While recent research on Brain-Computer Interfaces (BCI) has highlighted their potential for many applications, they remain barely used outside laboratories. The main reason is their lack of robustness. Indeed, with current BCI, mental state recognition is usually slow and often incorrect. Spontaneous BCI (i.e., mental imagery-based BCI) often rely on mutual learning efforts by the user and the machine, with BCI users learning to produce stable ElectroEncephaloGraphy (EEG) patterns (spontaneous BCI control being widely acknowledged as a skill) while the computer learns to automatically recognize these EEG patterns, using signal processing. Most research so far was focused on signal processing, mostly neglecting the human in the loop. However, how well the user masters the BCI skill is also a key element explaining BCI robustness. Indeed, if the user is not able to produce stable and distinct EEG patterns, then no signal processing algorithm would be able to recognize them. Unfortunately, despite the importance of BCI training protocols, they have been scarcely studied so far, and used mostly unchanged for years. In this paper, we advocate that current human training approaches for spontaneous BCI are most likely inappropriate. We notably study instructional design literature in order to identify the key requirements and guidelines for a successful training procedure that promotes a good and efficient skill learning. This literature study highlights that current spontaneous BCI user training procedures satisfy very few of these requirements and hence are likely to be suboptimal. We therefore identify the flaws in BCI training protocols according to instructional design principles, at several levels: in the instructions provided to the user, in the tasks he/she has to perform, and in the feedback provided. For each level, we propose new research directions that are theoretically expected to address some of these flaws and to help users learn the BCI skill more efficiently.

Episodic memory was assessed using Virtual Reality (VR). Forty-four (44) subjects visualized a target virtual apartment containing specific objects in each room. Then they visualized a second virtual apartment comprised of specific objects and objects shared by the two apartments. Subjects navigated in the virtual apartments in one of the following two conditions: active and passive. Four main episodic memory components were scored from the VR exposures: (1) learning effect; (2) active forgetting effect; (3) strategies at encoding and at retrieval; and (4) false recognitions (FRs). The effect of navigation mode (active vs. passive) on each memory component was examined. Active subjects had better learning and retrieval (recognition hits) performances compared to passive subjects. A beneficial effect of active navigation was also observed on the source-based FR rates. Active subjects made fewer source-based FRs compared to passive subjects. These overall results for the effect of active navigation are discussed in terms of the distinction between item-specific and relational processing.

The purpose of this study was to evaluate the effect the visual fidelity of a virtual environment (VE) (undetailed vs. detailed) has on the transfer of spatial knowledge based on the navigation mode (passive vs. active) for three different spatial recall tasks (wayfinding, sketch mapping, and picture sorting). Sixty-four subjects (32 men and 32 women) participated in the experiment. Spatial learning was evaluated by these three tasks in the context of the Bordeaux district. In the wayfinding task, the results indicated that the detailed VE helped subjects to transfer their spatial knowledge from the VE to the real world, irrespective of the navigation mode. In the sketch-mapping task, the detailed VE increased performances compared to the undetailed VE condition, and allowed subjects to benefit from the active navigation. In the sorting task, performances were better in the detailed VE; however, in the undetailed version of the VE, active learning either did not help the subjects or it even deteriorated their performances. These results are discussed in terms of appropriate perceptive-motor and/or spatial representations for each spatial recall task.

Unlike pencil-and-paper tests, virtual reality is useful to assess large-scale navigation strategies in patients with brain injury or schizophrenia, or in the context of ageing and dementia. Better knowledge about both the impact of the different aids and the cognitive processes involved is essential for the use of aids in neurorehabilitation.

The aim of this study was to evaluate motor control activity (active vs. passive condition) with regards to wayfinding and spatial learning difficulties in large-scale spaces for older adults. We compared virtual reality (VR)-based wayfinding and spatial memory (survey and route knowledge) performances between 30 younger and 30 older adults. A significant effect of age was obtained on the wayfinding performances but not on the spatial memory performances. Specifically, the active condition deteriorated the survey measure in all of the participants and increased the age-related differences in the wayfinding performances. Importantly, the age-related differences in the wayfinding performances, after an active condition, were further mediated by the executive measures. All of the results relative to a detrimental effect of motor activity are discussed in terms of a dual task effect as well as executive decline associated with aging.

The aim of this study was to evaluate in large-scale spaces wayfinding and spatial learning difficulties for older adults in relation to the executive and memory decline associated with aging. We compared virtual reality (VR)-based wayfinding and spatial memory performances between young and older adults. Wayfinding and spatial memory performances were correlated with classical measures of executive and visuo-spatial memory functions, but also with self-reported estimates of wayfinding difficulties. We obtained a significant effect of age on wayfinding performances but not on spatial memory performances. The overall correlations showed significant correlations between the wayfinding performances and the classical measures of both executive and visuo-spatial memory, but only when the age factor was not partialled out. Also, older adults underestimated their wayfinding difficulties. A significant relationship between the wayfinding performances and self-reported wayfinding difficulty estimates is found, but only when the age effect was partialled out. These results show that, even when older adults have an equivalent spatial knowledge to young adults, they had greater difficulties with the wayfinding task, supporting an executive decline view in age-related wayfinding difficulties. However, the correlation results are in favor of both the memory and executive decline views as mediators of age-related differences in wayfinding performances. This is discussed in terms of the relationships between memory and executive functioning in wayfinding task orchestration. Our results also favor the use of objective assessments of everyday navigation difficulties in virtual applications, instead of self-reported questionnaires, since older adults showed difficulties in estimating their everyday wayfinding problems.

Although spatial representations probably differ between the real and virtual environment, virtual reality remains a trusty assessment tool for spatial abilities.

The purpose of this study was to examine the effect of navigation mode (passive versus active) on the virtual/real transfer of spatial learning, according to viewpoint displacement (ground: 1 m 75 versus aerial: 4 m) and as a function of the recall tasks used. We hypothesize that active navigation during learning can enhance performances when route strategy is favored by egocentric match between learning (ground-level viewpoint) and recall (egocentric frame-based tasks). Sixty-four subjects (32 men and 32 women) participated in the experiment. Spatial learning consisted of route learning in a virtual district (four conditions: passive/ground, passive/aerial, active/ground, or active/aerial), evaluated by three tasks:wayfinding,sketch-mapping,andpicture-sorting. In thewayfinding task, subjects who were assigned the ground-level viewpoint in the virtual environment (VE) performed better than those with the aerial-level viewpoint, especially in combination with active navigation. In thesketch-mapping task, aerial-level learning in the VE resulted in better performance than the ground-level condition, while active navigation was only beneficial in the ground-level condition. The best performance in thepicture-sorting taskwas obtained with the ground-level viewpoint, especially with active navigation. This study confirmed the expected results that the benefit of active navigation was linked with egocentric frame-based situations.