title: Integrative activity of neural networks may code virtual spaces with internal representations.
abstract: It was shown recently in neuroimaging that spatial differentiation of brain activity provides novel information about brain function. This confirms the integrative organisation of brain activity, but given present technical limitations of neuroimaging approaches, the exact role of integrative activity remains unclear. We trained a neural network to integrate information using random numbers so as to imitate the "centre-periphery" pattern of brain activity in neuroimaging. Only the hierarchical organisation of the network permitted the learning of fast and reliable integration. We presented images to the trained network and, by spatial differentiation of the network activity, obtained virtual spaces with the presented images. Thus, our study established the necessity of the hierarchical organisation of neural networks for integration and demonstrated that the role of neural integration in the brain may be to create virtual spaces with internal representations of the objects.
authors.affiliation: CNRS, CERCO, UMR 5549, Faculté de Médecine de Rangueil, Pavillon Baudot CHU Purpan, BP 25202, 31052 Toulouse Cedex, France. Electronic address: kuzma@cerco.ups-tlse.fr.
authors.forename: Kuzma
authors.initials: K
authors.lastname: Strelnikov
mesh_terms: D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D006801:Humans; D008279:Magnetic Resonance Imaging; D016571:Neural Networks, Computer; D013028:Space Perception / Q000502:physiology*
keywords: Brain activity; Integrative; Internal representations; Neural coding