2018/06/04 by Paolo Zanardi, Zanardi, Paolo, Michael Tomka +3
Computer Science · Engineering · Neuroscience · Physics and Astronomy · #Advanced Memory and Neural Computing #FOS: Physical sciences #Neural Networks and Applications #Neural dynamics and brain function #Quantum Physics (quant-ph) #quant-ph
paper · pdf · doi:10.48550/arxiv.1806.01421
15 pages, 7 figures
openalex publication_date 2018/06/04 · arxiv created 2018/12/09 · arxiv updated 2018/12/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Integrated Information Theory (IIT) has emerged as one of the leading research lines in computational neuroscience to provide a mechanistic and mathematically well-defined description of the neural correlates of consciousness. Integrated Information (Φ) quantifies how much the integrated cause/effect structure of the global neural network fails to be accounted for by any partitioned version of it. The holistic IIT approach is in principle applicable to any information-processing dynamical network regardless of its interpretation in the context of consciousness. In this paper we take the first steps towards a formulation of a general and consistent version of IIT for interacting networks of quantum systems. A variety of different phases, from the dis-integrated (Φ=0) to the holistic one (extensive logΦ), can be identified and their cross-overs studied.