Theta rhythm oscillations and sequence encoding in the hippocampus. - Michael E. Hasselmo; Ajay Kapur; Bradley P. Wyble (Neurocomputing, 2001)

A Proposed Function for Hippocampal Theta Rhythm: Separate Phases of Encoding and Retrieval Enhance Reversal of Prior Learning. - Michael E. Hasselmo; Clara Bodelón; Bradley P. Wyble (Neural Comput., 2002)

The Attentional Blink at 20 items/sec, Model Prediction and Empirical Validation of Lag-2 Sparing. - Bradley P. Wyble; Howard Bowman (ICCM, 2004)

Process algebraic modelling of attentional capture and human electrophysiology in interactive systems. - Li Su 002; Howard Bowman; Philip J. Barnard; Bradley P. Wyble (Formal Aspects Comput., 2009)

The Attentional Blink Reveals Serial Working Memory Encoding: Evidence from Virtual and Human Event-related Potentials. - Patrick Craston; Bradley P. Wyble; Srivas Chennu; Howard Bowman (J. Cogn. Neurosci., 2009)

Attention Increases the Temporal Precision of Conscious Perception: Verifying the Neural-ST2 Model. - Srivas Chennu; Patrick Craston; Bradley P. Wyble; Howard Bowman (PLoS Comput. Biol., 2009)

Fortunate Conjunctions Revived: Feature Binding with the 2f-ST2 Model. - Srivas Chennu; Howard Bowman; Brad Wyble (CogSci, 2011)

The Attentional Blink Impairs Detection and Delays Encoding of Visual Information: Evidence from Human Electrophysiology. - Roberto Dell'Acqua; Paul E. Dux; Brad Wyble; Mattia Doro; Paola Sessa; Federica Meconi; Pierre Jolicoeur (J. Cogn. Neurosci., 2015)

Towards a unified multiresolution vision model for autonomous ground robots. - John P. Sustersic; Brad Wyble; Siddharth Advani; Vijaykrishnan Narayanan (Robotics Auton. Syst., 2016)

Rapid Presentation Rate Negatively Impacts the Contiguity Effect in Free Recall. - Claudio A. Toro-Serey; Ian Bright; Brad Wyble; Marc W. Howard (CogSci, 2019)

Using Navigational Information to Learn Visual Representations. - Lizhen Zhu; Brad Wyble; James Z. Wang 001 (CoRR, 2022)

What the Flip? What the P-N Flip Can Tell Us about Proactive Suppression. - Joyce Tam; Chloe Callahan-Flintoft; Brad Wyble (J. Cogn. Neurosci., 2022)

In Defense of Modular Thinking. - Brad Wyble (J. Cogn. Neurosci., 2023)

Context-driven self-supervised visual learning: Harnessing the environment as a data source. - Lizhen Zhu; James Z. Wang 001; Wonseuk Lee; Brad Wyble (CoRR, 2024)

Hopfield and Hinton's neural network revolution and the future of AI. - James Z. Wang 001; Brad Wyble (Patterns, 2024)

Incorporating simulated spatial context information improves the effectiveness of contrastive learning models. - Lizhen Zhu; James Z. Wang 001; Wonseuk Lee; Brad Wyble (Patterns, 2024)