Computational Aspects of Transient Brain Dynamics Experimental Evidence and Implications for New AI Approaches
Robert Kozma
Department of Computer Science, University of Massachusetts Amherst, MA, USA
Department of Mathematical Sciences, University of Memphis, TN, USA
Abstract
Recent progress with high-resolution brain imaging techniques, including functional
Magnetic Resonance Imaging (fMRI), Magnetoencephalography (MEG), Positron
Emission Tomography (PET), Electro-Corticography (ECoG), and ElectroEncephalography (EEG), demonstrates an amazing vista on the complex spatio-temporal
dynamics of cortical processes. Experiments show that the brain generates intermittent
synchronization-desynchronization transitions and that these transients correlate with
higher cognitive activity.
In this talk we summarize key results of brain imaging experiments and introduce
computational models of the observed brain oscillations and cognitive processing. We
elaborate on a neurodynamics approach, according to which brains are viewed as open
thermodynamic systems converting sensory data into meaningful knowledge during
repetitive phase transitions. We employ random graph theory and generalized percolation
processes to model experimental findings. Cortical phase transitions are viewed as neural
correlates of higher cognition, which can be implemented in computers to develop new
principles of intelligent computing and superior AI.
BIO:
Robert Kozma (Fellow of IEEE, Fellow of INNS) is Professor of Mathematical Sciences,
the University of Memphis, TN, and Professor of Computer Science at University of
Massachusetts Amherst, MA, USA. Dr. Kozma holds a Ph.D. in Physics (Delft,
Netherlands, 1992), two M.Sc. degrees (Mathematics, Budapest, Hungary 1988; and
Power Engineering, Moscow, Russia, 1982). He had a joint appointment with the
Division of Neurobiology and the EECS at UC Berkeley (1998-2000), and has held many
visiting positions, including at NASA/JPL, Sarnoff Co., Princeton, NJ; Lawrence
Berkeley Laboratory (LBL), and AFRL, Dayton, OH. He worked as Research Fellow at
the Hungarian Academy of Sciences, Budapest, Hungary. He has been Associate
Professor at Tohoku University, Sendai, Japan, Lecturer at Otago University, Dunedin,
New Zealand.
His research is focused on computational neurodynamics, large-scale brain networks, and
applying biologically motivated and cognitive principles for the development of
intelligent systems. He has published 8 books, 300+ papers, and two patents. His research
has been supported by NSF, NASA, JPL, AFRL, DARPA, FedEx, and by other agencies.
He is President of INNS (2017-2018), serves on the Board of IEEE SMC Society (20162018); has served on the AdCom of the IEEE Computational Intelligence Society (20092012) and on the Board of Governors of the International Neural Network Society (20072012). He has been General Chair of IJCNN2009, Atlanta, USA. Dr. Kozma is the
recipient of the INNS Gabor Award.