Data Sharing, or Open Data is the idea of researchers freely providing their datasets to others. It has led to make major breakthrough in different disciplines (e.g. Genetics, Astronomy) with an almost direct benefit for mankind. Unfortunately, within the brain research community this process has been remarkably slower, with scientists being reluctant to share data for several possible reasons. In this field of this research, open databases would enable faster, more relevant research, and more importantly favor replicability and reproducibility of results. This is particularly true in Neuroergonomics which is concerned with the understanding of the neural processes that take place in realistic settings. Most neuroergonomic experiments involving neurophysiological data collection with electroencephalography – EEG – or near infra-red spectroscopy – fNIRS – are challenging to perform since they require realistic environments (e.g. simulators or real vehicles) that are costly in terms of time to set–up and manpower. As a consequence, this research is performed with a limited number of volunteers and generally does not exceed one hour to avoid fatigue effects and discomfort for the participants. Moreover, the serviceability of datasets is limited by inter-subject and even inter-session variability issues. This latter point is of key importance as it prevents brain-computer-interfaces (BCI) and the design of neuroadaptive technology to be used on a day-to-day basis, outside laboratories.
This Research Topic calls for submissions that support data sharing of (neuro-)physiological data collected during complex real-life conditions, and that investigate cognition, emotion, perception, decision making, attention, working memory, cognitive workload, performance monitoring, human-machine-interaction, brain-computer interface, mobile brain and body imaging, and neuroadaptive technologies, but also submissions of replicated studies of this field. We encourage authors to provide their signal processing code using open-source software/platforms and to follow the guidelines from the Human Brain Mapping (OHBM) and the Brain Imaging Data structure (BIDS) for data labeling and organization.
Examples of submissions: research article with an open dataset, review on open datasets, research article that reproduces an experiment, Description of open data, open source code, open hardware, open protocols, or open experimental materials.
Data Sharing, or Open Data is the idea of researchers freely providing their datasets to others. It has led to make major breakthrough in different disciplines (e.g. Genetics, Astronomy) with an almost direct benefit for mankind. Unfortunately, within the brain research community this process has been remarkably slower, with scientists being reluctant to share data for several possible reasons. In this field of this research, open databases would enable faster, more relevant research, and more importantly favor replicability and reproducibility of results. This is particularly true in Neuroergonomics which is concerned with the understanding of the neural processes that take place in realistic settings. Most neuroergonomic experiments involving neurophysiological data collection with electroencephalography – EEG – or near infra-red spectroscopy – fNIRS – are challenging to perform since they require realistic environments (e.g. simulators or real vehicles) that are costly in terms of time to set–up and manpower. As a consequence, this research is performed with a limited number of volunteers and generally does not exceed one hour to avoid fatigue effects and discomfort for the participants. Moreover, the serviceability of datasets is limited by inter-subject and even inter-session variability issues. This latter point is of key importance as it prevents brain-computer-interfaces (BCI) and the design of neuroadaptive technology to be used on a day-to-day basis, outside laboratories.
This Research Topic calls for submissions that support data sharing of (neuro-)physiological data collected during complex real-life conditions, and that investigate cognition, emotion, perception, decision making, attention, working memory, cognitive workload, performance monitoring, human-machine-interaction, brain-computer interface, mobile brain and body imaging, and neuroadaptive technologies, but also submissions of replicated studies of this field. We encourage authors to provide their signal processing code using open-source software/platforms and to follow the guidelines from the Human Brain Mapping (OHBM) and the Brain Imaging Data structure (BIDS) for data labeling and organization.
Examples of submissions: research article with an open dataset, review on open datasets, research article that reproduces an experiment, Description of open data, open source code, open hardware, open protocols, or open experimental materials.
