Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Turning negative into positives! Exploiting ‘negative’ results in Brain–Machine Interface (BMI) research

Turning negative into positives! Exploiting ‘negative’ results in Brain–Machine Interface (BMI)... Results that do not confirm expectations are generally referred to as ‘negative’ results. While essential for scientific progress, they are too rarely reported in the literature – Brain–Machine Interface (BMI) research is no exception. This led us to organize a workshop on BMI negative results during the 2018 International BCI meeting. The outcomes of this workshop are reported herein. First, we demonstrate why (valid) negative results are useful, and even necessary for BMIs. These results can be used to confirm or disprove current BMI knowledge, or to refine current theories. Second, we provide concrete examples of such useful negative results, including the limits in BMI-control for complete locked-in users and predictors of motor imagery BMI performances. Finally, we suggest levers to promote the diffusion of (valid) BMI negative results, e.g. promoting hypothesis-driven research using valid statistical tools, organizing special issues dedicated to BMI negative results, or convincing institutions and editors that negative results are valuable. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Brain-Computer Interfaces Taylor & Francis

Turning negative into positives! Exploiting ‘negative’ results in Brain–Machine Interface (BMI) research

Turning negative into positives! Exploiting ‘negative’ results in Brain–Machine Interface (BMI) research

Abstract

Results that do not confirm expectations are generally referred to as ‘negative’ results. While essential for scientific progress, they are too rarely reported in the literature – Brain–Machine Interface (BMI) research is no exception. This led us to organize a workshop on BMI negative results during the 2018 International BCI meeting. The outcomes of this workshop are reported herein. First, we demonstrate why (valid) negative results are useful, and even necessary...
Loading next page...
 
/lp/taylor-francis/turning-negative-into-positives-exploiting-negative-results-in-brain-tDqme0lXQH
Publisher
Taylor & Francis
Copyright
© 2019 Informa UK Limited, trading as Taylor & Francis Group
ISSN
2326-2621
eISSN
2326-263x
DOI
10.1080/2326263X.2019.1697143
Publisher site
See Article on Publisher Site

Abstract

Results that do not confirm expectations are generally referred to as ‘negative’ results. While essential for scientific progress, they are too rarely reported in the literature – Brain–Machine Interface (BMI) research is no exception. This led us to organize a workshop on BMI negative results during the 2018 International BCI meeting. The outcomes of this workshop are reported herein. First, we demonstrate why (valid) negative results are useful, and even necessary for BMIs. These results can be used to confirm or disprove current BMI knowledge, or to refine current theories. Second, we provide concrete examples of such useful negative results, including the limits in BMI-control for complete locked-in users and predictors of motor imagery BMI performances. Finally, we suggest levers to promote the diffusion of (valid) BMI negative results, e.g. promoting hypothesis-driven research using valid statistical tools, organizing special issues dedicated to BMI negative results, or convincing institutions and editors that negative results are valuable.

Journal

Brain-Computer InterfacesTaylor & Francis

Published: Oct 2, 2019

Keywords: Negative results; hypothesis; models; theory; publication; guidelines; BCI; BMI

References