Citation Relationships
| Legends: | Link to a Model | Reference cited by multiple papers |
Richmond P, Buesing L, Giugliano M, Vasilaki E (2011) Democratic population decisions result in robust policy-gradient learning: a parametric study with GPU simulations. PLoS One 6:e18539 [PubMed]
| • | Democratic population decisions result in robust policy-gradient learning (Richmond et al. 2011) |
References and models cited by this paper | References and models that cite this paper | |||||||||||||||
Abbott LF, Nelson SB (2000) Synaptic plasticity: taming the beast. Nat Neurosci 3 Suppl:1178-83 [Journal] [PubMed] Amari S (1975) Homogeneous nets of neuron-like elements. Biol Cybern 17:211-20 [PubMed] Amari S (1977) Dynamics of pattern formation in lateral-inhibition type neural fields. Biol Cybern 27:77-87 [PubMed] Ananthanarayanan R, Esser SK, Simon HD, Modha DS (2009) The cat is out of the bag:cortical simulations with 10^9 neurons and 10^13 synapses Supercomputing `09: Proceedings of the ACM/IEEE SC2009 Conference on High Performance Networking and Computing, Portland, OR Baras D, Meir R (2007) Reinforcement learning, spike-time-dependent plasticity, and the BCM rule. Neural Comput 19:2245-79 [Journal] [PubMed] Barto AG (1985) Learning by statistical cooperation of self-interested neuron-like computing elements. Hum Neurobiol 4:229-56 [PubMed] Baxter J, Bartlett PL, Weaver L (2001) Experiments with infinite-horizon, policy-gradient estimation J Artif Intel Res 15:351-381 Beierholm UR, Dayan P (2010) Pavlovian-instrumental interaction in 'observing behavior'. PLoS Comput Biol [Journal] [PubMed] Bell N, Garland M (2008) Efficient sparse matrix-vector multiplication on CUDA NVIDIA Technical Report NVR-2008-004 Berdahl JP, Allingham RR, Johnson DH (2008) Cerebrospinal fluid pressure is decreased in primary open-angle glaucoma. Ophthalmology 115:763-8 [Journal] [PubMed] Bernhard F, Keriven R (2006) Spiking neurons on GPUs International Conference on Computational Science :236-243 Bhuiyan M, Pallipuram V, Smith M (2010) Acceleration of spiking neural networks in emerging multi-core and gpu architectures Parallel Distributed Processing, Workshops and Phd Forum (IPDPSW), 2010 IEEE International Symposium :1-8 Brüderle D, Müller E, Davison A, Muller E, Schemmel J, Meier K (2009) Establishing a novel modeling tool: a python-based interface for a neuromorphic hardware system. Front Neuroinform 3:17 [Journal] [PubMed] Bruederle D, Bill J, Kaplan B, Kremkow J, Meier K, Et_al (2010) Simulator-Like Exploration of Cortical Network Architectures with a Mixed-Signal VLSI System Proceedings of the 2010 IEEE International Symposium on Circuits and Systems (ISCAS 10) :2784-8787 Buck I, Foley T, Horn D, Sugerman J, Fatahalian K, Et_al (2004) Brook for gpus: stream computing on graphics hardware SIGGRAPH 904: ACM SIGGRAPH 2004 Papers :777-786 Corporation NVIDIA (2008) NVIDIA CUDA Programming Guide Coultrip R, Granger R, Lynch G (1992) A cortical model of winnertake-all competition via lateral inhibition Neural Networks 5:47-54 Davison A, Muller E, Bruederle D, Kremkow J (2010) A common language for neuronal networks in software and hardware The Neuromorphic Engineer Davison AP, Brüderle D, Eppler J, Kremkow J, Muller E, Pecevski D, Perrinet L, Yger P (2008) PyNN: A Common Interface for Neuronal Network Simulators. Front Neuroinform 2:11 [Journal] [PubMed] Davison AP, Hines ML, Muller E (2009) Trends in programming languages for neuroscience simulations. Front Neurosci 3:374-80 [Journal] [PubMed] Dayan P, Daw ND (2008) Decision theory, reinforcement learning, and the brain. Cogn Affect Behav Neurosci 8:429-53 [Journal] [PubMed] Di_castro d, Volkinshtein S, Meir R (2009) Temporal difference based actor critic learning- convergence and neural implementation NIPS 22:385-392 Dl LY, Paprotski V, Yen D (2008) Neural networks on gpus: Restricted boltzmann machines Restricted boltzmann machines. Technical report Eppler JM, Helias M, Muller E, Diesmann M, Gewaltig MO (2008) PyNEST: A Convenient Interface to the NEST Simulator. Front Neuroinform 2:12 [Journal] [PubMed] Farries MA, Fairhall