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Group Augmentation in Realistic Visual-Search Decisions via a Hybrid Brain-Computer Interface.

Valeriani, Davide and Cinel, Caterina and Poli, Riccardo (2017) 'Group Augmentation in Realistic Visual-Search Decisions via a Hybrid Brain-Computer Interface.' Scientific Reports, 7 (1). 7772-. ISSN 2045-2322

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Groups have increased sensing and cognition capabilities that typically allow them to make better decisions. However, factors such as communication biases and time constraints can lead to less-than-optimal group decisions. In this study, we use a hybrid Brain-Computer Interface (hBCI) to improve the performance of groups undertaking a realistic visual-search task. Our hBCI extracts neural information from EEG signals and combines it with response times to build an estimate of the decision confidence. This is used to weigh individual responses, resulting in improved group decisions. We compare the performance of hBCI-assisted groups with the performance of non-BCI groups using standard majority voting, and non-BCI groups using weighted voting based on reported decision confidence. We also investigate the impact on group performance of a computer-mediated form of communication between members. Results across three experiments suggest that the hBCI provides significant advantages over non-BCI decision methods in all cases. We also found that our form of communication increases individual error rates by almost 50% compared to non-communicating observers, which also results in worse group performance. Communication also makes reported confidence uncorrelated with the decision correctness, thereby nullifying its value in weighing votes. In summary, best decisions are achieved by hBCI-assisted, non-communicating groups.

Item Type: Article
Uncontrolled Keywords: Brain; Humans; Communication; Visual Perception; Decision Making; Adult; Female; Male; Brain-Computer Interfaces
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 22 Aug 2017 08:33
Last Modified: 18 Aug 2022 10:47

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