The Neural Basis of Functional MRI Responses

功能性 MRI 反应的神经基础

• 批准号: 9152122
• 负责人: David A Leopold
• 金额: $ 74.89万
• 依托单位: NATIONAL INSTITUTE OF MENTAL HEALTH
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9152122
• 关键词: Animals; Arousal; Awareness; Biological; Blood flow; Brain; Brain Mapping; Cerebral cortex; Clinic; Cognition; Complement; Complex; Couples; Coupling; Data; Diagnostic; Dimensions; Disease; District of Columbia; Electroencephalography; Electrons; Eye; Functional Magnetic Resonance Imaging; General Population; Goals; Head; Human; Implant; Individual; Influentials; Journals; Laboratories; Laboratory Research; Link; Magnetic Resonance Imaging; Maps; Measures; Mediator of activation protein; Methods; Nature; Neurons; Neurosciences; Paper; Pattern; Persons; Photic Stimulation; Population; Positioning Attribute; Publications; Publishing; Regulation; Relative (related person); Research; Rest; Scanning; Science; Scientist; Series; Shapes; Side; Signal Transduction; Societies; Structure; Telencephalon; Testing; Thinking; Time; Visual; Visual Cortex; Work; abstracting; awake; basal forebrain; base; blood perfusion; brain volume; density; fictional works; hemodynamics; insight; meetings; millimeter; neural circuit; neuroimaging; neuropsychiatry; neurotransmission; news; posters; relating to nervous system; research study; response; success; tool; visual stimulus

It is difficult to imagine neuroscience in 2015 without fMRI. No single method has been more influential in studying human cognition, with colorful maps in news outlets gradually raising the public awareness of neuroscientific progress. The fact that it is possible to look inside the head of an awake, behaving person to discover not only the detailed structure of their brain but also, to some extent, what they are thinking, is truly in the sphere of science fiction. At the same time, there is only so much information conveyed with an activity map, and the trajectory of the fMRI field is presently unclear. One of the major limiting factors of this method is the fact that its substrate for estimating brain activity is in a hemodynamic blood flow-based signal, which is quite a bit removed from the electrical activity of neurons that are at the core of our cognition. While the measured fMRI signal at a given point in the brain is known to reflect local neural activity, and is in this sense better than other human methods such as EEG and MEG, it does so in a manner that is very coarse, both in its timing and in its spatial precision. There is a general need to understand how measured fMRI signals might relate to underlying neural activity. There is a range of approaches to understanding this fMRI/neural relationship. In some laboratories, experiments are aimed at carefully determining what types of neurons and molecules serve as the actual mediators for regulating blood flow. Such experiments ask, what are the biological principles, and specific mechanisms, that determine neurovascular coupling? Our approach is somewhat different and focuses on more targeted and practical questions. One such question asks how does the firing of a single neuron, or a population of neurons, contribute to the measured fMRI response within a small volume of the brain, or voxel? Consider the following: When measuring brain activity with fMRI, the smallest unit of brain activity--the electron so to speak--is a voxel that is at least a millimeter in each dimension, often much more. As neurons are much smaller and packed in high density, each voxel in the brain contain hundreds of thousands of individual neurons. We know from direct recordings of such neurons that neural responses in such a volume are diverse. One can see this local diversity when observing spontaneous brain activity, or even under conditions of visual stimulation. For example, neighboring neurons within a single voxel respond very differently when a subject is viewing a video sequence. Yet, if all of the neurons respond differently at a given moment in time, then how can the hemodynamic signal from the point in the brain be interpreted in terms of neural firing? Would the fMRI signal reflect the mean neural activity in the population? Are there particular, special neurons that determine the fMRI signal? And would the relationship remain fixed, both during periods of stimulation and rest in which visual input is minimized? At present, there are several projects investigating these and related questions in the lab, with three papers on this topic published in the last year. In one project, we are taking a multimodal approach, combining implanted multielectrodes with fMRI to directly measure the relationship between fMRI and neural signals. In one project, we are focusing on spontaneous neural activity. Specifically, we are using the spiking responses of individual neurons to create functional activity maps of the brain. Our initial results, to be presented in two posters at this years society for Neuroscience meeting (Godlove et al., SFN Abstr (2015); Mpamaugo et al, SFN Abstr (2015)) show that the firing fluctuations of individual neurons correlate with discrete and circumscribed regions in the brain. For a given neuron, these maps are repeatable across scans and across sessions. Moreover, adjacent neurons can elicit very different spatial maps, presumably reflecting their differential involvement in particular brain networks. This project is, we believe, the beginning of a research line that has the potential to yield a new perspective on the link between local neural selectivity and large-scale brain specialization. In another project studying spontaneous activity, my laboratory has recently contributed to three publications investigating spontaneous fMRI activity (Liu et al., NeuroImage (2014); Liu et al. Cerebral Cortex (2015); Monosov et al, Journal of Neuroscience (2015)). Experiments going on in the lab currently attempt to ask whether the activity in the basal forebrain may be a critical factor shaping spontaneous neural activity throughout the rest of the brain. The basal forebrain is a small region that is the origin of many long-range anatomical projections that reach virtually the entire cerebral cortex. Our initial experiments inactivating portions of this structure in animals undergoing fMRI testing suggests that the basal forebrain is strongly involved in regulation of spontaneous signals throughout the telencephalon, particularly during over transitions of arousal gauged by eye opening and closure. This work has led to the publication of two abstracts at last years Society for Neuroscience Meeting in Washington, DC (Chang et al, SFN Abstr (2014); Turchi et al, SFN Abstr (2014)), with at least one publication planned within the next year. Finally, as another approach toward understanding how the activity of neurons all within half a millimeter of one another could be so uncoupled with one another, we are presently attempting testing individual neurons with thousands of different static and dynamic visual stimuli to understand under what conditions they behave similarly and under what conditions they begin to diverge. At the same time, we are attempting to understand what aspects of this population activity most closely match the fMRI signal measured from the same point in visual cortex (Park et al., SFN Abstr (2015)). These findings may provide some insights into the complex relationship between neural responses, the relationship of neural firing within a population, and the larger relationship to hemodynamic regulation.

很难想象2015年没有fMRI的神经科学。在研究人类认知方面，没有任何一种方法比这种方法更有影响力，新闻媒体上的彩色地图逐渐提高了公众对神经科学进展的认识。通过观察一个清醒的、行为正常的人的大脑内部，不仅可以发现他们大脑的详细结构，而且在某种程度上还能知道他们在想什么，这一事实确实属于科幻小说的范畴。与此同时，活动图所传达的信息有限，功能磁共振成像领域的轨迹目前尚不清楚。这种方法的一个主要限制因素是，它用于估计大脑活动的基础是基于血流动力学的信号，这与我们认知核心的神经元的电活动有很大的不同。虽然已知在大脑中给定点测量的fMRI信号反映局部神经活动，并且在这个意义上比其他人类方法（如脑电图和脑磁图）更好，但它在时间和空间精度方面都非常粗糙。人们普遍需要了解测量到的fMRI信号是如何与潜在的神经活动联系起来的。