Subproject 1

Mouse Brain Organisation

What we do

Human and animal brains share many characteristics, but it is more difficult for scientists to work on the former; there are experiments that cannot be done on humans for ethical reasons and so they are done on mice instead.

The human brain shares many common features with other non-human mammals. These features can be considered as basic building blocks of mammalian brain organisation. Therefore, choosing appropriate experiments to obtain strategic data that can be extrapolated to the human brain is a major goal in SP1. For this purpose, many neuroscientists suggest that the ideal experimental animals at present are rodents, because they can be manipulated to study many aspects from genes to behaviour. Furthermore, we can use relatively large numbers of animals at a relatively low cost.

The next challenge is what can be done with the data and how can it be interpreted. It seems that the most appropriate approach to better understand the brain is to link detailed structural data of the whole brain with genetic, molecular, cellular and physiological data. This integration allows the generation of models that present the data in a form that can be used to rationalise, make predictions and suggest new hypotheses to discover new aspects of the structural and functional organisation of the brain.

How we are organised

Work Package (WP) 1.1    Subcellular and Molecular: Many different levels of molecular data are required to understand the function of single cells, circuits and brain function. This Work Package will therefore generate, obtain and integrate data at various subcellular and molecular levels. Since the initial phase of the Project, rapid technological advances have enabled this type of data to be analysed at in much greater detail, and some of these methods have meant that diversity across many cells, brain regions and the whole brain can be mapped.

WP1.2    Cell and Microcircuitry: This Work Package aims to carry out novel analyses in order to generate the data needed for validated high-fidelity brain models. The work concentrates on four major brain regions: the neocortex, hippocampus, basal ganglia, and cerebellum. The data generated include the number and spatial distribution of neurons, glia, and specific types of synapses, as well as correlation between morphology and physiology.

WP1.3    Whole Brain: We propose to go beyond the state of the art by investigating meso-scale (millimetres to centimetres) multilevel maps of the mouse brain through an integrated view of anatomy and functionality. In terms of anatomy, the intention is to determine the spatial distribution of different cell types, based on the expression of certain proteins, across the entire brain, and to refine the maps produced according to different neuronal types. This will be complemented by imaging of cortical functionality, investigating the functional connectivity involved when specific tasks are performed.

WP1.4  Molecular, structural and functional integration of data in brain circuits: A main issue in Neuroscience is to reconnect brain organization and function across different scales, moving from single neurons to collections of neurons assembled into microcircuits and large-scale neworks. This involves the combination of advanced technologies in order to perform recordings at different scales. WP1.4 includes tasks facing the issue by building on some of the technologies adopted in WP1.2 and WP1.3 and strongly integrates with WP1.2 in order to reconnect the microscopic and mesoscopic to the macroscopic scale. WP1.4 addresses four key points for model reconstruction: neuroanatomical data collection for reconstruction of brain circuits; how neuronal activity is reorganized by neuromodulation in cortico-cortical and cortico-thalamic loops in the neocortex, how synaptic plasticity is distributed in the circuits during activity, how information is transferred through an extended loop formed by cerebellum, cerebral cortex and basal ganglia.

WP1.5   Comparative study of cells and microcircuits in the rodent and human brain: WP1.5 will generate strategic comparative data on human and rodent neurons and circuits that will directly be fed into theory and model simulations in SP4 and SP6. Thereby, this WP will provide anchor points for translation from rodent neuronal circuit simulations to human neuronal circuit simulations.

WP1.6  Scientific Coordination and Management: This Work Package aims to ensure that work within SP1 is carried out according to the planned objectives and to coordinate HBP research on strategic mouse brain data, ensuring that the work is efficiently organised and documented and that the research contributes to the overall HBP goals.

Key People

Publication highlights

• Miki T, Kaufmann WA, Malagon G, Gomez L, Tabuchi K, Watanabe M, et al. Correspondence between presynaptic Ca²⁺ channel clusters and functionally defined vesicular docking sites in single central synapses. Proc Nat Acad Sci USA 2017;114:E5246-E5255. DOI: 10.1073/pnas.1704470114.
• Schmid F, Barrett MJP, Jenny P, Weber B. Vascular density and distribution in neocortex. NeuroImage 2017; pii: S1053-8119(17)30516-5. DOI: 10.1016/j.neuroimage.2017.06.046.
• Eyal G, Verhoog MB, Testa-Silva G, Deitcher Y, Lodder JC, Benavides-Piccione R, et al. Unique membrane properties and enhanced signal processing in human neocortical neurons. eLife 2016;5:e16553. DOI: 10.7554/eLife.16553.
• Kohus Z, Káli S, Rovira-Esteban L, Schlingloff D, Papp O, Freund TF, et al. Properties and dynamics of inhibitory synaptic communication within the CA3 microcircuits of pyramidal cells and interneurons expressing parvalbumin or cholecystokinin. J Physiol 2016;594:3745–3774. DOI: 10.1113/JP272231.

Subproject 2

Human Brain Organisation

What we do

Our brain consists of around 86 billion nerve cells, the neurons. Each neuron is connected to between 1 and 200,000 other neurons, resulting in 100 trillion nerve fibres running through the brain. This high complexity is further increased by the inter-individual variability of the brain - each of us is different, has different talents, feelings and their own personality. How the brain is organised, which brain regions are interconnected and which areas work together to execute a certain function is by far not fully answered.

SP2 researchers from 14 research institutions throughout Europe are working on these questions by using many different methods. For example, researchers of the Forschungszentrum Jülich in Germany are working on a map of the human brain (JuBrain atlas) based on differences in the distribution and size of the neurons in brains of body donors. Connections between the neurons, i.e. nerve fibres and bundles can be detected by powerful methods such as polarized light imaging (PLI) and diffusion tensor imaging (DTI), where experts in Jülich and at the CEA in Paris collaborate. Functional magnetic resonance imaging (fMRI) is used by groups in the Netherlands, France, Belgium, UK and Germany to identify regions and networks involved in brain functions like visual and auditory processing or cognition, and reveals more and more details of the functional brain organisation.

