The BrainScaleS-2 Neuromorphic Platform — A Report on the Integration and Operation of an Open Science Hardware Platform within EBRAINS

This report presents the challenges encountered and the solutions created for the operation of the BrainScaleS neuromorphic platform, and the overall progress leading to this state at the end of the Human Brain Project (HBP)

The coming decade of digital brain research: a vision for neuroscience at the intersection of technology and computing

In recent years, brain research has indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modelling at multiple scales— from molecules to the whole brain. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain combines high-quality research, data integration across multiple scales, a new culture of multidisciplinary large-scale collaboration and translation into applications. As pioneered in Europe’s Human Brain Project (HBP), a systematic approach will be essential for meeting the coming decade’s pressing medical and technological challenges. The aims of this paper are to: develop a concept for the coming decade of digital brain research, discuss this new concept with the research community at large, to identify points of convergence, and derive therefrom scientific common goals; provide a scientific framework for the current and future development of EBRAINS, a research infrastructure resulting from the HBP’s work; inform and engage stakeholders, funding organisations and research institutions regarding future digital brain research; identify and address the transformational potential of comprehensive brain models for artificial intelligence, including machine learning and deep learning; outline a collaborative approach that integrates reflection, dialogues and societal engagement on ethical and societal opportunities and challenges as part of future neuroscience research

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Spiking neuromorphic chip learns entangled quantum states

The approximation of quantum states with artificial neural networks has gained a lot of attention during the last years. Meanwhile, analog neuromorphic chips, inspired by structural and dynamical properties of the biological brain, show a high energy efficiency in running artificial neural-network architectures for the profit of generative applications. This encourages employing such hardware systems as platforms for simulations of quantum systems. Here we report on the realization of a prototype using the latest spike-based BrainScaleS hardware allowing us to represent few-qubit maximally entangled quantum states with high fidelities. Bell correlations of pure and mixed two-qubit states are well captured by the analog hardware, demonstrating an important building block for simulating quantum systems with spiking neuromorphic chips.Comment: 9+13 pages, 4+2 figures; Submission to SciPos

SymPerf: Predicting Network Function Performance

The softwarization of networks provides a new degree of flexibil- ity in network operation but its software components can result in unexpected runtime performance and erratic network behav- ior. This challenges the deployment of flexible software functions in performance critical (core) networks. To address this challenge, we present a methodology enabling the prediction of runtime performance and testing of functional behavior of Network Functions. Unlike traditional performance evaluation, e.g., testbed testing or simulation, our methodology can characterize the Network Func- tion performance for any possible workload only by code analysis

The coming decade of digital brain research - A vision for neuroscience at the intersection of technology and computing

Brain research has in recent years indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modeling at multiple scales – from molecules to the whole system. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain integrates high-quality basic research, systematic data integration across multiple scales, a new culture of large-scale collaboration and translation into applications. A systematic approach, as pioneered in Europe’s Human Brain Project (HBP), will be essential in meeting the pressing medical and technological challenges of the coming decade. The aims of this paper are To develop a concept for the coming decade of digital brain research To discuss it with the research community at large, with the aim of identifying points of convergence and common goals To provide a scientific framework for current and future development of EBRAINS To inform and engage stakeholders, funding organizations and research institutions regarding future digital brain research To identify and address key ethical and societal issues While we do not claim that there is a ‘one size fits all’ approach to addressing these aspects, we are convinced that discussions around the theme of digital brain research will help drive progress in the broader field of neuroscience

The coming decade of digital brain research - A vision for neuroscience at the intersection of technology and computing

