Péter Érdi

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

Dynamic modeling of associative learning in schizophrenia.

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 the differences in the causal connection patterns and strengths between healthy and schizophrenic subjects.

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

A (not so) New Book!

Péter Érdi: Complexity Explained. Springer, 2007

Two (even older, but still excellent :-)) books

	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

• M San Miguel, JH Johnson, J Kertesz, K Kaski, A Díaz-Guilera, RS.MacKay, V Loreto, P Érdi, D Helbing: Challenges in Complex Systems Science (under revision)
• M Bányai, B Ujfalussy, V Diwadkar and P Érdi: Impairments in the prefronto-hippocampal interactions explain associative learning deficit in schizophrenia BMC Neuroscience, 12(Suppl 1):93, 2011.
• P Érdi, M Bányai, B Ujfalussy, V Diwadkar: The schizophrenic brain: A broken hermeneutic circle. Some new insights and results The 2011 International Joint Conference on Neural Networks (IJCNN), 2011. San José, CA, USA 3024-3027, 2011.
• Érdi P.: review on Cutsuridis et al. (eds): Perception¿action cycle. Models, architectures, and hardware Cognitive Neurodynamics, 5(411-412), 2011
• Bányai M, Diwadkar V, Érdi P: Model-based dynamical analysis of functional disconnection in schizophrenia NeuroImage, 58(3): 870-877, 2011.
• Érdi P: Towards a Post-Keplerian social science: Comments by P. Érdi on the Visioneer white papers by D. Helbing and S. Balietti. European Physical Journal, Special Topics, 195:147-151, 2011.
• Érdi P: Scope and Limits of Predictions by Social Dynamic Models: Crisis, Innovation, Decision Making. Evolutionary and Institutional Economics Review, 7(1): 21-42
• Gore CD, Bányai M, Gray PM, Diwadkar V, Érdi P: Pathological Effects of Cortical Architecture on Working Memory in Schizophrenia. Pharmacopsychiatry 43(Suppl 1)592-597,2010
• P. Érdi, T. Kiss, B. Ujfalussy : Multi-level models. In Hippocampal Microcircuits, eds. Vassilis Cutsuridis, Bruce Graham, Stuart Cobb, and Imre Vida. Springer 2010. pp. 527-554.
• B. Ujfalussy, T Kiss, P. Érdi: Parallel Computational Subunits in Dentate Granule Cells Generate Multiple Place Fields. In PLoS Comput Biol 5(9):e1000500, 2009
• Jones BD, Zalányi L, Baumgartner F and Érdi P: Dynamic Threshold Modeling of Budget Changes. In Proc. AAAI Fall Symp.; Complex Adaptive Systems and the Threshold Effect: Views from the Natural and Social Sciences. pp 61-66, 2009
• Drutchas G and Érdi P Dynamics of Price Sensitivity and Market Structure in an Evolutionary Economic Matching Model. In Proc. AAAI Fall Symp.; Complex Adaptive Systems and the Threshold Effect: Views from the Natural and Social Sciences, AAA Press, pp 39-46, 2009
• Érdi P., Ujfalussy B., Diwadkar V.: The schizophrenic brain: A broken hermeneutic circle. In Neural Network World 19(413-427)2009
• Zsófia Huhn, Zoltán Somogyvári, Tamás Kiss, Péter Érdi: Distance Coding Strategies based on the Entorhinal Grid Cell System. In Neural Networks 22(5-6): 536-543, 2009
• Katherine J. Strandburg, Gábor Csárdi, Jan Tobochnik, Péter Érdi, László Zalányi : Patent citation networks revisited: signs of a twenty-first century change? North Carolina Law Review 87(1657-1698)2009
• VA Diwadkar, B Flaugher, T Jones, Zalányi L, Ujfalussy B, MS Keshavan, Érdi P.: Impaired associative learning in schizophrenia: Behavioral and computational studies. Cognitive Neurodynamics 2(207-219)(2008)
• Érdi P, VA Diwadkar, Ujfalussy B.: The schizophrenic brain: A broken hermeneutic circle. In Artificial Neural Networks - ICANN 2008 Volume Editors: V Kurkova, R Neruda, J Koutnik, Part II. Lecture Notes in Computer Science 5164 Springer 2008, pp. 929-938
• P. Érdi, B. Ujfalussy, L. Zalányi, VA. Diwadkar: Computational approach to schizophrenia: Disconnection syndrome and dynamical pharmacology. In: A selection of papers of The BIOCOMP 2007 International Conference L. M. Ricciardi (ed.) Proceedings of the American Institute of Physics 1028, 65-87
• Csárdi G, KJ Strandburg, J Tobochnik, Érdi P.: The inverse problem of evolving networks - with application to social nets. Chapter 10 in Handbook of Large-Scale Random Networks, eds.: Béla Bollobás, Róbert Kozma, Dezsõ Miklós. Springer-Verlag
• B. Ujfalussy, T. Kiss, G. Orbán, WE. Hoffmann, P. Érdi and M. Hajós: Pharmacological and Computational Analysis of alpha-subunit Preferential GABAA Positive Allosteric Modulators on the Rat Septo-Hippocampal Activity. Neuropharmacology 52(3) (2007) 733-743
• G. Csárdi, KJ. Strandburg, L. Zalányi, J. Tobochnik, P. Érdi: Modeling innovation by a kinetic description of the patent citation system Physica A: Statistical and Theoretical Physics 374(1-2) (2007) 783-793
• Strandburg KJ, Csárdi G, Tobochnik J, Érdi P, Zalányi L: Law and the Science of Networks: an Overview and an Application to the "Patent Explosion" Berkeley Technology Law Journal, 21(4) (2006) 1293-1362
