Human Brain Project Mediation Report
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Reconstruction and Simulation of the Cerebellar Microcircuit: a Scaffold Strategy to Embed Different Levels of Neuronal Details
Reconstruction and simulation of the cerebellar microcircuit: a scaffold strategy to embed different levels of neuronal details Claudia Casellato, Elisa Marenzi, Stefano Casali, Chaitanya Medini, Alice Geminiani, Alessandra Pedrocchi, Egidio D’Angelo Department of Brain and Behavioral Sciences, University of Pavia, Italy Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy Computational models allow propagating microscopic phenomena into large‐scale networks and inferencing causal relationships across scales. Here we reconstruct the cerebellar circuit by bottom‐up modeling, reproducing the peculiar properties of this structure, which shows a quasi‐crystalline geometrical organization well defined by convergence/divergence ratios of neuronal connections and by the anisotropic 3D orientation of dendritic and axonal processes [1]. Therefore, a cerebellum scaffold model has been developed and tested. It maintains scalability and can be flexibly handled to incorporate neuronal properties on multiple scales of complexity. The cerebellar scaffold includes the canonical neuron types: Granular cell, Golgi cell, Purkinje cell, Stellate and Basket cells, Deep Cerebellar Nuclei cell. Placement was based on density and encumbrance values, connectivity on specific geometry of dendritic and axonal fields, and on distance‐based probability. In the first release, spiking point‐neuron models based on Integrate&Fire dynamics with exponential synapses were used. The network was run in the neural simulator pyNEST. Complex spatiotemporal patterns of activity, similar to those observed in vivo, emerged [2]. For a second release of the microcircuit model, an extension of the generalized Leaky Integrate&Fire model has been developed (E‐GLIF), optimized for each cerebellar neuron type and inserted into the built scaffold [3]. -
Reverse-Engineering the Brain [email protected]
Prof. Henry Markram Dr. Felix Schürmann Reverse-Engineering the Brain [email protected] http://bluebrainproject.epfl.ch Brain Mind Institute © Blue Brain Project The Electrophysiologist’s View BBP BBP BBP © Blue Brain Project Accurate Models that Relate to Experiment LBCÆPC SBCÆPC NBCÆPC BTCÆPC MCÆPC © Blue Brain Project BBP Phase I: Neocortical Column Create a faithful “in silico” replica at cellular level of a neocortical column of a young rat by the means of: • reverse engineering the biology components • forward constructing functional mathematical models • Building 10,000 morphologically complex neurons • Constructing a circuit with 30,000,000 dynamic synapses • Simulating the column close to real-time © Blue Brain Project Building and Simulating the NCC BBP © Blue Brain Project The Electrocphysiologist’s View - Revisited BBP BBP BBP © Blue Brain Project BBP Phase I: « in vitro » vs. « in silico » BBP BBP BBP BBP in silico in silico in vitro in vitro © Blue Brain Project Level of Detail 0x Channels ,00 Compartment 10 ~20HH style channels/compartment Neuron ~350compartments/neuron Synapses A Rat’s Neocortical Column: IT Challenge: • ~1mm^3 • 3,500,000 compartments • 6 layers • passive (cable, Gauss • > 50 morphological classes Elimination) • ~340 morpho-electrical types • active HH style channels • ~200 types of ion channels • 30,000,000 synapses ~3,000/neuron • 10,000 neurons • dynamic • 18 types of synapses • 30,000,000 synapses • Æ reporting 1 value/compartment Æ 140GB/biol sec © Blue Brain Project Usage of BG/L in the BBP Dedicated 4 rack BG/L @ EPFL with 8192 processors, 2TB of distributed memory, 22.4 TFlop (peak) ÆUsed throughout all parts of the project ÆAllows iteration of complete process within a week • Building: Run evolutionary algorithms for fitting of thousands of single cell models to data typical job size: 2048 procs S. -
A Case Study of a Blue Brain Working on the Neural Network Concept
