L. F. Abbott

According to our database, L. F. Abbott authored at least 51 papers between 1990 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Theory of coupled neuronal-synaptic dynamics.

David G. Clark, L. F. Abbott

CoRR, 2023

2022

Sparse RNNs can support high-capacity classification.

Denis Turcu, L. F. Abbott

PLoS Comput. Biol., December, 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., December, 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

Dimension of Activity in Random Neural Networks.

David G. Clark, L. F. Abbott, Ashok Litwin-Kumar

CoRR, 2022

The Implicit Bias of Gradient Descent on Generalized Gated Linear Networks.

Samuel Lippl, L. F. Abbott, SueYeon Chung

CoRR, 2022

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

2021

Neural population geometry: An approach for understanding biological and artificial neural networks.

SueYeon Chung, L. F. Abbott

CoRR, 2021

Credit Assignment Through Broadcasting a Global Error Vector.

David G. Clark, L. F. Abbott, SueYeon Chung

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2018

Training dynamically balanced excitatory-inhibitory networks.

Alessandro Ingrosso, L. F. Abbott

CoRR, 2018

Feedback alignment in deep convolutional networks.

Theodore H. Moskovitz, Ashok Litwin-Kumar, L. F. Abbott

CoRR, 2018

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

Balanced Excitation and Inhibition are Required for High-Capacity, Noise-Robust Neuronal Selectivity.

Ran Rubin, L. F. Abbott, Haim Sompolinsky

CoRR, 2017

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

Stability and Competition in Multi-spike Models of Spike-Timing Dependent Plasticity.

Baktash Babadi, L. F. Abbott

PLoS Comput. Biol., 2016

LFADS - Latent Factor Analysis via Dynamical Systems.

David Sussillo, Rafal Józefowicz, L. F. Abbott, Chethan Pandarinath

CoRR, 2016

2014

Hierarchical Control Using Networks Trained with Higher-Level Forward Models.

Greg Wayne, L. F. Abbott

Neural Comput., 2014

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

Pairwise Analysis Can Account for Network Structures Arising from Spike-Timing Dependent Plasticity.

Baktash Babadi, L. F. Abbott

PLoS Comput. Biol., 2013

2010

Intrinsic Stability of Temporally Shifted Spike-Timing Dependent Plasticity.

Baktash Babadi, L. F. Abbott

PLoS Comput. Biol., 2010

Inferring Stimulus Selectivity from the Spatial Structure of Neural Network Dynamics.

Kanaka Rajan, L. F. Abbott, Haim Sompolinsky

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2008

Mechanism of gain modulation at single neuron and network levels.

M. Brozovic, L. F. Abbott, Richard A. Andersen

J. Comput. Neurosci., 2008

2005

Supervised Learning Through Neuronal Response Modulation.

Christian D. Swinehart, L. F. Abbott

Neural Comput., 2005

2004

Control of network activity through neuronal response modulation.

Christian D. Swinehart, Kris Bouchard, Peretz Partensky, L. F. Abbott

Neurocomputing, 2004

Synaptic equalization by anti-STDP.

Clifton C. Rumsey, L. F. Abbott

Neurocomputing, 2004

2002

Modeling temporal combination selective neurons of the songbird.

Patrick J. Drew, L. F. Abbott

Neurocomputing, 2002

2001

Input-specific adaptation in complex cells through synaptic depression.

Frances S. Chance, L. F. Abbott

Neurocomputing, 2001

2000

Do Simple Cells in Primary Visual Cortex Form a Tight Frame?

Emilio Salinas, L. F. Abbott

Neural Comput., 2000

Gain modulation of recurrent networks.

Jian Zhang, L. F. Abbott

Neurocomputing, 2000

Temporally asymmetric Hebbian learning and neuronal response variability.

Sen Song, 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

A recurrent network model for the phase invariance of complex cell responses.

Frances S. Chance, Sacha B. Nelson, L. F. Abbott

Neurocomputing, 2000

1999

Network Stability from Activity-Dependent Regulation of Neuronal Conductances.

Jorge Golowasch, Michael Casey, L. F. Abbott, Eve Marder

Neural Comput., 1999

The Effect of Correlated Variability on the Accuracy of a Population Code.

L. F. Abbott, Peter Dayan

Neural Comput., 1999

Decorrelation of spike trains by synaptic depression.

Mark S. Goldman, Sacha B. Nelson, L. F. Abbott

Neurocomputing, 1999

Self-Assembly of Oscillatory Neurons and Networks.

Eve Marder, Jorge Golowasch, Kathryn S. Richards, Cristina Soto-Treviño, William L. Miller, L. F. Abbott

Proceedings of the Foundations and Tools for Neural Modeling, 1999

1998

Recurrent Cortical Amplification Produces Complex Cell Responses.

Frances S. Chance, Sacha B. Nelson, L. F. Abbott

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Temporally Asymmetric Hebbian Learning, Spike liming and Neural Response Variability.

L. F. Abbott, Sen Song

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

1997

Learning Navigational Maps Through Potentiation and Modulation of Hippocampal Place Cells.

Wulfram Gerstner, L. F. Abbott

J. Comput. Neurosci., 1997

1996

A model of spatial map formation in the hippocampus of the rat.

K. I. Blum, L. F. Abbott

Neural Comput., 1996

1995

Reduced Representation by Neural Networks with Restricted Receptive Fields.

Marco Idiart, Barry Berk, L. F. Abbott

Neural Comput., 1995

1994

When inhibition not excitation synchronizes neural firing.

Carl Vreeswijk, L. F. Abbott, G. Bard Ermentrout

J. Comput. Neurosci., 1994

Vector reconstruction from firing rates.

Emilio Salinas, L. F. Abbott

J. Comput. Neurosci., 1994

1993

Self-Sustained Firing in Populations of Integrate-and-Fire Neurons.

Carl Vanvreeswijk, L. F. Abbott

SIAM J. Appl. Math., 1993

Analysis of Neuron Models with Dynamically Regulated Conductances.

L. F. Abbott, Gwendal Le Masson

Neural Comput., 1993

1992

Reduction of conductance-based neuron models.

Thomas B. Kepler, L. F. Abbott, Eve Marder

Biol. Cybern., 1992

Hybrid Circuits of Interacting Computer Model and Biological Neurons.

Sylvie Renaud-Le Masson, Gwendal Le Masson, Eve Marder, L. F. Abbott

Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

1991

Oscillating Networks: Control of Burst Duration by Electrically Coupled Neurons.

L. F. Abbott, Eve Marder, Scott L. Hooper

Neural Comput., 1991

The path integral for dendritic trees.

L. F. Abbott, Edward Farhi, Sam Gutmann

Biol. Cybern., 1991

1990

Order Reduction for Dynamical Systems Describing the Behavior of Complex Neurons.

Thomas B. Kepler, L. F. Abbott, Eve Marder

Proceedings of the Advances in Neural Information Processing Systems 3, 1990

Oscillating networks: modeling the pyloric circuit of the stomatogastric ganglion.

L. F. Abbott, Scott L. Hooper, Thomas B. Kepler, Eve Marder

Proceedings of the IJCNN 1990, 1990