| Year |
Citation |
Score |
| 2023 |
Lansner A, Fiebig F, Herman P. Fast Hebbian plasticity and working memory. Current Opinion in Neurobiology. 83: 102809. PMID 37980802 DOI: 10.1016/j.conb.2023.102809 |
0.774 |
|
| 2022 |
Chrysanthidis N, Fiebig F, Lansner A, Herman P. Traces of semantization - from episodic to semantic memory in a spiking cortical network model. Eneuro. PMID 35803714 DOI: 10.1523/ENEURO.0062-22.2022 |
0.792 |
|
| 2020 |
Yang Y, Stathis D, Jordão R, Hemani A, Lansner A. Optimizing BCPNN Learning Rule for Memory Access. Frontiers in Neuroscience. 14: 878. PMID 32982673 DOI: 10.3389/Fnins.2020.00878 |
0.43 |
|
| 2020 |
Fiebig F, Herman P, Lansner A. An Indexing Theory for Working Memory based on Fast Hebbian Plasticity. Eneuro. PMID 32127347 DOI: 10.1523/ENEURO.0374-19.2020 |
0.783 |
|
| 2020 |
Stathis D, Sudarshan C, Yang Y, Jung M, Jafri SAMH, Weis C, Hemani A, Lansner A, Wehn N. eBrainII: a 3 kW Realtime Custom 3D DRAM Integrated ASIC Implementation of a Biologically Plausible Model of a Human Scale Cortex Journal of Signal Processing Systems. 1-21. DOI: 10.1007/S11265-020-01562-X |
0.4 |
|
| 2019 |
Chrysanthidis N, Fiebig F, Lansner A. Introducing double bouquet cells into a modular cortical associative memory model. Journal of Computational Neuroscience. PMID 31502234 DOI: 10.1007/S10827-019-00729-1 |
0.789 |
|
| 2019 |
Martinez RH, Lansner A, Herman P. Probabilistic associative learning suffices for learning the temporal structure of multiple sequences. Plos One. 14: e0220161. PMID 31369571 DOI: 10.1371/Journal.Pone.0220161 |
0.42 |
|
| 2017 |
Fiebig F, Lansner A. A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 37: 83-96. PMID 28053032 DOI: 10.1523/Jneurosci.1989-16.2016 |
0.81 |
|
| 2016 |
Berthet P, Lindahl M, Tully PJ, Hellgren-Kotaleski J, Lansner A. Functional Relevance of Different Basal Ganglia Pathways Investigated in a Spiking Model with Reward Dependent Plasticity. Frontiers in Neural Circuits. 10: 53. PMID 27493625 DOI: 10.3389/Fncir.2016.00053 |
0.339 |
|
| 2016 |
Tully PJ, Lindén H, Hennig MH, Lansner A. Spike-Based Bayesian-Hebbian Learning of Temporal Sequences. Plos Computational Biology. 12: e1004954. PMID 27213810 DOI: 10.1371/Journal.Pcbi.1004954 |
0.449 |
|
| 2016 |
Knight JC, Tully PJ, Kaplan BA, Lansner A, Furber SB. Large-Scale Simulations of Plastic Neural Networks on Neuromorphic Hardware. Frontiers in Neuroanatomy. 10: 37. PMID 27092061 DOI: 10.3389/Fnana.2016.00037 |
0.481 |
|
| 2015 |
Mazzoni A, Lindén H, Cuntz H, Lansner A, Panzeri S, Einevoll GT. Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models. Plos Computational Biology. 11: e1004584. PMID 26657024 DOI: 10.1371/Journal.Pcbi.1004584 |
0.492 |
|
| 2015 |
Krishnamurthy P, Silberberg G, Lansner A. Long-range recruitment of Martinotti cells causes surround suppression and promotes saliency in an attractor network model. Frontiers in Neural Circuits. 9: 60. PMID 26528143 DOI: 10.3389/Fncir.2015.00060 |
0.681 |
|
| 2015 |
Vogginger B, Schüffny R, Lansner A, Cederström L, Partzsch J, Höppner S. Reducing the computational footprint for real-time BCPNN learning. Frontiers in Neuroscience. 9: 2. PMID 25657618 DOI: 10.3389/Fnins.2015.00002 |
0.407 |
|
| 2014 |
Petrovici MA, Vogginger B, Müller P, Breitwieser O, Lundqvist M, Muller L, Ehrlich M, Destexhe A, Lansner A, Schüffny R, Schemmel J, Meier K. Characterization and compensation of network-level anomalies in mixed-signal neuromorphic modeling platforms. Plos One. 9: e108590. PMID 25303102 DOI: 10.1371/Journal.Pone.0108590 |
0.436 |
|
| 2014 |
Fiebig F, Lansner A. Memory consolidation from seconds to weeks: a three-stage neural network model with autonomous reinstatement dynamics. Frontiers in Computational Neuroscience. 8: 64. PMID 25071536 DOI: 10.3389/Fncom.2014.00064 |
0.779 |
|
| 2014 |
Tully PJ, Hennig MH, Lansner A. Synaptic and nonsynaptic plasticity approximating probabilistic inference. Frontiers in Synaptic Neuroscience. 6: 8. PMID 24782758 DOI: 10.3389/Fnsyn.2014.00008 |
0.415 |
|
| 2014 |
Berthet P, Lansner A. Optogenetic stimulation in a computational model of the basal ganglia biases action selection and reward prediction error. Plos One. 9: e90578. PMID 24614169 DOI: 10.1371/Journal.Pone.0090578 |
