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About EITN

Our Institute


The European Institute for Theoretical Neuroscience (EITN), an incubator of ideas in the HBP

The EITN is a science-oriented structure created as part of the Theoretical Neuroscience activities of the Human Brain Project (HBP). It is aimed to serve as an incubator of ideas in the project, creating interactions within the HBP, as well as between the HBP and the scientific community outside the project.
Funded in 2014, the institute is operated by the Paris-Saclay Institute of Neuroscience (Neuro-PSI), multidisciplinary and internationally recognized Institute and unit of the CNRS and has for scientific director Alain Destexhe (Neuro-PSI, CNRS, Gif-sur-Yvette). Its activities are essentially related to science and research.

 

Main activities
 

The workshops and visitor program, two main activities of the EITN, contribute to confront the ideas developed in the HBP with the international scientific community. The EITN not only broadcasts ideas and brain theories developed in the project, but also gathers new ideas from the intense interactions taking place during the workshops.

 

Public
 

The EITN is open to neuroscience researchers, from all over Europe and the rest of the world, whether there are HBP partners or not.

 

 

The theoretical neuroscience activities of the EITN are being animated by all principal investigators of the HBP theoretical neuroscience division. Several visitors, in addition to the Director and the EITN team will be welcoming you at the Institute.


Support Team
 

Alain Destexhe, Scientific Director

Irina Kopysova, Chief of Administrative and Technical team

Laurent Pinguet, Administrative and Financial assistant

Tom Messier, EITN Systems manager

Zélie Tournoud, Communication manager 

 

EITN Faculty members
 

The EITN forms a faculty of HBP theoreticians and computational neuroscientists.
 

ALAIN DESTEXHE, CNRS

Alain Destexhe is biophysicist and Research Director (DRCE) at the CNRS, within the Paris-Saclay Institute of Neuroscience (Neuro-PSI), UMR9197. At Neuro-PSI, he leads the computational neuroscience group comprising 15 researchers (permanent researchers, postdocs and PhD students) and staff members.
He is co-Editor in Chief of The Journal of Computational Neuroscience, and in the board of 7 other journals including Journal of Neural Engineering. He has been involved as WP leader in multiple European projects and numerous grant review committees in Europe and USA. He is author of 2 monographs, 6 edited books, and about 300 publications, including about 150 peer-reviewed journal articles. Alain Destexhe initiated the European Institute for Theoretical Neuroscience (EITN) in Paris, and he is currently the scientific director of the EITN.


 

ANDREW DAVISON, CNRS

Andrew Davison is a senior research scientist (CRCN) at the CNRS, within the Paris-Saclay Institute of Neuroscience, where he leads the Neuroinformatics research group. Dr Davison received his PhD in computational neuroscience from the University of Cambridge in 2001, then did post-docs at Yale University and the CNRS. His research interests are in large-scale, data-constrained, biologically-detailed modelling of neuronal networks, with a focus on development of tools and standards to promote collaboration, reproducibility, and data/model re-use in computational neuroscience, neuroinformatics, and neuromorphic computing.

For more information see http://andrewdavison.info.


 

GUSTAVO DECO, Pompeu Fabra University

Gustavo Deco is Research Professor at the Institucio Catalana de Recerca i Estudis Avançats. He is also Full Pofessor (Catedrático) at the Pompeu Fabra University (Barcelona), where he is also the head of the Computational and Theoretical Neuroscience Group and Director of the Center of Brain and Cognition. He received his Ph.D. degree in Physics in 1987 (National University of Rosario, Argentina). In 1997, he obtained his habilitation (academic degree in Germany) in Computer Science (Dr. rer. nat. habil.) at the Technical University of Munich for his thesis on Neural Learning. From 1990 to 2003, he headed Computational Neuroscience Group at the Siemens Corporate Research Center in Munich, Germany. In 2001, he received his PhD in Psychology (Dr. phil.) for his thesis on Visual Attention at the Ludwig-Maximilian-University of Munich. He was awarded an ERC Advanced Grant.


 

PAOLO DEL GIUDICE, Italian Institute of Health

Paolo Del Giudice, physicist by training, is senior researcher at the Italian Institute of Health, and adjunct professor of neural networks at the Physics Department of the Third University in Rome. He worked on several aspects of neural modelling, including dynamics and learning in populations of spiking neurons, neuromorphic implementation of spiking neural network models, and methods for the inference of neural models from electrophysiological data. He published about 90 papers, including 48 peer-reviewed journal papers, and co-organized five workshops/schools on neural networks. Held grants include four EU-FET grants, two Italy-US bilateral grants and several grants funded by the Italian National Institute for Nuclear Research.


