Recent advancements in brain-computer interface (BCI) technology have emphasized the promise of imagined speech and visual imagery as effective paradigms for intuitive communication. This study investigates the classification performance and brain connectivity patterns associated with these paradigms, focusing on decoding accuracy across selected word classes. Sixteen participants engaged in tasks involving thirteen imagined speech and visual imagery classes, revealing above-chance classification accuracy for both paradigms. Variability in classification accuracy across individual classes highlights the influence of sensory and motor associations in imagined speech and vivid visual associations in visual imagery. Connectivity analysis further demonstrated increased functional connectivity in language-related and sensory regions for imagined speech, whereas visual imagery activated spatial and visual processing networks. These findings suggest the potential of imagined speech and visual imagery as an intuitive and scalable paradigm for BCI communication when selecting optimal word classes. Further exploration of the decoding outcomes for these two paradigms could provide insights for practical BCI communication.

翻译：脑机接口技术的最新进展凸显了想象语音与视觉意象作为直观通信范式的潜力。本研究探究了与这些范式相关的分类性能及脑连接模式，重点关注选定词汇类别的解码准确性。十六名参与者参与了涉及十三类想象语音与视觉意象的任务，结果显示两种范式均获得了高于随机水平的分类准确率。不同类别间分类准确率的差异，突显了感觉与运动关联在想象语音中的作用，以及生动视觉关联在视觉意象中的影响。连接性分析进一步表明，想象语音增强了语言相关区域与感觉区域的功能连接，而视觉意象则激活了空间与视觉处理网络。这些发现表明，在选择最优词汇类别时，想象语音与视觉意象有潜力成为一种直观且可扩展的脑机接口通信范式。对这两种范式解码结果的进一步探索，可为实用的脑机接口通信提供见解。