Senior Lecturer, School of Computer Science,
   University of Lincoln, Lincoln, U.K.

Faculty, Athens International Masters Program in Neuroscience,
   Dept of Biology, University of Athens, Greece

Faculty, Budapest Semester in Cognitive Science,
   Eotvos Lorand University, Budapest, Hungary

Guest Lecturer, Institute of Automation,
   Chinese Academy of Sciences, Beijing, China

Associate Editor, Cognitive Computation

Guest Associate Editor, Frontiers in Systems Neuroscience

Associate Editor, Scholarpedia

Review Editor, Frontiers in Cognitive Science

Hippocampal Microcircuits:
A Computational Modeler's
Resource Book, 1st ed

Springer 2010
Perception-Action Cycle:
Models, Architectures
and Hardware

Springer 2011
Hippocampal Microcircuits:
A Computational Modeler's
Resource Book, 2nd ed

Springer, in 2017
Edited Proceedings

Brain Inspired
Cognitive Systems
(BICS) 2008

Springer 2008
Book Series

Springer Series in Cognitive
& Neural Systems

Trends in Augmentation
of Human Performance


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   • Cognitive Systems
   • Machine learning applications
   • Brain-machine interfaces
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Education, Career
Full CV   (July 20, 2016)

I am a computational scientist broadly interested to reverse engineer how the brain and mind work in health and disease in order to understand the circuits and patterns of neural activity that give rise to mental experience and behavior in order to design and develop more efficient intelligent methods and systems for complex data analysis in Neurosciences, Drug Discovery and Medical Imaging.

As advances in technologies are producing large, complex data sets at an unprecedented rate, novel theoretical and analytical approaches are needed to realize the potential of these rich datasets. Understanding neural circuitry requires an understanding of the algorithms and mechanisms that govern information processing within a circuit and between interacting circuits in the brain as a whole. Informed by rich observations, formalized theoretical frameworks allow researchers to infer general principles of brain function and the algorithms underlying functioning neural circuitry. Theory coupled with mathematical modeling and simulation approaches are needed to identify gaps in knowledge, to drive the systematic collection of the future data (e.g. so that the collected data specifically address the model parameters), and to formulate testable hypotheses of neural circuit mechanisms and how they govern behavioral and cognitive processes. New data analysis methods are needed to detect features in complex data, often spanning multiple modalities and scales, to reveal underlying mechanisms of brain function.

My approach in computational modeling is that a top-down theorist. I identify the problem in its most abstract form, then derive the algorithm that solves this problem, and finally look at how the brain implements the algorithm. Any successful computational model should first be constrained by large amounts of data, before it makes any further theoretical predictions, because otherwise too many plausible alternatives cannot be ruled out. A theory that hopes to link brain to behavior thus needs to discover the computational level on which brain dynamics control behavioral success.

Research aims to develop:
  • Theories, ideas and conceptual frameworks

  • Multiscale models to integrate information across large temporal and spatial scales in the nervous system

  • Intelligent new methods for complex data analysis

  • Intelligent machines with autonomous and creative behavior

Core scientific network: close collaborators, co-authors/editors, co-supervisors, and co-organizers
Nikolaos Smyrnis, Medical School, University of Athens, Greece (eye movements)
Ioannis Evdokimidis, Medical School, University of Athens, Greece (eye movements)
Sotiris Plainis, Medical School, University of Crete (psychophysics of reading)
Stavros Perantonis, IIT-NCSR Demokritos, Athens, Greece (neural networks)
Bruce P. Graham, University of Stirling (hippocampal modelling)
Stuart Cobb, University of Glasgow (in-vitro neurophysiology)
Ausra Saudargiene, University of Lithuania (computational neuroscience)
John G. Taylor, Kings College London (cognitive robotics)
Michael Hasselmo, Boston University (computational neuroscience)
Ahmed Moustafa, Western University of Sydney (computational neuroscience)
Joe Tsien, Georgia Regents University (behavioral neurophysiology)
Peter Erdi, Kalamazoo College, Michigan (cognitive science)
Gyorgi Kampis, ELTE, Hungary (evol comput)
Vaibhav Diwadkar, University of Pittsburg (fMRI)
Jiannis Taxidis, UCLA (computational neuroscience)
Mike Kokkinidis, University of Crete (neural networks & structural biology)
Amir Hussain, University of Stirling (cogn computation)
Motoharu Yoshida, DZNE Magdeburg (cognitive neurophysiology)
Thrish Nanayakkara, Kings College London (robotics)
Imre Vida, Charité - Universitätsmedizin Berlin (neural circuits)
George Kostpoulos, University of Patras (hippocampal modelling)