Tortolani Ariana F, Kunigk Nicolas G, Sobinov Anton R, Boninger Michael L, Bensmaia Sliman J, Collinger Jennifer L, Hatsopoulos Nicholas G, Downey John E
Committee on Computational Neuroscience, University of Chicago, Chicago, IL, United States of America.
Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States of America.
J Neural Eng. 2025 Feb 10;22(1):016032. doi: 10.1088/1741-2552/adb078.
. As brain-computer interface (BCI) research advances, many new applications are being developed. Tasks can be performed in different virtual environments, and whether a BCI user can switch environments seamlessly will influence the ultimate utility of a clinical device.. Here we investigate the importance of the immersiveness of the virtual environment used to train BCI decoders on the resulting decoder and its generalizability between environments. Two participants who had intracortical electrodes implanted in their precentral gyrus used a BCI to control a virtual arm, both viewed immersively through virtual reality goggles and at a distance on a flat television monitor.. Each participant performed better with a decoder trained and tested in the environment they had used the most prior to the study, one for each environment type. The neural tuning to the desired movement was minimally influenced by the immersiveness of the environment. Finally, in further testing with one of the participants, we found that decoders trained in one environment generalized well to the other environment, but the order in which the environments were experienced within a session mattered.. Overall, experience with an environment was more influential on performance than the immersiveness of the environment, but BCI performance generalized well after accounting for experience.Clinical Trial: NCT01894802.
随着脑机接口(BCI)研究的进展,许多新应用正在被开发。任务可以在不同的虚拟环境中执行,而BCI用户能否无缝切换环境将影响临床设备的最终效用。在这里,我们研究用于训练BCI解码器的虚拟环境的沉浸感对所得解码器及其在不同环境之间的通用性的重要性。两名在中央前回植入皮层内电极的参与者使用BCI控制虚拟手臂,既通过虚拟现实护目镜沉浸式观看,也在平板电视显示器上远距离观看。每个参与者在他们在研究前使用最多的环境中训练和测试的解码器表现更好,每种环境类型各有一个。对期望运动的神经调谐受环境沉浸感的影响最小。最后,在对其中一名参与者的进一步测试中,我们发现在一种环境中训练的解码器能很好地推广到另一种环境,但在一次会话中体验环境的顺序很重要。总体而言,与环境的体验对性能的影响比环境的沉浸感更大,但在考虑体验因素后,BCI性能能很好地推广。临床试验:NCT01894802。