Project

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PNEUMA

English title Plasticity in NEUral Memristive Architectures
Applicant Indiveri Giacomo
Number 138798
Funding scheme CHIST-ERA
Research institution Institut für Neuroinformatik Universität Zürich Irchel und ETH Zürich
Institution of higher education University of Zurich - ZH
Main discipline Electrical Engineering
Start/End 01.11.2011 - 30.04.2015
Approved amount 360'600.00
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All Disciplines (2)

Discipline
Electrical Engineering
Neurophysiology and Brain Research

Keywords (3)

memristor; neuromorphic; learning

Lay Summary (English)

Lead
Lay summary

Philosophers, cognitive scientists, and neuro-scientists have long attempted to provide authoritative definitions of consciousness within a neuro-biological framework. Engineers have recently joined this quest by providing neuromorphic micro-electronic systems that emulate biological functions in real-time. Yet, to date artificial systems have not been able to faithfully recreate natural attributes such as true processing locality (memory and computation) and complexity, preventing the creation of autonomous cognitive systems.

This project aspires to develop experimental platforms capable of perceiving, learning and adapting to stimuli, by leveraging on the latest developments of five leading European institutions in neuroscience, nano-technology, modeling and circuit design. The non-linear dynamics as well as the plasticity of the newly discovered memristor are shown to support Spike-Timing-Dependent-Plasticity (STDP), making this extremely compact device an excellent candidate for realizing large-scale learning neural networks; a step towards “autonomous cognitive systems”. The intrinsic properties of real neurons and synapses as well as their organization in forming neural circuits will be exploited for optimizing CMOS-based neurons, memristive grids and the integration of the two into real-time biophysically realistic neuromorphic systems. Finally, these systems will be tested with conventional as well as newly developed methods to evaluate their cognitive abilities.
Direct link to Lay Summary Last update: 21.02.2013

Employees

Collaboration

Group / person Country
Types of collaboration
Sevilla Microelectronics Institute (IMSE) Spain (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Imperial College London Great Britain and Northern Ireland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Institute for Theoretical Computer Science, TU-Graz Austria (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
LAAS-CNRS France (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved


Knowledge transfer events

Active participation

Title Type of contribution Date Place Persons involved
BrainFair Zürich 2012 12.03.2012 ETH Zürich Zentrum, Zurich


Associated projects

Number Title Start Funding scheme
146608 Spike-based computation and learning in distributed neuromorphic systems 01.08.2013 Project funding

Abstract

During the past two decades, philosophers, psychologists, cognitive scientists, clinicians and neuroscientists strived to provide authoritative definitions of consciousness within a neurobiological framework. Engineers have more recently joined this quest by developing neuromorphic VLSI circuits for emulating biological functions. Yet, to date artificial systems have not been able to faithfully recreate natural attributes such as true processing locality (memory and computation) and complexity (1010 synapses per cm2), preventing the achievement of a long-term goal: the creation of autonomous cognitive systems. This project aspires to develop experimental platforms capable of perceiving, learning and adapting to stimuli by leveraging on the latest developments of five leading Europeaninstitutions in neuroscience, nanotechnology, modeling and circuit design. The non-linear dynamics as well as the plasticity of the newly discovered memristor are shown to support Spike-based- and Spike-Timing-Dependent-Plasticity (STDP), making this extremely compact device an excellent candidate for realizing large-scale self-adaptive circuits; a steptowards “autonomous cognitive systems”. The intrinsic properties of real neurons and synapses as well as their organization in forming neural circuits will be exploited for optimizing CMOS-based neurons, memristive grids and the integration of the two into real-time biophysically realistic neuromorphic systems. Finally, the platforms would be tested withconventional as well as abstract methods to evaluate the technology and its autonomous capacity.
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