Neurophysiology and neuroimaging evidence suggests that the brain represents multiple environmental and body-related features in order to compute transformations from sensory input to motor output. However, it is unclear how these features interact to facilitate the necessary sensorimotor transformations. To investigate this issue, we examined the representations of sensory and motor features of hand movements within the left-hemisphere motor network. In a rapid event- related functional magnetic resonance imaging (fMRI) design, we measured blood oxygen level dependent (BOLD) brain activity as participants performed right-handed movements at the wrist, with either of two postures and two amplitudes, to move a cursor to targets at different locations. Using a multi-voxel analysis technique with rigorous generalization tests, we reliably distinguished the representations of task-related features (primarily target location, movement direction, and posture) in multiple regions. Generalization tests also identified two interactions: One interaction was between the decoding of target location and movement direction in the superior parietal lobule, which may underlie a transformation from the location of the target in space to movement vector. Additionally, there was an interaction between movement direction and posture in primary motor, premotor, and parietal regions--a requisite step in combining extrinsic and intrinsically organized information. Together, these results reveal the complex interactions between different sensory and motor features that drive the computation of sensorimotor transformations.