• G. Orbán, T. Kiss and P. Érdi: Intrinsic and synaptic mechanisms determining the timing of neuron population activity during hippocampal theta oscillation. Journal of Neurophysiology 96(6) (2006) 2889-2904
• Érdi P, Kiss T, Tóth J, Ujfalussy B and Zalányi L: From systems biology to dynamical neuropharmacology: Proposal for a new methodology. IEE Proceedings in Systems Biology 153(4) 299-308 (2006)
• I. Aradi and P. Érdi: Computational neuropharmacology: dynamical approaches in drug discovery. Trends in Pharmacological Sciences 27(5) (2006) 240-243
• T. Kiss and P. Érdi: From electric patterns to drugs: perspectives of computational neuroscience in drug design. BioSystems 86(1-3) 46-52 (2006)
• P. Érdi and J. Tóth: Towards a dynamic neuropharmacology: Integrating network and receptor levels. In: Brain, Vision and Artifical Intelligence. M. De Gregorio, V. Di Maio, M. Frucci and C. Musio (eds). Lecture Notes in Computer Science 3704, Springer, Berlin Helidelberg 2005, pp. 1-14.
• Zs. Huhn, G. Orbán, P. Érdi, M. Lengyel Theta oscillation-coupled dendritic spiking integrates inputs on a long time scale Hippocampus 15(7) (2005) 950-962
• P. Érdi, Zs. Huhn, T. Kiss: Hippocampal theta rhythms from a computational perspective: code generation, mood regulation and navigation Neural Networks 18(9) (2005) 1202-1211
• Z. Somogyvári, L. Zalányi, I. Ulbert, P. Érdi : Model-based source localization of extracellular action potentials. Journal of Neuroscience Methods 147(2) (2005) 126-137
• Zs. Huhn, M. Lengyel, G. Orbán, P. Érdi: Dendritic spiking accounts for rate and phase coding in a biophysical model of a hippocampal cell. Neurocomputing 65-66 (2005) 331-341
• Kiss T, Orbán G and Érdi P: Modelling hippocampal theta oscillation: applications in neuropharmacology and robot navigation. International Journal of Intelligent Systems 21(9) (2006) 903-917 (2006)
• P. Érdi: Nonlinear Spatio-temporal Neural Dynamics - Experiments and Theoretical Models, Editorial Biol Cybern 92(6) 349-349 (2005)
• M. Lengyel, Zs. Huhn, P. Érdi: Computational theories on the function of theta oscillation Biol Cybern 92(6) 393-408 (2005)
• R. Kozma, W.J. Freeman, D. Wong, P. Érdi: Learning environmental clues in the KIV model of the cortico-hippocampal formation Neurocomputing 58-60 (2004) 721-728
• G. Papp, Zs. Huhn, M. Lengyel, P. Érdi: Effect of dendritic location and different components of LTP expression on the bursting activity of hippocampal CA1 pyramidal cells Neurocomputing 58-60 (2004) 691-697
• M. Lengyel, P. Érdi: Theta modulated feed-forward network generates rate and phase coded firing in the entorhino-hippocampal system IEEE Transactions on Neural Networks 15 (2004) 1092-1099
• M. Hajós, WE. Hoffmann, G. Orbán, T. Kiss, P. Érdi: Modulation of septo-hippocampal theta activity by GABAA receptors: Experimental and computational approach Neuroscience 126/3 (2004) 599-610
• L. Zalányi, G. Csárdi, T. Kiss, M. Lengyel, R. Warner, J. Tobochnik, P. Érdi: Properties of a random attachment growing network Physical Review E 68 066104 (2003)
• M. Lengyel, Z. Szatmáry, P. Érdi: Dynamically detuned oscillations account for the coupled rate and temporal code of place cell firing. Hippocampus 13 (2003) 700-714
• Cs. Földy, Z. Somogyvári, P. Érdi: Hierarchically Organized Minority Games. Physica A, 323 (2003) 735-742
• R. Kozma, WJ. Freeman, P. Érdi: The KIV Model - Nonlinear Spatio-Temporal Dynamics of the Primordial Vertberate Forebrain. Neurocomputing, 52-54 (2003) 819-826

Teaching

Péter Érdi teaches courses on different interdisciplinary topics:

• The first goal of the Introduction to Nonlinear Dynamics and Chaos course is to teach WHY nonlinear dynamics and chaos theory are important in understanding complicated behaviors. The second goal is to give an introductory overview about HOW the basic methods of nonlinear dynamics work.
• At the Introduction to Cognitive Science course topics of information processing, intelligent systems, complex cognition, and lareg-scale computation are discussed from an interdisciplinary point of view.
• The Introduction to Complex Systems course discusses how collective behavior emerges from the parts of a system, due to the interaction between the system and its environment.
• The Computational Neuroscience course discusses mathematical models, computational algorithms, and simulation methods that contribute to our understanding of neural mechanisms.
• The Dynamic Models in Social Sciences course discusses WHY mathematical and computational methods are important in understanding social phenomena, and HOW different social phenonemena an be described by proper mathematical models.
• A course titled John von Neumann, the Birth of the Computer, Atomic Bombs and Game Theory is offered to celebrate the centenary of the birth of John von Neumann. The class will discuss Neumann's life in historical context. You will increase your knowledge of the intellectual life in Central Europe around the turn of the last century.