ModelDB: Models that contain Sequence learning

Model Concept: Sequence learning

Sequence learning via biophysically realistic learning rules (Cone and Shouval 2021)

Top authors for Sequence learning:

Cone I (1)
Shouval HZ (1)

Top concepts studied with Sequence learning:

Eligibility traces (1)

Top neurons studied with Sequence learning:

Abstract integrate-and-fire leaky neuron (1)

Top references cited by these models:

Billings G, Piasini E, Lőrincz A, Nusser Z, Silver RA. (2014). Network structure within the cerebellar input layer enables lossless sparse encoding. Neuron. 83 (1)
Binzegger T, Douglas RJ, Martin KA. (2009). Topology and dynamics of the canonical circuit of cat V1. Neural networks : the official journal of the International Neural Network Society. 22 (1)
Bittner KC, Milstein AD, Grienberger C, Romani S, Magee JC. (2017). Behavioral time scale synaptic plasticity underlies CA1 place fields. Science (New York, N.Y.). 357 (1)
Brunel N. (2003). Dynamics and plasticity of stimulus-selective persistent activity in cortical network models. Cerebral cortex (New York, N.Y. : 1991). 13 (1)
Brzosko Z, Zannone S, Schultz W, Clopath C, Paulsen O. (2017). Sequential neuromodulation of Hebbian plasticity offers mechanism for effective reward-based navigation. eLife. 6 (1)

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