Development of human EEG-ASL-BOLD neuroimaging and math modelling framework to quantify neuronal, haemodynamic and metabolic responses to stimulation

人类神经成像是一门非侵入性测量大脑功能的科学，这意味着不以任何方式进入身体。伯明翰大学和诺丁汉大学的研究人员之间的这项合作将开发新的成像技术和数学模型，以提高对人脑成像测量的生物学意义的理解。研究健康人脑的功能至关重要。提高对正常大脑功能的认识有助于了解患病大脑中出现的问题，并有助于医疗诊断，药物设计和治疗中风，癫痫，帕金森氏症和阿尔茨海默氏症等疾病。功能性磁共振成像（FMRI）技术至关重要，因为它可以准确地确定当我们体验感觉和感受时活跃的大脑区域，或者执行诸如抓杯子或看电影的动作。传统的功能磁共振成像使用的方法是敏感的变化，在血流和氧气水平在大脑的血液（BOLD）。第二种不太常见的功能磁共振成像方法，称为ASL，提供了营养血液输送到大脑信号细胞（称为神经元）的绝对测量。但是，BOLD和ASL响应都需要5秒才能达到最大级别。很明显，大脑活动的时间尺度要短得多。第三种技术称为脑电图（EEG），直接记录病人头皮上电极的神经元电活动。脑电图以毫秒级的精度提供大脑不同部位活动的信息，这三种技术广泛应用于大脑研究，并越来越多地应用于临床实践。然而，它们中没有一个单独提供大脑活动的决定性测量。准确地识别EEG信号的独特脑源通常是不可能的。可以测量BOLD信号的变化，这些变化仅由血流的差异引起，而没有电信号的任何变化。如果没有EEG测量，研究人员就不会知道这是一个“假”BOLD反应，如果没有ASL测量血流，研究人员就不会知道为什么这是一个“假”BOLD反应。同步EEG-BOLD-ASL测量将提供更完整的图像，显示神经元发出信号时发生的血流、能量使用和电活动的变化。血流、神经元活动和大脑能量使用变化之间耦合的数学模型将用于在计算机上重现大脑成像结果。这些模型是生物现实的简化版本，但基于科学文献中有充分依据的假设。模型的输出将与真实的EEG和fMRI数据进行比较，以帮助理解个体生物变量在创建观察到的脑信号时的重要性。由于需要EEG和ASL测量，因此所提出的成像开发至关重要，以便模型可以用于从组合信号中提取生理变量。只有将多维成像与建模相结合，我们才能解开影响BOLD信号的一些因素，从而能够更详细地描述伴随神经元活动的过程。该项目最终旨在回答两个目前知之甚少的非常重要的问题：1）EEG和FMRI测量的大脑活动的共同方面是什么？2)大脑的能量使用和脑电图测量的神经元活动之间的关系是什么？更好地了解EEG和FMRI信号之间的关系将有助于所有单独使用这些方法的研究人员和临床医生，并改善我们对健康大脑成像信号的解释以及它们如何随着衰老和疾病而变化。

Human neuroimaging is the science of measuring brain function non-invasively, meaning without physically entering the body in any way. This collaboration between researchers at the Universities of Birmingham and Nottingham will develop new imaging techniques and mathematical models to improve understanding of the biological meaning of human brain imaging measurements.Studying the function of the healthy human brain is vitally important. Improving knowledge of normal brain function helps the understanding of what goes wrong in the diseased brain and aids medical diagnoses, drug design and treatment for disorders such as stroke, epilepsy, Parkinson's, and Alzheimer's.The functional magnetic resonance imaging (FMRI) technique is crucially important because it can accurately pinpoint the brain regions that are active when we experience sensations and feelings, or perform an action such as grasping a cup or watching a movie. Conventional FMRI uses a method that is sensitive to changes in both blood flow and the level of oxygen in the brain's blood (BOLD). A second less-common FMRI method, called ASL, provides absolute measurements of the delivery of nutrient blood to the brain's signalling cells, called neurons. However, both BOLD and ASL responses take 5 seconds to reach their maximum level. Obviously, brain processes occur on a much shorter timescale. A third technique called electroencephalography (EEG) directly records the electrical activity of neurons from electrodes on the patient's scalp. EEG provides information on when different parts of the brain are active with millisecond precision.These three techniques are widely used in brain research and increasingly in clinical practise. However, none of them alone provides a conclusive measurement of brain activity. Accurately identifying unique brain sources of the EEG signal is often not possible. Changes in BOLD signal can be measured that are caused only by differences in blood flow without any change in electrical signaling. Without an EEG measurement of that event the researcher would not know that it was a 'false' BOLD response, and without an ASL measurement of blood flow the researcher would not know why it was a 'false' BOLD response.This research project will overcome these limitations by developing combined EEG-BOLD-ASL as a multi-dimensional imaging technique. Simultaneous EEG-BOLD-ASL measurement will provide a more complete picture of the changes in blood flow, energy usage and electrical activity that occur when neurons are signaling.Mathematical models of the coupling between changes in blood flow, neuronal activity and brain energy usage will be used to re-create brain imaging results on computers. These models are simplified versions of the biological reality but are based on well-founded assumptions from scientific literature. The models output will be compared to real EEG and fMRI data to help understand the significance of individual biological variables in creating the observed brain signals.The proposed imaging development is crucial as EEG and ASL measurements are required so that models can be used to extract physiological variables from the combined signals. Only by combining multi-dimensional imaging with modelling can we untangle some of the factors that influence the BOLD signal, enabling a much more detailed description of the processes accompanying neuronal activity to be made.This project ultimately aims to answer two very important questions that are currently poorly understood: 1) What common aspects of brain activity are represented in the measurements made by EEG and FMRI? 2) What is the relationship between the brain's energy usage and the neuronal activity measured by EEG?A better understanding of the relationship between EEG and FMRI signals will help all researchers and clinicians that use these methods individually and improve our interpretation of healthy brain imaging signals and how they change with aging and disease.