One of the greatest goals of SP2 is to develop the HBP Human Brain Atlas, which can be used by neuroscientists all over the world, in neurosurgery and as a basis to understand the differences between the healthy and diseased brain.

How we are organised

Work Package (WP) 2.1  Multimodal whole mapping: This Work Package contributes maps reflecting different modalities of brain organisation at different spatial scales including maps of functional specialisation, brain dynamics, connectivity, and microstructure, and analyses their relationship in order to come to a comprehensive understanding of the different principles contributing to brain organisation at different levels.

WP2.2   Development of a cognitive architecture for visuo-motor integration tasks based on the multi-level organization of the human brain: This Work Package uses multi-level and multi-species brain data to assign and model computational functions for more than 20 human brain areas subserving visuo-motor integration tasks.

WP2.3    Multi-modal, high resolution model of the human hippocampus including cells, fibres, receptors, gene expressions for theory, modelling, simulation and atlas: The aim of this Work Package is to obtain a description of the human hippocampal complex using various techniques that will produce different functional and morphological data of the region itself. Indeed, in general, each single group produces the own data without a link to other methodologies.

WP2.4   Inter-subject variability of the human brain at its relation to geno- and phenotype: Individuality is one of the defining factors of being human. And just as every person is different from anybody else, so are the individual neurobiological features of the human brain. However, only macroscopic features accessible through MR imaging are currently collectible across sufficiently large cohorts for the quantification of inter-individual variability and their relation to geno- and phenotypes. The emerging availability of datasets comprising hundreds to thousands of (on all levels) well- characterised subjects in turn is of high relevance to understanding and modelling the human brain, as it allows to provide location specific information on the relation between neurobiology, genetic data and most importantly phenotypes, i.e., individual behaviour. This Work Package capitalises on these developments in combination with the HBP-HPC infrastructure in order to provide Data and Models that quantify different aspects of inter-individual differences.

WP2.5  Cross-species comparisons of mouse, rat, monkey and human brains in visuo-motor areas and medial temporal lobe:  Due to the size, complexity, individual variation, and limited methods available to study the human brain, the great majority of basic neuroscience research focuses on model organisms with the assumption of partial conservation of function, structure and connectivity across mammalian species. This assumption is largely unfounded and has been costly, as the vast majority of preclinical trials based on rodent studies are unsuccessful. In addition, although the human and mouse brain share common brain areas, the 1000-fold larger human brain contains many brain areas supporting functions that do not exist in the rodent brain. Therefore, to determine which aspects translate from rodent brain to primate brain, and which do not, it is essential to identify features (structural and functional) that are conserved and divergent across species, to facilitate reaching HBP’s overarching goal to simulate human brain function based on strategic data from mouse brain. In this workpackage we will identify features at multiple levels of organisation by analysing inter-species differences and commonalities in mouse, rat, monkey and human brains in visuo-motor areas and the medial temporal lobe at different spatio-temporal scales.

WP2.6    Develop and apply tools in co-design projects to bring the knowledge and the results to the scientific community: This Work Package aggregates all the methodological efforts of the SP2’s team to finalise tools that are either required as plug- in in the HBP’s digital infrastructures (mainly SP5 & SP7, and maybe SP8), or required for high-throughput analysis of the data to be delivered by the other Workpackages of SP2. Therefore, this Workpackage creates the bridges required for the data and concepts generated by the other WP to be seamlessly embedded in the different platforms.

WP2.7    Coordination and Management. This Work Package aims to coordinate the scientific activities within SP2 and its interactions with other SPs, the entire HBP, and the larger community.

Key People

Publication highlights

• Amunts K, Ebell C, Muller J, Telefont M, Knoll A, Lippert T. The Human Brain Project: Creating a European research infrastructure to decode the human brain. Neuron 2016;92:574–581. DOI: 10.1016/j.neuron.2016.10.046
• Eickhoff SB, Constable RT; Yeo BT. Topographic organization of the cerebral cortex and brain cartography. Neuroimage (in press). DOI: 10.1016/j.neuroimage.2017.02.018
• Kemper VG, De Martino F, Emmerling TC, Yacoub E, Goebel R. 2017. High resolution data analysis strategies for mesoscale human functional MRI at 7 and 9.4 T. Neuroimage 2017; DOI: 10.1016/j.neuroimage.2017.03.058 (in press).
• Klink PC, Dagnino B, Gariel-Mathis MA, Roelfsema PR. Distinct feedforward and feedback effects of microstimulation in visual cortex reveal neural mechanisms of texture-segregation. Neuron 2017;95:209–220.e3 DOI: 10.1016/j.neuron.2017.05.033
• Nichols TE, Das S, Eickhoff SB, Evans AC, Glatard T, Hanke M, et al. Best practices in data analysis and sharing in neuroimaging using MRI. Nature Neurosci 2017;20:299–303. DOI: 10.1038/nn.4500

Contact Person:

Dr. Sabine BRADLER
Forschungszentrum Jülich
Wilhelm-Johnen-Straße
52428 Jülich
Germany
e-mail: s.bradler@fz-juelich.de

Subproject 3

Systems and Cognitive Neuroscience

What we do

Our goal is to uncover neural mechanisms underlying cognitive processes, such as learning, multisensory integration, perception, sleep, consciousness, and associated systems phenomena. The results provide the constraints for the development of computational models of cognitive and systems-level processes that will be implemented in robots and neuromorphic computing systems. SP3 addresses these issues at multiple study levels (cells, groups, networks, brain systems) and works to unify different disciplines.

One of the deepest unsolved problems in science is the nature of consciousness. How is consciousness generated by the brain? Current limitations in answering this question cause several clinical and ethical problems, such as assessing the level of consciousness in patients following brain injury. Novel ways to measure consciousness levels will make us less dependent on purely behavioural measures, which will benefit, for instance, minimally conscious patients.

Similarly, how can disparate phenomena such as sleep and wakefulness emerge from the same cortico-thalamic systems in the brain? To answer this question, we will investigate slow-wave activity and simulations of large populations of firing neurons in mice and humans.

