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Introduction
Published in Narayan Panigrahi, Saraju P. Mohanty, Brain Computer Interface, 2022
Narayan Panigrahi, Saraju P. Mohanty
Currently, the most widely used fMRI method is BOLD imaging, which detects the difference in magnetic susceptibility between oxygenated hemoglobin and deoxygenated hemoglobin. Hemoglobin is diamagnetic when oxygenated but paramagnetic when deoxygenated. The magnetic property of blood therefore depends on its oxygenation level. Although neuronal activities consume some oxygen, the increase in blood flow following neuronal activities supplies more oxygen than the neuronal consumption, resulting in an increase in oxygenated hemoglobin and therefore increased BOLD response. Although BOLD fMRI is an indirect measure of neuronal activities, there is strong empirical evidence that the BOLD signals are highly correlated with neuronal activities. Because the BOLD signals are usually stronger and require less time to acquire than perfusion signals, BOLD fMRI is more popular than perfusion fMRI.
Imaging of Hypoxia, Apoptosis, and Inflammation
Published in George C. Kagadis, Nancy L. Ford, Dimitrios N. Karnabatidis, George K. Loudos, Handbook of Small Animal Imaging, 2018
Stavros Spiliopoulos, Athanasios Diamantopoulos
MRI-based protocols for hypoxia include nuclear magnetic resonance spectroscopy, which detects abnormally increased tissue lactate levels and decreased ATP levels, as well as tissue pH. However, this modality demonstrates low sensitivity and spatial resolution (Gaertner et al. 2012). Blood oxygen level detection (BOLD) is a functional MRI application widely used for the detection of changes in tissue perfusion by the amount of oxygenated blood. However, the main limitation of BOLD is the fact that it cannot determine the level of oxygen in tissues or describe tumoral cellular modifications at a molecular level (Krishna et al. 2001). The most promising developing MRI technology in the field of hypoxia imaging is electron paramagnetic resonance imaging as it can detect cellular oxygen levels (Elas et al. 2003). Accordingly, PET imaging is still considered superior to the various MRI-based protocols for hypoxia imaging, while other in vivo imaging techniques include electron spin resonance and optical near-infrared techniques, which are presently under investigation (Brun et al. 1997).
Promises and Challenges in Translating Neurofunctional Research for Army Applications
Published in Steven Kornguth, Rebecca Steinberg, Michael D. Matthews, Neurocognitive and Physiological Factors During High-Tempo Operations, 2018
Functional (f)MRI is a technology that allows monitoring of blood flow in the brain. If one considers MRI to be a magnetic picture of the brain, fMRI is a magnetic movie. When neurons activate, they consume oxygen and the body responds by moving more oxygenated blood to the region of activity to refuel the neurons. Oxygenated blood looks different on a magnetic picture than deoxygenated blood that has refueled local neurons through oxygen metabolism. By snapping several magnetic pictures of the whole brain in rapid succession, our fMRI magnetic movie can be analyzed offline to determine where neural activity occurred in response to an external stimulus such as viewing an image. This is known as Blood Oxygen Level Dependent, or BOLD fMRI. Although other types of functional measurements exist in research, 95 percent of exams utilize the BOLD technique. In general, BOLD fMRI is currently considered synonymous with fMRI.
Discriminant subgraph learning from functional brain sensory data
Published in IISE Transactions, 2022
Lujia Wang, Todd J. Schwedt, Catherine D. Chong, Teresa Wu, Jing Li
The fMRI of each subject is a 4-D object, composed by 3-D brain images taken at a series of n time points. Each brain image includes many voxels as the basic units. At each voxel, the fMRI scan produces a time series measuring the dynamics of functional activity at that location, known as the blood oxygen level dependent (BOLD) signal. When studying a particular disease, it is commonplace to focus on a set of Regions of Interest (ROIs) of the brain related to the disease. Then, the voxel-wise BOLD signals within each ROI can be averaged into a ROI-wise signal. Let be the number of ROIs. For example, in our case study, corresponds to 33 ROIs based on a meta-study of the existing migraine literature (Chong et al., 2017). For each subject included in the study, let denote the BOLD signals of all the ROIs, i.e., is a matrix with representing the signal length.
Cognitive flexibility in humans and other laboratory animals
Published in Journal of the Royal Society of New Zealand, 2021
Quenten Highgate, Susan Schenk
There are several approaches that have been used to identify regions in the human brain involved in cognitive flexibility. Lesion studies measure cognitive flexibility in subjects with known brain damage, often caused by a traumatic head injury or medical complication. If they perform poorly, the region damaged becomes implicated in cognitive flexibility. Others use functional magnetic resonance imaging (fMRI) to measure changes in cerebral blood flow and oxygen concentrations (Blood Oxygen Level Dependent; BOLD). Regions with a greater BOLD response are more active at that current time (Evers et al. 2007). Changes in functional activity can be assessed in healthy subjects or cognitively inflexible psychiatric populations to determine the regions involved in normal and abnormal cognitive flexibility, respectively. These approaches have broadly implicated the frontal cortex and basal ganglia in WCST (Drewe 1974; Robinson et al. 1980; Stuss et al. 2000; Monchi et al. 2001), attentional set shifting (Owen et al. 1993; Pantelis et al. 1999; Rogers et al. 2000; Hampshire and Owen 2006), reversal learning (Kringelbach and Rolls 2003; Hornak et al. 2004; Cools et al. 2006; Kehagia et al. 2014), and task-switching (McDowell et al. 1998; Cools et al. 2004; Kim et al. 2011; Dang et al. 2012) performance.
The effects of Alzheimer's disease related striatal pathologic changes on the fractional amplitude of low-frequency fluctuations
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2020
BOLD response is a complex, nonlinear function of neuronal activity. The shape of the response depends both upon the applied stimulus and the hemodynamic response to neuronal events. There are different methods for modeling the BOLD signal. One of them is Balloon model which is non-linear physiological-based model, (Buxton et al. 1998). It describes the dynamics of cerebral blood volume and de-oxygenation and their effects on the resulting BOLD signal. The Balloon model is an input-state-output model with two state variables, volume (v) and deoxyhemoglobin content (q). A set of ordinary differential equations model the changes in blood volume, blood inflow, deoxyhemoglobin and flow-inducing signal, (Friston et al. 2003; Lindquist and Wager 2016).