Decoding of information from distributed motor maps

Two possible methods for decoding the saccadic command vector from distributed neural activity in the superior colliculus (SC) are vector summation (VS) and center of mass (CM). It has been suggested that the pattern of eye movement errors obtained following the placement of a collicular lesion can distinguish between these two mechanisms. We lesion a recurrent neural network model of the SC and show that the pattern of saccadic errors obtained appears to support the CM hypothesis, even though the model colliculus is decoded by VS. In addition, model saccade trajectories are not curved. The former result demonstrates that an explicit CM computation is not needed to reproduce physiological results, that have previously been taken to support the CM hypothesis. The latter result has implications for the role of the SC in the feedback loop thought to control saccadic trajectory.