Péter Érdi

Henry R. Luce Professor

Center for Complex Systems Studies
Department of Physics
Department of Psychology
Kalamazoo College
Kalamazoo, MI 49006
1200 Academy Street
(269) 337-5720

Email: perdi@kzoo.edu

Editor-in-Chief Cognitive Systems Research
Vice President for Membership (2017-) International Neural Network Society
Member of the Board of Governors (2012-2014, 2015-2017) of the International Neural Network Society
Senior Member of the International Neural Network Society
Member of the IEEE Computational Intelligence Society University Curriculum Subcommittee
Member of the FENS-IBRO European Neuroscience Schools Programme
Member of the Editorial and Programme Advisory Board of the Springer Complexity publishing program
Councilor at Large: The Michigan Chapter of the Society for Neuroscience (2013-2014)
Member of the Scientific Advisory Board of the EPJ Nonlinear Biomedical Physics
Member of the
International Editorial Board of the Neural Network World
Associate Editor of BioSystems
Member of the Executive Commitee of the European Neural Network (2002-2009) Society
Member of the Editorial Board of the Journal of Applied System Studies
Member of the Editorial Board of the Cognitive Neurodynamics
Member of Brain and Mind's Editorial Board (2000-2003)
Member of the Society for Chaos Theory in Psychology & Life Sciences.
Associate Editor of Neurobiology
Member of the Editorial Board Natural Computing.
Member of the Editorial Board Progress in Neuropsychopharmacology
Prof. Péter Érdi -- 2007
Picture taken in January, 2002

Prof. Péter Érdi -- 2008
Picture taken in February, 2008
Prof. Péter Érdi -- 2012
Picture taken in July, 2012
Prof. Péter Érdi --
Picture taken in December, 2016

Talks etc in 2017

Talks etc in 2016

Talks etc in 2015

Talks etc in 2014

Talks etc in 2013

Prediction of Emerging Technologies: Using Patent Citation Networks Analysis

Talks etc in 2012

Talks in 2011

Research Interests

Computational Neuroscience

Multiple modeling strategies to describe neurodynamic phenomena: single-cell, multi-level, and population models may be set up to study different dynamical neural phenomena. Computational psychiatry, computational neuropharmacology: Budapest Computational Neuroscience Group

Computational Neurology and Psychiatry Peter Erdi, Basabdatta Sen Bhattacharya and Amy L. Cochran (Editors)

Anxiety: A common effect of various types of drugs that reduce behaviors characteristic of anxiety is the reduced frequency of a slow oscillatory activity called hippocampal theta rhythm. The frequency of hippocampal theta rhythm increases linearly with the intensity of electrical stimulation to a region of the brainstem. The reduction of mean frequency and the slope of this linear relationship between stimulation intensity and theta frequency predicts the clinical efficacy of anxiolytic drugs. Combined physiological - computational studies help to uncover neural mechanisms. The purpose of this research was to investigate the mechanisms by which anxiolytics produce this characteristic effect on the slope and intercept of the stimulus-frequency relationship of hippocampal theta.

Schizophrenia: is a complex disease of very diverse symptoms and mostly unknown causes. A possible underlying phenomenon is described by the "disconnection syndrome" hypothesis, when the control signal flow between cortical areas is impaired. We examine dthe differences in the causal connection patterns and strengths between healthy and schizophrenic subjects.

Stochastic Modeling of Gene Expression

Stochastic kinetics of the circular gene hypothesis: feedback effects and protein fluctuations

Computational Social Science

Social network analysis is focused on searching and finding for the patters of people's interaction and has a grand tradition in sociology.

Prediction of technological development Vision: Identification of branches of technologies based on patent citation data Identification of patterns how these branches develop, such as rapid growth, shrinking, split and merges Identification of governing rules that are able to explain the pattern (backtesting) Come up with predictions for the near future: Which are the technologies of tomorrow?

Recently formal models also analyzed the evolution of structure of social and related networks.
Our main intention is to narrow the gap between the two perspectives and build realistic models by incorporating elements taken from both bodies of knowledge

In the news:
New Scientist, June 30th, 2012
Communications of the ACM, September 2012


Péter Érdi and Gábor Lente:Stochastic Chemical Kinetics. Theory and (Mostly) Systems Biological Applications (Springer Series in Synergetics) . Springer, 2014
Péter Érdi: Complexity Explained. Springer, 2007
Péter Érdi and János Tóth: Mathematical Models of Chemical Reactions: Theory and Applications of Deterministic and Stochastic Models. Princeton University Press
Michael A Arbib, Péter Érdi and János Szentágothai: Neural Organization: Structure, Function, and Dynamics. The MIT Press
Recent Papers


Péter Érdi teaches courses on different interdisciplinary topics: