SP4 workpackages details
October 2013 - March 2016
WP4.1 Bridging Scales - Leader: Alain Destexhe (CNRS)
- T4.1.1 Derive simplified neuron and neural circuit models from biophysically morphologically detailed models. Leader: Idan Segev (HUJI); Participants: Alain Destexhe (CNRS) and Wulfram Gerstner (EPFL).
- T4.1.2 Modelling brain signals at different scales, from intracellular, local field potentials, VSD up to EEG and MEG signals. Leader: Alain Destexhe (CNRS); Participant: Gaute Einevoll (UMB).
- T4.1.3 Mechanistic models of cognition linked to the neural substrate by population density methods. Leader: Marc de Kamps (ULEEDS).
WP4.2 Synaptic plasticity, learning and memory - Leader: Wulfram Gerstner (EPFL)
- T4.2.1 Derive learning rules from biophysical synapse models. Leader: Walter Senn (UBERN); Participants: Misha Tsodyks (WIS) and Wulfram Gerstner (EPFL).
- T4.2.2 Unsupervised learning rules and emergent connectivity. Leader: Wulfram Gerstner (EPFL).
- T4.2.3 Structures of spiking learning algorithms. Leader: Andre Grüning (SURREY).
WP4.3 Large-scale models of human cognitive function - Leader: Gustavo Deco (UPF)
- T4.3.1 Models for perception-action. Leader: Gustavo Deco (UPF); Participants: Neil Burgess (UCL) and Olivier Faugeras (INRIA).
- T4.3.2 Models of working memory and the effects of attention. Leader: Misha Tsodyks (WIZ)
- T4.3.3 Models of biologically realistic network states; wakefulness and sleep. Leader: Alain Destexhe (CNRS); Participants: Abigail Morrison (JÜLICH) and Gustavo Deco (UPF)
- T4.3.4 Computational model of astrocyte-neuron interaction for future large-scale simulations. Leader: Marja-Leena Linne (TUT).
WP4.4 Principles of brain computation - Leader: Wolfgang MAASS (TUGRAZ)
- T4.4.1 Principles of computation in single neurons nad neural microcircuits. Leader: Wolfgang Maass (TUGRAZ); Participants: Alain Destexhe (CNRS), Henry Markram (EPFL) and Idan Segev (HUJI).
- T4.4.2 Novel Computing systems inspired by biology. Leader: Joni Dambre (UGENT); Participant: Wolfgang Maass (TUGRAZ).
- T4.4.3 Closed loop analysis of population coding. Leader: Olivier Marre (UPMC).
WP4.5 The European Institute for Theoritical Neuroscience - Leader: Alain Destexhe (CNRS)
- T4.5.1 Setting up and administration of the Institute. Leader: Alain Destexhe (CNRS).
- T4.5.2 Visitor and workshop program. Leader: Alain Destexhe (CNRS).
WP4.6 Theoretical Neuroscience: Scientific coordination - Leader: Alain Destexhe (CNRS)
- T4.6.1 Scientific coordination and support. Leader: Alain Destexhe (CNRS).
ALAIN DESTEXHE, CNRS:
Alain Destexhe is physicist and Research Director (DR1) at the CNRS, in the Unité de Neurosciences, Information and Complexité (UNIC) of the Centre National de la Recherche Scientifique, France, CNRS UPR 3293. At UNIC he leads the computational neuroscience group comprising three permanent researchers, postdocs and PhD students. He is Editor in Chief of The Journal of Computational Neuroscience, and in the board of 5 other journals including Journal of Neuroscience and Journal of Neural Engineering. He has been involved in European projects (such as FACETS and BrainScaleS, where he was WP leader), and numerous grant review committees. He is author of 2 monographs, 3 edited books, and about 200 publications, including more than 100 peer-reviewed journal articles. In 2014, Alain Destexhe initiated the European Institute for Theoretical Neuroscience (EITN) in Paris, which he now leads as co-Director of SP4, in the framework of HBP.
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.
GUSTAVO DECO, UPF:
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. In 2001, he received his PhD in Psychology (Dr. phil.) for his thesis on Visual Attention at the Ludwig-Maximilian-University of Munich. He headed Computational Neuroscience Group at the Siemens Corporate Research Center in Munich from 1990 to 2003.