SP3 also investigates brain mechanisms of memory. Episodic memory is the memory of our personal, conscious experiences set within space and time. It defines who we are. The brain’s ability to recall objects and experiences from multisensory information, such as vision, audition or touch sensation is a key to understanding memory in humans and animals. We will conduct a coordinated series of experiments to identify the precise neuronal mechanisms behind episodic memory, and validate them by computational models and robotic systems.

In summary, by its cross-disciplinary approach to multiple levels of neural and brain organization, we will work to elucidate mind–brain relationships that have eluded explanation for centuries.

How we are organised

Work Package (WP) 3.1    Context-Sensitive Vision and Recognition. This Work Package aims to develop a sophisticated understanding of extensive neural interactions and subsequently develop models incorporating information processing in a realistic theory of how we recognise objects within certain contexts.

WP3.2    Sleep/wake transitions and slow-wave activity. This Work Package focuses on slow wave activity (SWA), and asks such questions as how SWA changes when the brain state changes.

WP3.3    Integration of multisensory information in perception and episodic memory: We conduct experiments to identify the precise neuronal mechanisms behind episodic memory (recollections of personal experiences), validate them using computational models and robotic systems, and test how they fail in old age and dementia.

WP3.4    Neural mechanisms of consciousness: experiments, modelling, quantitative measures: We aim to: a) test and improve physiological methods for assessing consciousness; and b) contribute to understanding the nature of consciousness by testing relevant theories. This will be done using experiments to test principles and ideas in mice, and then using the insights from these and from computational modelling to test and develop better non-invasive methods in humans.

WP3.5    Towards a comprehensive functional architecture for cognition and behaviour: This Work Package is a joint effort by all SP3 groups and proposes to begin work on a long-term Landmark to be pursued at least until 2023: a neurobiologically grounded, artificial, mammal-like agent (“mammalbot”) operating in a real-world and/or virtual-reality environment and driven by a whole-brain, functional-cognitive model with capacities for basic perception/awareness, attention, learning, memory encoding and recall, recognition, internal processing such as during sleep, goal-directed spatial behaviour and planning.

WP3.6    Scientific Coordination, Project Management and Communication: This Work Package coordinates inter-WP work within SP3 and its links with other SPs, the entire HBP and the larger neuroscience community. Its project management and communication brief covers quality assurance, ethics reporting, innovation, outreach, and public engagement.

Key People

Publication highlights

• Bodart O, Gosseries O, Wannez S, Thibaut A, Annen J, Boly M, et al. Measures of metabolism and complexity in the brain of patients with disorders of consciousness. NeuroImage: Clinical, 2017;14(Supplement C):354–362. DOI: 10.1016/j.nicl.2017.02.002.
• Bos JJ, Vinck M, van Mourik-Donga LA, Jackson JC, Witter MP et al. Perirhinal firing patterns are sustained across large spatial segments of the task environment. Nat Commun 2017;8:15602. DOI: 10.1038/ncomms15602.
• Bregestovski P, Maleeva G, Gorostiza P. Light-induced regulation of ligand-gated channel activity. Br J Pharmacol 2017; DOI: 10.1111/bph.14022.
• Meijer GT, Montijn JS, Pennartz CMA, Lansink CS. Audio-visual modulation in mouse V1 depends on cross-modal stimulus configuration and congruency. J Neurosci 2017;37:8783–8796. DOI: 10.1523/JNEUROSCI.0468-17.2017.
• Saiepour MH, Min R, Kamphuis W, Heimel JA, Levelt CN. β-Catenin in the adult visual cortex regulates NMDA-receptor function and visual responses. Cereb Cortex 2017;10:1–12. https://doi.org/10.1093/cercor/bhx029.
• Sanchez-Vives MV, Massimini M, Mattia M. Shaping the default activity pattern of the cortical network. Neuron 2017;94:993–1001. DOI: 10.1016/j.neuron.2017.05.015.
• Suzuki M, Larkum ME. Dendritic calcium spikes are clearly detectable at the cortical surface. Nature Commun. 2017;8:276. DOI: 10.1038/s41467-017-00282-4.

Contact Person:

Dr. Angelica DA SILVA LANTYER
Faculty of Science
Universiteit van Amsterdam
Science Park A, Science Park 904
Amsterdam, the Netherlands
e-mail: a.dasilvalantyer@uva.nl

Subproject 4

Theoretical Neuroscience

What we do

Our researchers in Theoretical Neuroscience work to simulate and capture key biological processes using mathematical models in order to try to better understand the brain

Theoretical Neuroscience is a link between experimentalists and technology. Brain mechanisms identified in the experimental HBP Subprojects are formalised into mathematical models, which are then made available to the HBP Platform Subprojects

Theoretical Neuroscience is needed for linking scales, another fundamental aspect of brain exploration. Scientists investigate the brain at multiple levels, from the microscopic (synapses, neurons), through mesoscopic (brain circuits) to macroscopic scales (areas of the brain), and each method of investigation has its own specific scale, e.g. single-neuron recordings, imaging methods such as local field potential (LFP), up to large-scale imaging such as EEG, fMRI, etc. One needs theoreticians not only to understand how these signals are generated, but also how to link them together

We also investigate key cognitive mechanisms, such as sensory processing (vision, auditory), learning and memory, spatial navigation or sensorimotor coordination through computational and mathematical models

Our researchers use tools such as Python, Brian, NEST, etc., and ensure compatibility with the HBP Platforms. We use the same software environment, pyNN, as the one used on the Neuromorphic Computing Platform so that the program code of many of our models developed can be directly implemented to simulate neural networks

Many of our results obtained are open-access, and are at the core of the discussions held at the events of the European Institute for Theoretical Neuroscience

How we are organised

WP4.1 Bridging Scales. Aims to provide models linking different scales of investigation, including linking models over spatial scales, such as synapses (μm) single-cell (tens of μm), local network (mm) or whole brain region (cm), as well as linking between models of different levels of complexity (e.g. detailed vs. simplified neuron models). We also develop models of the different brain signals accessible experimentally, across different scales.

