Literature DB >> 17251143

Neural systems engineering.

Steve Furber1, Steve Temple.   

Abstract

The quest to build an electronic computer based on the operational principles of biological brains has attracted attention over many years. The hope is that, by emulating the brain, it will be possible to capture some of its capabilities and thereby bridge the very large gulf that separates mankind from machines. At present, however, knowledge about the operational principles of the brain is far from complete, so attempts at emulation must employ a great deal of assumption and guesswork to fill the gaps in the experimental evidence. The sheer scale and complexity of the human brain still defies attempts to model it in its entirety at the neuronal level, but Moore's Law is closing this gap and machines with the potential to emulate the brain (so far as we can estimate the computing power required) are no more than a decade or so away. Do computer engineers have something to contribute, alongside neuroscientists, psychologists, mathematicians and others, to the understanding of brain and mind, which remains as one of the great frontiers of science?

Entities:  

Mesh:

Year:  2007        PMID: 17251143      PMCID: PMC2359843          DOI: 10.1098/rsif.2006.0177

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  19 in total

1.  Rate coding versus temporal order coding: what the retinal ganglion cells tell the visual cortex.

Authors:  R Van Rullen; S J Thorpe
Journal:  Neural Comput       Date:  2001-06       Impact factor: 2.026

2.  Branching dendritic trees and motoneuron membrane resistivity.

Authors:  W RALL
Journal:  Exp Neurol       Date:  1959-11       Impact factor: 5.330

3.  Polychronization: computation with spikes.

Authors:  Eugene M Izhikevich
Journal:  Neural Comput       Date:  2006-02       Impact factor: 2.026

Review 4.  The blue brain project.

Authors:  Henry Markram
Journal:  Nat Rev Neurosci       Date:  2006-02       Impact factor: 34.870

5.  Sparse distributed memory using rank-order neural codes.

Authors:  Stephen B Furber; Gavin Brown; Joy Bose; John Michael Cumpstey; Peter Marshall; Jonathan L Shapiro
Journal:  IEEE Trans Neural Netw       Date:  2007-05

6.  Spontaneous subthreshold activity at motor nerve endings.

Authors:  P FATT; B KATZ
Journal:  J Physiol       Date:  1952-05       Impact factor: 5.182

7.  Time structure of the activity in neural network models.

Authors: 
Journal:  Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics       Date:  1995-01

8.  A logical calculus of the ideas immanent in nervous activity. 1943.

Authors:  W S McCulloch; W Pitts
Journal:  Bull Math Biol       Date:  1990       Impact factor: 1.758

9.  Phase relationship between hippocampal place units and the EEG theta rhythm.

Authors:  J O'Keefe; M L Recce
Journal:  Hippocampus       Date:  1993-07       Impact factor: 3.899

Review 10.  Communication in neuronal networks.

Authors:  Simon B Laughlin; Terrence J Sejnowski
Journal:  Science       Date:  2003-09-26       Impact factor: 47.728

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  9 in total

Review 1.  The Human Brain Project and neuromorphic computing.

Authors:  Andrea Calimera; Enrico Macii; Massimo Poncino
Journal:  Funct Neurol       Date:  2013 Jul-Sep

2.  Associative memory realized by a reconfigurable memristive Hopfield neural network.

Authors:  S G Hu; Y Liu; Z Liu; T P Chen; J J Wang; Q Yu; L J Deng; Y Yin; Sumio Hosaka
Journal:  Nat Commun       Date:  2015-06-25       Impact factor: 14.919

3.  Incorporating neurophysiological concepts in mathematical thermoregulation models.

Authors:  Boris R M Kingma; M J Vosselman; A J H Frijns; A A van Steenhoven; W D van Marken Lichtenbelt
Journal:  Int J Biometeorol       Date:  2013-01-27       Impact factor: 3.787

4.  Benchmarking Spike-Based Visual Recognition: A Dataset and Evaluation.

Authors:  Qian Liu; Garibaldi Pineda-García; Evangelos Stromatias; Teresa Serrano-Gotarredona; Steve B Furber
Journal:  Front Neurosci       Date:  2016-11-02       Impact factor: 4.677

5.  Breaking the millisecond barrier on SpiNNaker: implementing asynchronous event-based plastic models with microsecond resolution.

Authors:  Xavier Lagorce; Evangelos Stromatias; Francesco Galluppi; Luis A Plana; Shih-Chii Liu; Steve B Furber; Ryad B Benosman
Journal:  Front Neurosci       Date:  2015-06-08       Impact factor: 4.677

6.  Serendipitous Offline Learning in a Neuromorphic Robot.

Authors:  Terrence C Stewart; Ashley Kleinhans; Andrew Mundy; Jörg Conradt
Journal:  Front Neurorobot       Date:  2016-02-15       Impact factor: 2.650

7.  Limits to high-speed simulations of spiking neural networks using general-purpose computers.

Authors:  Friedemann Zenke; Wulfram Gerstner
Journal:  Front Neuroinform       Date:  2014-09-11       Impact factor: 4.081

8.  Ultra-low-power switching circuits based on a binary pattern generator with spiking neurons.

Authors:  Takeaki Yajima
Journal:  Sci Rep       Date:  2022-01-21       Impact factor: 4.379

9.  Hardware Demonstration of SRDP Neuromorphic Computing with Online Unsupervised Learning Based on Memristor Synapses.

Authors:  Ruiyi Li; Peng Huang; Yulin Feng; Zheng Zhou; Yizhou Zhang; Xiangxiang Ding; Lifeng Liu; Jinfeng Kang
Journal:  Micromachines (Basel)       Date:  2022-03-11       Impact factor: 2.891

  9 in total

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