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      Finding a roadmap to achieve large neuromorphic hardware systems

      research-article
      ,
      Frontiers in Neuroscience
      Frontiers Media S.A.
      FPAA, Simulink, reconfigurable analog, neuromorphic engineering

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          Abstract

          Neuromorphic systems are gaining increasing importance in an era where CMOS digital computing techniques are reaching physical limits. These silicon systems mimic extremely energy efficient neural computing structures, potentially both for solving engineering applications as well as understanding neural computation. Toward this end, the authors provide a glimpse at what the technology evolution roadmap looks like for these systems so that Neuromorphic engineers may gain the same benefit of anticipation and foresight that IC designers gained from Moore's law many years ago. Scaling of energy efficiency, performance, and size will be discussed as well as how the implementation and application space of Neuromorphic systems are expected to evolve over time.

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          Most cited references110

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          A model is presented that reproduces spiking and bursting behavior of known types of cortical neurons. The model combines the biologically plausibility of Hodgkin-Huxley-type dynamics and the computational efficiency of integrate-and-fire neurons. Using this model, one can simulate tens of thousands of spiking cortical neurons in real time (1 ms resolution) using a desktop PC.
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            Activity-driven modifications in synaptic connections between neurons in the neocortex may occur during development and learning. In dual whole-cell voltage recordings from pyramidal neurons, the coincidence of postsynaptic action potentials (APs) and unitary excitatory postsynaptic potentials (EPSPs) was found to induce changes in EPSPs. Their average amplitudes were differentially up- or down-regulated, depending on the precise timing of postsynaptic APs relative to EPSPs. These observations suggest that APs propagating back into dendrites serve to modify single active synaptic connections, depending on the pattern of electrical activity in the pre- and postsynaptic neurons.
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              Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type.

              Q Bi, G Bi, M Poo (1998)
              In cultures of dissociated rat hippocampal neurons, persistent potentiation and depression of glutamatergic synapses were induced by correlated spiking of presynaptic and postsynaptic neurons. The relative timing between the presynaptic and postsynaptic spiking determined the direction and the extent of synaptic changes. Repetitive postsynaptic spiking within a time window of 20 msec after presynaptic activation resulted in long-term potentiation (LTP), whereas postsynaptic spiking within a window of 20 msec before the repetitive presynaptic activation led to long-term depression (LTD). Significant LTP occurred only at synapses with relatively low initial strength, whereas the extent of LTD did not show obvious dependence on the initial synaptic strength. Both LTP and LTD depended on the activation of NMDA receptors and were absent in cases in which the postsynaptic neurons were GABAergic in nature. Blockade of L-type calcium channels with nimodipine abolished the induction of LTD and reduced the extent of LTP. These results underscore the importance of precise spike timing, synaptic strength, and postsynaptic cell type in the activity-induced modification of central synapses and suggest that Hebb's rule may need to incorporate a quantitative consideration of spike timing that reflects the narrow and asymmetric window for the induction of synaptic modification.
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                Author and article information

                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                10 September 2013
                2013
                : 7
                : 118
                Affiliations
                School of Electrical and Computer Engineering, Georgia Institute of Technology Atlanta, GA, USA
                Author notes

                Edited by: Gert Cauwenberghs, University of California, San Diego, USA

                Reviewed by: Bernabe Linares-Barranco, Instituto de Microelectrónica de Sevilla, Spain; Theodore Yu, Texas Instruments Inc., USA; John Harris, University of Florida, USA

                *Correspondence: Jennifer Hasler, Georgia Institute of Technology, Atlanta, GA 30332-250, USA e-mail: phasler@ 123456ece.gatech.edu

                This article was submitted to Neuromorphic Engineering, a section of the journal Frontiers in Neuroscience.

                †Present address: Bo Marr, Raytheon Segundo, CA, USA

                Article
                10.3389/fnins.2013.00118
                3767911
                24058330
                b22f7436-6cb4-473c-a863-523ee54def15
                Copyright © 2013 Hasler and Marr.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 04 April 2012
                : 20 June 2013
                Page count
                Figures: 27, Tables: 6, Equations: 6, References: 161, Pages: 29, Words: 23140
                Categories
                Neuroscience
                Hypothesis and Theory Article

                Neurosciences
                fpaa,simulink,reconfigurable analog,neuromorphic engineering
                Neurosciences
                fpaa, simulink, reconfigurable analog, neuromorphic engineering

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