Alwashmi Kholoud, Rowe Fiona, Meyer Georg
Faculty of Health and Life Sciences, University of Liverpool, United Kingdom; Department of Radiology, Princess Nourah bint Abdulrahman University, Saudi Arabia.
IDEAS, University of Liverpool, United Kingdom.
Neuroimage. 2025 Jan;305:120983. doi: 10.1016/j.neuroimage.2024.120983. Epub 2024 Dec 26.
Recent work has shown rapid microstructural brain changes in response to learning new tasks. These cognitive tasks tend to draw on multiple brain regions connected by white matter (WM) tracts. Therefore, behavioural performance change is likely to be the result of microstructural, functional activation, and connectivity changes in extended neural networks. Here we show for the first time that learning-induced microstructural change in WM tracts, quantified with diffusion tensor and kurtosis imaging (DTI, DKI) is linked to functional connectivity changes in brain areas that use these tracts to communicate. Twenty healthy participants engaged in a month of virtual reality (VR) systematic audiovisual (AV) training. DTI analysis using repeated-measures ANOVA unveiled a decrease in mean diffusivity (MD) in the SLF II, alongside a significant increase in fractional anisotropy (FA) in optic radiations post-training, persisting in the follow-up (FU) assessment (post: MD t(76) = 6.13, p < 0.001, FA t(76) = 3.68, p < 0.01, FU: MD t(76) = 4.51, p < 0.001, FA t(76) = 2.989, p < 0.05). The MD reduction across participants was significantly correlated with the observed behavioural performance gains. A functional connectivity (FC) analysis showed significantly enhanced functional activity correlation between primary visual and auditory cortices post-training, which was evident by the DKI microstructural changes found within these two regions as well as in the sagittal stratum including WM tracts connecting occipital and temporal lobes (mean kurtosis (MK): cuneus t(19)=2.3 p < 0.05, transverse temporal t(19)=2.6 p < 0.05, radial kurtosis (RK): sagittal stratum t(19)=2.3 p < 0.05). DTI and DKI show complementary data, both of which are consistent with the task-relevant brain networks. The results demonstrate the utility of multimodal imaging analysis to provide complementary evidence for brain changes at the level of networks. In summary, our study shows the complex relationship between microstructural adaptations and functional connectivity, unveiling the potential of multisensory integration within immersive VR training. These findings have implications for learning and rehabilitation strategies, facilitating more effective interventions within virtual environments.
近期研究表明，大脑微观结构会因学习新任务而迅速发生变化。这些认知任务往往涉及由白质（WM）束连接的多个脑区。因此，行为表现的改变很可能是扩展神经网络中微观结构、功能激活及连接性变化的结果。在此，我们首次表明，通过扩散张量和峰度成像（DTI、DKI）量化的WM束中学习诱导的微观结构变化，与使用这些束进行通信的脑区中的功能连接变化相关。20名健康参与者进行了为期一个月的虚拟现实（VR）系统视听（AV）训练。使用重复测量方差分析的DTI分析显示，训练后上纵束II的平均扩散率（MD）降低，同时视辐射中的分数各向异性（FA）显著增加，并在随访（FU）评估中持续存在（训练后：MD t(76) = 6.13，p < 0.001，FA t(76) = 3.68，p < 0.01，FU：MD t(76) = 4.51，p < 0.001，FA t(76) = 2.989，p < 0.05）。参与者MD的降低与观察到的行为表现提升显著相关。功能连接（FC）分析显示，训练后初级视觉和听觉皮层之间的功能活动相关性显著增强，这在这两个区域以及矢状层（包括连接枕叶和颞叶的WM束）中发现的DKI微观结构变化中很明显（平均峰度（MK）：楔叶t(19)=2.3，p < 0.05，颞横回t(19)=2.6，p < 0.05，径向峰度（RK）：矢状层t(19)=2.3，p < 0.05）。DTI和DKI显示出互补的数据，两者均与任务相关的脑网络一致。结果表明多模态成像分析在为网络层面的大脑变化提供补充证据方面的实用性。总之，我们的研究显示了微观结构适应与功能连接之间的复杂关系，揭示了沉浸式VR训练中多感官整合的潜力。这些发现对学习和康复策略具有启示意义，有助于在虚拟环境中进行更有效的干预。
