| Literature DB >> 27590964 |
C Jeunet1, B N'Kaoua2, F Lotte3.
Abstract
While being very promising for a wide range of applications, mental-imagery-based brain-computer interfaces (MI-BCIs) remain barely used outside laboratories, notably due to the difficulties users encounter when attempting to control them. Indeed, 10-30% of users are unable to control MI-BCIs (so-called BCI illiteracy) while only a small proportion reach acceptable control abilities. This huge interuser variability has led the community to investigate potential predictors of performance related to users' personality and cognitive profile. Based on a literature review, we propose a classification of these MI-BCI performance predictors into three categories representing high-level cognitive concepts: (1) users' relationship with the technology (including the notions of computer anxiety and sense of agency), (2) attention, and (3) spatial abilities. We detail these concepts and their neural correlates in order to better understand their relationship with MI-BCI user-training. Consequently, we propose, by way of future prospects, some guidelines to improve MI-BCI user-training.Entities:
Keywords: Attention; Brain–computer interfaces; Computer anxiety; Improving training protocols; Interuser variability; Neural correlates; Predictors of performance; Sense of agency; Spatial abilities; User-training
Mesh:
Year: 2016 PMID: 27590964 DOI: 10.1016/bs.pbr.2016.04.002
Source DB: PubMed Journal: Prog Brain Res ISSN: 0079-6123 Impact factor: 2.453