 

MARKUS DIESMANN, Jülich Research Centre

Markus Diesmann is the director of the Institute of Neuroscience and Medicine (INM-6, Computational and Systems Neuroscience), the Institute for Advanced Simulation (IAS-6, Theoretical Neuroscience), and the JARA-Institut Brain structure-function relationships (INM-10) at Forschungszentrum Jülich, Germany, where he heads the Group on Computational Neurophysics. He is also full professor in Computational Neuroscience at the School of Medicine, RWTH University Aachen, Germany. He studied physics at the Ruhr University Bochum, Germany, and carried out his PhD studies at Weizmann Institute of Science, Rehovot, Israel, and Albert-Ludwigs-University, Freiburg, Germany. His main scientific interests include the correlation structure of neuronal networks, models of cortical networks, simulation technology and supercomputing. He is one of the original authors of the NEST simulation code and a member of the steering committee of the NEST Initiative.


 

GAUTE EINEVOLL, Norwegian University of Life Sciences and University of Oslo

Gaute T. Einevoll is a professor of physics at the Norwegian University of Life Sciences and University of Oslo. He is interested in various aspects of multiscale modeling of the brain, including how to compute brain signals, how to connect models at different levels of detail, modeling of astrocytes and their interactions with neurons, as well as development of neuroinformatics tools. Dr. Einevoll received his master’s in physics from the Norwegian University of Science and Technology in Trondheim in 1985 and his doctoral degree in theoretical physics from the same university in 1991. He is a co-leader of the Norwegian national node of the International Neuroinformatics Coordinating Society (INCF).


 

OLIVIER FAUGERAS, INRIA

Olivier Faugeras is a mathematician and computer scientist working in mathematical neuroscience. He is Emeritus Research Director at INRIA, co-Editor in chief of the Journal of Mathematical Neuroscience, and a member of the French Academy of Sciences.


 

STEN GRILLNER, Karolinska institute

Sten Grillner is professor at the Karolinska institute with a research focus on the cellular bases of behaviour and in particular the design of the spinal cord networks underlying locomotion and later the forebrain circuitry underlying the selection and initiation of different aspects of behaviour with a focus on the role of the basal ganglia. Since the late 80ies he has combined detailed cellular studies with simulation of the intrinsic function of these networks often together with Anders Lansner and Jeanette Hellgren - most recently detailed simulations of the striatum. His interest also includes the evolutionary aspect of the vertebrate motor system from lamprey to mammals. He is a member of the National Academy of Science and other institutions.


 

SONJA GRÜN, Forschungszentrum Jülich

Sonja Grün is the director of the Institute of Neuroscience and Medicine (INM-6, Computational and Systems Neuroscience) and the JARA-Institut Brain structure-function relationships (INM-10) at Forschungszentrum Jülich, Germany, where she heads the Group on Statistical Neuroscience. She is also a full professor for Theoretical Systems Neurobiology at RWTH Aachen University, Germany. After receiving her diploma and Dr. rer. nat. in physics and her habilitation in neurobiology and biophysics (University of Freiburg, Germany), she was a post-doc at the Hebrew University, Jerusalem, (Israel), where she performed multiple singleneuron recordings in behaving monkeys. She then returned to computational neuroscience to develop analysis tools for multi-electrode recordings, first at the Max-Planck Institute for Brain Research in Frankfurt/Main, Germany, and then as an Assistant Professor at the Freie Universität in Berlin.

In 2006 she became Unit Leader and in 2010 Team Leader at the RIKEN Brain Science Institute Wako-Shi, Japan, leading the Statistical Neuroscience lab.
Her research focuses on the identification and analysis of cooperative network dynamics relevant for brain function and behaviour.  


 

VIKTOR JIRSA, Aix-Marseille University

Viktor Jirsa is Director of the Inserm Institut de Neurosciences des Systèmes at Aix-Marseille-Université and Director of Research at the Centre National de la Recherche Scientifique (CNRS) in Marseille, France. Dr. Jirsa received his PhD in 1996 in Theoretical Physics and Applied Mathematics and has since then contributed to the field of Theoretical Neuroscience, in particular through the development of large-scale brain network models based on realistic connectivity, linking network dynamics to brain function and imaging. His work has been foundational for network science in medicine with translations to clinical applications in neurosurgery and has contributed to a better understanding of human behavior and epilepsy. Dr. Jirsa serves as scientific lead of the brain simulation platform The Virtual Brain (www.thevirtualbrain.org) and lead scientist (WP1) of the European flagship Human Brain Project (https://www.humanbrainproject.eu/).


