Abstract
There is an ongoing discussion in the NeuroIS (Neuro-Information-Systems) discipline on whether consumer-grade EEG instruments are as suitable for scientific research as research-grade instruments. Considering the increasing adoption of consumer-grade instruments along with the fact that many NeuroIS EEG papers used such tools, this debate is fundamental. We report on a study in which we contrasted a 61-channel EEG recording with a 14-channel recording that should simulate the electrode layout of the EPOC headset, the presumably worldwide most widely used consumer-grade tool. The contrast was carried out based on topographic mapping, because this kind of EEG data analysis does not only play a significant role in cognitive neuroscience, but also in NeuroIS research. Our findings show noticeable differences in the topoplots between both conditions. The current research results are limited by the fact that our task context is a non-IS context (i.e., upper limb movements). Hence, future research should validate our results based on IS tasks and situations in order to confirm, revise, or falsify the present results.
Original language | English |
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Title of host publication | Information Systems and Neuroscience: NeuroIS Retreat 2021 |
Editors | Fred D. Davis, René Riedl, Jan vom Brocke, Pierre-Majorique Léger, Adriane B. Randolph, Gernot Müller-Putz |
Place of Publication | Cham |
Publisher | Springer |
Pages | 90-95 |
Number of pages | 6 |
ISBN (Print) | 9783030888992 |
DOIs | |
Publication status | Published - 29 Oct 2021 |
Event | NeuroIS Retreat 2021 : Virtual Conference - Online, Online Duration: 1 Jun 2021 → 3 Jun 2021 http://www.neurois.org |
Publication series
Name | Lecture Notes in Information Systems and Organisation |
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Volume | 52 LNISO |
ISSN (Print) | 2195-4968 |
ISSN (Electronic) | 2195-4976 |
Conference
Conference | NeuroIS Retreat 2021 |
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Abbreviated title | NeuroIS |
City | Online |
Period | 01.06.2021 → 03.06.2021 |
Internet address |
Keywords
- Brain
- Consumer-grade EEG
- EEG
- EPOC
- Electroencephalography
- NeuroIS
- Research-grade EEG