0.321 |
|
| 2014 |
Kaplan BA, Lansner A. A spiking neural network model of self-organized pattern recognition in the early mammalian olfactory system. Frontiers in Neural Circuits. 8: 5. PMID 24570657 DOI: 10.3389/Fncir.2014.00005 |
0.396 |
|
| 2014 |
Kaplan BA, Khoei MA, Lansner A, Perrinet LU. Signature of an anticipatory response in area VI as modeled by a probabilistic model and a spiking neural network Proceedings of the International Joint Conference On Neural Networks. 3205-3212. DOI: 10.1109/IJCNN.2014.6889847 |
0.332 |
|
| 2014 |
Marco S, Gutiérrez-Gálvez A, Lansner A, Martinez D, Rospars JP, Beccherelli R, Perera A, Pearce TC, Verschure PFMJ, Persaud K. A biomimetic approach to machine olfaction, featuring a very large-scale chemical sensor array and embedded neuro-bio-inspired computation Microsystem Technologies. 20: 729-742. DOI: 10.1007/S00542-013-2020-8 |
0.321 |
|
| 2013 |
Meli C, Lansner A. A modular attractor associative memory with patchy connectivity and weight pruning. Network (Bristol, England). 24: 129-50. PMID 24251411 DOI: 10.3109/0954898X.2013.859323 |
0.434 |
|
| 2013 |
Kaplan BA, Lansner A, Masson GS, Perrinet LU. Anisotropic connectivity implements motion-based prediction in a spiking neural network. Frontiers in Computational Neuroscience. 7: 112. PMID 24062680 DOI: 10.3389/Fncom.2013.00112 |
0.424 |
|
| 2013 |
Lansner A, Marklund P, Sikström S, Nilsson LG. Reactivation in working memory: an attractor network model of free recall. Plos One. 8: e73776. PMID 24023690 DOI: 10.1371/Journal.Pone.0073776 |
0.386 |
|
| 2013 |
Herman PA, Lundqvist M, Lansner A. Nested theta to gamma oscillations and precise spatiotemporal firing during memory retrieval in a simulated attractor network. Brain Research. 1536: 68-87. PMID 23939226 DOI: 10.1016/J.Brainres.2013.08.002 |
0.417 |
|
| 2013 |
Lundqvist M, Herman P, Lansner A. Effect of prestimulus alpha power, phase, and synchronization on stimulus detection rates in a biophysical attractor network model. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 33: 11817-24. PMID 23864671 DOI: 10.1523/Jneurosci.5155-12.2013 |
0.317 |
|
| 2013 |
Lundqvist M, Herman P, Palva M, Palva S, Silverstein D, Lansner A. Stimulus detection rate and latency, firing rates and 1-40Hz oscillatory power are modulated by infra-slow fluctuations in a bistable attractor network model. Neuroimage. 83: 458-71. PMID 23851323 DOI: 10.1016/J.Neuroimage.2013.06.080 |
0.445 |
|
| 2013 |
Schain M, Benjaminsson S, Varnäs K, Forsberg A, Halldin C, Lansner A, Farde L, Varrone A. Arterial input function derived from pairwise correlations between PET-image voxels. Journal of Cerebral Blood Flow and Metabolism : Official Journal of the International Society of Cerebral Blood Flow and Metabolism. 33: 1058-65. PMID 23571279 DOI: 10.1038/Jcbfm.2013.47 |
0.756 |
|
| 2013 |
Tully P, Lindén H, Hennig MH, Lansner A. Probabilistic computation underlying sequence learning in a spiking attractor memory network Bmc Neuroscience. 14. DOI: 10.1186/1471-2202-14-S1-P236 |
0.499 |
|
| 2012 |
Benjaminsson S, Lansner A. Nexa: a scalable neural simulator with integrated analysis. Network (Bristol, England). 23: 254-71. PMID 23116128 DOI: 10.3109/0954898X.2012.737087 |
0.813 |
|
| 2012 |
Berthet P, Hellgren-Kotaleski J, Lansner A. Action selection performance of a reconfigurable basal ganglia inspired model with Hebbian-Bayesian Go-NoGo connectivity. Frontiers in Behavioral Neuroscience. 6: 65. PMID 23060764 DOI: 10.3389/Fnbeh.2012.00065 |
0.331 |
|
| 2012 |
Krishnamurthy P, Silberberg G, Lansner A. A cortical attractor network with Martinotti cells driven by facilitating synapses. Plos One. 7: e30752. PMID 22523533 DOI: 10.1371/Journal.Pone.0030752 |
0.67 |
|
| 2012 |
Lundqvist M, Herman P, Lansner A. Variability of spike firing during θ-coupled replay of memories in a simulated attractor network. Brain Research. 1434: 152-61. PMID 21907326 DOI: 10.1016/J.Brainres.2011.07.055 |
0.462 |
|
| 2011 |
Auffarth B, Kaplan B, Lansner A. Map formation in the olfactory bulb by axon guidance of olfactory neurons. Frontiers in Systems Neuroscience. 5: 84. PMID 22013417 DOI: 10.3389/Fnsys.2011.00084 |
