Journal articles on the topic 'Temporal Hebbian learning'
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Rao, Rajesh P. N., and Terrence J. Sejnowski. "Spike-Timing-Dependent Hebbian Plasticity as Temporal Difference Learning." Neural Computation 13, no. 10 (2001): 2221–37. http://dx.doi.org/10.1162/089976601750541787.
Full textCho, Myoung Won. "Temporal Hebbian plasticity designed for efficient competitive learning." Journal of the Korean Physical Society 64, no. 8 (2014): 1213–19. http://dx.doi.org/10.3938/jkps.64.1213.
Full textTully, Philip J., Henrik Lindén, Matthias H. Hennig, and Anders Lansner. "Spike-Based Bayesian-Hebbian Learning of Temporal Sequences." PLOS Computational Biology 12, no. 5 (2016): e1004954. http://dx.doi.org/10.1371/journal.pcbi.1004954.
Full textGirolami, Mark, and Colin Fyfe. "A temporal model of linear anti-Hebbian learning." Neural Processing Letters 4, no. 3 (1996): 139–48. http://dx.doi.org/10.1007/bf00426022.
Full textZenke, Friedemann, Wulfram Gerstner, and Surya Ganguli. "The temporal paradox of Hebbian learning and homeostatic plasticity." Current Opinion in Neurobiology 43 (April 2017): 166–76. http://dx.doi.org/10.1016/j.conb.2017.03.015.
Full textLee, Yun-Parn. "Multidimensional Hebbian Learning With Temporal Coding in Neocognitron Visual Recognition." IEEE Transactions on Systems, Man, and Cybernetics: Systems 47, no. 12 (2017): 3386–96. http://dx.doi.org/10.1109/tsmc.2016.2599200.
Full textKolodziejski, Christoph, Bernd Porr, and Florentin Wörgötter. "On the Asymptotic Equivalence Between Differential Hebbian and Temporal Difference Learning." Neural Computation 21, no. 4 (2009): 1173–202. http://dx.doi.org/10.1162/neco.2008.04-08-750.
Full textEl-Laithy, Karim, and Martin Bogdan. "A Reinforcement Learning Framework for Spiking Networks with Dynamic Synapses." Computational Intelligence and Neuroscience 2011 (2011): 1–12. http://dx.doi.org/10.1155/2011/869348.
Full textMitchison, Graeme. "Removing Time Variation with the Anti-Hebbian Differential Synapse." Neural Computation 3, no. 3 (1991): 312–20. http://dx.doi.org/10.1162/neco.1991.3.3.312.
Full textKempter, Richard, Wulfram Gerstner, and J. Leo van Hemmen. "Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning." Neural Computation 13, no. 12 (2001): 2709–41. http://dx.doi.org/10.1162/089976601317098501.
Full textStone, James V. "Learning Perceptually Salient Visual Parameters Using Spatiotemporal Smoothness Constraints." Neural Computation 8, no. 7 (1996): 1463–92. http://dx.doi.org/10.1162/neco.1996.8.7.1463.
Full textBush, Daniel, Andrew Philippides, Phil Husbands, and Michael O'Shea. "Reconciling the STDP and BCM Models of Synaptic Plasticity in a Spiking Recurrent Neural Network." Neural Computation 22, no. 8 (2010): 2059–85. http://dx.doi.org/10.1162/neco_a_00003-bush.
Full textNguyen, Tien, Khoa Pham, and Kyeong-Sik Min. "Memristor-CMOS Hybrid Circuit for Temporal-Pooling of Sensory and Hippocampal Responses of Cortical Neurons." Materials 12, no. 6 (2019): 875. http://dx.doi.org/10.3390/ma12060875.
Full textShigematsu, Yukifumi, Hiroshi Okamoto, Kazuhisa Ichikawa, and Gen Matsumoto. "Temporal Event Association and Output-Dependent Learning: A Proposed Scheme of Neural Molecular Connections." Journal of Advanced Computational Intelligence and Intelligent Informatics 3, no. 4 (1999): 234–44. http://dx.doi.org/10.20965/jaciii.1999.p0234.
Full textGillett, Maxwell, Ulises Pereira, and Nicolas Brunel. "Characteristics of sequential activity in networks with temporally asymmetric Hebbian learning." Proceedings of the National Academy of Sciences 117, no. 47 (2020): 29948–58. http://dx.doi.org/10.1073/pnas.1918674117.
Full textBrunel, Nicolas. "Hebbian Learning of Context in Recurrent Neural Networks." Neural Computation 8, no. 8 (1996): 1677–710. http://dx.doi.org/10.1162/neco.1996.8.8.1677.
Full textStone, James V. "A Canonical Microfunction for Learning Perceptual Invariances." Perception 25, no. 2 (1996): 207–20. http://dx.doi.org/10.1068/p250207.
