Developmental robotics focuses on how to endow robots with adaptive capabilities. Even though embodiment has been recognized as an essential factor for understanding development, there is yet not much work that investigates how the morphology of sensors and actuators shapes adaptivity and learning processes. Moreover, these studies are largely at an intuitive and qualitative level. In this paper, we address the issue by studying how in an active vision system sensor morphology and bodily features affect a behavior such as vergence. Specifically, we present an information-theoretic analysis of two experiments showing how adequate sensor morphology influences statistical dependencies in the sensorimotor loop. The results show that an appropriate morphology reduces the amount of input without disrupting the information structure in the sensorimotor loop. The second result shows how the later morphology under the vergence behavior increases the information structure among the motor actions and the pixels. We also speculate on the implications of our results for attention, reaching and grasping.