0.762 |
|
| 2011 |
Silverstein DN, Lansner A. Is attentional blink a byproduct of neocortical attractors? Frontiers in Computational Neuroscience. 5: 13. PMID 21625630 DOI: 10.3389/Fncom.2011.00013 |
0.402 |
|
| 2011 |
Brüderle D, Petrovici MA, Vogginger B, Ehrlich M, Pfeil T, Millner S, Grübl A, Wendt K, Müller E, Schwartz MO, de Oliveira DH, Jeltsch S, Fieres J, Schilling M, Müller P, ... ... Lansner A, et al. A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems. Biological Cybernetics. 104: 263-96. PMID 21618053 DOI: 10.1007/S00422-011-0435-9 |
0.318 |
|
| 2011 |
Lundqvist M, Herman P, Lansner A. Theta and gamma power increases and alpha/beta power decreases with memory load in an attractor network model. Journal of Cognitive Neuroscience. 23: 3008-20. PMID 21452933 DOI: 10.1162/Jocn_A_00029 |
0.41 |
|
| 2011 |
Silverstein D, Lansner A, Ingvar M, Öhman A. A neural model of human fear pathways based on anatomical and neuroimaging data Bmc Neuroscience. 12. DOI: 10.1186/1471-2202-12-S1-P241 |
0.402 |
|
| 2011 |
Silverstein D, Lansner A. Scaling of a biophysical neocortical attractor model using Parallel NEURON on the Blue Gene /P Bmc Neuroscience. 12. DOI: 10.1186/1471-2202-12-S1-P191 |
0.446 |
|
| 2011 |
Berthet P, Lansner A. An abstract model of the basal ganglia, reward learning and action selection Bmc Neuroscience. 12. DOI: 10.1186/1471-2202-12-S1-P189 |
0.368 |
|
| 2011 |
Benjaminsson S, Herman P, Lansner A. Odor segmentation and identification in an abstract large-scale model of the mammalian olfactory system Bmc Neuroscience. 12. DOI: 10.1186/1471-2202-12-S1-P188 |
0.803 |
|
| 2011 |
Krishnamurthy P, Silberberg G, Lansner A. A cortical attractor network with dynamic synapses Bmc Neuroscience. 12. DOI: 10.1186/1471-2202-12-S1-P187 |
0.676 |
|
| 2011 |
Kaplan B, Benjaminsson S, Lansner A. A large-scale model of the three first stages of the mammalian olfactory system implemented with spiking neurons Bmc Neuroscience. 12. DOI: 10.1186/1471-2202-12-S1-P185 |
0.803 |
|
| 2011 |
Rehn M, Silverstein D, Olmårs J, Lansner A. A hybrid model of the primary visual cortex Bmc Neuroscience. 12. DOI: 10.1186/1471-2202-12-S1-P184 |
0.652 |
|
| 2011 |
Lansner A. Perceptual and memory functions in a cortex-inspired attractor network model Bmc Neuroscience. 12. DOI: 10.1186/1471-2202-12-S1-K2 |
0.493 |
|
| 2011 |
Fonollosa J, Gutierrez-Galvez A, Lansner A, Martinez D, Rospars JP, Beccherelli R, Perera A, Pearce T, Vershure P, Persaud K, Marco S. Biologically inspired computation for chemical sensing Procedia Computer Science. 7: 226-227. DOI: 10.1016/J.Procs.2011.09.066 |
0.302 |
|
| 2010 |
Benjaminsson S, Fransson P, Lansner A. A novel model-free data analysis technique based on clustering in a mutual information space: application to resting-state FMRI. Frontiers in Systems Neuroscience. 4. PMID 20721313 DOI: 10.3389/Fnsys.2010.00034 |
0.779 |
|
| 2010 |
Lundqvist M, Compte A, Lansner A. Bistable, irregular firing and population oscillations in a modular attractor memory network. Plos Computational Biology. 6: e1000803. PMID 20532199 DOI: 10.1371/Journal.Pcbi.1000803 |
0.455 |
|
| 2010 |
Benjaminsson S, Lansner A. Adaptive sensor drift counteraction by a modular neural network Neuroscience Research. 68: e212. DOI: 10.1016/J.Neures.2010.07.2508 |
0.797 |
|
| 2009 |
Kozlov A, Huss M, Lansner A, Kotaleski JH, Grillner S. Simple cellular and network control principles govern complex patterns of motor behavior. Proceedings of the National Academy of Sciences of the United States of America. 106: 20027-32. PMID 19901329 DOI: 10.1073/Pnas.0906722106 |
0.737 |
|
| 2009 |
Sandström M, Lansner A, Hellgren-Kotaleski J, Rospars JP. Modeling the response of a population of olfactory receptor neurons to an odorant. Journal of Computational Neuroscience. 27: 337-55. PMID 19415478 DOI: 10.1007/S10827-009-0147-5 |
0.309 |
|
| 2009 |
Lansner A. Associative memory models: from the cell-assembly theory to biophysically detailed cortex simulations. Trends in Neurosciences. 32: 178-86. PMID 19187979 DOI: 10.1016/J.Tins.2008.12.002 |
0.34 |
|
| 2009 |
