title: Connectionism and an inescapable defect.
abstract: Linear connectionist models of neurocomputing show how input patterns may be recognized, stored, compared, and recalled for output in serial-parallel, quasi-Hebbian networks. This aids the design of hardware and software for better robotics, while offering useful insights to neuroscientists studying sensorimotor systems, but connectivity via quasi-Hebbian nodes and back-propagation layers alone cannot show us how vertebrate cerebellum, allocortex, and neocortex work.
authors: ERBP Laboratory, Milledgeville GA 31061.
authors: H
authors: H
authors: Stowell
mesh_terms: D000818:Animals; D001921:Brain / Q000502:physiology*; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009424:Nervous System Physiological Phenomena