Oscillating networks: modeling the pyloric circuit of the stomatogastric ganglion. - L. F. Abbott; Scott L. Hooper; Thomas B. Kepler; Eve Marder (IJCNN, 1990)

Order Reduction for Dynamical Systems Describing the Behavior of Complex Neurons. - Thomas B. Kepler; L. F. Abbott; Eve Marder (NIPS, 1990)

The path integral for dendritic trees. - L. F. Abbott; Edward Farhi; Sam Gutmann (Biol. Cybern., 1991)

Oscillating Networks: Control of Burst Duration by Electrically Coupled Neurons. - L. F. Abbott; Eve Marder; Scott L. Hooper (Neural Comput., 1991)

Hybrid Circuits of Interacting Computer Model and Biological Neurons. - Sylvie Renaud-Le Masson; Gwendal Le Masson; Eve Marder; L. F. Abbott (NIPS, 1992)

Reduction of conductance-based neuron models. - Thomas B. Kepler; L. F. Abbott; Eve Marder (Biol. Cybern., 1992)

Analysis of Neuron Models with Dynamically Regulated Conductances. - L. F. Abbott; Gwendal Le Masson (Neural Comput., 1993)

Self-Sustained Firing in Populations of Integrate-and-Fire Neurons. - Carl Vanvreeswijk; L. F. Abbott (SIAM J. Appl. Math., 1993)

Vector reconstruction from firing rates. - Emilio Salinas; L. F. Abbott (J. Comput. Neurosci., 1994)

When inhibition not excitation synchronizes neural firing. - Carl Vreeswijk; L. F. Abbott; G. Bard Ermentrout (J. Comput. Neurosci., 1994)

Reduced Representation by Neural Networks with Restricted Receptive Fields. - Marco Idiart; Barry Berk; L. F. Abbott (Neural Comput., 1995)

A model of spatial map formation in the hippocampus of the rat. - K. I. Blum; L. F. Abbott (Neural Comput., 1996)

Learning Navigational Maps Through Potentiation and Modulation of Hippocampal Place Cells. - Wulfram Gerstner; L. F. Abbott (J. Comput. Neurosci., 1997)

Temporally Asymmetric Hebbian Learning, Spike liming and Neural Response Variability. - L. F. Abbott; Sen Song (NIPS, 1998)

Recurrent Cortical Amplification Produces Complex Cell Responses. - Frances S. Chance; Sacha B. Nelson; L. F. Abbott (NIPS, 1998)

Self-Assembly of Oscillatory Neurons and Networks. - Eve Marder; Jorge Golowasch; Kathryn S. Richards; Cristina Soto-Treviño; William L. Miller; L. F. Abbott (IWANN (1), 1999)

Decorrelation of spike trains by synaptic depression. - Mark S. Goldman; Sacha B. Nelson; L. F. Abbott (Neurocomputing, 1999)

The Effect of Correlated Variability on the Accuracy of a Population Code. - L. F. Abbott; Peter Dayan (Neural Comput., 1999)

Network Stability from Activity-Dependent Regulation of Neuronal Conductances. - Jorge Golowasch; Michael Casey; L. F. Abbott; Eve Marder (Neural Comput., 1999)

A recurrent network model for the phase invariance of complex cell responses. - Frances S. Chance; Sacha B. Nelson; L. F. Abbott (Neurocomputing, 2000)

Dependence of firing pattern on intrinsic ionic conductances: Sensitive and insensitive combinations. - Mark S. Goldman; Jorge Golowasch; Eve Marder; L. F. Abbott (Neurocomputing, 2000)

Temporally asymmetric Hebbian learning and neuronal response variability. - Sen Song; L. F. Abbott (Neurocomputing, 2000)

Gain modulation of recurrent networks. - Jian Zhang 004; L. F. Abbott (Neurocomputing, 2000)

Do Simple Cells in Primary Visual Cortex Form a Tight Frame? - Emilio Salinas; L. F. Abbott (Neural Comput., 2000)

Input-specific adaptation in complex cells through synaptic depression. - Frances S. Chance; L. F. Abbott (Neurocomputing, 2001)

Modeling temporal combination selective neurons of the songbird. - Patrick J. Drew; L. F. Abbott (Neurocomputing, 2002)

Synaptic equalization by anti-STDP. - Clifton C. Rumsey; L. F. Abbott (Neurocomputing, 2004)

Control of network activity through neuronal response modulation. - Christian D. Swinehart; Kris Bouchard; Peretz Partensky; L. F. Abbott (Neurocomputing, 2004)

