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Henry Markram office(s): AAB110 phone(s): [+41 21 69] 39537,39569 BIOGRAPHY Henry Markram started a dual scientific and medical career at the University of Cape Town, in South Africa. His scientific work in the 80’s revealed the polymodal receptive fields of pontomedullary reticular formation neurons in vivo and how acetylcholine re-organized these sensory maps. He moved to Israel in 1988 and obtained his PhD at the Weizmann Institute where he discovered a link between acetylcholine and memory mechanisms by being the first to show that acetylcholine modulates the NMDA receptor in vitro studies, and thereby gates which synapses can undergo synaptic plasticity. He was also the first to characterize the electrical and anatomical properties of the cholinergic neurons in the medial septum diagonal band. He carried out a first postdoctoral study as a Fulbright Scholar at the NIH, on the biophysics of ion channels on synaptic vesicles using sub-fractionation methods to isolate synaptic vesicles and patch-clamp recordings to characterize the ion channels. He carried out a second postdoctoral study at the Max Planck Institute, as a Minerva Fellow, where he discovered that individual action potentials propagating back into dendrites also cause pulsed influx of Ca2+ into the dendrites and found that sub-threshold activity could also activated a low threshold Ca2+ channel. He developed a model to show how different types of electrical activities can divert Ca2+ to activate different intracellular targets depending on the speed of Ca2+ influx – an insight that helps explain how Ca2+ acts as a universal second messenger. His most well known discovery is that of the millisecond watershed to judge the relevance of communication between neurons marked by the back-propagating action potential. This phenomenon is now called Spike Timing Dependent Plasticity (STDP), which many laboratories around the world have subsequently found in multiple brain regions and many theoreticians have incorporated as a learning rule. At the Max-Planck he also started exploring the micro-anatomical and physiological principles of the different neurons of the neocortex and of the mono-synaptic connections that they form - the first step towards a systematic reverse engineering of the neocortical microcircuitry to derive the blue prints of the cortical column in a manner that would allow computer model reconstruction. He received a tenure track position at the Weizmann Institute where he continued the reverse engineering studies and also discovered a number of core principles of the structural and functional organization such as differential signaling onto different neurons, models of dynamic synapses with Misha Tsodyks, the computational functions of dynamic synapses, and how GABAergic neurons map onto interneurons and pyramidal neurons. A major contribution during this period was his discovery of Redistribution of Synaptic Efficacy (RSE), where he showed that co-activation of neurons does not only alter synaptic strength, but also the dynamics of transmission. At the Weizmann, he also found the “tabula rasa principle” which governs the random structural connectivity between pyramidal neurons and a non-random functional connectivity due to target selection. Markram also developed a novel computation framework with Wolfgang Maass to account for the impact of multiple time constants in neurons and synapses on information processing called liquid computing or high entropy computing. In 2002, he was appointed Full professor at the EPFL where he founded and directed the Brain Mind Institute. During this time Markram continued his reverse engineering approaches and developed a series of new technologies to allow large-scale multi-neuron patch-clamp studies. Markram’s lab discovered a novel microcircuit plasticity phenomenon where connections are formed and eliminated in a Darwinian manner as apposed to where synapses are strengthening or weakened as found for LTP. This was the first demonstration that neural circuits are constantly being re-wired and excitation can boost the rate of re-wiring. At the EPFL he also completed the much of the reverse engineering studies on the neocortical microcircuitry, revealing deeper insight into the circuit design