International Journal of Multidisciplinary Research and Growth Evaluation www.allmultidisciplinaryjournal.com International Journal of Multidisciplinary Research and Growth Evaluation ISSN: 2582-7138 Received: 03-06-2021; Accepted: 19-06-2021 www.allmultidisciplinaryjournal.com Volume 2; Issue 4; July-August 2021; Page No. 201-206 A case study of a blue brain working on the neural network concept Neha Verma Student, Department of Computer Applications, RIMT University, Mandi Gobindgarh, Punjab, India Corresponding Author: Neha Verma Abstract Blue brain is the name of the world's first virtual brain So IBM is trying to create an artificial brain that can think, initiated and founded by the scientist Henry Markram at response and take decisions like human brain. It is called EPFL in Lausanne Switzerland. The main aim behind this "Blue Brain". Hence this paper consists of the concepts of project is to save knowledge of the human brain for decades. Blue Brain, the requirements of the Blue Brain project, It is a well known fact that human doesn't live for thousands various strategies undertaken to build the Blue Brain, of years and the intelligence is also lost after a person's death. advantages and disadvantages and many more. Keywords: Neurons, Nanobots, Blue Gene, Virtual mind, Neuroscience 1. Introduction As we know the human brain is most powerful creation of God and it is very complex to understand the circuit of human brain. However with the advancement in technology, now it is possible to create a virtual brain so in future, the human brains are going to be attacked by the blue brain and it is going to be very useful for all of us. -
The Human Brain Project—Synergy Between Neuroscience, Computing, Informatics, and Brain-Inspired Technologies
COMMUNITY PAGE The Human Brain ProjectÐSynergy between neuroscience, computing, informatics, and brain-inspired technologies 1,2 3 4 5 Katrin AmuntsID *, Alois C. Knoll , Thomas LippertID , Cyriel M. A. PennartzID , 6 7 8 9 10 Philippe RyvlinID , Alain DestexheID , Viktor K. Jirsa , Egidio D'Angelo , Jan G. BjaalieID 1 Institute for Neuroscience and Medicine (INM-1), Forschungszentrum JuÈlich, Germany, 2 C. and O. Vogt Institute for Brain Research, University Hospital DuÈsseldorf, Heinrich Heine University DuÈsseldorf, DuÈsseldorf, Germany, 3 Institut fuÈr Informatik VI, Technische UniversitaÈt MuÈnchen, Garching bei MuÈnchen, a1111111111 Germany, 4 JuÈlich Supercomputing Centre, Institute for Advanced Simulation, Forschungszentrum JuÈlich, a1111111111 Germany, 5 Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, the a1111111111 Netherlands, 6 Department of Clinical Neurosciences, Centre Hospitalo-Universitaire Vaudois (CHUV) and a1111111111 University of Lausanne, Lausanne, Switzerland, 7 Unite de Neurosciences, Information & Complexite a1111111111 (UNIC), Centre National de la Recherche Scientifique (CNRS), Gif-sur-Yvette, France, 8 Institut de Neurosciences des Systèmes, Inserm UMR1106, Aix-Marseille UniversiteÂ, Faculte de MeÂdecine, Marseille, France, 9 Department of Brain and Behavioral Science, Unit of Neurophysiology, University of Pavia, Pavia, Italy, 10 Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway * [email protected] OPEN ACCESS Citation: Amunts K, Knoll AC, Lippert T, Pennartz CMA, Ryvlin P, Destexhe A, et al. (2019) The Abstract Human Brain ProjectÐSynergy between neuroscience, computing, informatics, and brain- The Human Brain Project (HBP) is a European flagship project with a 10-year horizon aim- inspired technologies. PLoS Biol 17(7): e3000344. ing to understand the human brain and to translate neuroscience knowledge into medicine https://doi.org/10.1371/journal.pbio.3000344 and technology. -
The Human Brain Project
HBP The Human Brain Project Madrid, June 20th 2013 HBP The Human Brain Project HBP FULL-SCALE HBP Ramp-up HBP Report mid 2013-end 2015 April, 2012 HBP-PS (CSA) (FP7-ICT-2013-FET-F, CP-CSA, Jul-Oct, 2012 May, 2011 HBP-PS Proposal (FP7-ICT-2011-FET-F) December, 2010 Proposal Preparation August, 2010 HBP PROJECT FICHE: PROJECT TITLE: HUMAN BRAIN PROJECT COORDINATOR: EPFL (Switzerland) COUNTRIES: 23 (EU MS, Switzerland, US, Japan, China); 22 in Ramp Up Phase. RESEARCH LABORATORIES: 256 in Whole Flagship; 110 in Ramp Up Phase RESEARCH INSTITUTIONS (Partners): • 150 in Whole Flagship • 82 in Ramp Up Phase & New partners through Competitive Call Scheme (15,5% of budget) • 200 partners expected by Y5 (Project participants & New partners through Competitive Call Scheme) DIVISIONS:11 SUBPROJECTS: 13 TOTAL COSTS: 1.000* M€; 