and theories in the development and evaluation of artifacts. As to the latter, he argues that neuroscientific approaches can also be used for generating and refining design theories. Fred D. Davis and Rajiv D. Banker focus on the integration of neuroscientific approaches to technology acceptance research. Since the 1980s, works on the technology acceptance model (TAM) have been published in large numbers. The authors find, however, that in recent years only incremental advances in