WP4.2 Simplified Spiking Models of Different Brain Areas Generic.  The aim of this Work Package is to provide methods for network models that can serve as prototypes or building blocks for large-scale brain simulations. The models under investigation are designed to be compatible with the simulation Platforms. WP4.2 builds simplified, large-scale models of single or multiple brain areas. The focus is on creating a methodological framework for simulations to be performed on the HPC Platform (SP7) and the Neuromorphic Platform (SP9). The models developed in this work elucidate requirements for the platforms and thereby contribute to the development of the corresponding computing systems.

WP4.3 Learning and Memory. Aims to formulate synaptic plasticity algorithms from experimental data. We also aim to develop models of learning and reward, compatible with neuromorphic systems, and develop models of behavioural learning and long-term memory in the brain.

WP4.4 Models of Brain Activity and Function. The goal of this Work Package is to develop models of brain activity and function. The resulting models will be compatible with the HBP Platforms. Different levels of brain activity and functionality are considered, from primary sensory processing up to more integrated functions such as spatial navigation or decision-making. WP4.4 also aims  to contribute to a multiscale theory by developing models at various spatio-temporal scales of representation and to understand their interrelations.

WP4.5  Linking Model Activity And Function To Experimental Data. Aims to link theoretical models at different levels of description to create bridges between neuroscience and the models implemented in various HBP Platforms. This will involve mathematical principles and theoretical methods to integrate neuroscience data into models and compare the results with the existing data.

WP4.6 The European Institute For Theoretical Neuroscience. Located in Paris area, the European Institute for Theoretical Neuroscience (EITN) aims to serve as an incubator of ideas and foster the exchange of ideas between theoreticians and experimentalists, and is open to researchers from the field worldwide, whether they are HBP Partners or not.

WP4.7 Scientific Coordination. Coordinates and monitors the scientific activities of SP4, and the interactions with the other SPs.

Key People

Publication highlights

Deco G, and Kringelbach M L. Hierarchy of Information Processing in the Brain: A Novel ‘Intrinsic Ignition’ Framework. Neuron 2017. 94 (5). Elsevier Inc.: 961–68. doi:10.1016/j.neuron.2017.03.028.

Katkov M, Romani S, and Tsodyks M. Memory Retrieval from First Principles. Neuron 2017, 94 (5). Elsevier Inc.: 1027–32. doi:10.1016/j.neuron.2017.03.048.

Zerlaut Y , Destexhe A. Enhanced Responsiveness and Low-Level Awareness in Stochastic Network States. Neuron 2017, 94 (5). Elsevier Inc.:1002–9. doi:10.1016/j.neuron.2017.04.001.

Contact Person:

Tom MESSIER
Paris-Saclay Institute of Neuroscience (Neuro-PSI)
CNRS
UPR-3293, Bat 33
1 Avenue de la Terrasse
91198 Gif-sur-Yvette, France
e-mail: tom.messier@cnrs.fr

Subproject 5

Neuroinformatics Platform

What we do

Understanding the brain requires that huge amounts of complex data collected at many levels of investigation and with a multitude of methods be combined. Such data integration can be compared to a multi-dimensional puzzle consisting of data about genes and molecules, cells, connections and networks, regions of and the whole brain, plus cognition and behaviour. Fitting data together from this puzzle into meaningful information – a gigantic challenge - is one of the main goals of the Human Brain Project (HBP).

We provide the informatics tools and services that make data integration in HBP possible. Data from the brain produced in other Subprojects are organized and managed, then made available for collaborative use by all researchers in HBP and the wider neuroscience community. The online web services that will make this possible are being established stepwise and we will demonstrate several of the tools and services that are currently in place.

SP5 tools are used to tag the data with important additional information. Such “metadata” explain what the data are about, how they are collected, where in the brain they are from, and what they represent. This will make it possible to search and find data, aimed at advanced analysis of new combinations of data. Data are stored at the supercomputer centres in Europe managed by SP7, and the same computing services will embed analytical tools and workflows from SP5, providing increased capacity and capability for analysis of brain data, feeding information into the computational modelling and simulation of the brain taking place in other HBP Subprojects.

How we are organised

Work Package (WP) 5.1       Data Curation Support Lab. We aim to make HBP data and models discoverable and accessible (already pledged to the HBP community), via metadata enrichment and storage in a federated data infrastructure. Users can curate and share data or models with other HBP researchers in the open data domain and reach high data consistency levels.

WP5.2     Multi-level Atlas of the Rodent Brain. This Work Package aims to integrate heterogeneous multi-level rodent brain data in common reference atlases, and provide services for exploration, enrichment and analysis. Spatially anchored data, organized in the KnowledgeGraph, can be shared with the research community for use in data mining and predictive neuroinformatics.

WP5.3     Multi-Level Atlas of the Human Brain. This Work Package does for the human brain what WP5.2 does for that of the rodent.

WP5.4     Data and Atlas Curation Tools. The aim of this Work Package is to deliver a suite of tools for data curation, spatial integration or 2D and 3D viewing of multi-level human/rodent brain image data.

WP5.5     Community-Driven Neuroinformatics Platform and Infrastructure Operations. We aim to develop and operate the service infrastructure required for an engaging, community centric, multi-level, multi-modal open data ecosystem.

WP5.6     Data Mining and Analysis Neuroinformatics Capabilities. This Work Package brings learning-based image analysis to HBP neuroscientists by creating the ilastik toolkit, a simple, user-friendly tool for interactive image classification, segmentation, and analysis of neural images.

WP5.7     Tools and Curation for Integrated Parallelized Analysis of Activity Data. We aim to enable users to work with dynamic functional data from experiments or simulations by providing tools and services to integrate and analyse activity data, e.g. those from neuron spiking.

WP5.8     Management and Coordination. This Work Package coordinates SP activities and maintains an efficient and proactive relationship with other SPs and the broader science community, including securing integration of the Neuroinformatics Platform into other relevant services.