Silverstein D, Lansner A. Simulating attentional blink with a neocortical attractor model Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P309 |
0.356 |
|
| 2009 |
Sandström M, Proschinger T, Lansner A. A bulb model implementing fuzzy coding of odor concentration Aip Conference Proceedings. 1137: 159-162. DOI: 10.1063/1.3156496 |
0.532 |
|
| 2009 |
Johansson C, Lansner A. Implementing plastic weights in neural networks using low precision arithmetic Neurocomputing. 72: 968-972. DOI: 10.1016/J.Neucom.2008.04.007 |
0.564 |
|
| 2009 |
Lansner A, Benjaminsson S, Johansson C. From ANN to biomimetic information processing Studies in Computational Intelligence. 188: 33-43. DOI: 10.1007/978-3-642-00176-5_2 |
0.746 |
|
| 2008 |
Djurfeldt M, Ekeberg O, Lansner A. Large-scale modeling - a tool for conquering the complexity of the brain. Frontiers in Neuroinformatics. 2: 1. PMID 18974793 DOI: 10.3389/Neuro.11.001.2008 |
0.758 |
|
| 2008 |
Sandström M, Proschinger T, Lansner A. Fuzzy interval representation of olfactory stimulus concentration in an olfactory glomerulus model Bmc Neuroscience. 9. DOI: 10.1186/1471-2202-9-S1-P123 |
0.579 |
|
| 2008 |
Djurfeldt M, Lundqvist M, Johansson C, Rehn M, Ekeberg OO, Lansner A. Brain-scale simulation of the neocortex on the IBM Blue Gene/L supercomputer Ibm Journal of Research and Development. 52: 31-42. DOI: 10.1147/Rd.521.0031 |
0.801 |
|
| 2007 |
Grillner S, Kozlov A, Dario P, Stefanini C, Menciassi A, Lansner A, Hellgren Kotaleski J. Modeling a vertebrate motor system: pattern generation, steering and control of body orientation. Progress in Brain Research. 165: 221-34. PMID 17925249 DOI: 10.1016/S0079-6123(06)65014-0 |
0.78 |
|
| 2007 |
Brette R, Rudolph M, Carnevale T, Hines M, Beeman D, Bower JM, Diesmann M, Morrison A, Goodman PH, Harris FC, Zirpe M, Natschläger T, Pecevski D, Ermentrout B, Djurfeldt M, ... Lansner A, et al. Simulation of networks of spiking neurons: a review of tools and strategies. Journal of Computational Neuroscience. 23: 349-98. PMID 17629781 DOI: 10.1007/S10827-007-0038-6 |
0.749 |
|
| 2007 |
Johansson C, Lansner A. Imposing biological constraints onto an abstract neocortical attractor network model. Neural Computation. 19: 1871-96. PMID 17521282 DOI: 10.1162/Neco.2007.19.7.1871 |
0.627 |
|
| 2007 |
Huss M, Lansner A, Wallén P, El Manira A, Grillner S, Kotaleski JH. Roles of ionic currents in lamprey CpG neurons: a modeling study. Journal of Neurophysiology. 97: 2696-711. PMID 17287443 DOI: 10.1152/Jn.00528.2006 |
0.807 |
|
| 2007 |
Kozlov AK, Lansner A, Grillner S, Kotaleski JH. A hemicord locomotor network of excitatory interneurons: a simulation study. Biological Cybernetics. 96: 229-43. PMID 17180687 DOI: 10.1007/S00422-006-0132-2 |
0.701 |
|
| 2007 |
Johansson C, Lansner A. Towards cortex sized artificial neural systems. Neural Networks : the Official Journal of the International Neural Network Society. 20: 48-61. PMID 16860539 DOI: 10.1016/J.Neunet.2006.05.029 |
0.617 |
|
| 2007 |
Westermark PO, Kotaleski JH, Björklund A, Grill V, Lansner A. A mathematical model of the mitochondrial NADH shuttles and anaplerosis in the pancreatic beta-cell. American Journal of Physiology. Endocrinology and Metabolism. 292: E373-93. PMID 16849626 DOI: 10.1152/Ajpendo.00589.2005 |
0.472 |
|
| 2007 |
Sandström M, Lansner A, Rospars J. Modelling the population of olfactory receptor neurons Bmc Neuroscience. 8. DOI: 10.1186/1471-2202-8-S2-P156 |
0.62 |
|
| 2007 |
Djurfeldt M, Lansner A. Workshop report: 1st INCF Workshop on Large-scale Modeling of the Nervous System Nature Precedings. 2: 1-1. DOI: 10.1038/Npre.2007.262.1 |
0.729 |
|
| 2007 |
Sandström M, Hellgren Kotaleski J, Lansner A. Scaling effects in a model of the olfactory bulb Neurocomputing. 70: 1802-1807. DOI: 10.1016/J.Neucom.2006.10.062 |
0.8 |
|
| 2007 |
Johansson C, Rehn M, Lansner A. Attractor neural networks with patchy connectivity Esann 2005 Proceedings - 13th European Symposium On Artificial Neural Networks. 429-434. DOI: 10.1016/J.Neucom.2005.12.002 |
0.723 |
|
| 2006 |
Johansson C, Ekeberg O, Lansner A. Clustering of stored memories in an attractor network with local competition. International Journal of Neural Systems. 16: 393-403. PMID 17285686 DOI: 10.1142/S0129065706000809 |