Dr. Jirsa has been awarded several international and national awards for his research including the Grand Prix Départemental de Recherche en Provence (2018), Early Career Distinguished Scholar Award (NASPSPA, 2004) and Francois Erbsmann Prize (2001). Dr. Jirsa serves on various Editorial and Scientific Advisory Boards and has published more than 160 scientific articles and book chapters, as well as co-edited several books including the Handbook of Brain Connectivity.


 

JEANETTE HELLGREN KOTALESKI, KTH Royal Institute of Technology

Jeanette Hellgren Kotaleski holds an MSc in Engineering Physics, a Licentiate degree in Medical Sciences and a Ph.D. in Computer Science. Since her postdoctoral studies in systems biology at the Krasnow Institute, George Mason University, USA, she has been a full professor in Neuroinformatics at KTH since 2007. She is the coordinator of an international Erasmus Mundus joint Ph.D. programme involving Partners from Germany, UK and India and is the leader of the Swedish INCF node. Dr. Hellgren-Kotaleski co-directs the HBP Brain Simulation Subproject.


 

MARJA-LEENA LINNE, Tampere University

Marja-Leena Linne is a Research Director at Tampere University (Finland). She was awarded an Academy of Finland Research Fellow position (equivalent to Associate Professor) in 2004 to establish an interdisciplinary research group in the interface of computer science, biology and neuroscience. As an electrical engineer with PhD in signal processing (2001), she has combined engineering and neuroscience to become an electrophysiologist and computational neuroscientist. She performed in vitro experiments on neurons and astrocytes in the 1990s and has used patch clamp, microelectrode arrays, and microscopy to develop theoretical and computational models of neural systems in silico. Over the years, her research group has developed models of neural systems at the levels of networks, cells and cellular signalling pathways by using both detailed biophysical and phenomenological approaches while employing a variety of mathematical techniques not conventionally used in neuroscience. Prof. Linne’s current research focus is on neuron-glia interactions and their role in excitability, neurotransmission and plasticity in mammalian cortical networks.

Prof. Linne has served as a board member of international neuroscience organizations, including Organization for Computational Neuroscience (OCNS), Federation of European Neuroscience Societies (FENS), and International Neuroinformatics Coordination Facility (INCF).

ORCID: https://orcid.org/0000-0003-2577-7329


 

MAURIZIO MATTIA, Italian Institute of Health (Istituto Superiore di Sanità)

Maurizio Mattia is a physicist by training with a PhD in Neurophysiology, holding a permanent Researcher position at the Italian Institute of Health in Rome. He is also an adjunct professor of Neural Networks at the Physics Department of the “Sapienza” University of Rome. Since April 2016, he is core member of the FET Flagship Human Brain Project. His interest is in bridging the gap between theory and experimental evidence on cortical network dynamics, by developing novel data analyses and theoretical approaches, with a focus on the collective dynamics underlying both the spontaneous activity under different brain states and the neural correlate of cognitive tasks like motor decision.

See here for more publication.


 

JORGE MEJIAS, University of Amsterdam

Jorge F. Mejias is Principal Investigator and Assistant Professor of Computational Neuroscience at the University of Amsterdam in the Netherlands. With a background in physics and mathematics, he obtained a PhD in computational neuroscience from the University of Granada in 2009, under the supervision of Prof. Joaquin Torres. Dr. Mejias has worked as a postdoctoral researcher in the labs of Profs. Andre Longtin (University of Ottawa) and Xiao-Jing Wang (New York University) before joining the University of Amsterdam in 2017. His research is focused on the study of anatomically-constrained large-scale brain networks during perception and cognition, including working memory and multisensory integration. He is also interested in how neural and circuit heterogeneity shapes the dynamics of neural systems and their function. Dr. Mejias is also a member of the Institute Carlos I for Theoretical and Computational Physics in Spain, and director at the Organization for Computational Neurosciences.


