Neglect is an acquired cognitive disorder characterized by a lack of processing of one side of a stimulus or representational space. There are hemispheric asymmetries in its cause and in its effects, but implemented computational models of neglect have tended not to incorporate this fact. The authors report a series of neural network simulations of the line-bisection task. They test the hypothesis that simple, neuroanatomically realistic principles of connectivity in the nervous system can produce emergent behaviors that capture a wide range of quantitative and qualitative data observed in neglect patients presenting with general visuospatial neglect. They demonstrate that exploring low-level architectural principles in implemented computational models is both a productive avenue of research and offers the most parsimonious explanations of behaviors observed in patients.