Neural bases of self‐ and object‐motion in a naturalistic vision

Abstract

To plan movements toward objects our brain must recognize whether retinal displacement is due to self‐motion and/or to object‐motion. Here, we aimed to test whether motion areas are able to segregate these types of motion. We combined an event‐related functional magnetic resonance imaging experiment, brain mapping techniques, and wide‐field stimulation to study the responsivity of motion‐sensitive areas to pure and combined self‐ and object‐motion conditions during virtual movies of a train running within a realistic landscape. We observed a selective response in MT to the pure object‐motion condition, and in medial (PEc, pCi, CSv, and CMA) and lateral (PIC and LOR) areas to the pure self‐motion condition. Some other regions (like V6) responded more to complex visual stimulation where both object‐ and self‐motion were present. Among all, we found that some motion regions (V3A, LOR, MT, V6, and IPSmot) could extract object‐motion information from the overall motion, recognizing the real movement of the train even when the images remain still (on the screen), or moved, because of self‐movements. We propose that these motion areas might be good candidates for the “flow parsing mechanism,” that is the capability to extract object‐motion information from retinal motion signals by subtracting out the optic flow components.