The human brainstem is a highly complex structure where even small lesions can give rise to a variety of symptoms and outward signs. Localising the area of dysfunction within the brainstem is often a difficult task. To make localisation easier, a neural net system has been developed which uses 72 clinical and neurophysiological data inputs to provide a display (using 5268 voxels) on a three-dimensional model of the human brainstem. The net was trained by means of a back-propagation algorithm, over a pool of 580 example cases. Assessed on 200 test cases, the net correctly localised 83.6% of the target voxels; furthermore the net correctly localised the lesions in 31 out of 37 patients. Because this computer-assisted method provides reliable and quantitative localisation of brainstem areas of dysfunction and can be used as a 3D interactive functional atlas, it is expected to prove useful as a diagnostic tool for assessing focal brainstem lesions.