Relevant publications:
- J. Jaramillo, J. F. Mejias and X.-J. Wang, Engagement of pulvino-cortical feedforward and feedback pathways in cognitive computations, Neuron, 101, 321-336, 2019.
- J. F. Mejias, J. D. Murray, H. Kennedy and X.-J Wang, Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex, Science Advances, 2, e1601335, 2016.
- J. F. Mejias and A. Longtin, Differential effects of excitatory and inhibitory heterogeneity on the gain and asynchronous state of sparse cortical networks, Frontiers in Comput. Neurosci., 8:107, 2014.


 

MICHELE MIGLIORE, Michele Migliore's lab

D.Phil. in Physics (1980, Summa cum Laude, University of Palermo, Italy). Director of the Palermo Section of the Institute of Biophysics (National Research Council, Italy, 2015-2017), Visiting Professor of Cybernetics at the Department of Mathematics and Informatics of the University of Palermo (Italy), Visiting Professor of Computational Neuroscience at the University of Rome "La Sapienza" (Italy), and Visiting Scientist at the Department of Neuroscience of the Yale University School of Medicine (New Haven, USA). His lab is involved in modelling realistic neurons and networks, synaptic integration processes, and plasticity mechanisms. The main long-term goal is to understand the emergence of higher brain functions and dysfunctions from cellular processes, implementing new tools and using state of the art simulation environments on different supercomputer systems.

Most cited publications: https://publons.com/researcher/2792741/michele-migliore/


 

PIER STANISLAO PAOLUCCI, Istituto Nazionale di Fisica Nucleare

Pier Stanislao Paolucci current research focuses on the modeling of the cognitive functions of sleep, of the spatio-temporal features of cortical slow waves and on the transition to higher complexity states. Also, he works on the hardware-software co-design of fast, scalable simulation systems. Previously, he coordinated the European EURETILE and SHAPES project. He is a permanent staff researcher of the INFN APE laboratory since its foundation (1984), where he participated in the design of several generations of massive parallel/distributed numerical computers. During the 2000-2010 period, he served as CTO of the Roman design center of ATMEL, a leading semiconductor manufacturer, and guided the design of the DIOPSIS MPSoCs (Multi Processor Systems on Chip) and mAgic VLIW numerical processors. Paolucci is the inventor/co-inventor of international patents, hardware/software numerical algorithms and hardware/software co-design techniques. Paolucci also invented the `Cubed-Sphere' gridding technique and co-invented 'Evolving Grammars'. Paolucci received his Physics M.Sc. degree from University Sapienza (Rome, Italy).

For more information, click here.


 

CYRIEL PENNARTZ, University of Amsterdam

 

Cyriel Pennartz is full professor at the University of Amsterdam and head of the Department of Cognitive and Systems Neuroscience. His current research focuses on the neural basis of perceptual representation, in particular on interactions between different sensory modalities and between sensory and memory systems. This work is paralleled by a theoretical research line on consciousness (neurorepresentationalism). He pursues these research lines using a combination of behavior, high-density ensemble recordings, 2-photon imaging, interventional techniques such as optogenetics and computational modelling. In addition to cortical and hippocampal systems, he has a background in basal ganglia research, in particular the role of the prefrontal-ventral striatal system in motivation, learning and emotional behavior.

With his group he also develops novel neurotechnology with fundamental and preclinical applications. His computational work comprises the development of novel data-analytic tools to study e.g. multi-area population coding, phase synchronization in EEG signals and spikes, as well as deep-learning predictive coding and neurodynamic models to study how perceptual representations arise in the brain.


 

SPASE PETKOSKI, Aix-Marseille University

After studying electrical engineering and information technologies in Skopje, Spase Petkoski enrolled to a PhD program in the Biomedical and Nonlinear Physics at Lancaster University. He graduated in 2014 after obtaining a distinction as a best international student at the Physics Department. Since then, he has been working as a postdoctoral researcher at Theoretical Neuroscience Group of the Institute of Systems Neurosciences in Marseille, led by Viktor Jirsa. From 2017 he is also part of the Human Brain Project (HBP). His research focus is at the intersection of nonlinear dynamics and computational neuroscience. More specifically, Spase Petkoski is interested in the synchronization and emergent dynamics, and in their application to modeling large-scale brain dynamics. Besides the more theoretical background on the Kuramoto oscillators, lately he has been using the brain-network modelling paradigm to study the effect of time-delays on the synchronization between brain regions, as well as the network impact from the lesions in the structural links.