0.683 |
|
| 2006 |
Lundqvist M, Rehn M, Djurfeldt M, Lansner A. Attractor dynamics in a modular network model of neocortex. Network (Bristol, England). 17: 253-76. PMID 17162614 DOI: 10.1080/09548980600774619 |
0.812 |
|
| 2006 |
Lundqvist M, Rehn M, Lansner A. Attractor dynamics in a modular network model of the cerebral cortex Neurocomputing. 69: 1155-1159. DOI: 10.1016/J.Neucom.2005.12.065 |
0.652 |
|
| 2006 |
Sandström M, Hjorth J, Lansner A, Kotaleski JH. The impact of the distribution of isoforms on CaMKII activation Neurocomputing. 69: 1010-1013. DOI: 10.1016/J.Neucom.2005.12.035 |
0.746 |
|
| 2006 |
Johansson C, Lansner A. Attractor memory with self-organizing input Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3853: 265-280. DOI: 10.1007/11613022_22 |
0.573 |
|
| 2005 |
De Schutter E, Ekeberg O, Kotaleski JH, Achard P, Lansner A. Biophysically detailed modelling of microcircuits and beyond. Trends in Neurosciences. 28: 562-9. PMID 16118023 DOI: 10.1016/J.Tins.2005.08.002 |
0.634 |
|
| 2005 |
Yuste R, MacLean JN, Smith J, Lansner A. The cortex as a central pattern generator. Nature Reviews. Neuroscience. 6: 477-83. PMID 15928717 DOI: 10.1038/Nrn1686 |
0.306 |
|
| 2005 |
Çürüklü B, Lansner A. A model of the summation pools within the layer 4 (area 17) Neurocomputing. 65: 167-172. DOI: 10.1016/J.Neucom.2004.10.004 |
0.322 |
|
| 2004 |
Svantesson A, Westermark PO, Kotaleski JH, Gharizadeh B, Lansner A, Nyrén P. A mathematical model of the Pyrosequencing reaction system. Biophysical Chemistry. 110: 129-45. PMID 15223150 DOI: 10.1016/J.Bpc.2004.01.010 |
0.509 |
|
| 2004 |
Rehn M, Lansner A. Sequence memory with dynamical synapses Neurocomputing. 58: 271-278. DOI: 10.1016/J.Neucom.2004.01.055 |
0.605 |
|
| 2004 |
Johansson C, Lansner A. Towards cortex sized attractor ANN Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3141: 63-79. DOI: 10.1007/978-3-540-27835-1_6 |
0.569 |
|
| 2004 |
Johansson C, Lansner A. Towards Cortex Sized Artificial Nervous Systems Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3213: 959-966. |
0.385 |
|
| 2003 |
Sandberg A, Tegnér J, Lansner A. A working memory model based on fast Hebbian learning. Network (Bristol, England). 14: 789-802. PMID 14653503 DOI: 10.1088/0954-898X/14/4/309 |
0.555 |
|
| 2003 |
Westermark PO, Lansner A. A model of phosphofructokinase and glycolytic oscillations in the pancreatic beta-cell. Biophysical Journal. 85: 126-39. PMID 12829470 DOI: 10.1016/S0006-3495(03)74460-9 |
0.506 |
|
| 2003 |
Lansner A, Fransén E, Sandberg A. Cell assembly dynamics in detailed and abstract attractor models of cortical associative memory Theory in Biosciences. 122: 19-36. DOI: 10.1078/1431-7613-00072 |
0.593 |
|
| 2003 |
Kozlov A, Lansner A, Grillner S. Burst dynamics under mixed NMDA and AMPA drive in the models of the lamprey spinal CPG Neurocomputing. 52: 65-71. DOI: 10.1016/S0925-2312(02)00795-6 |
0.632 |
|
| 2003 |
Huss M, Hess D, d'Incamps BL, El Manira A, Lansner A, Kotaleski JH. Role of A-current in lamprey locomotor network neurons Neurocomputing. 52: 295-300. DOI: 10.1016/S0925-2312(02)00784-1 |
0.738 |
|
| 2003 |
Eriksson D, Fransén E, Zilberter Y, Lansner A. Effects of short-term synaptic plasticity in a local microcircuit on cell firing Neurocomputing. 52: 7-12. DOI: 10.1016/S0925-2312(02)00757-9 |
0.301 |
|
| 2002 |
Sandberg A, Lansner A, Petersson KM, Ekeberg O. A Bayesian attractor network with incremental learning. Network (Bristol, England). 13: 179-94. PMID 12061419 DOI: 10.1088/0954-898X/13/2/302 |
0.694 |
|
| 2002 |
Kozlov AK, Ullén F, Fagerstedt P, Aurell E, Lansner A, Grillner S. Mechanisms for lateral turns in lamprey in response to descending unilateral commands: a modeling study. Biological Cybernetics. 86: 1-14. PMID 11918208 DOI: 10.1007/S004220100272 |
0.643 |
|
| 2002 |
Sandberg A, Lansner A. Synaptic depression as an intrinsic driver of reinstatement dynamics in an attractor network Neurocomputing. 44: 615-622. DOI: 10.1016/S0925-2312(02)00448-4 |
0.579 |
|
| 2002 |
Johansson C, Sandberg A, Lansner A. Attractor neural networks with hypercolumns Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2415: 192-197. |
0.635 |
|
| 2001 |