Full textBARRETO, GUILHERME DE A., and ALUIZIO F. R. ARAÚJO. "Unsupervised Learning and Recall of Temporal Sequences: An Application to Robotics." International Journal of Neural Systems 09, no. 03 (1999): 235–42. http://dx.doi.org/10.1142/s012906579900023x.
Full textSchulz, Reiner, and James A. Reggia. "Temporally Asymmetric Learning Supports Sequence Processing in Multi-Winner Self-Organizing Maps." Neural Computation 16, no. 3 (2004): 535–61. http://dx.doi.org/10.1162/089976604772744901.
Full textPorr, Bernd, and Florentin Wörgötter. "Strongly Improved Stability and Faster Convergence of Temporal Sequence Learning by Using Input Correlations Only." Neural Computation 18, no. 6 (2006): 1380–412. http://dx.doi.org/10.1162/neco.2006.18.6.1380.
Full textWallis, Guy, and Roland Baddeley. "Optimal, Unsupervised Learning in Invariant Object Recognition." Neural Computation 9, no. 4 (1997): 883–94. http://dx.doi.org/10.1162/neco.1997.9.4.883.
Full textDE A. BARRETO, GUILHERME, and ALUIZIO F. R. ARAÚJO. "UNSUPERVISED LEARNING AND TEMPORAL CONTEXT TO RECALL COMPLEX ROBOT TRAJECTORIES." International Journal of Neural Systems 11, no. 01 (2001): 11–22. http://dx.doi.org/10.1142/s0129065701000461.
Full textKAWATA, SOTARO, and AKIRA HIROSE. "FREQUENCY-MULTIPLEXING ABILITY OF COMPLEX-VALUED HEBBIAN LEARNING IN LOGIC GATES." International Journal of Neural Systems 18, no. 02 (2008): 173–84. http://dx.doi.org/10.1142/s0129065708001488.
Full textLobov, Sergey A., Andrey V. Chernyshov, Nadia P. Krilova, Maxim O. Shamshin, and Victor B. Kazantsev. "Competitive Learning in a Spiking Neural Network: Towards an Intelligent Pattern Classifier." Sensors 20, no. 2 (2020): 500. http://dx.doi.org/10.3390/s20020500.
Full textZappacosta, Stefano, Francesco Mannella, Marco Mirolli, and Gianluca Baldassarre. "General differential Hebbian learning: Capturing temporal relations between events in neural networks and the brain." PLOS Computational Biology 14, no. 8 (2018): e1006227. http://dx.doi.org/10.1371/journal.pcbi.1006227.
Full textSaudargiene, Ausra, Bernd Porr, and Florentin Wörgötter. "How the Shape of Pre- and Postsynaptic Signals Can Influence STDP: A Biophysical Model." Neural Computation 16, no. 3 (2004): 595–625. http://dx.doi.org/10.1162/089976604772744929.
Full textCui, Yuwei, Subutai Ahmad, and Jeff Hawkins. "Continuous Online Sequence Learning with an Unsupervised Neural Network Model." Neural Computation 28, no. 11 (2016): 2474–504. http://dx.doi.org/10.1162/neco_a_00893.
Full textSenn, Walter, Martin Schneider, and Berthold Ruf. "Activity-Dependent Development of Axonal and Dendritic Delays, or, Why Synaptic Transmission Should Be Unreliable." Neural Computation 14, no. 3 (2002): 583–619. http://dx.doi.org/10.1162/089976602317250915.
Full textWörgötter, Florentin, and Bernd Porr. "Temporal Sequence Learning, Prediction, and Control: A Review of Different Models and Their Relation to Biological Mechanisms." Neural Computation 17, no. 2 (2005): 245–319. http://dx.doi.org/10.1162/0899766053011555.
Full textTreur, Jan. "Relating Emerging Adaptive Network Behavior to Network Structure: A Declarative Network Analysis Perspective." Vietnam Journal of Computer Science 08, no. 01 (2020): 39–92. http://dx.doi.org/10.1142/s2196888821500020.
Full textBodyanskiy, Yevgeniy, and Artem Dolotov. "A Multilayered Self-Learning Spiking Neural Network and its Learning Algorithm Based on ‘Winner-Takes-More’ Rule in Hierarchical Clustering." Scientific Journal of Riga Technical University. Computer Sciences 40, no. 1 (2009): 66–74. http://dx.doi.org/10.2478/v10143-010-0009-7.
Full textBELATRECHE, AMMAR, LIAM P. MAGUIRE, MARTIN MCGINNITY, and QING XIANG WU. "EVOLUTIONARY DESIGN OF SPIKING NEURAL NETWORKS." New Mathematics and Natural Computation 02, no. 03 (2006): 237–53. http://dx.doi.org/10.1142/s179300570600049x.
Full textBoerlin, Martin, Tobi Delbruck, and Kynan Eng. "Getting to Know Your Neighbors: Unsupervised Learning of Topography from Real-World, Event-Based Input." Neural Computation 21, no. 1 (2009): 216–38. http://dx.doi.org/10.1162/neco.2009.06-07-554.