WP5.9     HBP Joint Platform Support. The HLST is a joint group of experts from the HBP Platforms. The HLST presents one single face to the users, helping to tame the complexities of HBP infrastructure access while making the full broadness of activities visible to the researchers. 

WP5.10     The Virtual Brain (TVB). The Virtual Brain (TVB) will enhance the HBP’s Brain Simulation Platform by providing multi-scale computational models that bridge brain structure and function to infer the mechanistic basis of cognitive processes and brain pathologies. TVB is a computational modelling and neuroinformatics toolset for large-scale brain simulation at the macroscopic level of networks of neural populations. 

Key People

Publication highlights

• Amunts K, Hawrylycz MJ, Van Essen DC, Van Horn JD, Harel N, Poline JB, et al. Interoperable atlases of the human brain. Neuroimage. 2014;99:525–532.
• Amunts K, Lepage C, Borgeat L, Mohlberg H, Dickscheid T, Rousseau MÉ, et al. BigBrain: an ultrahigh-resolution 3D human brain model. Science 2013;340:1472–1475.
• Grillner S. Megascience efforts and the brain. Neuron 2014;82:1209-1211.
• Papp EA, Leergaard TB, Calabrese E, Johnson GA, Bjaalie JG. Waxholm Space atlas of the Sprague Dawley rat brain. Neuroimage 2014;97:374–386.
• Tiesinga P, Bakker R, Hill S, Bjaalie JG. Feeding the human brain model. Curr Opin Neurobiol 2015;32:107–114.

Related websites

Contact Person:

Sofia Anderholm Strand
Sognsvannsveien 9
Domus Medica
N-0372 OSLO Norway
e-mail: s.a.strand@medisin.uio

Subproject 6

Brain Simulation Platform

What we do

The Brain Simulation Platform (BSP) is an internet-accessible collaborative platform designed for the digital reconstruction and simulation of brain models. Researchers can access the BSP to reconstruct and simulate models of the brain at different levels of detail to study their structure and function. In June 2017, the second version of the BSP was released. This new version is more user-centric and user-friendly, so that users with different levels of neuroscientific or technical expertise can benefit from the BSP for their research or just for curiosity!

Along with the new version of the BSP, we released the first MOOC (massive open online course), on simulation neuroscience. There will be three MOOCs in total that will teach participants how to use the state-of-the-art modelling tools of the BSP to simulate neurons, build neural networks, and perform simulation experiments. In the first MOOC, you can learn how to digitally reconstruct a single neuron. The first run of the first MOOC has finished, but the self-paced course is available again. If you are interested in our goal to reconstruct and simulate the brain, do follow the MOOC!

How we are organised

Work Package (WP) 6.1       Multi-scale Modelling of Plasticity and Neuromodulation. This Work Package creates multiscale scaffold models of key signalling cascades in neurons for use in bootstrap data-driven community modelling efforts. It uses inputs from SP1, SP2 and molecular dynamics to parameterise subcellular models and it integrates models of key signalling cascades into single neuron models, which should make it possible to model neuromodulation and plasticity.

WP6.2     Data-driven Model Reconstruction and Refinement. We build cellular level models of target areas of the rodent brain and a point neuron Whole Mouse Brain Model, adapting tools and workflows developed for the somatosensory cortex for use in other brain regions (cerebellum, hippocampus, basal ganglia), and the whole mouse brain. In parallel, we will continue the exploratory modelling of human neurons started in the Ramp-Up Phase.

WP6.3     Software Tools and Model Reconstruction Tools. This Work Package is building tools and workflows for data-driven reconstruction and simulation of brain models at different levels of biological organisation, exploiting data available through the Neuroinformatics Platform (SP5). The tools, which will facilitate building of scaffold and community models elsewhere in the SP, will include a Hodgkin-Huxley Neuron Builder and tools for in silico experimentation.

WP6.4     Platform Services. We design, implement and operate the HBP Brain Simulation Platform. This comprises a collection of Apps, APIs and Platform Foundation Software, which support collaborations to build, simulate, analyse, validate and disseminate data-driven brain models. Part of the software underlying the Platform will be developed in WP6.3; other parts will come from efforts of WP6.1 and WP6.2 and from community activities. We will seed the development of Apps and APIs for a subset of this software, which has reached a high level of maturity. In the medium term, it is expected that most Apps will come from the community.

WP6.5     Administration, Community and Coordination. This Work Package coordinates the work of the SP6 WPs and their interaction with the HBP management, other SPs and the wider community.

Key People

Publication highlights

• Hahne J, Helias M, Kunkel S, Igarashi J, Bolten M, Frommer A et al. A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations. Front Neuroinform 2015;9:22.
• Markram H, Muller E, Ramaswamy S, Reimann MW, Abdellah M, Sanchez CA et al. Reconstruction and simulation of neocortical microcircuitry. Cell 2015;163:456–492.
• Ramaswamy S, Courcol JD, Abdellah M, Adaszewski SR, Antille N, Arsever S et al. The neocortical microcircuit collaboration portal: a resource for rat somatosensory cortex. Front Neural Circuits 2015;9:44.

Related Links

Contact Person (KTH):

Dr. Daniel VARE
School of Computer Science & Communication
Kungliga Tekniska Hoegskolan
AlbaNova University Center
106 91 Stockholm, Sweden
e-mail: vare@kth.se    

Contact Person (EPFL):

Dr. Katrien VAN LOOK
Blue Brain Project
École Polytechnique Fédérale de Lausanne
Campus Biotech
Chemin des Mines 9
CH-1202 Geneva, Switzerland

e-mail: katrien.vanlook@epfl.ch

Subproject 7

High-Performance Analytics and Computing Platform

What we do

One of today’s science challenges is to understand how our brains work. Usually new endeavours require new tools and technologies to get to the next level. Neuroscientists in the Human Brain Project (HBP) collect a lot of data, develop models based on this data that try to explain how mechanisms in the brain work, and finally they simulate these models. In these simulations, neural networks (parts of the neurons and their connections in the brain) are built in the computer, get some input stimulation (like the actual brain gets input from our senses) and then these “digital” neurons and neural networks react to it. The scientists analyse the simulation results and compare them to experimental data to improve their models.

