SELF-ORGANIZATION OF BINOCULAR DISPARITY TUNING BY RECIPROCAL CORTICOGENICULATE INTERACTIONS

This article develops a neural model of how sharp disparity tuning can arise through experience-dependent development of cortical complex ce lls. This learning process clarifies how complex cells can binocularly match left and right eye image features with the same contrast polari ty, yet also pool signals with opposite contrast polarities. Antagonis tic rebounds between LGN ON and OFF cells and cortical simple cells se nsitive to opposite contrast polarities enable anticorrelated simple c ells to learn to activate a shared set of complex cells. Feedback from binocularly tuned cortical cells to monocular LGN cells is proposed t o carry out a matching process that dynamically stabilizes the learnin g process. This feedback represents a type of matching process that is elaborated at higher visual processing areas into a volitionally cont rollable type of attention. We show stable learning when both of these properties hold. Learning adjusts the initially coarsely tuned dispar ity preference to match the disparities present in the environment, an d the tuning width decreases to yield high disparity selectivity, whic h enables the model to quickly detect image disparities. Learning is i mpaired in the absence of either antagonistic rebounds or corticogenic ulate feedback. The model also helps to explain psychophysical and neu robiological data about adult 3-D vision.