Full textJames, Logan S., and Jon T. Sakata. "Vocal motor changes beyond the sensitive period for song plasticity." Journal of Neurophysiology 112, no. 9 (2014): 2040–52. http://dx.doi.org/10.1152/jn.00217.2014.
Full textWagatsuma, Hiroaki, and Yoko Yamaguchi. "Cognitive Map Formation Through Sequence Encoding by Theta Phase Precession." Neural Computation 16, no. 12 (2004): 2665–97. http://dx.doi.org/10.1162/0899766042321742.
Full textO'Reilly, Randall C., and Mark H. Johnson. "Object Recognition and Sensitive Periods: A Computational Analysis of Visual Imprinting." Neural Computation 6, no. 3 (1994): 357–89. http://dx.doi.org/10.1162/neco.1994.6.3.357.
Full textPham, D. T., M. S. Packianather, and E. Y. A. Charles. "Control chart pattern clustering using a new self-organizing spiking neural network." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 222, no. 10 (2008): 1201–11. http://dx.doi.org/10.1243/09544054jem1054.
Full textRolls, E. T., L. Franco, and S. M. Stringer. "The Perirhinal Cortex and Long-Term Familiarity Memory." Quarterly Journal of Experimental Psychology Section B 58, no. 3-4b (2005): 234–45. http://dx.doi.org/10.1080/02724990444000122.
Full textBuonomano, D. V., and M. M. Merzenich. "Associative synaptic plasticity in hippocampal CA1 neurons is not sensitive to unpaired presynaptic activity." Journal of Neurophysiology 76, no. 1 (1996): 631–36. http://dx.doi.org/10.1152/jn.1996.76.1.631.
Full textRolls, Edmund T., and T. Milward. "A Model of Invariant Object Recognition in the Visual System: Learning Rules, Activation Functions, Lateral Inhibition, and Information-Based Performance Measures." Neural Computation 12, no. 11 (2000): 2547–72. http://dx.doi.org/10.1162/089976600300014845.
Full textCARTLING, BO. "GENERATION OF ASSOCIATIVE PROCESSES IN A NEURAL NETWORK WITH REALISTIC FEATURES OF ARCHITECTURE AND UNITS." International Journal of Neural Systems 05, no. 03 (1994): 181–94. http://dx.doi.org/10.1142/s0129065794000207.
Full textStein, Barry E., Liping Yu, Jinghong Xu, and Benjamin A. Rowland. "Plasticity in the acquisition of multisensory integration capabilities in superior colliculus." Seeing and Perceiving 25 (2012): 133. http://dx.doi.org/10.1163/187847612x647658.
Full textSong, Sen, and L. F. Abbott. "Temporally asymmetric Hebbian learning and neuronal response variability." Neurocomputing 32-33 (June 2000): 523–28. http://dx.doi.org/10.1016/s0925-2312(00)00208-3.
Full textSuri, Roland E., and Terrence J. Sejnowski. "Spike propagation synchronized by temporally asymmetric Hebbian learning." Biological Cybernetics 87, no. 5-6 (2002): 440–45. http://dx.doi.org/10.1007/s00422-002-0355-9.
Full textGütig, R., R. Aharonov, S. Rotter, and Haim Sompolinsky. "Learning Input Correlations through Nonlinear Temporally Asymmetric Hebbian Plasticity." Journal of Neuroscience 23, no. 9 (2003): 3697–714. http://dx.doi.org/10.1523/jneurosci.23-09-03697.2003.
Full textMatsumoto, Narihisa, and Masato Okada. "Self-Regulation Mechanism of Temporally Asymmetric Hebbian Plasticity." Neural Computation 14, no. 12 (2002): 2883–902. http://dx.doi.org/10.1162/089976602760805322.
Full textWallenstein, Gene V., and Michael E. Hasselmo. "GABAergic Modulation of Hippocampal Population Activity: Sequence Learning, Place Field Development, and the Phase Precession Effect." Journal of Neurophysiology 78, no. 1 (1997): 393–408. http://dx.doi.org/10.1152/jn.1997.78.1.393.
Full textYANG, ZHIJUN, KATHERINE L. CAMERON, ALAN F. MURRAY, and VASIN BOONSOBHAK. "AN ADAPTIVE VISUAL NEURONAL MODEL IMPLEMENTING COMPETITIVE, TEMPORALLY ASYMMETRIC HEBBIAN LEARNING." International Journal of Neural Systems 16, no. 03 (2006): 151–62. http://dx.doi.org/10.1142/s0129065706000573.
Full textPulvermüller, Friedemann. "Words in the brain's language." Behavioral and Brain Sciences 22, no. 2 (1999): 253–79. http://dx.doi.org/10.1017/s0140525x9900182x.
Full textHowe, Michael, and Risto Miikkulainen. "Hebbian learning and temporary storage in the convergence-zone model of episodic memory." Neurocomputing 32-33 (June 2000): 817–21. http://dx.doi.org/10.1016/s0925-2312(00)00248-4.
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