and built databases of the “blue-print” of the cortical column. In 2005 he used these databases to launched the Blue Brain Project. The BBP used IBM’s most advanced supercomputers to reconstruct a detailed computer model of the neocortical column composed of 10’000 neurons, more than 340 different types of neurons distributed according to a layer-based recipe of composition and interconnected with 30 million synapses (6 different types) according to synaptic mapping recipes. The Blue Brain team built dozens of applications that now allow automated reconstruction, simulation, visualization, analysis and calibration of detailed microcircuits. This Proof of Concept completed, Markram’s lab has now set the agenda towards whole brain and molecular modeling. With an in depth understanding of the neocortical microcircuit, Markram set a path to determine how the neocortex changes in Autism. He found hyper-reactivity due to hyper-connectivity in the circuitry and hyper-plasticity due to hyper-NMDA expression. Similar findings in the Amygdala together with behavioral evidence that the animal model of autism expressed hyper-fear led to the novel theory of Autism called the “Intense World Syndrome” proposed by Henry and Kamila Markram. The Intense World Syndrome claims that the brain of an Autist is hyper-sensitive and hyper-plastic which renders the world painfully intense and the brain overly autonomous. The theory is acquiring rapid recognition and many new studies have extended the findings to other brain regions and to other models of autism. Markram aims to eventually build detailed computer models of brains of mammals to pioneer simulation-based research in the neuroscience which could serve to aggregate, integrate, unify and validate our knowledge of the brain and to use such a facility as a new tool to explore the emergence of intelligence and higher cognitive functions in the brain, and explore hypotheses of diseases as well as treatments. MAIN PUBLICATIONS Journal Papers Pending C. Cali, T.K. Berger, M. Pignatelli, A. Carleton, H. Markram and M. Giugliano, Inferring connection proximity in networks of electrically coupled cells by subthreshold frequency response analysis, J Comput Neurosci, 2008, 24, 330-45. To appear. [ detailed record ] 2009 S. Gawad, M. Giugliano, M.O. Heuschkel, B. Wessling, H. Markram, V. Schnakenberg, P. Renaud and H. Morgan, Substrate arrays of iridium oxide microelectrodes for in-vitro neuronal interfacing, Frontiers in Neuroengineering, 2009, 2, 1.1-1.7. [ detailed record ] [ full document ] 2008 T. Rinaldi, G. Silberberg and H. Markram, Hyperconnectivity of Local Neocortical Microcircuitry Induced by Prenatal Exposure to Valproic Acid, Cereb Cortex, 2008, 18, 763-70. [ detailed record ] K. Markram, T. Rinaldi, D.L. Mendola, C. Sandi and H. Markram, Abnormal fear conditioning and amygdala processing in an animal model of autism, Neuropsychopharmacology, 2008, 33, 901-12. [ detailed record ] J. Kozloski, K. Sfyrakis, S. Hill, F. Schürmann, C. Peck and H. Markram, Identifying, tabulating, and analyzing contacts between branched neuron morphologies, IBM Journal of Research and Development, 2008, 52, 43-55. [ detailed record ] 2007 H. Markram, T. Rinaldi and K. Markram, The intense world syndrome – an alternative hypothesis for autism, Front. Neurosci., 2007, 1, 77-96. [ detailed record ] S. Druckmann, Y. Banitt, A. Gidon, F. Schürmann, H. Markram and I. Segev, A novel multiple objective optimization framework for constraining conductance-based neuron models by experimental data, Front. Neurosci., 2007, 1, 7-18. [ detailed record ] G. Silberberg and H. Markram, Disynaptic inhibition between neocortical pyramidal cells mediated by Martinotti cells, Neuron, 2007, 53, 735-46. [ detailed record ] T. Rinaldi, K. Kulangara, K. Antoniello and H. Markram, Elevated NMDA receptor levels and enhanced postsynaptic long-term potentiation induced by prenatal exposure to valproic acid, Proc Natl Acad Sci U S A, 2007, 104, 13501-6. [ detailed record ] A. Mazzatenta, M. Giugliano, S. Campidelli, L. Gambazzi, L. Businaro, H. Markram, M. Prato and L. Ballerini, Interfacing neurons with carbon nanotubes: electrical signal transfer and synaptic stimulation in cultured brain circuits, J Neurosci, 2007, 27, 6931-6936. [ detailed record ] H. Markram, Bioinformatics: industrializing neuroscience, Nature, 2007, 445, 160-1. [ detailed record ] J.V. Le Be, G. Silberberg, Y. Wang and H. Markram, Morphological, electrophysiological, and synaptic properties of corticocallosal pyramidal cells in the neonatal rat neocortex, Cereb Cortex, 2007, 17, 2204-13. [ detailed record ] 2006 J.V. Le Be and H. Markram, Spontaneous and evoked synaptic rewiring in the neonatal neocortex, Proc Natl Acad Sci U S A, 2006, 103, 13214-9. [ detailed record ] J.V. Le Be and H. Markram, Spontaneous and evoked synaptic rewiring in the neonatal neocortex, Proc Natl Acad Sci U S A, 2006, 103, 13214-9. [ detailed record ] Y. Wang, H. Markram, P.H. Goodman, T.K. Berger, J. Ma and P.S. Goldman-Rakic, Heterogeneity in the pyramidal network of the medial prefrontal cortex, Nat Neurosci, 2006, 9, 534-42. [ detailed record ] M. Migliore, C. Cannia, W.W. Lytton, H. Markram and M.L. Hines, Parallel network simulations with NEURON, J Comput Neurosci, 2006, 21, 119-29. [ detailed record ] J.V. Le Be and H. Markram, [A new mechanism for memory: neuronal networks rewiring in the young rat neocortex], Med Sci (Paris), 2006, 22, 1031-3. [ detailed record ] 2005 M. Toledo-Rodriguez, P. Goodman, M. Illic, C. Wu and H. Markram, Neuropeptide and calcium-binding protein gene expression profiles predict neuronal anatomical type in the juvenile rat, J Physiol, 2005, 567, 401-13. [ detailed record ] A.J. Muhammad and H. Markram, NEOBASE: databasing the neocortical microcircuit, Stud Health Technol Inform, 2005, 112, 167-77. [ detailed record ] N. Kalisman, G. Silberberg and H. Markram, The neocortical microcircuit as a tabula rasa, Proc Natl Acad Sci U S A, 2005, 102, 880-5. [ detailed record ] O. Melamed, G. Silberberg, H. Markram, W. Gerstner and M.J.E. Richardson, Subthreshold cross-correlations between cortical neurons: A reference model with static synapses, NEUROCOMPUTING, 2005, 685-690. [ detailed record ] [ full document ] M.J.E. Richardson, O. Melamed, G. Silberberg, W. Gerstner and H. Markram, Short-term-plasticity orchestrates the response of pyramidal cells and interneurons to population bursts, J. Computational Neuroscience, 2005, 18, 323-331. [ detailed record ] [ full document ] 2004 G. Silberberg, M. Bethge, H. Markram, K. Pawelzik and M. Tsodyks, Dynamics of population rate codes in ensembles of neocortical neurons, Journal of Neurophysiology, 2004, 91, 704-709. [ detailed record ] Y. Wang, M. Toledo-Rodriguez, A. Gupta, C. Wu, G. Silberberg, J. Luo and H. Markram, Anatomical, physiological and molecular properties of Martinotti cells in the somatosensory cortex of the juvenile rat, J Physiol, 2004, 561, 65-90. [ detailed record ] M. Toledo-Rodriguez, B. Blumenfeld, C. Wu, J. Luo, B. Attali, P. Goodman and H. Markram, Correlation maps allow neuronal electrical properties to be predicted from single-cell gene expression profiles in rat neocortex, Cereb Cortex, 2004, 14, 1310-27. [ detailed record ] G. Silberberg, C. Wu and H. Markram, Synaptic dynamics control the timing of neuronal excitation in the activated neocortical microcircuit, J Physiol, 2004, 556, 19-27. [ detailed record ] W. Maass, T. Natschlager and H. Markram, Fading memory and kernel properties of generic cortical microcircuit models, J Physiol Paris, 2004, 98, 315-30. [ detailed record ] O. Melamed, W. Gerstner, W. Maass, M. Tsodyks and H. Markram, Coding and Learning of behavioral sequences, Trends in Neurosciences, 2004, 27, 11-14. [ detailed record ] [ full document ] 2003 S. Häusler, H. Markram and W. Maass, Perspectives of the high-dimensional dynamics of neural microcircuits from the point of view of low-dimensional readouts, Complexity, 2003, 8, 39 - 50. [ detailed record ] J.F. Linden and H. Markram, Preface to the Special Issue, Cerebral Cortex, 2003, 13, 1. [ detailed record ] N. Kalisman, G. Silberberg and H. Markram, Deriving physical connectivity from neuronal morphology, Biol Cybern, 2003, 88, 210-8. [ detailed record ] 2002 Y. Wang, A. Gupta, M. Toledo-Rodriguez, C.Z. Wu and H. Markram, Anatomical, physiological, molecular and circuit properties of nest basket cells in the developing somatosensory cortex, Cereb Cortex, 2002, 12, 395-410. [ detailed record ] T. Natschläger, W. Maass and H. Markram, The "Liquid Computer": A Novel Strategy for Real-Time Computing on