AL (2007) Reinforcement learning with modulated spike timing dependent synaptic plasticity. J Neurophysiol 98:3648-65 [Journal] [PubMed] Fiete IR, Seung HS (2006) Gradient learning in spiking neural networks by dynamic perturbation of conductances. Phys Rev Lett 97:048104 [Journal] [PubMed] Florian RV (2007) Reinforcement learning through modulation of spike-timing-dependent synaptic plasticity. Neural Comput 19:1468-502 [Journal] [PubMed] Friedrich J, Urbanczik R, Senn W (2010) Learning spike-based population codes by reward and population feedback. Neural Comput 22:1698-717 [Journal] [PubMed] Georgopoulos AP, Schwartz AB, Kettner RE (1986) Neuronal population coding of movement direction. Science 233:1416-9 [PubMed] Gerstner W, Kempter R, van Hemmen JL, Wagner H (1996) A neuronal learning rule for sub-millisecond temporal coding. Nature 383:76-81 [Journal] [PubMed] Gerstner W, Kistler WM (2002) Spiking neuron models Gerwinn S, Macke JH, Bethge M (2010) Bayesian inference for generalized linear models for spiking neurons. Front Comput Neurosci 4:12 [Journal] [PubMed] Goodman D, Brette R (2008) Brian: a simulator for spiking neural networks in python. Front Neuroinform 2:5 [Journal] [PubMed] Goodman DF (2010) Code generation: a strategy for neural network simulators. Neuroinformatics 8:183-96 [Journal] [PubMed] Gummaraju J, Rosenblum M (2005) Stream programming on general-purpose processors MICRO 38: Proceedings of the 38th annual IEEE ACM International Symposium on Microarchitecture :343-354 Hamaguchi K, Okada M, Yamana M, Aihara K (2005) Correlated firing in a feedforward network with Mexican-hat-type connectivity. Neural Comput 17:2034-59 [Journal] [PubMed] Hines ML, Morse T, Migliore M, Carnevale NT, Shepherd GM (2004) ModelDB: A Database to Support Computational Neuroscience. J Comput Neurosci 17:7-11 [Journal] [PubMed] Izhikevich EM (2007) Solving the distal reward problem through linkage of STDP and dopamine signaling. Cereb Cortex 17:2443-52 [Journal] [PubMed]
Jensen O, Lisman JE (2000) Position reconstruction from an ensemble of hippocampal place cells: contribution of theta phase coding. J Neurophysiol 83:2602-9 [Journal] [PubMed] Kempter R, Gerstner W, van_Hemmen JL (1999) Hebbian learning and spiking neurons Physical Review E 59:4498-4514 [Journal] Legenstein R, Pecevski D, Maass W (2008) A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedback. PLoS Comput Biol 4:e1000180 [Journal] [PubMed]
Legenstein R, Wilbert N, Wiskott L (2010) Reinforcement learning on slow features of high-dimensional input streams. PLoS Comput Biol 6: Martnez-zarzuela M, Daz_pernas_f , Dez_higuera_j , Rodrguez M (2007) Fuzzy art neural network parallel computing on the gpu Lecture Notes in Computer Science, Sandoval F:Prieto A:Cabestany J:Graa M, ed. pp.463 Nageswaran JM, Dutt N, Krichmar JL, Nicolau A, Veidenbaum AV (2009) A configurable simulation environment for the efficient simulation of large-scale spiking neural networks on graphics processors. Neural Netw 22:791-800 [Journal] [PubMed] O'Keefe J, Dostrovsky J (1971) The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. Brain Res 34:171-5 [PubMed] Pfister JP, Toyoizumi T, Barber D, Gerstner W (2006) Optimal spike-timing-dependent plasticity for precise action potential firing in supervised learning. Neural Comput 18:1318-48 [Journal] [PubMed] Piekniewski F (2010) Persistent activation blobs in spiking neural networks with mexican hat connectivity Artifical Intelligence and Soft Computing, Rutkowski L:Scherer R:Tadeusiewicz R:Zadeh L:Zurada J, ed. pp.64 Potjans W, Morrison A, Diesmann M (2009) A spiking neural network model of an actor-critic learning agent. Neural Comput 21:301-39 [Journal] [PubMed] Renaud S, Tomas J, Daouzli A (2007) Neuromimetic ICs with analog cores: an alternative for simulating spiking neural networks International symposium on circuits and systems (ISCAS07) :3355-3358 Richmond P, Romano D (2008) A high performance framework for agent based pedestrian dynamics on gpu hardware Proceedings of EUROSIS ESM Richmond P, Walker D, Coakley S, Romano D (2010) High performance cellular