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2017/2018  KAN-CCMVV5032U  Neuro Research Design

English Title
Neuro Research Design

Course information

Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Quarter
Start time of the course First Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 80
Study board
Study Board for MSc in Economics and Business Administration
Course coordinator
  • Jesper Clement - Department of Marketing (Marketing)
This course is part of the minor in Behavioral Neuroscience and Economy
Main academic disciplines
  • Customer behaviour
  • Marketing
Last updated on 03-03-2017

Relevant links

Learning objectives
To achieve the grade 12, students should meet the following learning objectives with no or only minor mistakes or errors: To achieve the grade 12, students should meet the following learning objectives with no or only minor mistakes or errors: The learning objectives of this course are that a student can:
  • Specifically: - describe and discuss structure and content of a neuroscientific research design aimed to provide insights into nonconscious interpretations and decisions
  • - reflect and explain overall objectives for different research setups
  • - describe the optimal for data collection and analysis
  • - reflect on the utility of different frameworks and principles for a neuroscientific research setup
  • In general: - select and apply a neuroscientific research design to a marketing project.
  • - find arguments for and against a specific neuroscientific research design
  • - make a plan for the essential parts of a neuroscientific research design (considerations, steps/processes, plan, ethics …)
  • - make a prototype of the research design and draw conclusions from the analysis and discuss implications
Course prerequisites
Students should have some background in one or more of the following areas: marketing, communication, advertising, consumer behaviour, marketing research, or the like
Neuro Research Design:
Exam ECTS 7,5
Examination form Oral exam based on written product

In order to participate in the oral exam, the written product must be handed in before the oral exam; by the set deadline. The grade is based on an overall assessment of the written product and the individual oral performance.
Individual or group exam Oral group exam based on written group product
Number of people in the group 2-4
Size of written product Max. 20 pages
Definition of number of pages:
Groups of
2 students 10 pages max.
3 students 15 pages max
4 students 20 pages max

Note that the exam is a group exam. If you are not able to find a group yourself, you have to address the course coordinator who will place you in a group.

Students who wish to have an individual exam might be able to write a term paper in the course. Please see the cand.merc. rules for term papers for more information.
Assignment type Report
Written product to be submitted on specified date and time.
15 min. per student, including examiners' discussion of grade, and informing plus explaining the grade
Grading scale 7-step scale
Examiner(s) Internal examiner and second internal examiner
Exam period Autumn
Make-up exam/re-exam
Same examination form as the ordinary exam
Re-take exam is to be based on the same report as the ordinary exam:

* if a student is absent from the oral exam due to documented illness but has handed in the written group product she/he does not have to submit a new product for the re-take.

* if a whole group fails the oral exam they must hand in a revised product for the re-take.

* if one student in the group fails the oral exam the course coordinator chooses whether the student will have the oral exam on the basis of the same product or if he/she has to hand in a revised product for the re- take.
Course content and structure

Asking people have been common in marketing research and do still have advantages. On the other hand, getting insights into nonconscious interpretations and decisions other research tools have to be taken into consideration. Neuroscientific research design refers to such a toolbox, which contains both technical equipment and ways of doing experimental research. The goal for this course is to give an overview of this fast developing toolbox and hands-on experience with some specific neuroscientific research designs. The course makes use of literature review for knowing the trends over the last decades and cases to enhance student’s ability to plan, setup, and analyze data from neuroscientific studies. These cases will be group presentations in class followed be a discussion lead by two opposing groups.

Teaching methods
The teaching method for the courses in the Minor is a blend of self-paced on-line learning and dialog-based lectures, discussions, and presentations in class. Common Neuroscientific theories and models relevant to all three courses within the Minor are given by asynchronous and synchronous on-line lectures, on-line discussions, quizzes and individual/group assignments. Specific topics for this course are given in lecture form. Chapters from textbook and articles will be assigned for reading and time in class will be devoted to discussions and questions regarding these readings
Feedback during the teaching period
Feedback is given through one or more short assignments during the semester. On-line exercises will be part of home preparation and discussed in class. Office hours will be provided as an opportunity for group or individual feedback.
Student workload
Preperation 123 hours
Teaching 33 hours
Exam 50 hours
Further Information

This course is part of the minor in Behavioral Neuroscience and Economy 

Expected literature

Ariely, Dan, and Gregory S. Berns. "Neuromarketing: the hope and hype of neuroimaging in business." Nature Reviews Neuroscience 11.4 (2010): 284-292.

Plassmann, Hilke, Thomas Zoëga Ramsøy, and Milica Milosavljevic. "Branding the brain: A critical review and outlook." Journal of Consumer Psychology 22.1 (2012): 18-36.

Tatler, B. W., Gilchrist, I. D., & Land, M. F. (2005). Visual memory for objects in natural scenes: From fixations to object files. The Quarterly Journal of Experimental Psychology Section A, 58(5), 931-960.

