Speeded near infrared spectroscopy (NIRS) response detection

Cui, Bray, Reiss (2010) Speeded near infrared spectroscopy (NIRS) response detection PLoS One (IF: 3.7) 5(11) e15474

Abstract

The hemodynamic response measured by Near Infrared Spectroscopy (NIRS) is temporally delayed from the onset of the underlying neural activity. As a consequence, NIRS based brain-computer-interfaces (BCIs) and neurofeedback learning systems, may have a latency of several seconds in responding to a change in participants' behavioral or mental states, severely limiting the practical use of such systems. To explore the possibility of reducing this delay, we used a multivariate pattern classification technique (linear support vector machine, SVM) to decode the true behavioral state from the measured neural signal and systematically evaluated the performance of different feature spaces (signal history, history gradient, oxygenated or deoxygenated hemoglobin signal and spatial pattern). We found that the latency to decode a change in behavioral state can be reduced by 50% (from 4.8 s to 2.4 s), which will enhance the feasibility of NIRS for real-time applications.

通过近红外光谱（NIRS）测量的血液动力学响应在时间上从基础神经活动的开始延迟。因此，基于NIRS的脑计算机接口（BCI）和神经反馈学习系统可能具有几秒钟的延迟以响应参与者的行为或精神​​状态的变化，严重限制了这样的系统的实际使用。为了探讨减少这种延迟的可能性，我们使用多变量模式分类技术（线性支持向量机，SVM）从测量的神经信号解码真实行为状态，并系统地评估不同特征空间的性能（信号历史，历史梯度，氧合或脱氧血红蛋白信号和空间模式）。我们发现解码行为状态变化的延迟可以减少50％（从4.8秒到2.4秒），这将增强NIRS的实时应用的可行性。

Links

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2978722
http://www.ncbi.nlm.nih.gov/pubmed/21085607
http://dx.doi.org/10.1371/journal.pone.0015474

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