Open AccessNeural bases of self‐ and object‐motion in a naturalistic vision
Author(s) -
Pitzalis Sabrina,
Serra Chiara,
Sulpizio Valentina,
Committeri Giorgia,
Pasquale Francesco,
Fattori Patrizia,
Galletti Claudio,
Sepe Rosamaria,
Galati Gaspare
Publication year - 2020
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.24862
Subject(s) - computer vision , motion (physics) , artificial intelligence , structure from motion , computer science , object (grammar) , motion field , functional magnetic resonance imaging , displacement (psychology) , optical flow , neuroscience , psychology , psychotherapist , image (mathematics)
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.