title: Where the abstract feature maps of the brain might come from.
abstract: Three types of neuronal organization can be called 'brain maps': sets of feature-sensitive cells, ordered projections between neuronal layers and ordered maps of abstract features. The latter are most intriguing as they reflect the central properties of an organism's experiences and environment. It is proposed that such feature maps are learned in a process that involves parallel input to neurons in a brain area and adaptation of neurons in the neighborhood of the cells that respond most strongly to this input. This article presents a new mathematical formulation for such adaptation and relates it to physiological functions.
authors: Neural Networks Research Centre, Helsinki University of Technology, Espoo, Finland.
authors: T
authors: T
authors: Kohonen
authors: R
authors: R
authors: Hari
mesh_terms: D000465:Algorithms; D001921:Brain / Q000166:cytology; D006801:Humans; D007858:Learning / Q000502:physiology; D008959:Models, Neurological; D009024:Morphogenesis; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D009474:Neurons / Q000145:classification / Q000502:physiology*; D009569:Nitric Oxide / Q000502:physiology; D012660:Semantics; D013569:Synapses / Q000502:physiology
chemical_list: D009569:Nitric Oxide