HBP SGA2 - Human Brain Project Specific 2

Funding & Project no.: EU; 785907

Project leader: Wolfgang Maass

Duration: 01. April 2018 - 31. März 2020

Abstract: Understanding the human brain is one of the greatest scientific challenges of our time. Such an understanding can provide profound insights into our humanity, leading to fundamentally new computing technologies, and transforming the diagnosis and treatment of brain disorders. Modern ICT brings this prospect within reach. The HBP Flagship Initiative (HBP) thus proposes a unique strategy that uses ICT to integrate neuroscience data from around the world, to develop a unified multi-level understanding of the brain and diseases, and ultimately to emulate its computational capabilities. The goal is to catalyze a global collaborative effort. During the HBP’s first Specific Grant Agreement (SGA1), the HBP Core Project will outline the basis for building and operating a tightly integrated Research Infrastructure, providing HBP researchers and the scientific Community with unique resources and capabilities. Partnering Projects will enable independent research groups to expand the capabilities of the HBP Platforms, in order to use them to address otherwise intractable problems in neuroscience, computing and medicine in the future. In addition, collaborations with other national, European and international initiatives will create synergies, maximizing returns on research investment. This document describes the HBP’s plans for SGA1, and details what steps will be taken to move the HBP closer to achieving its ambitious Flagship Objectives.

SYNCH - A SYnaptically connected brain-silicon Neural Closed-loop Hybrid system

Funding & Project no.: EU-Horizon 2020, 824162

Project leader: Robert Legenstein

Duration: 01. Januar 2019 - 30. Dezember 2022

Abstract: The brain, with its remarkable computational properties, provides animals with capabilities of physical autonomy, interaction and adaptation that are unmatched by any artificial system. The brain is a complex network that has evolved to optimize processing of real-world inputs by relying on event-based signaling and self-reorganizing connectivity. Spikes (the events) are transmitted between neurons through synapses which undergo continuous ‘birth’-‘death’ and adjustment, reconfiguring brain circuits and adapting processing to ever changing inputs. The scientific and technological objective of the project is to create a hybrid system where a neural network in the brain of a living animal (BNN) and a silicon neural network of spiking neurons on a chip (SNN) are interconnected by neuromorphic synapses, thus enabling co-evolution of connectivity and coprocessing of information of the two networks.

Partners: aiCTX AG; ArC Instruments LTD; Bar Ilan University; EnginSoft; Technische Universität Dresden; Università degli Studi di Padova: University of Southampton

VORONOI++ - Circle Expansion and abstract Voronoi diagrams

Funding & Project no.: FWF, I1836-N15

Project leader: Franz Aurenhammer

Duration: 01.Juni 2015 - 31. Mai 2020

Abstract: This project is concerned with a versatile and influential data structure called the Voronoi diagram, a geometric structure which makes explicit the proximity information exerted by a given set of sites in space. Space partitioning structures of this kind have proven useful not only in computational geometry and more applied areas of computer science, but also in the natural and economical sciences. Fast construction methods and, as a prerequisite, a thorough understanding of their structural and algorithmic properties, are in demand. In this DACH project, we intend to join forces to conduct research on some of these problems. The involved research groups (R. Klein, Bonn; E. Papadopoulou, Lugano; B. Jüttler, Linz; F. Aurenhammer, Graz) have successfully worked on this topic within the framework of EuroGIGA (initiated by F. Aurenhammer) in the Collaborative Research Project VORONOI'', which is documented by numerous relevant publications. Our main goal is to generalize Voronoi diagrams to such an extent that modeling real life scenarios becomes possible. The progress we have already made in previous collaborations has put this goal within our reach. Among our planned research topics are Abstract Voronoi diagrams, cluster Voronoi diagrams, anisotropic diagrams, and skeletal structures in 3D. These topics show the necessary diversity for a successful research and, on the other hand, are strongly interrelated which promises a (continuing) fruitful cooperation between the project partners. Complementing the planned theoretical research, practical aspects will be emphasized. The complexity of the structures to be investigated has reached a level where visualization tools (like interactive applets) are needed, which are intended to be made public later on. To put the findings of this project to practical use, software implementations of the developed algorithms for anisotropic Voronoi diagrams and 3D straight skeletons will be available.

Partner: Johannes Kepler Universität Linz (JKU)

SASNN - Stochastic Assemblies in Spiking Neural Networks

Funding & Project no.: FWF, I3251-N33

Project leader: Robert Legenstein

Duration: 01. März 2017 - 28. Februar 2021

Abstract: Recent experimental results have provided valuable insights in the organization of computations in biological neuronal networks. In particular, evidence for two main features of cortical computation is rapidly accumulating. First, neurons operate in concert with other neurons in so-called cell assemblies. Second, the activity of single neurons, synapses, and assemblies in the brain is highly stochastic. These findings force us to rethink how computations are organized in cortical neuronal networks. However, an integrated view on stochasticity and assembly organization in spiking neural networks is still missing. In this project, we will investigate stochastic assembly organization both in organic and artificial spiking neural networks. One emphasis will be the characterization of stochastic assembly activation in highly controllable setups and assembly emergence through plasticity processes. Experiments will be accompanied by theoretical modeling, analysis, and computer simulations that will help to understand the basic mechanisms that give rise to assembly formation. In particular, the investigations in this project will focus on (a) the characterization of stochastic assemblies their emergence through plasticity processes in cultured neural networks and acute brain slices, (b) the control of stochastic assemblies in cultured neural networks and its application to neuroprosthetics, and (c) computations in artificial spiking neural networks based on emergent stochastic assemblies with applications to novel computing and learning devices.

Partners: Universität Antwerpen


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Univ.-Prof. Dipl.-Ing. Dr. techn. Robert Legenstein