Modelling confounding effects from extracerebral contamination and systemic factors on functional near-infrared spectroscopy

被引:91
作者
Caldwell, Matthew [1 ]
Scholkmann, Felix [2 ]
Wolf, Ursula [3 ]
Wolf, Martin [2 ]
Elwell, Clare [1 ]
Tachtsidis, Ilias [1 ]
机构
[1] UCL, Dept Med Phys & Biomed Engn, Biomed Opt Res Lab, Gower St, London WC1E 6BT, England
[2] Univ Zurich Hosp, Dept Neonatol, Biomed Opt Res Lab, CH-8091 Zurich, Switzerland
[3] Univ Bern, Inst Complementary Med, CH-3012 Bern, Switzerland
基金
英国惠康基金; 英国工程与自然科学研究理事会;
关键词
Functional near-infrared spectroscopy; Brain; Modelling; Confounding; Scalp; CO2; reactivity; FRONTAL-LOBE ACTIVATION; BLOOD-FLOW; CEREBRAL HEMODYNAMICS; INTRACRANIAL-PRESSURE; VASCULAR-RESPONSES; OXYGEN-SATURATION; CO2; REACTIVITY; BRAIN; SKIN; AUTOREGULATION;
D O I
10.1016/j.neuroimage.2016.08.058
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Haemodynamics-based neuroimaging is widely used to study brain function. Regional blood flow changes characteristic of neurovascular coupling provide an important marker of neuronal activation. However, changes in systemic physiological parameters such as blood pressure and concentration of CO2 can also affect regional blood flow and may confound haemodynamics-based neuroimaging. Measurements with functional near-infrared spectroscopy (fNIRS) may additionally be confounded by blood flow and oxygenation changes in extracerebral tissue layers. Here we investigate these confounds using an extended version of an existing computational model of cerebral physiology, 'BrainSignals'. Our results show that confounding from systemic physiological factors is able to produce misleading haemodynamic responses in both positive and negative directions. By applying the model to data from previous fNIRS studies, we demonstrate that such potentially deceptive responses can indeed occur in at least some experimental scenarios. It is therefore important to record the major potential confounders in the course of fNIRS experiments. Our model may then allow the observed behaviour to be attributed among the potential causes and hence reduce identification errors. (C) 2016 The Authors. Published by Elsevier Inc.
引用
收藏
页码:91 / 105
页数:15
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