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2020 – today
- 2021
[j11]Davide Zambrano, Pieter R. Roelfsema, Sander M. Bohté:
Learning continuous-time working memory tasks with on-policy neural reinforcement learning. Neurocomputing 461: 635-656 (2021)- [j10]Ulf H. Schnabel, Tobias Van der Bijl, Pieter R. Roelfsema, Jeannette A. M. Lorteije:
A Direct Comparison of Spatial Attention and Stimulus-Response Compatibility between Mice and Humans. J. Cogn. Neurosci. 33(5): 771-783 (2021) - [j9]Wouter Kruijne, Sander M. Bohté, Pieter R. Roelfsema, Christian N. L. Olivers
:
Flexible Working Memory Through Selective Gating and Attentional Tagging. Neural Comput. 33(1): 1-40 (2021) - 2020
- [c6]Isabella Pozzi, Sander M. Bohté, Pieter R. Roelfsema:
Attention-Gated Brain Propagation: How the brain can implement reward-based error backpropagation. NeurIPS 2020
2010 – 2019
- 2019
- [j8]Matthew W. Self, Timo van Kerkoerle, Rainer Goebel, Pieter R. Roelfsema:
Benchmarking laminar fMRI: Neuronal spiking and synaptic activity during top-down and bottom-up processing in the different layers of cortex. NeuroImage 197: 806-817 (2019) - 2018
- [i2]Isabella Pozzi, Sander M. Bohté, Pieter R. Roelfsema:
A Biologically Plausible Learning Rule for Deep Learning in the Brain. CoRR abs/1811.01768 (2018) - 2015
- [j7]Jaldert O. Rombouts, Sander M. Bohté, Pieter R. Roelfsema:
How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks. PLoS Comput. Biol. 11(3) (2015) - [j6]Tobias Brosch, Heiko Neumann, Pieter R. Roelfsema:
Reinforcement Learning of Linking and Tracing Contours in Recurrent Neural Networks. PLoS Comput. Biol. 11(10) (2015) - [c5]Davide Zambrano, Pieter R. Roelfsema, Sander M. Bohté:
Continuous-time on-policy neural Reinforcement Learning of working memory tasks. IJCNN 2015: 1-8 - 2014
- [c4]Jaldert O. Rombouts, Pieter R. Roelfsema, Sander M. Bohté:
Learning resets of neural working memory. ESANN 2014 - 2012
- [c3]Jaldert O. Rombouts, Arjen van Ooyen, Pieter R. Roelfsema, Sander M. Bohté:
Biologically Plausible Multi-dimensional Reinforcement Learning in Neural Networks. ICANN (1) 2012: 443-450 - [c2]Jaldert O. Rombouts, Sander M. Bohté, Pieter R. Roelfsema:
Neurally Plausible Reinforcement Learning of Working Memory Tasks. NIPS 2012: 1880-1888 - [i1]Jaldert O. Rombouts, Pieter R. Roelfsema, Sander M. Bohté:
Learning to Recall. ERCIM News 2012(91) (2012) - 2011
- [c1]Paolo Dario, Paul F. M. J. Verschure, Tony J. Prescott, Gordon Cheng, Giulio Sandini, Roberto Cingolani, Rüdiger Dillmann, Dario Floreano, Christophe Leroux, Sheila MacNeil, Pieter R. Roelfsema, Xenophon Verykios, Antonio Bicchi, Chris Melhuish, Alin Albu-Schäffer:
Robot Companions for Citizens. FET 2011: 47-51 - 2010
- [j5]Ariel Zylberberg, Diego Fernández Slezak, Pieter R. Roelfsema, Stanislas Dehaene, Mariano Sigman:
The Brain's Router: A Cortical Network Model of Serial Processing in the Primate Brain. PLoS Comput. Biol. 6(4) (2010)
2000 – 2009
- 2009
- [j4]Judith C. Peters, Rainer Goebel, Pieter R. Roelfsema:
Remembered but Unused: The Accessory Items in Working Memory that Do Not Guide Attention. J. Cogn. Neurosci. 21(6): 1081-1091 (2009) - 2005
- [j3]Pieter R. Roelfsema, Arjen van Ooyen:
Attention-Gated Reinforcement Learning of Internal Representations for Classification. Neural Comput. 17(10): 2176-2214 (2005) - 2000
- [j2]Sander M. Bohté, Henk Spekreijse, Pieter R. Roelfsema:
The Effects of Pair-wise and Higher-order Correlations on the Firing Rate of a Postsynaptic Neuron. Neural Comput. 12(1): 153-179 (2000)
1990 – 1999
- 1995
- [j1]Peter König, Andreas K. Engel, Pieter R. Roelfsema, Wolf Singer:
How precise is neuronal synchronization? Neural Comput. 7(3): 469-485 (1995)
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