Kozlov A, Kotaleski JH, Aurell E, Grillner S, Lansner A. Modeling of substance P and 5-HT induced synaptic plasticity in the lamprey spinal CPG: consequences for network pattern generation. Journal of Computational Neuroscience. 11: 183-200. PMID 11717534 DOI: 10.1023/A:1012806018730 |
0.652 |
|
| 2001 |
Wahlgren N, Lansner A. Biological evaluation of a Hebbian-Bayesian learning rule Neurocomputing. 38: 433-438. DOI: 10.1016/S0925-2312(01)00370-8 |
0.313 |
|
| 2001 |
Sandberg A, Lansner A, Petersson KM. Selective enhancement of recall through plasticity modulation in an autoassociative memory Neurocomputing. 38: 867-873. DOI: 10.1016/S0925-2312(01)00363-0 |
0.551 |
|
| 2000 |
Sandberg A, Lansner A, Petersson KM, Ekeberg O. A palimpsest memory based on an incremental Bayesian learning rule Neurocomputing. 32: 987-994. DOI: 10.1016/S0925-2312(00)00270-8 |
0.679 |
|
| 2000 |
Kozlov A, Kotaleski JH, Aurell E, Grillner S, Lansner A. Modeling of plasticity of the synaptic connections in the lamprey spinal CPG - Consequences for network behavior Neurocomputing. 32: 441-446. DOI: 10.1016/S0925-2312(00)00197-1 |
0.639 |
|
| 2000 |
Orre R, Lansner A, Bate A, Lindquist M. Bayesian neural networks with confidence estimations applied to data mining Computational Statistics and Data Analysis. 34: 473-493. DOI: 10.1016/S0167-9473(99)00114-0 |
0.769 |
|
| 1999 |
Kotaleski JH, Grillner S, Lansner A. Neural mechanisms potentially contributing to the intersegmental phase lag in lamprey.I. Segmental oscillations dependent on reciprocal inhibition. Biological Cybernetics. 81: 317-30. PMID 10541935 DOI: 10.1007/S004220050565 |
0.674 |
|
| 1999 |
Kotaleski JH, Lansner A, Grillner S. Neural mechanisms potentially contributing to the intersegmental phase lag in lamprey.II. Hemisegmental oscillations produced by mutually coupled excitatory neurons. Biological Cybernetics. 81: 299-315. PMID 10541934 DOI: 10.1007/S004220050564 |
0.665 |
|
| 1999 |
Djurfeldt M, Sandberg A, Ekeberg O, Lansner A. See - A framework for simulation of biologically detailed and artificial neural networks and systems Neurocomputing. 26: 997-1003. DOI: 10.1016/S0925-2312(99)00096-X |
0.802 |
|
| 1999 |
Kotaleski JH, Tegnér J, Grillner S, Lansner A. Control of burst proportion and frequency range by drive-dependent modulation of adaptation Neurocomputing. 26: 185-191. DOI: 10.1016/S0925-2312(99)00080-6 |
0.645 |
|
| 1998 |
Lansner A, Kotaleski JH, Grillner S. Modeling of the spinal neuronal circuitry underlying locomotion in a lower vertebrate. Annals of the New York Academy of Sciences. 860: 239-49. PMID 9928316 DOI: 10.1111/J.1749-6632.1998.Tb09053.X |
0.699 |
|
| 1998 |
Fransén E, Lansner A. A model of cortical associative memory based on a horizontal network of connected columns. Network (Bristol, England). 9: 235-64. PMID 9861988 DOI: 10.1088/0954-898X/9/2/006 |
0.497 |
|
| 1998 |
Ullström M, Kotaleski JH, Tegnér J, Aurell E, Grillner S, Lansner A. Activity-dependent modulation of adaptation produces a constant burst proportion in a model of the lamprey spinal locomotor generator. Biological Cybernetics. 79: 1-14. PMID 9742673 DOI: 10.1007/S004220050453 |
0.671 |
|
| 1998 |
Bate A, Lindquist M, Edwards IR, Olsson S, Orre R, Lansner A, De Freitas RM. A Bayesian neural network method for adverse drug reaction signal generation. European Journal of Clinical Pharmacology. 54: 315-21. PMID 9696956 DOI: 10.1007/S002280050466 |
0.76 |
|
| 1998 |
Grillner S, Ekeberg, El Manira A, Lansner A, Parker D, Tegnér J, Wallén P. Intrinsic function of a neuronal network - a vertebrate central pattern generator. Brain Research. Brain Research Reviews. 26: 184-97. PMID 9651523 DOI: 10.1016/S0165-0173(98)00002-2 |
0.766 |
|
| 1998 |
Tegnér J, Lansner A, Grillner S. Modulation of burst frequency by calcium-dependent potassium channels in the lamprey locomotor system: dependence of the activity level. Journal of Computational Neuroscience. 5: 121-40. PMID 9617663 DOI: 10.1023/A:1008897031013 |
0.683 |
|
| 1998 |
Li G, Lansner A, Svensson B. Self-orienting with on-line learning of environmental features Adaptive Behavior. 6: 535-566. DOI: 10.1177/105971239800600308 |
0.303 |
|
| 1997 |
