Neuromorphic Implementation of Attractor Dynamics in a Two-Variable Winner-Take-All Circuit with NMDARs: A Simulation Study
暂无分享,去创建一个
[1] Steve B. Furber,et al. The SpiNNaker Project , 2014, Proceedings of the IEEE.
[2] Xiao-Jing Wang. Synaptic reverberation underlying mnemonic persistent activity , 2001, Trends in Neurosciences.
[3] Chiara Bartolozzi,et al. Synaptic Dynamics in Analog VLSI , 2007, Neural Computation.
[4] Xiao-Jing Wang,et al. A Recurrent Network Mechanism of Time Integration in Perceptual Decisions , 2006, The Journal of Neuroscience.
[5] Kwabena Boahen,et al. Point-to-point connectivity between neuromorphic chips using address events , 2000 .
[6] Chiara Bartolozzi,et al. Neuromorphic Electronic Circuits for Building Autonomous Cognitive Systems , 2014, Proceedings of the IEEE.
[7] P. Goldman-Rakic,et al. Temporally irregular mnemonic persistent activity in prefrontal neurons of monkeys during a delayed response task. , 2003, Journal of neurophysiology.
[8] Giacomo Indiveri,et al. A device mismatch compensation method for VLSI neural networks , 2010, 2010 Biomedical Circuits and Systems Conference (BioCAS).
[9] R. Sekuler,et al. Hysteresis in the perception of motion direction as evidence for neural cooperativity , 1986, Nature.
[10] Hongzhi You,et al. Neuromorphic implementation of attractor dynamics in decision circuit with NMDARs , 2016, 2016 IEEE International Symposium on Circuits and Systems (ISCAS).
[11] Kazuyuki Aihara,et al. Circuit Implementation and Dynamics of a Two-Dimensional MOSFET Neuron Model , 2007, Int. J. Bifurc. Chaos.
[12] Daniel Robert,et al. Synchrony through twice-frequency forcing for sensitive and selective auditory processing , 2009, Proceedings of the National Academy of Sciences.
[13] Larissa Albantakis,et al. The encoding of alternatives in multiple-choice decision-making , 2009, Proceedings of the National Academy of Sciences.
[14] W. Newsome,et al. Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. , 2001, Journal of neurophysiology.
[15] X. Wang,et al. Synaptic Basis of Cortical Persistent Activity: the Importance of NMDA Receptors to Working Memory , 1999, The Journal of Neuroscience.
[16] Piotr Dudek,et al. VLSI circuits implementing computational models of neocortical circuits , 2012, Journal of Neuroscience Methods.
[17] Giacomo Indiveri,et al. A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity , 2006, IEEE Transactions on Neural Networks.
[18] Yulia Sandamirskaya,et al. Dynamic neural fields as a step toward cognitive neuromorphic architectures , 2014, Front. Neurosci..
[19] Timothy D. Hanks,et al. Bounded Integration in Parietal Cortex Underlies Decisions Even When Viewing Duration Is Dictated by the Environment , 2008, The Journal of Neuroscience.
[20] Rodrigo Alvarez-Icaza,et al. Neurogrid: A Mixed-Analog-Digital Multichip System for Large-Scale Neural Simulations , 2014, Proceedings of the IEEE.
[21] Yannick Bornat,et al. A Library of Analog Operators Based on the Hodgkin-Huxley Formalism for the Design of Tunable, Real-Time, Silicon Neurons , 2011, IEEE Transactions on Biomedical Circuits and Systems.
[22] Patrick Camilleri,et al. Robust Working Memory in an Asynchronously Spiking Neural Network Realized with Neuromorphic VLSI , 2011, Frontiers in Neuroscience.
[23] Andrew Philippides,et al. Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP , 2016, PLoS Comput. Biol..
[24] C. Koch,et al. Attention activates winner-take-all competition among visual filters , 1999, Nature Neuroscience.
[25] Sumio Hosaka,et al. Associative memory realized by a reconfigurable memristive Hopfield neural network , 2015, Nature Communications.
[26] Kwabena Boahen,et al. Dynamical System Guided Mapping of Quantitative Neuronal Models Onto Neuromorphic Hardware , 2012, IEEE Transactions on Circuits and Systems I: Regular Papers.
[27] Dante R. Chialvo,et al. Modulated noisy biological dynamics: Three examples , 1993 .