The former is applied in the study of connectome changes due to processes such as ageing, while the latter is relevant for the propagation patterns of epileptic seizures and stroke.

Highlighted publications:
- AL Allegra Mascaro, E Falotico, S Petkoski et al, Experimental and computational study on motor control and recovery after stroke: towards a constructive loop between experimental and virtual embodied neuroscience, Frontiers in Systems Neuroscience, doi:10.3389/fnsys.2020.00031, 2020.
- S Petkoski, JM Palva, VK Jirsa, Phase-lags in large scale brain synchronization: Methodological considerations and in-silico analysis, PLoS Computational Biology 14(7), 2018.


 

IDAN SEGEV, Hebrew University of Jerusalem

Idan Segev is the David and Inez Myers Professor in Computational Neuroscience at the Edmond and Lily Center for Brain Sciences (ELSC), and the former director of the Interdisciplinary Center for Neural Computation (ICNC) at the Hebrew University of Jerusalem. He received his B.Sc (1973) in Math and his Ph.D (1982) in experimental and theoretical neurobiology from the Hebrew University. His work is published in reputed journals and he has received several several Intl. awards, some for his excellent teaching abilities. Segev takes a keen interest in the connection between art and the brain and has recently co-edited “Artists” book with original etchings by ten top Israeli artists following an intense encounter with 10 brain-researchers. Segev, the world’s undisputed leader and a pioneer on model neurons, has been instrumental in providing the theoretically ground for an automated building of model neurons used presently in in the Blue Brain Project and in Allen Institute.
He is a Chief editor for the open access journal, Frontiers in Neuroscience, and co-editor for Frontiers for Young Minds, an open journal for kids, written by top scientists worldwide and reviewed by kids.


 

WALTER SENN, University of Bern

Walter Senn is Full Professor for Computational Neuroscience at the Institute of Physiology, University of Bern, since 2006 and since 2010 Co-Director of the same Institute. He has a PhD in Mathematics and is interested in theoretical models of how cognitive functions such as learning, memory and perception emerge from interacting neurons in the brain. His research covers mathematical models of neurons, synaptic plasticity, and learning. Based on electrophysiological recordings of neuronal activity in vitro or in vivo he develops models of neurons and networks which explain behavior. He was pioneering models of spike-timing-dependent synaptic plasticity and its applications. In a series of papers he developed algorithms for reinforcement learning in populations of spiking neurons with delayed reward. He is also involved in building a theory of reward-based leaning in multi-compartment neurons with dendritic nonlinearities. He currently promotes a neural principle of least action from which basic laws of neuron and synaptic dynamics are derived in a similar way as the law of motion is derived from the least action principle in physics. The theory links cortical microcircuits with artificial intelligence and serves as a basis for designing neuromorphic hardware.


 

SACHA VAN ALBADA, Jülich Research Centre

Sacha van Albada leads the group "Theoretical Neuroanatomy" at the Institute of Neuroscience and Medicine (INM-6) at Research Center Jülich, and is Junior Professor in Computational Neuroanatomy at the University of Cologne, Germany. She combines anatomical and physiological data from a wide range of sources to build neural network models of mammalian cerebral cortex. The aim is to understand relationships between cortical structure and dynamics, and to provide models that serve as platforms for further refinement and for incorporating cortical function.

Selected recent publications:
-  Schmidt M, Bakker R, Shen K, Bezgin G, Diesmann M, van Albada SJ. A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas. PLOS Computational Biology. 2018; 14(10). 
-  Schmidt M, Bakker R, Hilgetag CC, Diesmann M, van Albada SJ. Multi-scale account of the network structure of macaque visual cortex. Brain Structure and Function. 2018; 223(3):1409-35.    
- van Albada SJ, Rowley AG, Senk J, Hopkins M, Schmidt M, Stokes AB, Lester DR, Diesmann M, Furber SB. Performance comparison of the digital neuromorphic hardware SpiNNaker and the neural network simulation software NEST for a full-scale cortical microcircuit model. Frontiers in Neuroscience. 2018; 12:291.
- Maksimov A, Diesmann M, van Albada SJ. Criteria on balance, stability, and excitability in cortical networks for constraining computational models. Frontiers in Computational Neuroscience. 2018; 12:44.


