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，也就是说，不需要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了解有助于了解疾病大脑中哪里出了问题，并有助于医学诊断、药物设计和中风、癫痫、帕金森氏症和阿尔茨海默氏症等疾病的治疗。功能磁共振成像(FMRI)技术至关重要，因为它可以准确地定位当我们体验感觉和感觉时，或执行诸如抓杯子或看电影等动作时活跃的大脑区域。传统的功能磁共振成像使用的方法对血流和大脑血液中氧气水平的变化都很敏感(BOLD)。第二种不太常见的功能磁共振成像方法，称为ASL，它提供了营养血液输送到大脑信号细胞(称为神经元)的绝对测量结果。然而，粗体和ASL回复都需要5秒才能达到其最大级别。显然，大脑过程发生的时间要短得多。第三种技术称为脑电(EEG)，它直接记录患者头皮上电极上神经元的电活动。脑电提供了大脑不同部位何时活跃的信息，精确度为毫秒。这三种技术在大脑研究中得到了广泛应用，并越来越多地应用于临床实践。然而，它们中的任何一个都不能单独提供大脑活动的确凿测量。准确识别脑电信号的独特大脑来源通常是不可能的。BOLD信号的变化可以测量，这些变化仅由血流的差异引起，而不会对电信号产生任何影响。如果没有对这一事件的脑电测量，研究人员就不会知道这是一种“虚假的”大胆反应，如果没有对血流的ASL测量，研究人员就不会知道为什么这是一种“虚假的”大胆反应。这项研究项目将通过开发组合EEG-BOLD-ASL作为一种多维成像技术来克服这些限制。同时EEG-BOLD-ASL测量将提供当神经元发出信号时发生的血流、能量使用和电活动的变化的更完整的图景。血流、神经元活动和大脑能量使用变化之间的耦合的数学模型将被用来在计算机上重建大脑成像结果。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，以帮助理解单个生物变量在创建观察到的脑信号中的重要性。拟议的成像开发至关重要，因为需要进行EEG和ASL测量，以便可以使用模型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，我们才能理清影响粗体信号的一些因素，这个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)脑电和功能磁共振成像的测量代表了大脑活动的哪些共同方面？2)大脑的能量使用和脑电测量的神经元活动之间有什么关系？更好地理解脑电和功能磁共振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，并改进我们对健康的大脑成像信号的解释，以及它们如何随着年龄和疾病的变化而变化。

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.