Intersession consistency of single-trial classification of the prefrontal response to mental arithmetic and the no-control state by NIRS.
Intersession consistency of single-trial classification of the prefrontal response to mental arithmetic and the no-control state by NIRS.
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DOI：
10.1371/journal.pone.0037791
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发表时间：
2012
期刊：
影响因子：
3.7
通讯作者：
Chau T
中科院分区：
文献类型：
--
作者：
Power SD;Kushki A;Chau T
近红外光谱（NIRS）最近被研究用于无创脑机接口（BCI）技术。先前的研究已经证明了使用 NIRS 信号对与不同心理任务（例如心算）相关的神经激活模式进行分类的能力。尽管这些研究代表了实现 NIRS-BCI 的重要一步，但关于这些反应的一致性以及在多次试验中对它们进行单次试验分类的能力的文献却很少。当从实验环境转向实际系统时，这一点很重要，因为必须在较长时间内保持性能。当考虑跨会话的响应一致性时，出现两个问题：1）对激活任务的血流动力学响应能否与跨会话一致的基线（或其他任务）条件区分开来，如果是这样，2）是响应的时空特征，最好将其与跨会话一致的基线（或其他任务）条件区分开来。答案将对 NIRS-BCI 系统的可行性以及所采用的设计策略（特别是分类器训练协议）产生影响。在这项研究中，我们研究了五个实验阶段心算任务分类和无控制条件的一致性。会话内分类准确度的混合模型线性回归表明，任务和基线状态在多个会话中保持可微分，准确度没有显着下降 (p = 0.67)。然而，闭会期间分析揭示了时空响应特征的不一致。基于这些结果，我们研究了几种不同的实用分类器训练协议，包括训练和测试数据来自 1) 不同会话、2) 同一会话以及 3) 两者组合的场景。结果表明，在为 NIRS-BCI 选择最佳分类器训练方案时，必须考虑准确性和便利性之间的折衷（例如，训练数据收集的持续时间/频率）。
Near-infrared spectroscopy (NIRS) has been recently investigated for use in noninvasive brain-computer interface (BCI) technologies. Previous studies have demonstrated the ability to classify patterns of neural activation associated with different mental tasks (e.g., mental arithmetic) using NIRS signals. Though these studies represent an important step towards the realization of an NIRS-BCI, there is a paucity of literature regarding the consistency of these responses, and the ability to classify them on a single-trial basis, over multiple sessions. This is important when moving out of an experimental context toward a practical system, where performance must be maintained over longer periods. When considering response consistency across sessions, two questions arise: 1) can the hemodynamic response to the activation task be distinguished from a baseline (or other task) condition, consistently across sessions, and if so, 2) are the spatiotemporal characteristics of the response which best distinguish it from the baseline (or other task) condition consistent across sessions. The answers will have implications for the viability of an NIRS-BCI system, and the design strategies (especially in terms of classifier training protocols) adopted. In this study, we investigated the consistency of classification of a mental arithmetic task and a no-control condition over five experimental sessions. Mixed model linear regression on intrasession classification accuracies indicate that the task and baseline states remain differentiable across multiple sessions, with no significant decrease in accuracy (p = 0.67). Intersession analysis, however, revealed inconsistencies in spatiotemporal response characteristics. Based on these results, we investigated several different practical classifier training protocols, including scenarios in which the training and test data come from 1) different sessions, 2) the same session, and 3) a combination of both. Results indicate that when selecting optimal classifier training protocols for NIRS-BCI, a compromise between accuracy and convenience (e.g., in terms of duration/frequency of training data collection) must be considered.
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影响因子：
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作者：
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通讯作者：
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DOI：
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发表时间：
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期刊：
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