Henry Markram is a professor of neuroscience at the Swiss Federal Institute for Technology (EPFL), director of the Laboratory of Neural Microcircuitry (LNMC) and the Founder and Director of the Blue Brain Project.
After earning his PhD at the Weizmann Institute of Science, with distinction, he was a Fulbright scholar at the National Institutes of Health, and a Minerva Fellow at the Max-Planck Institute for Medical Research. 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 organization 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 Project to digitally reconstruct and simulate the mouse brain.
Markram has published well over three hundred papers which have been cited over 25’000 times. Since 2002, he has spearheaded Switzerland’s ambition to become a world leader in high performance computing and to prioritize simulation-based research; these fields are now two of the three national research priorities declared by the Swiss government.
Markram is also the founder of the Brain Mind Institute and the founder of the European Human Brain Project, one of two ten-year one billion Euro Flagship Projects selected in January 2013 by the European Commission. He designed and co-founded the Frontiers open access publishing model to bring efficiency, accountability and transparency to peer-review (frontiersin.org).
Markram has received numerous awards including the Shannon Visionary Award from Bell Labs and the International Hebb Award from the International Neural Network Society.
Henry has five kids and what he likes most is to go hiking with them in the Alps.
Amsalem, O., King, J., Reimann, M., Ramaswamy, S., Muller, E., Markram, H. Dense Computer Replica of Cortical Microcircuits Unravels Cellular Underpinnings of Auditory Surprise Response (2020)
Chindemi, G., Abdellah, M., Amsalem, O., Benavides-Piccione, R., Delattre, V., Doron, M., Ecker, A., King, J., Kumbhar, P., Monney, C., Perin, R., Rössert, C., Van Geit, W., DeFelipe, J., Graupner, M., Segev, I., Markram, H., & Muller, E. (2020). A calcium-based plasticity model predicts long-term potentiation and depression in the neocortex. bioRxiv, 2020.04.19. https://doi.org/10.1101/2020.04.19.043117
Nolte, M., Gal, E., Markram, H., and Reimann, M.W. (2020). Impact of higher-order network structure on emergent cortical activity. Network Neuroscience. 4, 1–36.
Newton, T., Abdellah, M., Chevtchenko, G., Muller, E., Markram, H. Voltage-Sensitive Dye Imaging reveals inhibitory modulation of ongoing cortical activity (October 2019)
Barros-Zulaica, N., Rahmon, J., Chindemi, G., Perin, R., Markram, H., Ramaswamy, S., and Muller, E. Estimating the readily-releasable vesicle pool size at layer 5 pyramidal connections in the neocortex. Front. Synaptic Neurosci., 15 October 2019.
Nolte M., Reimann M.W., King J., Markram H., Muller E., Cortical reliability amid noise and chaos Nature Communications, 22 August 2019,
Ranjan R, Logette E, Marani M, Herzog M, Tâche V, Scantamburlo E, Buchillier V and Markram H. A Kinetic Map of the Homomeric Voltage-Gated Potassium Channel (Kv) Family. Front. Cell. Neurosci., 20 August 2019.
Iavarone E., Yi J., Shi Y., Zandt B.J., O’Reilly C., Van Geit W., Rössert C., Markram, H., Hill, S.L. (2019) Experimentally-constrained biophysical models of tonic and burst firing modes in thalamocortical neurons. PLOS Computational Biology 15(5): 1-23. e1006753.
Fan X and Markram H (2019). A Brief History of Simulation Neuroscience. Front. Neuroinform. 13:32.07 May 2019-
Kanari, L., Ramaswamy, S., Shi, Y., Morand, S., Meystre, Julie., Perin, R., Abdellah, M., Wang, Y., Hess, K., Markram., Objective Morphological Classification of Neocortical Pyramidal Cells. Cerebral Cortex, Volume 29, Issue 4, April 2019, Pages 1719–1735, DOI: 10.1093/cercor/bhy339
Erö, C., Gewaltig, M.-O., Keller, D., and Markram, H. (2018). A Cell Atlas for the Mouse Brain. Frontiers in Neuroinformatics 12, 84.