Bojko, A. A. (2009). Informative or misleading? Heatmaps deconstructed. In Human-computer interaction. New trends (pp. 30-39). Springer Berlin Heidelberg.

Le Meur, O., & Baccino, T. (2013). Methods for comparing scanpaths and saliency maps: strengths and weaknesses. Behavior research methods, 45(1), 251-266.

Mormann, M. M., Navalpakkam, V., Koch, C., & Rangel, A. (2012). Relative visual saliency differences induce sizable bias in consumer choice. Journal of Consumer Psychology, 22(1).

Pieters, R., & Wedel, M. (2007). Goal control of attention to advertising: The Yarbus implication. Journal of Consumer Research, 34(2), 224-233.

Reutskaja, E., Nagel, R., Camerer, C. F., & Rangel, A. (2011). Search dynamics in consumer choice under time pressure: An eye-tracking study. The American Economic Review, 900-926.

Tatler, B. W. (2007). The central fixation bias in scene viewing: Selecting an optimal viewing position independently of motor biases and image feature distributions. Journal of Vision, 7(14), 4.

(additional) Milosavljevic, M., & Cerf, M. (2008). First attention then intention: Insights from computational neuroscience of vision. International Journal of Advertising, 27(3), 381-398.

Groeppel-Klein, A. (2005). Arousal and consumer in-store behavior. Brain research bulletin, 67(5), 428-437.

Bradley, M. M., Miccoli, L., Escrig, M. A., & Lang, P. J. (2008). The pupil as a measure of emotional arousal and autonomic activation. Psychophysiology, 45(4), 602-607.

Teixeira, T., Wedel, M., & Pieters, R. (2012). Emotion-induced engagement in internet video advertisements. Journal of Marketing Research, 49(2), 144-159.

Lee, V. K., & Harris, L. T. (2013). How social cognition can inform social decision making. Frontiers in neuroscience, 7.

Plassmann, H., O'Doherty, J., Shiv, B., & Rangel, A. (2008). Marketing actions can modulate neural representations of experienced pleasantness. Proceedings of the National Academy of Sciences, 105(3), 1050-1054.

McClure, S. M., Li, J., Tomlin, D., Cypert, K. S., Montague, L. M., & Montague, P. R. (2004). Neural correlates of behavioral preference for culturally familiar drinks. Neuron, 44(2), 379-387.

Rozenkrants, B., & Polich, J. (2008). Affective ERP processing in a visual oddball task: arousal, valence, and gender. Clinical Neurophysiology, 119(10), 2260-2265.

Vecchiato, G., Astolfi, L., De Vico Fallani, F., Toppi, J., Aloise, F., Bez, F., ... & Mattia, D. (2011). On the use of EEG or MEG brain imaging tools in neuromarketing research. Computational intelligence and neuroscience,2011, 3.

Ravaja, N., Somervuori, O., & Salminen, M. (2013). Predicting purchase decision: The role of hemispheric asymmetry over the frontal cortex. Journal of Neuroscience, Psychology, and Economics, 6(1), 1.

Solnais, C., Andreu-Perez, J., Sánchez-Fernández, J., & Andréu-Abela, J. (2013). The contribution of neuroscience to consumer research: A conceptual framework and empirical review. Journal of Economic Psychology, 36, 68-81.

Dmochowski, J. P., Bezdek, M. A., Abelson, B. P., Johnson, J. S., Schumacher, E. H., & Parra, L. C. (2014). Audience preferences are predicted by temporal reliability of neural processing. Nature communications, 5.

Khushaba, R. N., Wise, C., Kodagoda, S., Louviere, J., Kahn, B. E., & Townsend, C. (2013). Consumer neuroscience: Assessing the brain response to marketing stimuli using electroencephalogram (EEG) and eye tracking. Expert Systems with Applications, 40(9), 3803-3812.

Millsap, R. E., & Maydeu-Olivares, A. (Eds.). (2009). The SAGE handbook of quantitative methods in psychology. London: SAGE Publications Ltd. .( eBook – CBS library access)
Ch.2 Experimental design

Murphy, E. R., Illes, J., & Reiner, P. B. (2008). Neuroethics of neuromarketing. Journal of Consumer Behaviour, 7(4-5), 293-302.

Tom, G., Nelson, C., Srzentic, T., & King, R. (2007). Mere exposure and the endowment effect on consumer decision making. The Journal of Psychology, 141(2), 117-125.

Ramsøy, Thomas Zoëga, and Martin Skov. "Brand preference affects the threshold for perceptual awareness." Journal of Consumer Behaviour 13.1 (2014): 1-8.

American Psychological Association. Publication manual of the American Psychological Association- 6th edition. Washington DC (ISBN-13:9781433805615) (Book- available physically in the  library)
Ch. 1-2

Hegde, D. S. (2015). Essays on Research Methodology.( eBook – CBS library access)
Ch.3: Logical and Epistemological Norms in Scientific Theory Construction

Last updated on 03-03-2017