Brain research has in recent years indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modeling at multiple scales – from molecules to the whole system. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain integrates high-quality basic research, systematic data integration across multiple scales, a new culture of large-scale collaboration and translation into applications. A systematic approach, as pioneered in Europe’s Human Brain Project (HBP), will be essential in meeting the pressing medical and technological challenges of the coming decade. The aims of this paper are To develop a concept for the coming decade of digital brain research To discuss it with the research community at large, with the aim of identifying points of convergence and common goals To provide a scientific framework for current and future development of EBRAINS To inform and engage stakeholders, funding organizations and research institutions regarding future digital brain research To identify and address key ethical and societal issues While we do not claim that there is a ‘one size fits all’ approach to addressing these aspects, we are convinced that discussions around the theme of digital brain research will help drive progress in the broader field of neuroscience. Comments on this manuscript are welcome This manuscript is a living document that is being further developed in a participatory process. The work has been initiated by the Science and Infrastructure Board of the Human Brain Project (HBP). Now, the entire research community is invited to contribute to shaping the vision by submitting comments. Comments can be submitted via an online commentary form here. All submitted comments will be considered and discussed. The final decision on whether edits or additions will be made to the next version of the manuscript based on an individual comment will be made by the Science and Infrastructure Board (SIB) of the Human Brain Project (HBP) at regular intervals. New versions of the manuscript will be published every few months on Zenodo. Comments may be submitted until the beginning of 2023. During the Human Brain Project Summit 2023, the manuscript will be adopted by HBP and non-HBP participants, and a final version will be published shortly after

The coming decade of digital brain research - A vision for neuroscience at the intersection of technology and computing

<p>Brain research has in recent years indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modeling at multiple scales – from molecules to the whole system. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain integrates high-quality basic research, systematic data integration across multiple scales, a new culture of large-scale collaboration and translation into applications. A systematic approach, as pioneered in Europe's Human Brain Project (HBP), will be essential in meeting the pressing medical and technological challenges of the coming decade. The aims of this paper are</p><ul><li>To develop a concept for the coming decade of digital brain research</li><li>To discuss it with the research community at large, with the aim of identifying points of convergence and common goals</li><li>To provide a scientific framework for current and future development of EBRAINS</li><li>To inform and engage stakeholders, funding organizations and research institutions regarding future digital brain research</li><li>To identify and address key ethical and societal issues</li></ul><p>While we do not claim that there is a 'one size fits all' approach to addressing these aspects, we are convinced that discussions around the theme of digital brain research will help drive progress in the broader field of neuroscience.</p><p><strong>As the final version 5 has now been published, comments on this manuscript are now closed. We thank everyone who made a valuable contribution to this paper.</strong></p><p>This manuscript has been developed in a participatory process. The work has been initiated by the Science and Infrastructure Board of the Human Brain Project (HBP), and the entire research community was invited to contribute to shaping the vision by submitting comments. </p><p>All submitted comments were considered and discussed. The final decision on whether edits or additions was made to each version of the manuscript based on an individual comment was made by the Science and Infrastructure Board (SIB) of the Human Brain Project (HBP).</p><p><strong>Supporters of the paper</strong>: Pietro Avanzini, Marc Beyer, Maria Del Vecchio, Jitka Annen, Maurizio Mattia, Steven Laureys, Rosanne Edelenbosch, Rafael Yuste, Jean-Pierre Changeux, Linda Richards, Hye Weon Jessica Kim, Chrysoula Samara, Luis Miguel González de la Garza, Nikoleta Petalidou, Vasudha Kulkarni, Cesar David Rincon, Isabella O'Shea, Munira Tamim Electricwala, Bernd Carsten Stahl, Bahar Hazal Yalcinkaya, Meysam Hashemi, Carola Sales Carbonell, Marcel Carrère, Anthony Randal McIntosh, Hiba Sheheitli, Abolfazl Ziaeemehr, Martin Breyton, Giovanna Ramos Queda, Anirudh NIhalani Vattikonda, Gyorgy Buzsaki, George Ogoh, William Knight, Torbjørn V Ness, Michiel van der Vlag, Marcello Massimini, Thomas Nowontny, Alex Upton, Yaseen Jakhura, Ahmet Nihat Simsek, Michael Hopkins, Addolorata Marasco, Shamim Patel, Jakub Fil, Diego Molinari, Susana Bueno, Lia Domide, Cosimo Lupo, Mu-ming Poo, George Paxinos, Huifang Wang.</p&gt