Kanari, L., Dłotko, P., Scolamiero, M., Levi, R., Shillcock, J., Hess, K., and Markram, H. (2018a). A Topological Representation of Branching Neuronal Morphologies. Neuroinformatics 16, 3–13.
Abdellah, M., Hernando, J., Antille, N., Eilemann, S., Markram, H., and Schürmann, F. (2017). Reconstruction and visualization of large-scale volumetric models of neocorticalcircuits for physically-plausible in silico optical studies. BMC Bioinformatics 18, 402.
Gal, E., London, M., Globerson, A., Ramaswamy, S., Reimann, M.W., Muller, E., Markram, H., and Segev, I. (2017). Rich cell-type-specific network topology in neocortical microcircuitry. Nat. Neurosci. 20, 1004–1013.
Reimann, M.W., Nolte, M., Scolamiero, M., Turner, K., Perin, R., Chindemi, G., Dłotko, P., Levi, R., Hess, K., and Markram, H. (2017). Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function. Front Comput Neurosci 11, 48.
Amsalem, O., Van Geit, W., Muller, E., Markram, H., and Segev, I. (2016). From Neuron Biophysics to Orientation Selectivity in Electrically Coupled Networks of Neocortical L2/3 Large Basket Cells. Cereb. Cortex 26, 3655–3668.
Kanari, L., Dlotko, P., Scolamiero, M., Levi, R., Shillcock, J., Hess, K., and Markram, H. (2016). Quantifying topological invariants of neuronal morphologies. arXiv.
Markram, H., Lubke, J. Frotscher M., and Sakmann. B., (1997). Spike Timing Dependent Plasticity – Spike Times Matter: Regulation of Synaptic Efficacy by Coindence of Postsynaptic APs and EPSPs. Science, 275, pp. 213-215.
Markram H., and Tsodyks. M., (1996). Redistribution of Synaptic Dynamics – Plasticity of Short-Term Dynamics: Redistribution of Synaptic Efficacy Between Neocortical Pyramidal Neurons. Nature, 382, pp. 807-810.
Tsodyks, M., and Markram. H., (1997). The Tsodyks-Markram Model of dynamic synaptic transmission: The Neural Code Between Neocortical Pyramidal Neurons Depends on Neurotransmitter Release Probability. PNAS, 94, pp. 719-723.
Markram H., and Segal. M., (1990). Gating synaptic plasticity: Long-Lasting Facilitation of Excitatory Postsynaptic Potentials in the Rat Hippocampus by Acetylcholine. J Physiol, 427, pp. 381-393.
Delattre, V. , Keller, D., Perich, M., Markram H., and Muller, E. B., (2015). Network Timing Plasticity – Timing of the Network Matters: Network-timing-dependent plasticity. Frontiers in Cellular Neuroscience, 9, pp. 220.
Le Be, J. –V., and Markram, H., (2006). Rewiring neural microcircuitry: Spontaneous and Evoked Synaptic Rewiring in the Neonatal Neocortex. PNAS, 103(35), pp. 13214-9.
Markram, H., Lubke, J., Frotscher, M., Roth, A., and Sakmann, B., (1997). First detailed Anatomical and Physiological Map of a Neocortical Synaptic Pathway: Physiology and Anatomy of Synaptic Connections Between Thik Tufted Pyramidal Neurones in the Developing Rat Neocortex. J Physiol, 500, pp. 409-440.
Markram, H., Wang, Y., Tsodyks. M., (1998). Axons speak many “languages”: Differential Signaling via the Same Axon of Neocortical Pyramidal Neurons. PNAS, 95, pp. 5323-5328.
Gupta, A., Wang, Y., and Markram, H., (2000). Map of Inhibitory Synapses of the Neocortex: Organizing Principles for a Diversity of GABAergic Interneurons and Synapses in the Neocortex. Science, 287(5451), pp. 273-8.
Raimondo, J. V., Markram, H., and Akerman, C. J., (2012). Plasticity of Inhibitory Synapses: Short-Term Ionic Plasticity at GABAergic Synapses. Frontiers in Synaptic Neuroscience, 4, pp. 5.
