title: Informational theories of consciousness: a review and extension.
abstract: In recent years a number of people have suggested that there is a close link between conscious experience and the differentiation and integration of information in certain areas of the brain. The balance between differentiation and integration is often called information integration, and a number of algorithms for measuring it have been put forward, which can be used to make predictions about consciousness and to understand the relationships between neurons in a network. One of the key problems with the current information integration measures is that they take a lot of computer processing power, which limits their application to networks of around a dozen neurons. There are also more general issues about whether the current algorithms accurately reflect the consciousness associated with a system. This paper addresses these issues by exploring a new automata-based algorithm for the calculation of information integration. To benchmark different approaches we implemented the Balduzzi and Tononi algorithm as a plugin to the SpikeStream neural simulator, and used it to carry out some preliminary comparisons of the liveliness and Φ measures on simple four neuron networks.
authors: Department of Electrical Engineering, Imperial College, London SW7 2BT, UK. i.aleksander@imperial.ac.uk
authors: Igor
authors: I
authors: Aleksander
authors: David
authors: D
authors: Gamez
mesh_terms: D003196:Computer Graphics; D003198:Computer Simulation; D003243:Consciousness; D006801:Humans; D008962:Models, Theoretical; D009474:Neurons / Q000502:physiology; D012984:Software