We support neuroscientists to do this research by developing the tools and technology that they need for it. We make huge storage available at four centres in Europe to store the data. The storage at one site alone would be enough to store 3–4 billion books or for 250–300 years of high definition movies. At the same centres, there are also supercomputers, which are among the most powerful computers worldwide. The human brain is so complex that a normal computer in the scientist’s office is not enough to simulate even a fraction of the human brain. One of the supercomputers is as powerful as about 350,000 standard computers.

Our job in the HBP is not only to make this hardware available to the scientists, but also to develop software that supports neuroscientists in their endeavour, e.g. to manage their huge datasets, to simulate models most efficiently on the supercomputers (getting better results as fast as possible) or to look at “visualisations” of the datasets. A visualisation turns the columns of numbers produced by a simulation into a graphical representation like pictures or even 3D objects.

How we are organised

Work Package (WP) 7.1       Architecture specification and validation. This Work Package defines and validates the HPAC architecture.

WP7.2     Data Federation and Data-Intensive Supercomputing. We aim to link extreme scale data processing challenges to the exploitation of scalable computer resources. Our work is driven by specific use cases coming from different areas of the HBP to ensure that R&D work is guided towards enabling infrastructure for future neuroscience research.

WP7.3     Exascale simulator and visualization technology. This Work Package develops the concepts, numerical algorithms, and software technologies for the simulation codes of the HBP and corresponding in-situ visual analysis of data generated by simulations.

WP7.4     User support and community building. This Work Package links the HPAC Platform with the user communities. It provides the support for the HPAC Platform. 

WP7.5     Integration and operation.  The main activities of this Work Package are infrastructure operations, middleware services, identity management, development and support for platform and software development services, orchestration of resource usage, reporting and accounting, software deployment and DevOps.

WP7.6     Management and Coordination. We manage the High Performance Analytics and Computing Platform. Our objective is to coordinate and validate the technology and infrastructure development in the Subproject, ensuring that the work is aligned with the overall HBP objectives, meets actual user needs and is efficiently organized and documented.

Key People

Publication highlights

• Amunts K, Ebell C, Muller J, Telefont M, Knoll A, Lippert L. The Human Brain Project: Creating a European Research Infrastructure to Decode the Human Brain. Neuron 2016;92:574-581. DOI: 10.1016/j.neuron.2016.10.046.
• Hahne J, Helias M, Kunkel S, Igarashi J, Kitayama I, Wylie B et al. Including Gap Junctions into Distributed Neuronal Network Simulations. In: Brain-Inspired Computing pp. 43-57. Cham: Springer International Publishing/ Amunts, Katrin (Editor) ; Cham : Springer International Publishing, 2016
• Hänel C, Khatami M, , B. Towards Multi-user Provenance Tracking of Visual Analysis Workflows over Multiple Applications. In: Proceedings of EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3), Barcelona, 2016.
• Lopez V, Jokanovic A, D'Amico M, Garcia M, Sirvent R, Corbalan J. DJSB: Dynamic Job Scheduling Benchmark. 21st Workshop on Job Scheduling Strategies for Parallel Processing (JSSPP17), in conjunction with IPDPS 2017, Orlando, 2016. 
• Rinke S, Naveau M, Wolf F, Butz-Ostendorf M. Critical periods emerge from homeostatic structural plasticity in a full-scale model of the developing cortical column. In: The Rewiring Brain - A Computational Approach to Structural Plasticity in the Adult Brain. Academic Press, New York, 2017.

Related Websites

*HBP account required

Subproject 8

Medical Informatics Platform

What we do

Our goal is to provide a collaborative open source platform, the Medical Informatics Platform (MIP), that allows researchers worldwide to share medical data, enabling the use of machine-learning tools for brain-related diseases, while strictly preserving patient confidentiality.

A combination of medicine and computer science, we aim to break down barriers between patient care, brain science, and clinical research to minimize the delays involved in diagnosis of brain diseases and institution of the most effective treatments.

As in many IT contexts, data security is treated as a top priority, the need for which is made all the more pressing due to the long-standing commitment of the medical profession to patient confidentiality. The Subproject aims to preserve hospital ownership and control of data by developing a federated query engine within the hospitals, leaving patient data in its original location and format. This is a fundamental change, compared to traditional schemes in which data are moved to accommodate the needs of the query engine. The research team is also developing techniques to ensure that it will not be possible to infer personal information about patients from query results while performing advance machine learning analytics.

We urgently need better diagnostic tools and treatments for brain-related diseases. People are living longer, thanks to improved sanitation, nutrition and treatments for infectious diseases. As a consequence, chronic diseases – which include most brain-related diseases – form the largest part of the overall health burden, and their share is growing. In 2010, the annual cost of managing the 500 or so brain disorders, from migraine through degenerative diseases like Alzheimer’s and Parkinson’s, to conditions like autism, were estimated at EUR 800 billion in the EU alone, and that cost will continue to increase.

How we are organised

Work Package (WP) 8.1       Coordination and Communication. This Work Package provides direction and guidance to the whole SP8 project, overseeing all its scientific, medical, technical and administrative aspects, and ensures that its values and expectations are fully met.

WP8.2     MIP Deployment, Operation and Maintenance. This Work Package will ensure the availability of the Medical Informatics Platform to the end-users. This requires proper operation on all levels of the platform - infrastructure, networking, technical components, application software components. 

WP8.3     Capacity Building of the MIP Clinical Neuroscience Network. This Work Package will ensure that SP8 and the MIP can gain access to a large volume of high-quality patient data during SGA2, by addressing the potential obstacles to reaching this objective.

WP8.4     Biostatistics and Analytical Tools. This Work Package provides methods for data analysis based on statistical and machine learning tools, including both off the shelf and newly developed tools. The research in this work package will target modelling and validation of disease models, potential genetic and biomarkers and the identification of disease features as potential targets for therapy.

WP8.5     MIP Development, Enhancement, and Robustisation. The goal of this Work Package is to develop subsequent versions of the MIP by refining its existing architecture, where if/necessary, extending and enhancing its present components, and adding new ones to achieve the desired functionality, performance, robustness and scalability.