Perin, R. Berger, T. K., and Markram, H., (2011). The Common Neighbor Rule for Synaptic Connectivity: A Synaptic Organizing Principle for Cortical Neuronal Groups. PNAS, 108(13), pp. 5419-24.
Hill, S. L., Wang,Y., Riachi, I., Schürmann, F., and Markram, H., (2012). Order in networks by chance: Statistical Connectivity Provides a Sufficient Foundation for Specific Functional Connectivity in Neocortical Neural Microcircuits. PNAS, 109(42), pp. e2885-94.
Kalisman, N., Silberberg, G., and Markram, H., (2005). A vast potential: The Neocortical Microcircuit as a Tabula Rasa. PNAS, 102(3), pp. 880-5.
Reimann, M. W., King, J. G., Muller, E. B., Ramaswamy, S., and Markram, H., (2015). The connectome can be computed: An Algorithm to Predict the Connectome of Neural Microcircuits. Frontiers in Computational Neuroscience, 9, pp. 120.
Markram, H., Muller, E., Ramaswamy, S., Reimann, M. W., Abdellah, M. et al. First digital reconstruction of the neocortical column: Reconstruction and Simulation of Neocortical Microcircuitry. Cell, 163(2), pp. 456-492.
Markram, H., and Sakmann, B., (1994). A “soft: dendritic calcium signal: Calcium Transients in Apical Dendrites Evoked by Single Sub-Threshold Excitatory Post-Synaptic Potentials via Low Voltage-Activated Calcium Channels. PNAS, 91, pp. 5207-5211.
Markram, H., Helm, P. J., and Sakmann, B., (1995). A “loud” dendritic calcium signal: Dendritic Calcium Transients Evoked by Single Back-Propagating Action Potentials in Rat Neocortical Pyramidal Neurons. J Physiol, 485, pp. 1-20.
Ramaswamy, S., Hill, S. L., King, J. G., Markram, H., Schürmann, F., Wang, Y., et al. Power of being different: Intrinsic Morphological Diversity of Thick-Tufted Layer 5 Pyramidal Neurons Ensures Robust and Invariant Properties of In Silico Synaptic Connections. J Physiol, 590, pp. 737-52.
Rinaldi, T., Silberberg, G., and Markram, H., (2008). Hyperconnectivity of Local Neocortical Microcircuitry Induced by Prenatal Exposure to Valproic Acid. Cereb Cortex, 18(4), pp. 763-70.
Rinaldi, T., Kulangara, K., Antoniello, K., Markram, H., (2007). Super synaptic learning in autism: Elevated NMDA Receptor Levels and Enhanced Postsynaptic Long-Term Potentiation Induced by Prenatal Exposure to Valproic Acid. PNAS, 104(33), pp. 13501-6.
Silva, T., Le Bé, J. -V., Riachi, I., Rinaldi, T., Markram, K., Markram, M, (2009). Super circuit learning in autism: Enhanced Long-Term Microcircuit Plasticity in the Valproic Acid Animal Model of Autism. Frontiers in Synaptic Neuroscience, 1, pp. 1.
Markram, K., Rinaldi, T., La Mendola, D., Sandi, C., and Markram, H., (2008). Super fear in autism: Abnormal Fear Conditioning and Amygdala Processing in an Animal Model of Autism. Neuropsychopharmacology, 33(4), pp. 901-12.
Monica Regina, F., La Mendola, D., Meystre, J., Christodoulou, D., Cochrane, M. et al. (2015). Curing the negative symptoms in autism: Predictable Enriched Environment Prevents Development of Hyper-Emotionality in the VPA Rat Model of Autism. Frontiers in Neuroscience, 9(127).
Markram, K., and Markram, H., (2010). Just too intense: The Intense World Theory – a Unifying Theory of the Neurobiology of Autism. Frontiers in Human Neuroscience, 4, pp. 224.
Maass, W., Natschläger, T., and Markram, H., (2002). The brain as a super liquid: Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations. Neural Computation, 14(11), pp. 2531-2560.