[28] Massimiliano Giulioni,et al. Decision making and perceptual bistability in spike-based neuromorphic VLSI systems , 2015, 2015 IEEE International Symposium on Circuits and Systems (ISCAS).
[29] Kwabena Boahen,et al. Silicon-Neuron Design: A Dynamical Systems Approach , 2011, IEEE Transactions on Circuits and Systems I: Regular Papers.
[30] J. Fellous,et al. A role for NMDA-receptor channels in working memory , 1998, Nature Neuroscience.
[31] H. Haken. Synergetics: an Introduction, Nonequilibrium Phase Transitions and Self-organization in Physics, Chemistry, and Biology , 1977 .
[32] Jia Wang,et al. DaDianNao: A Machine-Learning Supercomputer , 2014, 2014 47th Annual IEEE/ACM International Symposium on Microarchitecture.
[33] Xiao-Jing Wang,et al. Probabilistic Decision Making by Slow Reverberation in Cortical Circuits , 2002, Neuron.
[34] Kazuyuki Aihara,et al. A two-variable silicon neuron circuit based on the Izhikevich model , 2011, Artificial Life and Robotics.
[35] Gert Cauwenberghs,et al. Analog VLSI Biophysical Neurons and Synapses With Programmable Membrane Channel Kinetics , 2010, IEEE Transactions on Biomedical Circuits and Systems.
[36] Giacomo Indiveri,et al. Synthesizing cognition in neuromorphic electronic systems , 2013, Proceedings of the National Academy of Sciences.
[37] Davide Badoni,et al. Spike-Driven Synaptic Plasticity: Theory, Simulation, VLSI Implementation , 2000, Neural Computation.
[38] Arindam Basu,et al. Analysis and reduction of mismatch in silicon neurons , 2011, 2011 IEEE Biomedical Circuits and Systems Conference (BioCAS).
[39] KongFatt Wong-Lin,et al. Neural Circuit Dynamics Underlying Accumulation of Time-Varying Evidence During Perceptual Decision Making , 2007, Frontiers Comput. Neurosci..
[40] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[41] Emmanuel M. Drakakis,et al. Systematic Computation of Nonlinear Cellular and Molecular Dynamics with Low-Power CytoMimetic Circuits: A Simulation Study , 2013, PloS one.
[42] H. Haken,et al. Synergetics , 1988, IEEE Circuits and Devices Magazine.
[43] Karl J. Friston,et al. The Neural Structures Expressing Perceptual Hysteresis in Visual Letter Recognition , 2002, Neuron.
[44] Giacomo Indiveri,et al. Frontiers in Neuromorphic Engineering , 2011, Front. Neurosci..
[45] P. Holmes,et al. The dynamics of choice among multiple alternatives , 2006 .
[46] E. Knudsen. Fundamental components of attention. , 2007, Annual review of neuroscience.
[47] T. Sejnowski,et al. Neurocomputational models of working memory , 2000, Nature Neuroscience.
[48] M. Shadlen,et al. Decision Making as a Window on Cognition , 2013, Neuron.
[49] Hongzhi You,et al. The neural dynamics for hysteresis in visual perception , 2011, Neurocomputing.
[50] G. E. Alexander,et al. Neuron Activity Related to Short-Term Memory , 1971, Science.
[51] Hongzhi You,et al. Dynamics of Multiple-Choice Decision Making , 2013, Neural Computation.
[52] Tianshi Chen,et al. DaDianNao: A Neural Network Supercomputer , 2017, IEEE Transactions on Computers.
[53] Giacomo Indiveri,et al. A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses , 2015, Front. Neurosci..
[54] Andrew Nere,et al. A Neuromorphic Architecture for Object Recognition and Motion Anticipation Using Burst-STDP , 2012, PloS one.
[55] Giacomo Indiveri,et al. Spike-based learning with a generalized integrate and fire silicon neuron , 2010, Proceedings of 2010 IEEE International Symposium on Circuits and Systems.
[56] B. Gilbert. Translinear circuits: a proposed classification , 1975 .
[57] R. Douglas,et al. Event-Based Neuromorphic Systems , 2015 .
[58] Xiao-Jing Wang,et al. From Distributed Resources to Limited Slots in Multiple-Item Working Memory: A Spiking Network Model with Normalization , 2012, The Journal of Neuroscience.