Tegnér J, Hellgren-Kotaleski J, Lansner A, Grillner S. Low-voltage-activated calcium channels in the lamprey locomotor network: simulation and experiment. Journal of Neurophysiology. 77: 1795-812. PMID 9114237 DOI: 10.1152/Jn.1997.77.4.1795 |
0.646 |
|
| 1997 |
Wadden T, Hellgren J, Lansner A, Grillner S. Intersegmental coordination in the lamprey: Simulations using a network model without segmental boundaries Biological Cybernetics. 76: 1-9. DOI: 10.1007/S004220050316 |
0.635 |
|
| 1996 |
Lansner A, Holst A. A higher order Bayesian neural network with spiking units. International Journal of Neural Systems. 7: 115-28. PMID 8823623 DOI: 10.1142/S0129065796000816 |
0.432 |
|
| 1995 |
Grillner S, Deliagina T, Ekeberg O, el Manira A, Hill RH, Lansner A, Orlovsky GN, Wallén P. Neural networks that co-ordinate locomotion and body orientation in lamprey. Trends in Neurosciences. 18: 270-9. PMID 7571002 DOI: 10.1016/0166-2236(95)80008-P |
0.811 |
|
| 1995 |
Ekeberg Ö, Grillner S, Lansner A. The Neural Control of Fish Swimming Studied Through Numerical Simulations Adaptive Behavior. 3: 363-384. DOI: 10.1177/105971239500300402 |
0.736 |
|
| 1995 |
Fransén E, Lansner A. Low spiking rates in a population of mutually exciting pyramidal cells Network: Computation in Neural Systems. 6: 271-288. DOI: 10.1088/0954-898X_6_2_008 |
0.461 |
|
| 1995 |
Lansner A, Fransén E. Distributed cell assemblies and detailed cell models Behavioral and Brain Sciences. 18: 637-638. DOI: 10.1017/S0140525X00040292 |
0.411 |
|
| 1994 |
Lansner A, Ekeberg O. Neuronal network models of motor generation and control. Current Opinion in Neurobiology. 4: 903-8. PMID 7888775 DOI: 10.1016/0959-4388(94)90140-6 |
0.63 |
|
| 1993 |
Holst A, Lansner A. A flexible and fault tolerant query-reply system based on a Bayesian neural network. International Journal of Neural Systems. 4: 257-67. PMID 8293231 DOI: 10.1142/S0129065793000213 |
0.322 |
|
| 1993 |
Tråvén HG, Brodin L, Lansner A, Ekeberg O, Wallén P, Grillner S. Computer simulations of NMDA and non-NMDA receptor-mediated synaptic drive: sensory and supraspinal modulation of neurons and small networks. Journal of Neurophysiology. 70: 695-709. PMID 8105036 DOI: 10.1152/Jn.1993.70.2.695 |
0.735 |
|
| 1993 |
HAMMARLUND P, LEVIN B, LANSNER A. BIOLOGICALLY REALISTIC AND ARTIFICIAL NEURAL NETWORK SIMULATORS ON THE CONNECTION MACHINE International Journal of Modern Physics C. 4: 49-63. DOI: 10.1142/S0129183193000070 |
0.44 |
|
| 1992 |
Hellgren J, Grillner S, Lansner A. Computer simulation of the segmental neural network generating locomotion in lamprey by using populations of network interneurons. Biological Cybernetics. 68: 1-13. PMID 1486127 DOI: 10.1007/Bf00203132 |
0.681 |
|
| 1992 |
Wallén P, Ekeberg O, Lansner A, Brodin L, Tråvén H, Grillner S. A computer-based model for realistic simulations of neural networks. II. The segmental network generating locomotor rhythmicity in the lamprey. Journal of Neurophysiology. 68: 1939-50. PMID 1283406 DOI: 10.1152/Jn.1992.68.6.1939 |
0.762 |
|
| 1991 |
Ekeberg O, Wallén P, Lansner A, Tråvén H, Brodin L, Grillner S. A computer based model for realistic simulations of neural networks. I. The single neuron and synaptic interaction. Biological Cybernetics. 65: 81-90. PMID 1912005 DOI: 10.1007/Bf00202382 |
0.771 |
|
| 1991 |
Brodin L, Tråvén HG, Lansner A, Wallén P, Ekeberg O, Grillner S. Computer simulations of N-methyl-D-aspartate receptor-induced membrane properties in a neuron model. Journal of Neurophysiology. 66: 473-84. PMID 1723094 DOI: 10.1152/Jn.1991.66.2.473 |
0.712 |
|
| 1991 |
Grillner S, Wallén P, Brodin L, Lansner A. Neuronal network generating locomotor behavior in lamprey: circuitry, transmitters, membrane properties, and simulation. Annual Review of Neuroscience. 14: 169-99. PMID 1674412 DOI: 10.1146/Annurev.Ne.14.030191.001125 |
0.644 |
|
| 1989 |
Wallén P, Christenson J, Brodin L, Hill R, Lansner A, Grillner S. Mechanisms underlying the serotonergic modulation of the spinal circuitry for locomotion in lamprey. Progress in Brain Research. 80: 321-7; discussion 31. PMID 2699371 DOI: 10.1016/S0079-6123(08)62227-X |
0.602 |
|
| 1989 |
