How precise is neuronal synchronization? - Peter König; Andreas K. Engel; Pieter R. Roelfsema; Wolf Singer (Neural Comput., 1995)

The Effects of Pair-wise and Higher-order Correlations on the Firing Rate of a Postsynaptic Neuron. - Sander M. Bohté; Henk Spekreijse; Pieter R. Roelfsema (Neural Comput., 2000)

Attention-Gated Reinforcement Learning of Internal Representations for Classification. - Pieter R. Roelfsema; Arjen van Ooyen (Neural Comput., 2005)

Remembered but Unused: The Accessory Items in Working Memory that Do Not Guide Attention. - Judith C. Peters; Rainer Goebel; Pieter R. Roelfsema (J. Cogn. Neurosci., 2009)

The Brain's Router: A Cortical Network Model of Serial Processing in the Primate Brain. - Ariel Zylberberg; Diego Fernández Slezak; Pieter R. Roelfsema; Stanislas Dehaene; Mariano Sigman (PLoS Comput. Biol., 2010)

Robot Companions for Citizens. - 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; et al. (FET, 2011)

Biologically Plausible Multi-dimensional Reinforcement Learning in Neural Networks. - Jaldert O. Rombouts; Arjen van Ooyen; Pieter R. Roelfsema; Sander M. Bohté (ICANN (1), 2012)

Neurally Plausible Reinforcement Learning of Working Memory Tasks. - Jaldert O. Rombouts; Sander M. Bohté; Pieter R. Roelfsema (NIPS, 2012)

Learning to Recall. - Jaldert O. Rombouts; Pieter R. Roelfsema; Sander M. Bohté (ERCIM News, 2012)

Learning resets of neural working memory. - Jaldert O. Rombouts; Pieter R. Roelfsema; Sander M. Bohté (ESANN, 2014)

Continuous-time on-policy neural Reinforcement Learning of working memory tasks. - Davide Zambrano; Pieter R. Roelfsema; Sander M. Bohté (IJCNN, 2015)

Reinforcement Learning of Linking and Tracing Contours in Recurrent Neural Networks. - Tobias Brosch; Heiko Neumann; Pieter R. Roelfsema (PLoS Comput. Biol., 2015)

How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks. - Jaldert O. Rombouts; Sander M. Bohté; Pieter R. Roelfsema (PLoS Comput. Biol., 2015)

A Biologically Plausible Learning Rule for Deep Learning in the Brain. - Isabella Pozzi; Sander M. Bohté; Pieter R. Roelfsema (CoRR, 2018)

Benchmarking laminar fMRI: Neuronal spiking and synaptic activity during top-down and bottom-up processing in the different layers of cortex. - Matthew W. Self; Timo van Kerkoerle; Rainer Goebel; Pieter R. Roelfsema (NeuroImage, 2019)

Attention-Gated Brain Propagation: How the brain can implement reward-based error backpropagation. - Isabella Pozzi; Sander M. Bohté; Pieter R. Roelfsema (NeurIPS, 2020)

Learning continuous-time working memory tasks with on-policy neural reinforcement learning. - Davide Zambrano; Pieter R. Roelfsema; Sander M. Bohté (Neurocomputing, 2021)

A Direct Comparison of Spatial Attention and Stimulus-Response Compatibility between Mice and Humans. - Ulf H. Schnabel; Tobias Van der Bijl; Pieter R. Roelfsema; Jeannette A. M. Lorteije (J. Cogn. Neurosci., 2021)

Flexible Working Memory Through Selective Gating and Attentional Tagging. - Wouter Kruijne; Sander M. Bohté; Pieter R. Roelfsema; Christian N. L. Olivers (Neural Comput., 2021)

MonkeySee: Space-time-resolved reconstructions of natural images from macaque multi-unit activity. - Lynn Le; Paolo Papale; Katja Seeliger; Antonio Lozano; Thirza Dado; Feng Wang; Pieter R. Roelfsema; Marcel A. J. van Gerven; Yagmur Güçlütürk; Umut Güçlü (NeurIPS, 2024)

Brain2GAN: Feature-disentangled neural encoding and decoding of visual perception in the primate brain. - Thirza Dado; Paolo Papale; Antonio Lozano; Lynn Le; Feng Wang; Marcel van Gerven; Pieter R. Roelfsema; Yagmur Güçlütürk; Umut Güçlü (PLoS Comput. Biol., 2024)

Recurrent neural networks that learn multi-step visual routines with reinforcement learning. - Sami Mollard; Catherine Wacongne; Sander M. Bohté; Pieter R. Roelfsema (PLoS Comput. Biol., 2024)