Many factors can influence, or bias, human decision making. A considerable amount of research has investigated the neural correlates of such biases, mostly correlating hemodynamic responses in brain areas with some aspect of the decision. These studies, typically done using Functional Magnetic Resonance ImagingFunctional Magnetic Resonance Imaging (fMRI)A functional neuroimaging procedure using MRI technology that measures brain activity by detecting changes associated with blood flow. This technique relies on the fact that cerebral blood flow and neuronal activation are coupled. When an area of the brain is in use, blood flow to that region also increases.[citation needed] The primary form of fMRI uses the blood-oxygen-level dependent (BOLD) contrast, discovered by Seiji Ogawa. This is a type of specialized brain and body scan used to map neural activity in the brain or spinal cord of humans or other animals by imaging the change in blood flow (hemodynamic response) related to energy use by brain cells. Since the early 1990s, fMRI has come to dominate brain mapping research because it does not require people to undergo shots, surgery, or to ingest substances, or be exposed to ionising radiation, etc. or positron emission tomography, have provided useful information about the location of processing in the brain. However, comparatively little research has examined when these processes occur. The present experiment addressed this question by using Magnetoencephalography Magnetoencephalography (MEG)A noninvasive technique that detects magnetic fields above the surface of the head produced by postsynaptic potentials in the brain. to record brain activity while subjects chose preferred options from decision sets. We found that MEGMagnetoencephalography (MEG)A noninvasive technique that detects magnetic fields above the surface of the head produced by postsynaptic potentials in the brain. signal deviations for biased decisions occurred as early as 250-750 ms following stimulus onset. Such deviations occurred earliest in sensors over the right anterior cortex. These findings improve our understanding of temporal dynamics of decision biases and suggest ways that existing explanations for this bias could be refined.