Supervised Learning Through Neuronal Response Modulation. - Christian D. Swinehart; L. F. Abbott (Neural Comput., 2005)

Mechanism of gain modulation at single neuron and network levels. - M. Brozovic; L. F. Abbott; Richard A. Andersen (J. Comput. Neurosci., 2008)

Inferring Stimulus Selectivity from the Spatial Structure of Neural Network Dynamics. - Kanaka Rajan; L. F. Abbott; Haim Sompolinsky (NIPS, 2010)

Intrinsic Stability of Temporally Shifted Spike-Timing Dependent Plasticity. - Baktash Babadi; L. F. Abbott (PLoS Comput. Biol., 2010)

Pairwise Analysis Can Account for Network Structures Arising from Spike-Timing Dependent Plasticity. - Baktash Babadi; L. F. Abbott (PLoS Comput. Biol., 2013)

A Complex-Valued Firing-Rate Model That Approximates the Dynamics of Spiking Networks. - Evan S. Schaffer; Srdjan Ostojic; L. F. Abbott (PLoS Comput. Biol., 2013)

Hierarchical Control Using Networks Trained with Higher-Level Forward Models. - Greg Wayne; L. F. Abbott (Neural Comput., 2014)

LFADS - Latent Factor Analysis via Dynamical Systems. - David Sussillo; Rafal Józefowicz; L. F. Abbott; Chethan Pandarinath (CoRR, 2016)

Stability and Competition in Multi-spike Models of Spike-Timing Dependent Plasticity. - Baktash Babadi; L. F. Abbott (PLoS Comput. Biol., 2016)

Tuning Curves for Arm Posture Control in Motor Cortex Are Consistent with Random Connectivity. - Hagai Lalazar; L. F. Abbott; Eilon Vaadia (PLoS Comput. Biol., 2016)

Balanced Excitation and Inhibition are Required for High-Capacity, Noise-Robust Neuronal Selectivity. - Ran Rubin; L. F. Abbott; Haim Sompolinsky (CoRR, 2017)

full-FORCE: A Target-Based Method for Training Recurrent Networks. - Brian DePasquale; Christopher J. Cueva; Kanaka Rajan; G. Sean Escola; L. F. Abbott (CoRR, 2017)

Feedback alignment in deep convolutional networks. - Theodore H. Moskovitz; Ashok Litwin-Kumar; L. F. Abbott (CoRR, 2018)

Training dynamically balanced excitatory-inhibitory networks. - Alessandro Ingrosso; L. F. Abbott (CoRR, 2018)

Credit Assignment Through Broadcasting a Global Error Vector. - David G. Clark; L. F. Abbott; SueYeon Chung (NeurIPS, 2021)

Neural population geometry: An approach for understanding biological and artificial neural networks. - SueYeon Chung; L. F. Abbott (CoRR, 2021)

Input correlations impede suppression of chaos and learning in balanced rate networks. - Rainer Engelken; Alessandro Ingrosso; Ramin Khajeh; Sven Goedeke; L. F. Abbott (CoRR, 2022)

The Implicit Bias of Gradient Descent on Generalized Gated Linear Networks. - Samuel Lippl; L. F. Abbott; SueYeon Chung (CoRR, 2022)

Dimension of Activity in Random Neural Networks. - David G. Clark; L. F. Abbott; Ashok Litwin-Kumar (CoRR, 2022)

Sparse balance: Excitatory-inhibitory networks with small bias currents and broadly distributed synaptic weights. - Ramin Khajeh; Francesco Fumarola; L. F. Abbott (PLoS Comput. Biol., 2022)

Input correlations impede suppression of chaos and learning in balanced firing-rate networks. - Rainer Engelken; Alessandro Ingrosso; Ramin Khajeh; Sven Goedeke; L. F. Abbott (PLoS Comput. Biol., 2022)

Sparse RNNs can support high-capacity classification. - Denis Turcu; L. F. Abbott (PLoS Comput. Biol., 2022)

Theory of coupled neuronal-synaptic dynamics. - David G. Clark; L. F. Abbott (CoRR, 2023)

Emergent neural dynamics and geometry for generalization in a transitive inference task. - Kenneth Kay; Natalie Biderman; Ramin Khajeh; Manuel Beiran; Christopher J. Cueva; Daphna Shohamy; Greg Jensen; Xue-Xin Wei; Vincent P. Ferrera; L. F. Abbott (PLoS Comput. Biol., 2024)