title: Unsmearing visual motion: Development of long-range horizontal intrinsic connections creator: Martin, K.E. creator: Marshall, J.A. subject: Artificial Intelligence subject: Machine Learning subject: Machine Vision subject: Neural Nets subject: Statistical Models subject: Perceptual Cognitive Psychology description: Human vision systems integrate information nonlocally, across long spatial ranges. For example, a moving stimulus appears smeared when viewed briefly (30 ms), yet sharp when viewed for a longer exposure (100 ms) (Burr, 1980). This suggests that visual systems combine information along a trajectory that matches the motion of the stimulus. Our self-organizing neural network model shows how developmental exposure to moving stimuli can direct the formation of horizontal trajectory-specific motion integration pathways that unsmear representations of moving stimuli. These results account for Burr's data and can potentially also model other phenomena, such as visual inertia. publisher: San Mateo: CA: Morgan Kaufman contributor: Hanson, S. J. contributor: Cown, J. D. contributor: Giles, G. L. date: 1993 type: Book Chapter type: NonPeerReviewed format: application/postscript identifier: http://cogprints.org/441/2/smear9305.ps identifier: Martin, K.E. and Marshall, J.A. (1993) Unsmearing visual motion: Development of long-range horizontal intrinsic connections. [Book Chapter] relation: http://cogprints.org/441/