Balas BJ, Sinha P (2006) Receptive field structures for recognition. Neural Comput 18:497-520 [Journal] [PubMed]

Falconbridge MS, Stamps RL, Badcock DR (2005) A Simple Hebbian/Anti-Hebbian Network Learns the Sparse, Independent Components of Natural Images Neural Comput 18:415-429

Hawkins J, Ahmad S (2016) Why Neurons Have Thousands of Synapses, a Theory of Sequence Memory in Neocortex. Front Neural Circuits 10:23 [Journal] [PubMed]

•	Theory of sequence memory in neocortex (Hawkins & Ahmad 2016) [Model]

King PD, Zylberberg J, DeWeese MR (2013) Inhibitory interneurons decorrelate excitatory cells to drive sparse code formation in a spiking model of V1. J Neurosci 33:5475-85 [Journal] [PubMed]

•	Inhibitory cells enable sparse coding in V1 model (King et al. 2013) [Model]

Li M, Clark JJ (2004) A temporal stability approach to position and attention-shift-invariant recognition. Neural Comput 16:2293-321 [Journal] [PubMed]

Li Y, Cichocki A, Amari S (2004) Analysis of sparse representation and blind source separation. Neural Comput 16:1193-234 [Journal] [PubMed]

Lian Y, Grayden DB, Kameneva T, Meffin H, Burkitt AN (2019) Toward a Biologically Plausible Model of LGN-V1 Pathways Based on Efficient Coding Frontiers in Neural Circuits 13:13 [Journal]

•	Towards a biologically plausible model of LGN-V1 pathways (Lian et al 2019) [Model]

Lörincz A, Buzsáki G (2000) Two-phase computational model training long-term memories in the entorhinal-hippocampal region. Ann N Y Acad Sci 911:83-111 [PubMed]

Murray JF, Kreutz-Delgado K (2007) Visual recognition and inference using dynamic overcomplete sparse learning. Neural Comput 19:2301-52 [Journal] [PubMed]

Olshausen BA, Field DJ (2005) How close are we to understanding v1? Neural Comput 17:1665-99 [Journal] [PubMed]

Osindero S, Welling M, Hinton GE (2005) Topographic Product Models Applied to Natural Scene Statistics Neural Comput 18:381-414

Rao RP, Ballard DH (1999) Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. Nat Neurosci 2:79-87 [Journal] [PubMed]

Rehn M, Sommer FT (2007) A network that uses few active neurones to code visual input predicts the diverse shapes of cortical receptive fields. J Comput Neurosci 22:135-46 [Journal] [PubMed]

Swindale NV (2008) Feedback decoding of spatially structured population activity in cortical maps. Neural Comput 20:176-204 [Journal] [PubMed]

Szatmáry B, Lorincz A (2001) Independent component analysis of temporal sequences subject to constraints by lateral geniculate nucleus inputs yields all the three major cell types of the primary visual cortex. J Comput Neurosci 11:241-8 [PubMed]

Vertechi P, Brendel W, Machens CK (2014) Unsupervised learning of an efficient short-term memory network Advances in Neural Information Processing Systems 27:1-9 [Journal]

•	Unsupervised learning of an efficient short-term memory network (Vertechi, Brendel & Machens 2014) [Model]

Weber C, Wermter S, Elshaw M (2006) A hybrid generative and predictive model of the motor cortex. Neural Netw 19:339-53 [Journal] [PubMed]

•	Cortex learning models (Weber at al. 2006, Weber and Triesch, 2006, Weber and Wermter 2006/7) [Model]

Wolfrum P, von der Malsburg C (2007) What is the optimal architecture for visual information routing? Neural Comput 19:3293-309 [Journal] [PubMed]

Zhang K, Chan LW (2005) An Adaptive Method for Subband Decomposition ICA Neural Comput 18:191-223