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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.
Biomedical Imaging Magnetic Resonance Imaging
Published in Lawrence S. Chan, William C. Tang, Engineering-Medicine, 2019
MRI is useful for imaging not only anatomy, but also functions. In neurofunctional imaging, BOLD contrast is a primary contrast mechanism based on which the vast majority of functional MRI (fMRI) studies have been performed. When neurons are activated, the increased need for oxygen is overcompensated by a larger increase in delivery of oxygenated blood supply. As a result, the venous oxyhemoglobin concentration increases and the deoxyhemoglobin concentration decreases. Because oxyhemoglobin is diamagnetic while deoxyhemoglobin paramagnetic, the T2* value in the activated areas increases, resulting in an elevated MRI signal intensity in a T2*-weighted image (Ogawa et al. 1990). Conversely, when there is no neuronal activation, a lower signal intensity is expected. This alternating signal pattern can be correlated to the task-on and task-off states according to a pre-designed paradigm for investigating a specific neurocognitive function (Kwong et al. 1992).
fMRI and Nanotechnology
Published in Sarhan M. Musa, Nanoscale Spectroscopy with Applications, 2018
Aditi Deshpande, George C. Giakos
The basic fMRI scan uses the BOLD as the contrast parameter to image the brain function. New biomarkers are being studied and tested to provide better enhanced contrast [15]. These include temperature and calciumsensitive agents. As the burning of glucose raises temperature, it can act as a marker of brain activity. We know that action potentials travel through neurons and other cells via calcium channels. It is now possible to track calcium as it flows into the neurons when they activate. Thus, calcium-sensitive compounds can be used as biomarkers for brain function. Researchers at the McGovern Institute for Brain Research at MIT have developed calciumsensitive contrast agents at the nano-sized level, which the MRI scanner can detect [17]. Their proposed technique of using calcium-sensitive nanoparticles overcomes the two main limitations of conventional fMRI—the time lag between neural activity and corresponding hemodynamic changes and the slightly decreased spatial resolution due to the compact spacing of tiny blood vessels. This is achieved due to the fact that calcium enters neurons almost immediately as they get activated and the potential shoots up. With increased activation levels, the amount of calcium and the rapidness of its inflow increase too. Thus, calcium provides a direct measure of the brain activity. The design of this method shall be elaborated on later in the chapter.
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).
A Novel Machine Learning Based Framework for Detection of Autism Spectrum Disorder (ASD)
Published in Applied Artificial Intelligence, 2022
Hamza Sharif, Rizwan Ahmed Khan
It is important to note that studies that combine machine learning with brain imaging data collected from multiple sites like ABIDE (Di Martino et al. 2014) to identify Autism demonstrated that classification accuracy tends to decreases (Arbabshirani et al. 2017). In this study we also observed same trend. Nielsen et al. (Nielsen et al. 2013) also discovered the same pattern/trend from ABIDE dataset and also concluded that those sites with longer BOLD imaging time significantly have higher classification accuracy. In contrast, Blood Oxygen Level Dependent (BOLD) is an imaging method used in fMRI to observe active regions using blood flow variation. In those regions, blood concentration appears to be more active than in other regions (Huettel, et al., 2004).