 

Members in previous phase

 

NEIL BURGESS, UCL

Neil Burgess is a professor of cognitive and computational neuroscience, a Wellcome Trust Principal Research Fellow, and Deputy Director of the UCL Institute of Cognitive Neuroscience. His laboratory investigates the neural mechanisms of memory using a combination of methods including computational modelling, human neuropsychology and functional neuroimaging, and single unit recordings in freely moving rodents. His main goal is to understand how the actions of networks of neurons in our brains allow us to remember events and the spatial locations where they occurred. After studying math and physics at UCL he did a Ph.D. in theoretical physics in Manchester and a research fellowship in Rome, before returning to UCL funded by a Royal Society University Research Fellowship and the Medical Research Council (UK).


 

JONI DAMBRE, UGENT

Joni Dambre is a professor at Ghent University and head of the UGent Reservoir Lab in the Engineering Faculty. Her lab addresses theoretical research and applications of recurrent neural networks, reservoir computing, and several other machine learning techniques. The group has a special interest in neuro-inspired computing by directly exploiting the dynamics of analogue systems. As an engineer and a computer scientist, Prof. Dambre’s original research addressed interconnection complexity in digital design. In 2008, she shifted towards reservoir computing in general and analogue hardware realisations of the reservoir computing concept in particular. Currently she is focused on building biologically plausible analogue reservoir architectures that can learn without global supervision, i.e. using either unsupervised or reward modulated learning. She is very interested in model abstractions that can bridge the gap between biologically plausible learning mechanisms and learning rules that are efficient in complex tasks.


 

MARC DE KAMPS, LEEDS

Marc de Kamps is a researcher in the School of Computing of the University of Leeds. His expertise is in population density techniques, applied to populations of spiking neurons. He holds a PhD in high energy physics, and has considerable experience in the application of stochastic methods to neural dynamics, using a combined analytic and numerical approach. He also works on models of visual attention and neural language representation. In the past he was responsible for running the FET-funded Thematic Network nEUro-IT.net, which was instrumental in bringing together a European network of neuroscientists, engineers and computer scientists.


 

WULFRAM GERSTNER, EPFL

Wulfram Gerstner studied physics at the universities of Tubingen and Munich and received a Ph.D. from the Technical University of Munich. His research in computational neuroscience concentrates on models of spiking neurons and spike-timing dependent plasticity, on neuronal coding in single neurons and populations, and on the role of spatial representation for navigation of rat-like autonomous agents. He currently has a joint appointment at the School of Life Sciences and the School of Computer and Communications Sciences at EPFL, wherehe teaches courses for physicists, computer scientists, mathematicians, and life scientists.


 

MICHELE GIUGLIANO, UA

Michele Giugliano is a Principal Investigator and a tenured Associate Professor (ZAP-BOF research mandate, Hoofddocent) in the Department of Biomedical Sciences and at the University of Antwerp in Belgium. He leads the of the Laboratory for Theoretical Neurobiology and Neuroengineering.His studies focus on cortical and cerebellar function using a combination of technological, experimental and theoretical approaches. These range from substrate arrays of microelectrodes to patch-clamp, from in vitro cellular electrophysiology to in vivo recordings, from the micro- and nanotechnologies for neural engineering applications to the computer simulation of realistic models of neurons and neuronal networks. His group also develop neural simulation software (visit their website for simulated calcium images of a modelled cerebellar Purkinje cell).


 

ANDRE GRÜNING, HOST

Andre Grüning is a Professor of Mathematics and Computational Intelligence at the University of Applied Science Stralsund (Germany). Previously he was a Senior Lecturer (Associate Professor) in Computational Intelligence in the Department of Computer Science of the University of Surrey (UK). He held research posts in Computational Neuroscience at SISSA, Trieste, and in Cognitive Neuroscience, University of Warwick. He was awarded his PhD from the University of Leipzig, pursuing his PhD research at the Max Planck Institute for Mathematics in the Sciences, Leipzig, working in the complex systems group.
His research concentrates on the overlap of AI and Computational and Cognitive Neuroscience, especially learning algorithms for spiking neural networks. In particular, Prof Grüning has been working on the computational power of neural networks, aspects of unifying reinforcement and supervised learning approaches or learning in multi-layered spiking neural networks, and biologically based implementing learning rules on neuromorphic hardware.


