The functionality of the human brain is still relatively unknown although much effort has been put into revealing its secrets. A new tool for this purpose is functional Magnetic Resonance Imaging (fMRI). The aim in fMRI is to map cognitive, motor and sensor functions to specific areas in the brain. The physical basis for the method is the fact that oxygenated and deoxygenated blood have different magnetic properties. When a neuron in the brain is active it consumes oxygen, which is supplied by the blood. To compensate for the increased rate of oxygen consumption in an active brain area, the bloodflow and the oxygenation level of the blood to this area are increased. This increase can be measured in a magnetic resonance scanner. Thus, we can locate areas of brain activity indirectly by locating areas with elevated blood oxygen levels.

To map e.g. the sensory function of the right index finger, one can for instance stimulate the finger on a volunteer with a brush, while images of the brain continuously are acquired by the MR-scanner. The scanner produces image-slices like the one below. During the stimulation of the finger there is an increase in image intensity (i.e. the active area becomes brighter) compared to a resting state. Thus, to detect activity we need to compare an image where the finger is stimulated by the brush to an reference image acquired in a resting state. The areas where the "activated" image are brighter than image acquired in the "rest"-state are areas activated when the brush stimulates the finger.

To capture the dynamics of the brain we must acquire each image-slice rapidly. Unfortunately, this makes the images heavily contaminated by random noise. Hence, it is not enough to acquire just one image in activity and one in rest, since it is likely that we can not detect any significant change in intensity due to the high noise level. For this reason typically 75 to 100 slices are acquired in each state of activity and rest respectively, in order to obtain a more reliable result.

The experiment is often divided into blocks where the volunteer alternately is asked to rest and to perform an activity. This is called the paradigm and it is viewed graphically to the right. At each dot an image is acquired. In our finger stimulation example above, the activity periods consist brushing the finger with the brush and the rest periods consist of just pure relaxation.

Now, we have collected a series of images where the volunteers right index finger was brushed and where the volunteer rested, according to the paradigm. We look for areas where the intensity in the image follows the paradigm. The image below illustrates the intensity values at a pixel when we look at it through time. Clearly, the pixel marked by green has an intensity-timecourse which has no resemblance at all to the paradigm, and we conclude that the finger-brushing did not affect this area of the brain. However, if we look at the pixel marked by blue we see a close match to the paradigm, and thus this area is activated when the brush stimulates the finger. It is not possible to inspect every pixel manually, we need a computer to do this automatically and to classify each pixel as "activated" or "nonactivated". The image below shows the final result from an experiment involving hand movement. Areas active during right hand movement are marked by green and areas active during left hand movement are marked by red.