WP8.6     Modelling for drug discovery. This Work Package will design novel allosteric ligands with possible applications for diagnosis and therapeutic purposes. We will focus on developing molecular-based simulations tools to target allosteric sites in pharmaceutically relevant classes of biomolecules involved in neuropathologies.

WP8.7     The Neurodegenerative Virtual Brain (TVD-NDD). This Work Package develops a Use Case of a computational modelling system - as integral part of MIP - that is tailored to the individual, and bridges multiple scales to identify key mechanisms that predict neurodegenerative disease (NDD) progression. Central is The Virtual Brain simulator that is developed in CDP8. 

WP8.8     Medical Informatics Platform for Stereoelectroencephalography (SEEG).  The goal of this Work Package is the integration of a multicentre database of human intracranial responses to direct cortical stimulations (CCEP) performed during SEEG explorations of epileptic patients candidates to resective surgery. This will allow the standardisation of patients exploration and the development of a human atlas of cortico-cortical connections.

WP8.9     Comprehensive Ontologies for Brain Disease. The activities of this Work Package will be carried out by new partners following a Call for Expression of Interest (CEoI). The WP will develop a broad set of ontologies, covering a wide range of brain diseases and types of data. 

WP8.10    Testing and applying neurobehavioural symptom clusters from shared brain mechanisms. This Work Package will generate a validated psychopathological model of neurobehavioural symptom clusters in major psychiatric disorders using the newly established MIP infrastructure.

Key People

Publication highlights

• Cui J, Zufferey V, Kherif F. In-vivo brain neuroimaging provides a gateway for integrating biological and clinical biomarkers of Alzheimer’s disease. Curr Opin Neurol 2015;28:351–357. DOI 10.1097/WCO.0000000000000225.
• Gamberger D, Ženko B, Mitelpunkt A, Shachar N, Lavrač N. Clusters of male and female Alzheimer’s disease patients in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Brain Inform 2016;3:169–179. DOI: 10.1007/s40708-016-0035-5
• Venetis T, Ailamaki A, Heinis T, Karpathiotakis M, Kherif F, Mitelpunkt A et al. Towards the Identification of Disease Signatures. In: Brain Informatics and Health, pp. 145-155. Cham, Springer International Publishing, 2015.
• Zufferey V, Donati A, Popp J, Meuli R, Rossier J, Frackowiak R et al. Neuroticism, depression, and anxiety traits exacerbate the state of cognitive impairment and hippocampal vulnerability to Alzheimer's disease. Alzheimers Dement (Amst) 2017:7:107-114.

Related Websites

Contact Person:

Sandra SCHWEIGHAUSER
Department of Clinical Neuroscience
Centre hospitalier universitaire vaudois (CHUV)
Campus Biopôle 3
CH-1066 Epalinges
Switzerland
e-mail: sandra.schweighauser@chuv.ch

Subproject 9

Neuromorphic Computing Platform

What we do

The Neuromorphic Computing Platform takes two fundamentally different paths to support scientific research and applications.

The BrainScaleS system, based in Heidelberg, employs a mixed signal approach employing analogue electronics to model 4 million neurons and 1 billion synapses, as well as their connections and intercellular communications, using digital communications protocols. It is targeted to the emerging field of bio-inspired AI as well as a better understanding of the learning and development in the brain. The system is a direct, silicon-based image of the neuronal networks found in nature and runs 10,000 times faster than its biological archetype, allowing a day of biological development to be compressed into 10 seconds.

The SpiNNaker system, based in Manchester, is a massively parallel computing platform, targeted towards neuroscience, robotics and computer science. For robotics, SpiNNaker provides mobile, low power computation, and makes possible the simulation of networks of tens of thousands of spiking neurons, as well as processing sensory input and generate motor output, all in real time and in a low power system. The system is unconventional in that SpiNNaker nodes communicate using simple messages (spikes) that are inherently unreliable. This break with determinism not only offers new challenges, but also the potential to discover powerful new principles of massively parallel computation.

Both approaches are involved in technological next generation development (both hardware and software) and integration. The establishment of principles for brain-like computation, computational capabilities through learning and large scale organisation of cognitive computation are also focuses of interest. Outreach activities include user training, support, and coordination for effective application of the Platform.

How we are organised

Work Package (WP) 9.1       Platform Software and Operations. This WP operates the Neuromorphic Computing Platform constructed in the HBP Ramp-Up Phase, maintains and further develops the software methods and tools required for the neuromorphic hardware systems, and integrates them with the HBP Collaboratory, other HBP Platforms and, where possible, external resources.

WP9.2     BrainScaleS Systems. We develop, prototype, manufacture, assemble, test and operate next-generation hardware systems to implement massively parallel, physical models of brain cells, circuits and networks. 

WP9.3     SpiNNaker Systems. The goal of WP 9.3 is to develop the next generation many-core hardware microchip to implement massively parallel, many-core models of brain cells, circuits and networks, and to extend the software support for the current many-core system.

WP9.4     Computational Principles. In this WP, we use brain activity and plasticity data to develop principles that enable brain-like computation, cognition, and learning in neuromorphic systems. This work supports emulation of specific brain functions or cognitive processes in existing neuromorphic hardware and will guide the design of next-generation neuromorphic systems.

WP9.5     Applications and Benchmarks. The goal of this Work Package is to develop applications with special emphasis on implementation in the BrainScaleS-2 and SpiNNaker-2 systems. Applications in WP 9.5 are thought of as 'demonstrators' that display the use of the neuromorphic platforms to obtain new scientific insight, and exhibit novel technological solutions for future computing and robotics. 

WP9.6     Platform Training and Coordination. This WP provides training and documentation for SP9’s various neuromorphic systems and ensures that these are accessible via the Neuromorphic Computing Platform. It also coordinates the SP’s R&D work and its integration with the rest of the HBP.

