Concept

Blood-oxygen-level-dependent imaging

Summary
Blood-oxygen-level-dependent imaging, or BOLD-contrast imaging, is a method used in functional magnetic resonance imaging (fMRI) to observe different areas of the brain or other organs, which are found to be active at any given time. Neurons do not have internal reserves of energy in the form of sugar and oxygen, so their firing causes a need for more energy to be brought in quickly. Through a process called the haemodynamic response, blood releases oxygen to active neurons at a greater rate than to inactive neurons. This causes a change of the relative levels of oxyhemoglobin and deoxyhemoglobin (oxygenated or deoxygenated blood) that can be detected on the basis of their differential magnetic susceptibility. In 1990, three papers published by Seiji Ogawa and colleagues showed that hemoglobin has different magnetic properties in its oxygenated and deoxygenated forms (deoxygenated hemoglobin is paramagnetic and oxygenated hemoglobin is diamagnetic), both of which could be detected using MRI. This leads to magnetic signal variation which can be detected using an MRI scanner. Given many repetitions of a thought, action or experience, statistical methods can be used to determine the areas of the brain which reliably have more of this difference as a result, and therefore which areas of the brain are most active during that thought, action or experience. Although most fMRI research uses BOLD contrast imaging as a method to determine which parts of the brain are most active, because the signals are relative, and not individually quantitative, some question its rigor. Other methods which propose to measure neural activity directly have been attempted (for example, measurement of the Oxygen Extraction Fraction, or OEF, in regions of the brain, which measures how much of the oxyhemoglobin in the blood has been converted to deoxyhemoglobin), but because the electromagnetic fields created by an active or firing neuron are so weak, the signal-to-noise ratio is extremely low and statistical methods used to extract quantitative data have been largely unsuccessful so far.
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