Lansner A, Ekeberg Ö. A ONE-LAYER FEEDBACK ARTIFICIAL NEURAL NETWORK WITH A BAYESIAN LEARNING RULE International Journal of Neural Systems. 1: 77-87. DOI: 10.1142/S0129065789000499 |
0.639 |
|
| 1988 |
Grillner S, Buchanan JT, Lansner A. Simulation of the segmental burst generating network for locomotion in lamprey. Neuroscience Letters. 89: 31-5. PMID 3399139 DOI: 10.1016/0304-3940(88)90476-4 |
0.679 |
|
| 1985 |
Lansner A, Ekeberg O. Reliability and speed of recall in an associative network. Ieee Transactions On Pattern Analysis and Machine Intelligence. 7: 490-8. PMID 21869287 DOI: 10.1109/Tpami.1985.4767688 |
0.581 |
|
| 1970 |
Lansner A, Benjaminsson S, Fransson P. A novel model-free fMRI data analysis technique based on clustering in a mutual information space Frontiers in Neuroinformatics. DOI: 10.3389/Conf.Neuro.11.2009.08.028 |
0.76 |
|
| Low-probability matches (unlikely to be authored by this person) |
| 1994 |
Lansner A, Liljenström H. Computer models of the brain--how far can they take us? Journal of Theoretical Biology. 171: 61-73. PMID 7844995 DOI: 10.1006/Jtbi.1994.1212 |
0.292 |
|
| 2021 |
Wang D, Xu J, Stathis D, Zhang L, Li F, Lansner A, Hemani A, Yang Y, Herman P, Zou Z. Mapping the BCPNN Learning Rule to a Memristor Model. Frontiers in Neuroscience. 15: 750458. PMID 34955716 DOI: 10.3389/fnins.2021.750458 |
0.29 |
|
| 2018 |
Iatropoulos G, Herman P, Lansner A, Karlgren J, Larsson M, Olofsson JK. The language of smell: Connecting linguistic and psychophysical properties of odor descriptors. Cognition. 178: 37-49. PMID 29763790 DOI: 10.1016/J.Cognition.2018.05.007 |
0.285 |
|
| 2014 |
Farahini N, Hemani A, Lansner A, Clermidy F, Svensson C. A scalable custom simulation machine for the Bayesian Confidence Propagation Neural Network model of the brain Proceedings of the Asia and South Pacific Design Automation Conference, Asp-Dac. 578-585. DOI: 10.1109/ASPDAC.2014.6742953 |
0.285 |
|
| 1984 |
Wallen P, Lansner A. Do the motoneurones constitute a part of the spinal network generating the swimming rhythm in the lamprey? Journal of Experimental Biology. 493-497. |
0.232 |
|
| 2009 |
Çürüklü B, Lansner A. Configuration-specific facilitation phenomena explained by layer 2/3 summation pools in V1 Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P177 |
0.215 |
|
| 2000 |
Björklund A, Lansner A, Grill VE. Glucose-induced [Ca2+]i abnormalities in human pancreatic islets: important role of overstimulation. Diabetes. 49: 1840-8. PMID 11078450 DOI: 10.2337/Diabetes.49.11.1840 |
0.199 |
|
| 1992 |
Lansner A, Fransen E. Modelling hebbian cell assemblies comprised of cortical neurons Network: Computation in Neural Systems. 3: 105-119. DOI: 10.1088/0954-898X_3_2_002 |
0.197 |
|
| 2023 |
Wang D, Xu J, Li F, Zhang L, Cao C, Stathis D, Lansner A, Hemani A, Zheng LR, Zou Z. A Memristor-Based Learning Engine for Synaptic Trace-Based Online Learning. Ieee Transactions On Biomedical Circuits and Systems. PMID 37390002 DOI: 10.1109/TBCAS.2023.3291021 |
0.18 |
|
| 2015 |
Eriksson J, Vogel EK, Lansner A, Bergström F, Nyberg L. Neurocognitive Architecture of Working Memory. Neuron. 88: 33-46. PMID 26447571 DOI: 10.1016/J.Neuron.2015.09.020 |
0.18 |
|
| 2014 |
Lansner A, Hemani A, Farahini N. Spiking brain models: Computation, memory and communication constraints for custom hardware implementation Proceedings of the Asia and South Pacific Design Automation Conference, Asp-Dac. 556-562. DOI: 10.1109/ASPDAC.2014.6742950 |
0.173 |
|
| 1999 |
Li G, Svensson B, Lansner A. Neuro-computational model for mobile robot self-orientation in partially known environments Doktorsavhandlingar Vid Chalmers Tekniska Hogskola. 115-124. |
0.086 |
|
| 2013 |
Marco S, Gutiérrez-Gálvez A, Lansner A, Martinez D, Rospars JP, Beccherelli R, Perera A, Pearce T, Vershure P, Persaud K. Biologically inspired large scale chemical sensor arrays and embedded data processing Proceedings of Spie - the International Society For Optical Engineering. 8763. DOI: 10.1117/12.2018402 |
0.077 |
|
| 1986 |
Eklundh JO, Lansner A, Wessblad R. CLASSIFICATION OF MULTISPECTRAL IMAGES USING ASSOCIATIVE NETS Proceedings - International Conference On Pattern Recognition. 1240-1243. |
0.028 |
|
| Hide low-probability matches. |