72,7 M€ in Ramp Up Phase * 1160 M€ Project Total Costs (October, 2012) HBP Main Scheme of The Human Brain Project: HBP Phases 2013 2015 2016 2020 2023 RAMP UP (A) FULLY OPERATIONAL (B) SUSTAINED OPERATIONS (C) Y1 Y2 Y3a Y3b Y4 Y5 Y6 Y7 Y8 Y9 Y10 2014 2020 HBP Structure HBP: 11 DIVISIONS; 13 SUBPROJECTS (10 SCIENTIFIC & APPLICATIONS & ETHICS & MGT) DIVISION SPN1 SUBPROJECTS AREA OF ACTIVITY MOLECULAR & CELLULAR NEUROSCIENCE SP1 STRATEGIC MOUSE BRAIN DATA SP2 STRATEGIC HUMAN BRAIN DATA DATA COGNITIVE NEUROSCIENCE SP3 BRAIN FUNCTION THEORETICAL NEUROSCIENCE SP4 THEORETICAL NEUROSCIENCE THEORY NEUROINFORMATICS SP5 THE NEUROINFORMATICS PLATFORM BRAIN SIMULATION SP6 BRAIN SIMULATION PLATFORM HIGH PERFORMANCE COMPUTING (HPC) SP7 HPC -
Blue Brain Project
Blue Brain Project The Blue Brain Project is an attempt to create a with 100 mesocircuits totalling a hundred million cells. synthetic brain by reverse-engineering mammalian brain Finally a cellular human brain is predicted possible by circuitry. The aim of the project, founded in May 2005 by 2023 equivalent to 1000 rat brains with a total of a hun- the Brain and Mind Institute of the École Polytechnique dred billion cells.[8][9] Fédérale de Lausanne (EPFL) in Switzerland, is to study Now that the column is finished, the project is currently the brain’s architectural and functional principles. busying itself with the publishing of initial results in sci- The project is headed by the founding director Henry entific literature, and pursuing two separate goals: Markram and co-directed by Felix Schürmann and Sean Hill. Using a Blue Gene supercomputer running Michael 1. construction of a simulation on the molecular Hines’s NEURON software, the simulation does not con- level,[1] which is desirable since it allows studying sist simply of an artificial neural network, but involves the effects of gene expression; a biologically realistic model of neurons.[1][2][3] It is hoped that it will eventually shed light on the nature of 2. simplification of the column simulation to allow for consciousness.[3] parallel simulation of large numbers of connected There are a number of sub-projects, including the Cajal columns, with the ultimate goal of simulating a Blue Brain, coordinated by the Supercomputing and Vi- whole neocortex (which in humans consists of about sualization Center of Madrid (CeSViMa), and others run 1 million cortical columns). -
NEST Desktop
NEST Conference 2019 A Forum for Users & Developers Conference Program Norwegian University of Life Sciences 24-25 June 2019 NEST Conference 2019 24–25 June 2019, Ås, Norway Monday, 24th June 11:00 Registration and lunch 12:30 Opening (Dean Anne Cathrine Gjærde, Hans Ekkehard Plesser) 12:50 GeNN: GPU-enhanced neural networks (James Knight) 13:25 Communication sparsity in distributed Spiking Neural Network Simulations to improve scalability (Carlos Fernandez-Musoles) 14:00 Coffee & Posters 15:00 Sleep-like slow oscillations induce hierarchical memory association and synaptic homeostasis in thalamo-cortical simulations (Pier Stanislao Paolucci) 15:20 Implementation of a Frequency-Based Hebbian STDP in NEST (Alberto Antonietti) 15:40 Spike Timing Model of Visual Motion Perception and Decision Making with Reinforcement Learning in NEST (Petia Koprinkova-Hristova) 16:00 What’s new in the NEST user-level documentation (Jessica Mitchell) 16:20 ICEI/Fenix: HPC and Cloud infrastructure for computational neuroscientists (Jochen Eppler) 17:00 NEST Initiative Annual Meeting (members-only) 19:00 Conference Dinner Tuesday, 25th June 09:00 Construction and characterization of a detailed model of mouse primary visual cortex (Stefan Mihalas) 09:45 Large-scale simulation of a spiking neural network model consisting of cortex, thalamus, cerebellum and basal ganglia on K computer (Jun Igarashi) 10:10 Simulations of a multiscale olivocerebellar spiking neural network in NEST: a case study (Alice Geminiani) 10:30 NEST3 Quick Preview (Stine Vennemo & Håkon Mørk) -
Blue Brain-A Massive Storage Space
