Our previous works showed that feed forward models cannot fully explain the mechanism of object/face representation especially in the challenging conditions. Thus, we aimed to investigate about the possible neural mechanism explaining the brain behavior in challenging conditions like object/face recognition with rotation of views in depth and plane, illumination variations and occlusion.
Object/Face recognition, using represented information over time required a temporal decision making mechanism. This mechanism is different from classical classifiers implemented in the object recognition models. Thus, our second goal is to understand that how the brain integrates temporal senso ry information to commit to a choice.
Our minds conveniently interact to each other to use one of the most prevalent and essential information in daily life: Social Information. Using computational approaches derived primarily form individual decision making, we aimed to understand social decision making by multi-dimensional and inter-connected individual models. Through this approach, our goal is to bridge the gap between decision making in the isolated and social context.
Ebrahimpour [at] ipm [dot] ir
afarzmahdi [at] ipm [dot] ir
s.zabbah [at] ipm [dot] ir
jimi.esmaily [at] gmail [dot] com