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.
GAUTE EINEVOLL, NMBU:
Gaute T. Einevoll is a professor of physics at the Department of Mathematical Sciences and Technology at the Norwegian University of Life Sciences. He is contributing his expertise on biophysical modelling of electrical signals in the brain to this Subproject. Dr. Einevoll is also interested in various aspects of multiscale modeling of early sensory pathways, including how to connect models at different levels of detail, biophysical modeling of astrocytes and their interactions with neurons, as well 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 currently serving as the vice-president of the Organization
of Computational Neurosciences, and is also 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 theoretical neuroscience. He is Research Director at INRIA, where he leads the NeuroMathComp Laboratory, a joint scientific venture between INRIA, the ENS (computer science department), and the JAD Laboratory at the UNSA.
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.
ANDRE GRÜNING, SURREY:
Andre Grüning has been a lecturer in the Department of Computing at the University of Surrey since 2007 after postdoctoral stations at Scuola Internazionale Superioredi Studi Avanzati (SISSA) in Trieste, Italy (in neuroscience) and the University of Warwick, UK (in cognitive science). Dr. Gruning pursued his doctoral studies at the Max Planck Institute for Mathematics in the Sciences in Leipzig, Germany. There he was a member of the complex systems group, which applied mathematical concepts to natural complex systems such as neural networks, pattern formation, and systems biology. He received his diploma degree in mathematical physics from the University of Gottingen, Germany, and studied physics and mathematics in Gottingen and Uppsala, Sweden. Dr. Gruning has been working in the fields of computational, cognitive and theoretical neuroscience with publications on the computational power of neural networks, aspects of unifying reinforcement and supervised learning approaches or learning in multi-layered spiking neural networks.
MARJA-LEENA LINNE, TUT:
Marja-Leena Linne is a Research Team Leader at Tampere University of Technology (TUT, Finland) and Coordinator of INCF National Node of Finland. She holds an Adjunct Professorship in Computational Neuroscience and Neuroinformatics at TUT. Dr. Linne received her M.Sc. in electrical engineering in 1993 and a Ph.D. in signal processing and computational neuroscience in 2001. She was awarded an Academy Research Fellow position (equivalent to Associate Professor) in 2004 to establish an interdisciplinary research team in computational neuroscience. Dr. Linne’s current research interests include development of new models for cellular and subcellular (both neuronal and glial) mechanisms responsible for excitability and plasticity in mammalian cortical networks. She performed experimental work on astrocytes in the early 1990s and used patch clamp, multi-electrode arrays, and microscopy in her work. Her research group also develops theoretical tools to assess the growth and structure-function relationships in local networks. Dr. Linne has developed novel stochastic approaches to model neural systems.
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.
IDAN SEGEV, HUJI:
Idan Segev is the David and Inez Myers Professor in Computational Neuroscience 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 important awards, some for his excellent teaching abilities. He takes a keen interest in the connection between art and the brain. Prompted by an encounter with ICNC researchers, he has recently co-edited an “Artists” book with original etchings by ten top Israeli artists. Segev, the world’s undisputed leader and a pioneer on model neurons, has been instrumental in theoretically ground automated building of model neurons in the Blue Brain Project.
WALTER SENN, UBERN:
Walter Senn holds a Ph.D. in differential geometry and calculus of variation from the University of Bern. After post-doctoral studies in Neural Computation at Hebrew University, Jerusalem, under Professor Idan Segev, and research at the National Institutes of Health and the Center for Neural Sciences (USA), he joined the Department of Physiology at the University of Bern, where he is a full professor in the Department of Computational Neuroscience and co- Editor-in-Chief of Biological Cybernetics. His interests include explaining learning and behaviour using mathematical models of neurons and synapses, and using spiking neuron models and spike-timing dependent synaptic plasticity to understand how learning, memory and perception can emerge from mutually connected neurons. His current focus is on reward-based learning, decision making and spatial map formation.
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.
