Henry MarkramHenry Markram started a dual scientific and medical career at the University of Cape Town, in South Africa. His scientific work in the 80s 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. Markrams 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 IBMs most advanced supercomputers to reconstruct a detailed computer model of the neocortical column composed of 10000 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, Markrams 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.
Maria del Carmen Sandi PerezACADEMIC POSITION:
Professor, Director of the Laboratory of Behavioral Genetics, Brain Mind Institute, Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland.
EDUCATION:
BS MS Salamanca, Spain, 1984
PhD Cajal Institute, CSIC, and University Autonoma of Madrid, Spain, 1988
PROFESSIONAL EXPERIENCE:
Postdoc at INSERM, Bordeaux, France, and Cajal Institute Madrid, Spain, 1989-1990
Postdoc at the Open University, UK, 1991-1992, 1996
Research Associate, Cajal Institute, CSIC, Madrid, 1993-1995
Associate Professor Tenured, UNED University, Madrid, 1996-2003
Sabbatical Professor, University of Bern, Switzerland, 2002-2003
Assistant Professor Tenure-Track, EPFL, 2003-2007
Associate Professor Tenured, EPFL, 2007-2012
Full Professor, EPFL, 2012-
Director, Brain Mind Institute, EPFL, 2012-
PRINCIPAL BOARDS:
President, European Brain and Behavior Society (EBBS), 2009-2012
Editor-in-Chief Frontiers in Behavioral Neuroscience
Member of Scientific Advisory Panel, European College Neuropsychopharmacology (ECNP)
Member of the European Dana Alliance for the Brain (EDAB)
Associate Editor Frontiers in Neuroscience
Editorial Board Member Neurobiology of Learning and Memory
Editorial Board Member Journal of Psychiatry Research
Editorial Board Member Stress
Editorial Board Member Biology of Mood and Anxiety Disorders
Editorial Board Member Neuroscience and Biobehavioral Reviews
Volkan CevherVolkan Cevher received the B.Sc. (valedictorian) in electrical engineering from Bilkent University in Ankara, Turkey, in 1999 and the Ph.D. in electrical and computer engineering from the Georgia Institute of Technology in Atlanta, GA in 2005. He was a Research Scientist with the University of Maryland, College Park from 2006-2007 and also with Rice University in Houston, TX, from 2008-2009. Currently, he is an Associate Professor at the Swiss Federal Institute of Technology Lausanne and a Faculty Fellow in the Electrical and Computer Engineering Department at Rice University. His research interests include machine learning, signal processing theory, optimization theory and methods, and information theory. Dr. Cevher is an ELLIS fellow and was the recipient of the Google Faculty Research award in 2018, the IEEE Signal Processing Society Best Paper Award in 2016, a Best Paper Award at CAMSAP in 2015, a Best Paper Award at SPARS in 2009, and an ERC CG in 2016 as well as an ERC StG in 2011.
Auke IjspeertAuke Ijspeert is a full professor at the EPFL, and head of the Biorobotics Laboratory (BioRob). He has a B.Sc./M.Sc. in physics from the EPFL (1995), and a PhD in artificial intelligence from the University of Edinburgh (1999). He carried out postdocs at IDSIA and EPFL, and at the University of Southern California (USC). He then became a research assistant professor at USC, and an external collaborator at ATR (Advanced Telecommunications Research institute) in Japan. In 2002, he came back to the EPFL as an SNF assistant professor. He was promoted to associate professor in October 2009 and to full professor in April 2016. His primary affiliation is with the Institute of Bioengineering, and secondary affiliation with the Institute of Mechanical Engineering. His research interests are at the intersection between robotics, computational neuroscience, nonlinear dynamical systems, and machine learning. He is interested in using numerical simulations and robots to get a better understanding of sensorimotor coordination in animals, and in using inspiration from biology to design novel types of robots and adaptive controllers. (see for instance Ijspeert et al Science 2007, Ijspeert Science 2014, and Nyakatura et al Nature 2019). He is also investigating how to assist people with limited mobility using exoskeletons and assistive furniture. He is regularly invited to give talks on these topics (e.g. TED talk given at TED Global Geneva, Dec 8 2015). With his colleagues, he has received paper awards at ICRA2002, CLAWAR2005, IEEE Humanoids 2007, IEEE ROMAN 2014, CLAWAR 2015, SAB2018, and CLAWAR 2019. He is an IEEE Fellow, member of the Board of Reviewing Editors of Science magazine, and associate editor for the IEEE Transactions on Medical Robotics and Bionics and for the International Journal of Humanoid Robotics. He has acted as an associate editor for the IEEE Transactions on Robotics (2009-2013) and for Soft Robotics (2018-2021). He was a guest editor for the Proceedings of IEEE, IEEE Transactions on Biomedical Engineering, Autonomous Robots, IEEE Robotics and Automation Magazine, and Biological Cybernetics. He has been the organizer of 7 international conferences (BioADIT2004, SAB2004, AMAM2005, BioADIT2006, LATSIS2006, SSRR2016, AMAM2019), and a program committee member of over 50 conferences.
Jean-Philippe ThiranJean-Philippe Thiran was born in Namur, Belgium, in August 1970. He received the Electrical Engineering degree and the PhD degree from the Université catholique de Louvain (UCL), Louvain-la-Neuve, Belgium, in 1993 and 1997, respectively. From 1993 to 1997, he was the co-ordinator of the medical image analysis group of the Communications and Remote Sensing Laboratory at UCL, mainly working on medical image analysis. Dr Jean-Philippe Thiran joined the Signal Processing Institute (ITS) of the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, in February 1998 as a senior lecturer. He was promoted to Assistant Professor in 2004, to Associate Professor in 2011 and is now a Full Professor since 2020. He also holds a 20% position at the Department of Radiology of the University of Lausanne (UNIL) and of the Lausanne University Hospital (CHUV) as Associate Professor ad personam. Dr Thiran's current scientific interests include
Computational medical imaging: acquisition, reconstruction and analysis of imaging data, with emphasis on regularized linear inverse problems (compressed sensing, convex optimization). Applications to medical imaging: diffusion MRI, ultrasound imaging, inverse planning in radiotherapy, etc.Computer vision & machine learning: image and video analysis, with application to facial expression recognition, eye tracking, lip reading, industrial inspection, medical image analysis, etc.