 

WOLFGANG MAASS, TUGRAZ

Wolfgang Maass’early research was in the theory of computation in mathematicsafter which he moved on to computational complexity theory and the theory of learning in theoretical computer science. Since 1995 his research has focused on the extraction of principles of brain computation and learning from experimental data. Maassand Henry Markram designed the liquid computing model for understanding universal computations in cortical microcircuits. This has now become a classical reference work, inspiring numerous innovative ideas in engineering. In his current research, he is analysing the role of noise and variability in computation and learning by biological neural systems. He has published some 200 research articles and has been editor of several journals.


 

HENRY MARKRAM, EPFL

Henry Markram is the founder of the Brain Mind Institute, founder and director of the Blue Brain Project, and the coordinator of the Human Brain Project. After earning his Ph.D at the Weizmann Institute of Science (Israel), with distinction, he was a Fulbright scholar at the National Institutes of Health (USA), and a Minerva Fellow at the Max-Planck Institute for Medical Research, Germany. In 1995 he returned to the Weizmann Institute, becoming an Associate Professor in 2000. In 2002 he became a full professor at EPFL. Markram’s research has focused on synaptic plasticity and the microcircuitry of the neocortex, in which he has discovered fundamental principles governing synaptic plasticity and the structural and functional organisation of neural microcircuitry. Other key discoveries include the concept of Liquid Computing and the Intense World Theory of Autism. In 2005 he launched the Blue Brain Projectto develop a data integration strategy for neuroscience that plays an important role in the HBP. Markram has published more than 100 papers and has an H-index of 53, one of the highest in his area of research and stage of career. Since 2002, Markram has spearheaded Switzerland’s ambition to become a world leader in High Performance Computing and to prioritise simulation-based research; these fields are now two of the three national research priorities declared by the Swiss government (http://www.ethrat.ch/en/ section-general-news/successes-education- and-research-call-more-resources). Markram is also founder of Frontiers (frontiersin.org), a new model for peer-reviewed open-access publishing.


 

OLIVIER MARRE, UPMC

Olivier Marre is an INSERM researcher (since 2013) in the Vision Institute (Paris), working in the team headed by Serge Picaud. He did his PhD (defended in 2008) with Yves Fregnac (CNRS, Gif-sur-Yvette) studying the visual cortex with both theoretical models and intracellular recordings in vivo. He then did a post-doc at Princeton University with Michael Berry, where he developed a new technique to record almost all the output neurons in a patch of retina. He is a laureate of the “ANR retour post-doc” (2012-2014) return grant to start working in the Vision Institute. He designed models of the visual cortex network during his PhD, and also did experiments to study the neural coding of natural stimuli by the neurons of the primary visual cortex of the cat. He also developed a technique to measure the retinal output sent to the brain during his post-doc at Princeton University, and showed that the recorded output can be used to precisely reconstruct the trajectory of a randomly moving object from the responses of hundreds of neurons to this stimulus.


 

ABIGAIL MORRISON, JÜLICH

Abigail Morrison received a Master’s degree in non-symbolic artificial intelligence from the University of Edinburgh, UK and a Ph.D. from Albert Ludwigs University and the Bernstein Center for Computational Neuroscience, Freiburg, Germany. In 2006, she performed postdoctoral work at the Bernstein Center for Computational Neuroscience, Freiburg, Germany and then became a Research Scientist in Computational Neurophysics, RIKEN Brain Science Institute, Wako-Shi, Saitama, Japan (2007-2009). Between 2009 and 2012 she was a Junior Professor for Computational Neuroscience and led the Functional Neural Circuits Group, Faculty of Biology, Albert Ludwigs University, Freiburg, Germany. Since 2012, she has led the Functional Neural Circuits Group, INM-6, Forschungszentrum Jülich, and Professor at the Ruhr University of Bochum, Germany. Since 2013, she has headed the Simulation Laboratory Neuroscience at Jülich Supercomputing Centre, Forschungszentrum Jülich.


 

MISHA TSODYKS, WEIZMANN

Misha Tsodyks has a Ph. D. in theoretical physics from Landau Institute of Theoretical Physics, Moscow (Russia). He has worked as a researcher in mathematical neuroscience at the Institute of Neurophysiology of the Soviet Union Academy of Science, and then as a senior lecturer at the Hebrew University of Jerusalem, where he researched neural networks theory. He was post-doctoral fellow at the Salk Institute (USA) in computational neuroscience, after which he returned to Israel to take a faculty position at the Weizmann Institute of Science.


 

SHIMON ULLMAN, WEIZMANN

Shimon Ullman is a Professor of Computer Science at the Weizmann Institute. He is also member of the Israeli Academy of Science and the Humanities.