HBP research is organised into twelve Subprojects, each broken down into Work Packages and Tasks, with well-defined goals and milestones. Six Subprojects are building the ICT Platforms, while the other six are gathering data, clarifying theory and controlling ethical aspects. An additional Subproject manages and coordinates the HBP. Theoretical work in the HBP addresses a set of strategic issues, all related to the goal of achieving a multi-level understanding of the brain. The EITN is part of the Theory subproject (SP4).
To fulfil the EITN goals, our Sp partners are all involved in the Institute in someway.
SP4 co-leaders: Alain Destexhe (CNRS) and Wulfram Gerstner (EPFL).
“To produce simplified models of complex brain structures and dynamics; rules linking learning and memory to synaptic plasticity; large-scale models creating a bridge between ‘high-level’ behavioural and imaging data; and mathematical descriptions of neural computation at different levels of brain organisation.”
More information about the last Human Brain Project Summit 2015: Into the future, a Public Lecture by Prof. Idan Segev to Queen Sofia of Spain and HPB participants.
SP4 workpackages details
April 2016 - March 2018
WP4.1 Bridging Scales - Leader: Alain Destexhe (CNRS)
- T4.1.1 Simplified dendritic neuron models. Leader: Idan Segev (HUJI); Participants: Alain Destexhe (CNRS).
- T4.1.2 Input-output transfer functions of morphologically detailed neuronal models. Leader : Michele Giugliano (UA) ; Participants : Idan Segev (HUJI).
- T4.1.3 Mean-field and population models. Leader : Olivier Faugeras (INRIA) ; Participants : Alain Destexhe (CNRS) and Marc de Kamps (ULEEDS).
- T4.1.4 Models of brain signals. Leader : Alain Destexhe (CNRS) ; Participants : Gaute Einevoll (NMBU)
WP4.2 Generic Models of Brain Circuits- Leader: Markus Diesmann (JUELICH)
- T4.2.1 Simplified network models of different cortical areas. Leader: Markus Diesmann (JUELICH); Participants: Viktor Jirsa (AMU).
- T4.2.2 Network models including neuron-glia interactions. Leader: Marja-Leena Linne (TUT); Participants: André Grüning (SURREY).
WP4.3 Learning and Memory- Leader: Wulfram Gerstner (EPFL)
- T4.3.1 Plasticity algorithms. Leader: Wulfram Gerstner (EPFL); Participants: Walter Senn (UBERN).
- T4.3.2 Learning in networks of neurons. Leader: Walter Senn (UBERN); Participants: Wulfram Gerstner (EPFL) and Misha Tsodyks (WEIZMANN).
- T4.3.3 Functional plasticity for multi-compartment neurons. Leader: André Grüning (SURREY); Participants: Walter Senn (UBERN) and Marja-Leena Linne (TUT).
WP4.4 Models of Cognitive Processes- Leader: Gustavo Deco (UPF)
- T4.4.1 Models of spontaneous brain activity. Leader: Gustavo Deco (UPF); Participants: Alain Destexhe (CNRS).
- T4.4.2 Models of low-level vision. Leader : Olivier Marre (UPMC) ; Participants : Shimon Ullman (WEIZMANN).
- T4.4.3 Models of motor control. Leader : Jeanette Hellgren Kotaleski (KTH).
- T4.4.4 Models of spatial navigation. Leader : Neil Burgess (UCL).
- T4.4.5 Development of a large-scale, mean field model on sensorimotor integration. Leader : Gustavo Deco (UPF).
WP4.5 Linking Model Activity and Function to Experimental data- Leader: Sonja Grün (JUELICH)
- T4.5.1 Comparing models with mouse and human brains. Leader: Sonja Grün (JUELICH); Participants: Viktor Jirsa (AMU).
- T4.5.2 Mouse brain function from structure. Leader: Viktor Jirsa (AMU); Participants: Gustavo Deco (UPF).
WP4.6 The European Institute for Theoritical Neuroscience - Leader: Alain Destexhe (CNRS)
- T4.5.1 EITN coordination. Leader: Alain Destexhe (CNRS).
- T4.5.2 EITN programme. Leader: Alain Destexhe (CNRS).
WP4.7 Theoretical Neuroscience: Scientific coordination - Leader: Alain Destexhe (CNRS)
- T4.6.1 Scientific coordination. Leader: Alain Destexhe (CNRS).