Advances in Computational Sciences and Technology ISSN 0973-6107 Volume 10, Number 7 (2017) pp. 2125-2136 © Research India Publications http://www.ripublication.com Blue Brain-A Massive Storage Space Y.Vijayalakshmi Dept. of CSE, Karpagam University, Coimbatore, Tamilnadu, India Teena Jose Research Scholar, CS, Bharathiar University Coimbatore, Tamilnadu, India Dr. S. Sasidhar Babu Professor, Dept. of CSE, Sree Narayana Gurukulam College of Engineering, Ernakulam Dt. Kerala, India Sruthi R. Glorya Jose Dept. of CS, St.Thomas College, Thrisur, Kerala, India Dr. P. Manimegalai Prof.,Dept. of ECE, Karpagam University, Coimbatore, Tamilnadu, India. Abstract Human brain, the greatest creation of god which is package of unimaginative functions. A man is intelligent because of the brain. ”Blue Brain” is world’s first virtual brain. Pink brain is special because of that it can think, respond, take decision without any effort and keep anything in memory. Aim of the project is to archive features of Pink brain to a Digital system. In short, ”Brain to a Digital System”. After death of a human, data including intelligence, knowledge, personality, memory and feelings can be used for further development of society. BB Storage space is an extracted concept from Blue brain project. Storing numerous and variety of data on memory is an advantage provided. By this concept, registers act as neurons and Electric signals as simulation impulses. Variation of data are identified based on signal variation that reach the registers. Registers mentioned here is same that a normal system maintains. Benefit 2126 Y.Vijayalakshmi et al focused by this concept of storage is storing data without deletion on real time as normal brain does. -
Large-Scale Simulation of Brain Tissue, Blue Brain Project, EPFL
ANL/ALCF/ESP-17/3 Large-Scale Simulation of Brain Tissue, Blue Brain Project, EPFL Technical Report for the ALCF Theta Early Science Program Argonne Leadership Computing Facility ALCF Early Science Program (ESP) Technical Report ESP Technical Reports describe the code development, porting, and optimization done in preparing an ESP project's application code(s) for the next generation ALCF computer system. This report is for a project in the Theta ESP, preparing for the ALCF Theta computer system. About Argonne National Laboratory Argonne is a U.S. Department of Energy laboratory managed by UChicago Argonne, LLC under contract DE-AC02-06CH11357. The Laboratoryfs main facility is outside Chicago, at 9700 South Cass Avenue, Argonne, Illinois 60439. For information about Argonne and its pioneering science and technology programs, see www.anl.gov. DOCUMENT AVAILABILITY Online Access: U.S. Department of Energy (DOE) reports produced after 1991 and a growing number of pre-1991 documents are available free at OSTI.GOV (http://www.osti.gov/), a service of the U.S. Dept. of Energy's Office of Scientific and Technical Information Reports not in digital format may be purchased by the public from the National Technical Information Service (NTIS): U.S. Department of Commerce National Technical Information Service 5301 Shawnee Rd Alexandria, VA 22312 www.ntis.gov Phone: (800) 553-NTIS (6847) or (703) 605-6000 Fax: (703) 605-6900 Email: [email protected] Reports not in digital format are available to DOE and DOE contractors from the Office of Scientific and Technical Information (OSTI): U.S. Department of Energy Office of Scientific and Technical Information P.O. -
An Overview of Mind Uploading
IOSR Journal of Engineering (IOSR JEN) www.iosrjen.org ISSN (e): 2250-3021, ISSN (p): 2278-8719 PP 18-25 An Overview of Mind Uploading Mrs. Mausami Sawarkar1, Mr. Dhiraj Rane2 Dept of CSE, Priydarshani J L CoE, Nagpur Dept. of CS, GHRIIT, Nagpur Abstract: Mind uploading is an ongoing area of active research, bringing together ideas from neuroscience, computer science, engineering, and philosophy. Realistically, mind uploading likely lies many decades in the future, but the short-term offers the possibility of advanced neural prostheses that may benefit us. Mind uploading is the conceptual futuristic technology of transferring human minds tocomputer hardware using whole-brain emulation process. In this research work, we have discuss the brief review of the technological prospectsfor mind uploading, a range of philosophical and ethical aspects of the technology. We have also summarizes various issues for mind uploading. There are many technologies are working on these issues will be summarize. These include questions about whether uploads will have consciousness and whether