Models of distributed associative memory. - David Willshaw (1971)

Optimal Plasticity from Matrix Memories: What Goes Up Must Come Down. - David J. Willshaw; Peter Dayan (Neural Comput., 1990)

Optimising synaptic learning rules in linear associative memories. - Peter Dayan; David J. Willshaw (Biol. Cybern., 1991)

Bee-havior in a mobile robot: the construction of a self-organized cognitive map and its use in robot navigation within a complex, natural environment. - V. Ashley Walker; John Hallam; David Willshaw (ICNN, 1993)

Presynaptic and postsynaptic competition in models for the development of neuromuscular connections. - Carl Edward Rasmussen; David J. Willshaw (Biol. Cybern., 1993)

Capacity and Information Efficiency of a Brain-like Associative Net. - Bruce Graham; David J. Willshaw (NIPS, 1994)

Elastic Net Model of Ocular Dominance: Overall Stripe Pattern and Monocular Deprivation. - Geoffrey J. Goodhill; David J. Willshaw (Neural Comput., 1994)

The Role of Activity in Synaptic Competition at the Neuromuscular Junction. - Samuel R. H. Joseph; David J. Willshaw (NIPS, 1995)

Improving recall from an associative memory. - Bruce P. Graham; David J. Willshaw (Biol. Cybern., 1995)

Information Efficiency of the Associative Net at Arbitrary Coding Rates. - Bruce Graham; David J. Willshaw (ICANN, 1996)

A Model of Clipped Hebbian Learning in a Neocortical Pyramidal Cell. - Bruce Graham; David J. Willshaw (ICANN, 1997)

Competition Amongst Neurons for Neurotrophins. - Arjen van Ooyen; David J. Willshaw (ICANN, 1997)

How a Single Purkinje Cell Could Learn the Adaptive Timing of the Classically Conditioned Eye-Blink Response. - Volker Steuber; David J. Willshaw (ICANN, 1997)

A Model of the Interactions between the Globus Pallidus and Subthalamic Nucleus. - A. Gillies; David J. Willshaw (ICONIP (1), 1997)

Marr's Theory of the Neocortex as a Self-Organizing Neural Network. - David J. Willshaw; John Hallam; Sarah Gingell; Soo Leng Lau (Neural Comput., 1997)

A new approach to Kanerva's sparse distributed memory. - Tim A. Hely; David J. Willshaw; Gillian M. Hayes (IEEE Trans. Neural Networks, 1997)

Evolving Swimming Controllers for a Simulated Lamprey with Inspiration from Neurobiology. - Auke Jan Ijspeert; John Hallam; David J. Willshaw (Adapt. Behav., 1999)

Adaptive leaky integrator models of cerebellar Purkinje cells can learn the clustering of temporal patterns. - Volker Steuber; David J. Willshaw (Neurocomputing, 1999)

Probabilistic Synaptic Transmission in the Associative Net. - Bruce Graham; David J. Willshaw (Neural Comput., 1999)

Influence of dendritic morphology on axonal competition. - Arjen van Ooyen; David J. Willshaw; Ger J. A. Ramakers (Neurocomputing, 2000)

Towards Novel Neuroscience-Inspired Computing. - Stefan Wermter; Jim Austin; David J. Willshaw; Mark Elshaw (Emergent Neural Computational Architectures Based on Neuroscience, 2001)

An evaluation of recurrent feedforward memory networks and their relevance to the hippocampus. - Kit Longden; David J. Willshaw (Neurocomputing, 2002)

Neuroscience data and tool sharing - A legal and policy framework for neuroinformatics. - Peter Eckersley; Gary F. Egan; Erik De Schutter; Yiyuan Tang; Mirko Novak; Václav Sebesta; Line Matthiessen; Iiro P. Jääskeläinen; Ulla Ruotsalainen; Andreas V. M. Herz; K. Peter Hoffmann; Raphael Ritz; et al. (Neuroinformatics, 2003)

Hippocampal mossy fibre boutons as dynamical synapses. - Paulo Aguiar; David Willshaw (Neurocomputing, 2004)

A Biophysical Model of Synaptic Delay Learning and Temporal Pattern Recognition in a Cerebellar Purkinje Cell. - Volker Steuber; David J. Willshaw (J. Comput. Neurosci., 2004)

Synaptic Rewiring for Topographic Map Formation. - Simeon A. Bamford; Alan F. Murray; David J. Willshaw (ICANN (2), 2008)

Large developing axonal arbors using a distributed and locally-reprogrammable address-event receiver. - Simeon A. Bamford; Alan F. Murray; David J. Willshaw (IJCNN, 2008)

Inhomogeneities in Heteroassociative Memories with Linear Learning Rules. - David C. Sterratt; David J. Willshaw (Neural Comput., 2008)

Optimal learning rules for familiarity detection. - Andrea Greve; David C. Sterratt; David I. Donaldson; David J. Willshaw; Mark C. W. van Rossum (Biol. Cybern., 2009)

Synaptic rewiring for topographic mapping and receptive field development. - Simeon A. Bamford; Alan F. Murray; David J. Willshaw (Neural Networks, 2010)

Large developing receptive fields using a distributed and locally reprogrammable address-event receiver. - Simeon A. Bamford; Alan F. Murray; David J. Willshaw (IEEE Trans. Neural Networks, 2010)

Spike-Timing-Dependent Plasticity With Weight Dependence Evoked From Physical Constraints. - Simeon A. Bamford; Alan F. Murray; David J. Willshaw (IEEE Trans. Biomed. Circuits Syst., 2012)

morphforge: a toolbox for simulating small networks of biologically detailed neurons in Python. - Michael J. Hull; David J. Willshaw (Frontiers Neuroinformatics, 2013)

Standard Anatomical and Visual Space for the Mouse Retina: Computational Reconstruction and Transformation of Flattened Retinae with the Retistruct Package. - David C. Sterratt; Daniel Lyngholm; David J. Willshaw; Ian D. Thompson (PLoS Comput. Biol., 2013)

Modelling the Effects of Electrical Coupling between Unmyelinated Axons of Brainstem Neurons Controlling Rhythmic Activity. - Michael J. Hull; Stephen R. Soffe; David J. Willshaw; Alan Roberts (PLoS Comput. Biol., 2015)

Modelling Feedback Excitation, Pacemaker Properties and Sensory Switching of Electrically Coupled Brainstem Neurons Controlling Rhythmic Activity. - Michael J. Hull; Stephen R. Soffe; David J. Willshaw; Alan Roberts (PLoS Comput. Biol., 2016)