Time Series, Special Issue on Foundations of Information Processing of TELEMATIK , 2002, 8, 39-43. [ detailed record ] W. Maass and H. Markram, Synapses as dynamic memory buffers, Neural Networks, 2002, 15, 155-161. [ detailed record ] G. Fuhrmann, I. Segev, H. Markram and M. Tsodyks, Coding of temporal information by activity-dependent synapses, J Neurophysiol, 2002, 87, 140-8. [ detailed record ] G. Fuhrmann, H. Markram and M. Tsodyks, Spike frequency adaptation and neocortical rhythms, Journal of Neurophysiology, 2002, 88, 761-770. [ detailed record ] W. Maass, T. Natschlager and H. Markram, Real-time computing without stable states: a new framework for neural computation based on perturbations, Neural Comput, 2002, 14, 2531-60. [ detailed record ] 1997 W. Gerstner, A.K. Kreiter, H. Markram and A.V.M. Herz, Neural codes: firing rates and beyond, Proc. Natl. Acad. Sci. USA, 1997, 94, 12740-12741. [ detailed record ] Conference Papers 2003 W. Maass, T. Natschläger and H. Markram, A Model for Real-Time Computation in Generic Neural Microcircuits, 2003. [ detailed record ] 2002 W. Maass, R.A. Legenstein and H. Markram, A New Approach towards Vision Suggested by Biologically Realistic Neural Microcircuit Models, Biologically Motivated Computer Vision, 2002, 282-293. [ detailed record ] Reviews 2006 H. Markram, The blue brain project, Nat Rev Neurosci, 2006, 7, 153-60. [ detailed record ] 2005 G. Silberberg, S. Grillner, F.E. LeBeau, R. Maex and H. Markram, Synaptic pathways in neural microcircuits, Trends Neurosci, 2005, 28, 541-51. [ detailed record ] S. Grillner, H. Markram, E. De Schutter, G. Silberberg and F.E. LeBeau, Microcircuits in action--from CPGs to neocortex, Trends Neurosci, 2005, 28, 525-33. [ detailed record ] 2004 H. Monyer and H. Markram, Interneuron Diversity series: Molecular and genetic tools to study GABAergic interneuron diversity and function, Trends Neurosci, 2004, 27, 90-7. [ detailed record ] H. Markram, M. Toledo-Rodriguez, Y. Wang, A. Gupta, G. Silberberg and C. Wu, Interneurons of the neocortical inhibitory system, Nat Rev Neurosci, 2004, 5, 793-807. [ detailed record ] 2003 R. Legenstein, H. Markram and W. Maass, Input prediction and autonomous movement analysis in recurrent circuits of spiking neurons, Rev Neurosci, 2003, 14, 5-19. [ detailed record ] 2002 G. Silberberg, A. Gupta and H. Markram, Stereotypy in neocortical microcircuits, Trends Neurosci, 2002, 25, 227-30. [ detailed record ] Books 2006 A.J. Ijspeert, J. Buchli, A. Selverston, M. Rabinovich, M. Hasler, W. Gerstner, A. Billard, H. Markram and D. Floreano, Dynamical principles for neuroscience and intelligent biomimetic devices, Lausanne : EPFL, 2006. [ detailed record ] Book Chapters 2005 H. Markram, X. Luo, G. Silberberg, M. Toledo-Rodriguez and A. Gupta, The Neocortical Microcircuit Database (NMDB). , in Databasing the Brain: From Data to Knowledge (Neuroinformatics), Wiley Press, 2005. [ detailed record ] 2004 W. Maass, T. Natschläger and H. Markram, Computational Models for Generic Cortical Microcircuits, in Computational Neuroscience: A Comprehensive Approach, Chapman & Hall/CRC, 2004. [ detailed record ] A. Gupta, M. Toledo-Rodriguez, G. Silberberg and H. Markram, Interneuron Heterogeneity in the Neocortex, in Excitatory-Inhibitory Balance: Synapses, Circuits, Systems , Kluwer Academic Publishing, 2004. [ detailed record ] 2003 T. Natschläger, H. Markram and W. Maass, Computer models and analysis tools for neural microcircuits, in Neuroscience Databases: A Practical Guide,, Kluwer Academic Publishers , 2003. [ detailed record ] W. Maass and H. Markram, Temporal integration in recurrent microcircuits, in The Handbook of Brain Theory and Neural Networks, MIT Press, 2003. [ detailed record ] Patents 2007 H. Markram, T. Rinaldi, T. Markram, M. Rodriguez Bravo, B. Mattson and K. Kulangara, Methods For Treating And/Or Preventing Pervasive Developmental Disorders In A Subject, Patent # WO2007029063. [ detailed record ]

Teaching Life Sciences and Technologies Neurosciences III [en] (SSC SPH SSV) Phd programs Neuroscience Phd Students Delattre Vincent Gambazzi Luca Ghobril Jean Pierre Jan Asif Muhammad Khazen Georges Muralidhar Shruti Pedrossian Coelho Mônica Regina Perin Rodrigo de Campos Rajnish Ranjan Ramaswamy Srikanth Reimann Michael Riachi Imad Tauheed Farhan