level agent-based simulation with FLAME for the GPU. Brief Bioinform 11:334-47 [Journal] [PubMed] Rossant C, Goodman DF, Platkiewicz J, Brette R (2010) Automatic fitting of spiking neuron models to electrophysiological recordings. Front Neuroinform 4:2 [Journal] [PubMed] Sanders J, Kandrot E (2010) CUDA by Example: An Introduction to General- Purpose GPU Programming. Sengupta S, Harris M, Zhang Y, Owens JD (2007) Scan primitives for gpu computing GH 907: Proceedings of the 22nd ACM SIGGRAPH- EUROGRAPHICS symposium on Graphics hardware :97-106 Seung HS (2003) Learning in spiking neural networks by reinforcement of stochastic synaptic transmission. Neuron 40:1063-73 [PubMed] Sheynikhovich D, Chavarriaga R (2005) Spatial representation and navigation in a bio-inspired robot Biomimetic neural learning for intelligent robots: Intelligent systems, cognitive robotics, and neuroscience :245-264 Spiridon M, Gerstner W (2001) Effect of lateral connections on the accuracy of the population code for a network of spiking neurons. Network 12:409-21 [PubMed] STEIN RB (1965) A THEORETICAL ANALYSIS OF NEURONAL VARIABILITY. Biophys J 5:173-94 [PubMed] Steiner J, Bernstein HG, Bielau H, Berndt A, Brisch R, Mawrin C, Keilhoff G, Bogerts B (2007) Evidence for a wide extra-astrocytic distribution of S100B in human brain. BMC Neurosci 8:2 [Journal] [PubMed] Suri RE, Schultz W (2001) Temporal difference model reproduces anticipatory neural activity. Neural Comput 13:841-62 [PubMed] Sutton RS, Barto AG (1998) Reinforcement learning: an introduction [Journal]
Talmi D, Dayan P, Kiebel SJ, Frith CD, Dolan RJ (2009) How humans integrate the prospects of pain and reward during choice. J Neurosci 29:14617-26 [Journal] [PubMed] Van Rossum MC (2001) The transient precision of integrate and fire neurons: effect of background activity and noise. J Comput Neurosci 10:303-11 [Journal] [PubMed] van Rossum MC, Turrigiano GG, Nelson SB (2002) Fast propagation of firing rates through layered networks of noisy neurons. J Neurosci 22:1956-66 [PubMed] Van_meel J, Arnold A, Frenkel D, Portegies_zwart_s , Belleman R (2008) Harvesting graphics power for MD simulations Molecular Simulation 34:259-266 van_Rossum MCW, Renart A (2004) Computation with population codes in layered networks of integrate-and-fire neurons Neurocomputing 58:265-270 Vasilaki E, Frémaux N, Urbanczik R, Senn W, Gerstner W (2009) Spike-based reinforcement learning in continuous state and action space: when policy gradient methods fail. PLoS Comput Biol 5:e1000586 [Journal] [PubMed] Vasilaki E, Fusi S, Wang XJ, Senn W (2009) Learning flexible sensori-motor mappings in a complex network. Biol Cybern 100:147-58 [Journal] [PubMed] Wang XJ (2006) A microcircuit model of prefrontal functions: Ying and Yang of reverberatory neurodynamics in cognition The Prefrontal Lobes: Development, Function and Pathology, Risberg J:Grafman J:Boller F, ed. pp.92 Watkins CJCH (1989) Learning from delayed rewards Unpublished doctoral dissertation Williams RJ (1992) Simple statistical gradient-following algorithms for connectionist reinforcement learning Mach Learn 8:229-256 Xie X, Seung HS (2004) Learning in neural networks by reinforcement of irregular spiking. Phys Rev E Stat Nonlin Soft Matter Phys 69:041909 [Journal] [PubMed] | Esposito U, Giugliano M, van Rossum M, Vasilaki E (2014) Measuring symmetry, asymmetry and randomness in neural network connectivity. PLoS One 9:e100805 [Journal] [PubMed]
Esposito U, Giugliano M, Vasilaki E (2014) Adaptation of short-term plasticity parameters via error-driven learning may explain the correlation between activity-dependent synaptic properties, connectivity motifs and target specificity. Front Comput Neurosci 8:175 [Journal] [PubMed]
Gehring TV, Luksys G, Sandi C, Vasilaki E (2015) Detailed classification of swimming paths in the Morris Water Maze: multiple strategies within one trial. Sci Rep 5:14562 [Journal] [PubMed]
Vasilaki E, Giugliano M (2014) Emergence of connectivity motifs in networks of model neurons with short- and long-term plastic synapses. PLoS One 9:e84626 [Journal] [PubMed]
| |||||||||||||||