Key People

Publication highlights

SpiNNaker System

• Sen-Bhattacharya B, Serrano-Gotarredona T, Balassa L, Bhattacharya A, Stokes A, Rowley A, et al. A spiking neural network model of the lateral geniculate nucleus on the SpiNNaker machine. Front Neurosci 2017;11:454 DOI: 10.3389/fnins.2017.00454.
• Liu Q, Pineda-García G, Stromatias E, Serrano-Gotarredona T, Furber SB. Benchmarking spike-based visual recognition: A dataset and evaluation. Front Neurosci 2016;10:496. DOI: 10.3389/fnins.2016.00496.
• Knight JC, Tully PJ, Kaplan BA, Lansner A, Furber SB. Large-scale simulations of plastic neural networks on neuromorphic hardware. Front Neuroanat 2016;10:37. DOI: 10.3389/fnana.2016.00037.

BrainScaleS System

• Friedmann S, Schemmel J, Grübl A, Hartel A, Hock M, Meier K. Demonstrating hybrid learning in a flexible neuromorphic hardware system. In: IEEE Transactions on Biomedical Circuits and Systems, Vol 11, pp. 128–142. New York, NY: IEEE, 2017. DOI: 10.1109/TBCAS.2016.2579164.
• Schemmel J, Kriener L, Müller P, Meier K. An accelerated analog neuromorphic hardware system emulating NMDA- and calcium-based non-linear dendrites. 2017, arXiv preprint arXiv:1703.07286.
• Schmitt S, Klähn J, Bellec G, Grübl A, Guettler M, Hartel A, et al. Neuromorphic hardware in the loop: Training a deep spiking network on the BrainScaleS wafer-scale system. In: 2017 International Joint Conference on Neural Networks (IJCNN), pp. 2227–2234. New York, NY: IEEE, 2017.

Related Websites

Contact Person:

Dr. Björn KINDLER
Kirchoff-Institut für Physik
Ruprecht-Karls-Universität Heidelberg
Im Neuenheimer Feld 227
D-69120 Heidelberg
Germany
e-mail: bjoern.kindler@kip.uni-heidelberg.de

Subproject 10

Neurorobotics Platform

What we do

Contact Person:

Fabrice MORIN
Department of Informatics VI
Technische Universität München
Boltzmannstr. 3
D-85748 Garching
Germany
e-mail: morinf@in.tum.de

Subproject 11

Management & Coordination

What we do

Contact Person:

Mr Terrence SIMMONS
Ecole Polytechnique Federale de Lausanne,
Campus Biotech - Chemin des Mines, 9
CH-1202 Geneva – Switzerland
Email: terrence.simmons@epfl.ch

Subproject 12

Ethics and Society

What we do

The HBP aims to increase our understanding of the brain, its functions and malfunctions. Its research and methodology, as well as the potential application of its findings, raise a number of questions and concerns. The Ethics and Society Subproject focuses on the implications of HBP research. Our methods include conceptual and philosophical analyses, organizing workshops and webinars, and performance of interviews with experts. We aim to develop better foresight and ethical analysis, to promote engagement with broader audiences, and to raise awareness among researchers on how to recognise ethical issues and the possibilities for action when they arise.

At present, we are carrying out research on a number of issues such as the possible military interest in HBP research (“dual use”). We are developing an Opinion on how to manage and regulate military uses of civilian research. This includes recommendations, guidelines, and training methods for HBP researchers on how to act in cases where their research could have potential military applications. We are also putting into action recommendations previously developed on privacy and data protection.

How we are organised

Work Package (WP) 12.1     Foresight Laboratory & Researcher Awareness. This WP identifies potential ethical and social concerns at an early stage by producing scenarios of potential developments and implications, produces reports and publications, and feeds these back to the HBP researchers to build capacity to adapt to differing uncertain futures.

WP12.2         Neuroethics and Philosophy. We perform philosophical, ethical, and social analyses of HBP key activities and issues, thereby furthering conceptual clarity in the analysis of the neuro- and computational sciences and the issues they raise and promoting the reflective capacity of HBP researchers and others in addressing societal implications.

WP12.3         Public Dialogue and Engagement. This WP assists the HBP in creating a constructive dialogue not only with public and private stakeholders, but also with the general public. This WP maintains an intense engagement with points of view external to the HBP, thereby identifying emerging controversies and formulating recommendations for HBP research organisation and research priorities.

WP12.4         Ethics Support. We develop ethics governance measures to ensure compliance, reflection, and engagement with ethics among the entire HBP community. We work with all ethics stakeholders, notably the Ethics Advisory Board and Ethics Rapporteurs, to ensure that ethics-related activities of the scientific and technical SPs are collected and communicated, and ensure open interaction between SP12's wider research and that of other SPs. These activities ensure that ethical issues are managed to the highest standards within the HBP and that international best practice is developed.

WP12.4         Ethics Management. The aim of this Work Package is to support the SP leader by coordinating the day-to-day operation of SP12.

Key People

Publication highlights

• Aicardi C, Reinsborough M, Rose N. The integrated ethics and society program of the Human Brain Project: Reflecting on an ongoing experience. Special Issue: Neurotechnology and Society. Towards Responsible Innovation. J Responsible Innovation 2017; DOI: 10.1080/23299460.2017.1331101.
• Evers K. The contribution of neuroethics to international brain research initiatives. Nature Rev Neurosci 2016;18:1-2.
• Farisco M, Evers K, Salles A. Big Science, Brain Simulation and Neuroethics. AJOB Neuroscience 2016;7:28-30.
• Rose N. Reading the human brain: How the mind became legible. Body Soc 2016; DOI: 10.1177/1357034X15623363.
• Stahl BC, Wakunuma K, Rainey S, Hansen C.Improving brain computer interface research through user involvement - The transformative potential of integrating civil society organisations in research projectsPLoS ONE. 2017;12(2), e0171818. DOI: 10.1371/journal.pone.0171818.
• Stahl BC, Timmermans J, Mittelstadt BD.The ethics of computing: a survey of the computing-oriented literatureACM Computing Surveys 2016;48:55. http://doi.org/10.1145/2871196.

Related Websites

updated Sep 2018