uploading willpreserve personal identity, as well as what impact on society a working uploading technology is likelyto have and whether these impacts are desirable. The issue of whether we ought to move forwardstowards uploading technology remains as unclear as ever. Keywords: Mind Uploading, Whole brain simulation, I. Introduction Mind uploading is an ongoing area of active research, bringing together ideas from neuroscience, computer science, engineering, and philosophy. Realistically, mind uploading likely lies many decades in the future, but the short-term offers the possibility of advanced neural prostheses that may benefit us. Mind uploading is a popular term for a process by which the mind, a collection of memories, personality, and attributes of a specific individual, is transferred from its original biological brain to an artificial computational substrate. -
Brain Modelling As a Service: the Virtual Brain on EBRAINS
Brain Modelling as a Service: The Virtual Brain on EBRAINS Michael Schirnera,b,c,d,e, Lia Domidef, Dionysios Perdikisa,b, Paul Triebkorna,b,g, Leon Stefanovskia,b, Roopa Paia,b, Paula Prodanf, Bogdan Valeanf, Jessica Palmera,b, Chloê Langforda,b, André Blickensdörfera,b, Michiel van der Vlagh, Sandra Diaz-Pierh, Alexander Peyserh, Wouter Klijnh, Dirk Pleiteri,j, Anne Nahmi, Oliver Schmidk, Marmaduke Woodmang, Lyuba Zehll, Jan Fousekg, Spase Petkoskig, Lionel Kuschg, Meysam Hashemig, Daniele Marinazzom,n, Jean-François Mangino, Agnes Flöelp,q, Simisola Akintoyer, Bernd Carsten Stahls, Michael Cepict, Emily Johnsont, Gustavo Decou,v,w,x, Anthony R. McIntoshy, Claus C. Hilgetagz, a, Marc Morgank, Bernd Schulleri, Alex Uptonb, Colin McMurtrieb, Timo Dickscheidl, Jan G. Bjaaliec, Katrin Amuntsl,d, Jochen Mersmanne, Viktor Jirsag, Petra Rittera,b,c,d,e,* aBerlin Institute of Health at Charité – Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany bCharité – Universitätsmedizin Berlin, corporate memBer of Freie Universität Berlin and HumBoldt Universität zu Berlin, Department of Neurology with Experimental Neurology, Charitéplatz 1, 10117 Berlin, Germany cBernstein Focus State Dependencies of Learning & Bernstein Center for Computational Neuroscience, Berlin, Germany dEinstein Center for Neuroscience Berlin, Charitéplatz 1, 10117 Berlin, Germany eEinstein Center Digital Future, Wilhelmstraße 67, 10117 Berlin, Germany fCodemart, Str. Petofi Sandor, Cluj Napoca, Romania gInstitut de Neurosciences des Systèmes, Aix Marseille Université, -
© CIC Edizioni Internazionali
4-EDITORIALE_FN 3 2013 08/10/13 12:22 Pagina 143 editorial The XXIV Ottorino Rossi Award Who was Ottorino Rossi? Ottorino Rossi was born on 17th January, 1877, in Solbiate Comasco, a tiny Italian village near Como. In 1895 he enrolled at the medical fac- ulty of the University of Pavia as a student of the Ghislieri College and during his undergraduate years he was an intern pupil of the Institute of General Pathology and Histology, which was headed by Camillo Golgi. In 1901 Rossi obtained his medical doctor degree with the high- est grades and a distinction. In October 1902 he went on to the Clinica Neuropatologica (Hospital for Nervous and Mental Diseases) directed by Casimiro Mondino to learn clinical neurology. In his spare time Rossi continued to frequent the Golgi Institute which was the leading Italian centre for biological research. Having completed his clinical prepara- tion in Florence with Eugenio Tanzi, and in Munich at the Institute directed by Emil Kraepelin, he taught at the Universities of Siena, Sassari and Pavia. In Pavia he was made Rector of the University and was instrumental in getting the buildings of the new San Matteo Polyclinic completed. Internazionali Ottorino Rossi made important contributions to many fields of clinical neurology, neurophysiopathology and neuroanatomy. These include: the identification of glucose as the reducing agent of cerebrospinal fluid, the demonstration that fibres from the spinal ganglia pass into the dorsal branch of the spinal roots, and the description of the cerebellar symp- tom which he termed “the primary asymmetries of positions”. Moreover, he conducted important studies on the immunopathology of the nervous system, the serodiagnosis of neurosyphilis and the regeneration of the nervous system.