Pitch Acts as a Distractor in Optimal Estimation of Yaw in Dynamic Natural Scenery

Estimating motion as a function of visual signals is an important biological problem that is behaviorally relevant to many organisms. The need for efficient and accurate estimators of motion implies there is a strong evolutionary pressure for biological systems to develop optimal estimators of motion. However, surprisingly, many biological motion estimators have strong systematic biases. One possible explanation for this is these biases arise in response to features of the statistics of natural scenes. Here, we computationally investigate this problem in the context of the blowfly (Calliphora vicina) visual system. To do this, we first sampled the joint distribution of fly visual inputs and motion traces with a specially designed "FlEye" camera equipped with joint gyroscope and accelerometer. Using this library of motion traces, we were then able to computationally construct and investigate a family of optimal local estimators of yaw. We show that conditioning yaw estimation on pitch intensity significantly changes the qualitative behavior of the optimal estimator. Higher absolute pitch intensity results in a more diffuse yaw estimator, suggesting pitch acts as a distractor motion in yaw estimation. This distractor behavior mimics previous results found in the motion encodings of a wide-field motion sensitive cell in the blowfly visual system, suggesting that this form of interference is relevant in a biological context.