LA
L. F. Abbott
Models, Neurologicalneuroscienceq-bio.NCNeural Networks, ComputerNeuronsBraincond-mat.dis-nnDrosophila melanogastercs.LGcs.NE
On Valency
published · living versionsW_gwnb3ukw·v1 · currentpublished
LFADS - Latent Factor Analysis via Dynamical Systems
with David Sussillo, Rafal Jozefowicz, Chethan Pandarinath
1 version
Preprints & journals
85 papers in the corpus · 1988–2026Associative synaptic plasticity creates dynamic persistent activity.42809398 · Wakhloo, Albert J, Clark, David G, Abbott, L F2026 · 2 citationsProceedings of the National Academy of Sciences of the United States of America. 2026;123(40):e2526156123
Connectome analysis of a cerebellum-like circuit for sensory prediction.42686902 · Perks, Krista E, Petkova, Mariela D, Muller, Salomon Z et al.2026 · 2 citationsNature. 2026
A vector-based strategy for olfactory navigation in Drosophila.42486983 · Siliciano, Andrew F, Minni, Sun, Morton, Chad et al.2026 · 2 citationsNature. 2026;657(8131):443-454
Representations of the intrinsic value of information in mouse orbitofrontal cortex.42533133 · Bussell, Jennifer J, Badman, Ryan P, Márton, David et al.2026 · 0 citationsNature neuroscience. 2026;29(9):2261-2272
Associative synaptic plasticity creates dynamic persistent activity10.1101/2025.08.20.671131v2 · Wakhloo, A. J., Clark, D. G., Abbott, L.2025 · 2 citationsbioRxiv
Neuronal calcium spikes enable vector inversion in the Drosophila brain.41468883 · Ishida, Itzel G, Sethi, Sachin, Mohren, Thomas L et al.2026 · 5 citationsCell. 2026;189(3):748-764.e25
Neuronal calcium spikes enable vector inversion in the Drosophila brain10.1101/2023.11.24.568537v4 · Ishida, I. G., Sethi, S., Mohren, T. L. et al.2023 · 11 citationsbioRxiv
Symmetries and continuous attractors in disordered neural circuits10.1101/2025.01.26.634933v2 · Clark, D. G., Abbott, L. F., Sompolinsky, H.2025 · 10 citationsbioRxiv
Connectome analysis of a cerebellum-like circuit for sensory prediction10.1101/2025.07.03.662989v1 · Perks, K. E., Petkova, M. D., Muller, S. Z. et al.2025 · 2 citationsbioRxiv
An end-to-end model of active electrosensation.40273914 · Turcu, Denis, Zadina, Abigail N, Abbott, L F et al.2025 · 3 citationsCurrent biology : CB. 2025;35(10):2295-2306.e4
A mathematical theory of relational generalization in transitive inference.38968113 · Lippl, Samuel, Kay, Kenneth, Jensen, Greg et al.2025 · 15 citationsProceedings of the National Academy of Sciences of the United States of America. 2024;121(28):e2314511121
A vector-based strategy for olfactory navigation in Drosophila10.1101/2025.02.15.638426v1 · Siliciano, A. F., Minni, S., Morton, C. et al.2025 · 9 citationsbioRxiv
An end-to-end model of active electrosensation10.1101/2024.10.22.619741v1 · Turcu, D., Zadina, A. N., Abbott, L. et al.2024 · 4 citationsbioRxiv
Representations of the intrinsic value of information in mouse orbitofrontal cortex10.1101/2023.10.13.562291v3 · Bussell, J. J., Badman, R. P., Marton, C. D. et al.2023 · 10 citationsbioRxiv
Hue selectivity from recurrent circuitry in Drosophila.38755272 · Christenson, Matthias P, Sanz Diez, Alvaro, Heath, Sarah L et al.2024 · 21 citationsNature neuroscience. 2024;27(6):1137-1147
Emergent neural dynamics and geometry for generalization in a transitive inference task.38662797 · Kay, Kenneth, Biderman, Natalie, Khajeh, Ramin et al.2024 · 15 citationsPLoS computational biology. 2024;20(4):e1011954
A mathematical theory of relational generalization in transitive inference10.1101/2023.08.22.554287v2 · Lippl, S., Kay, K., Jensen, G. et al.2023 · 16 citationsbioRxiv
Converting an allocentric goal into an egocentric steering signal.38326612 · Mussells Pires, Peter, Zhang, Lingwei, Parache, Victoria et al.2024 · 118 citationsNature. 2024;626(8000):808-818
Theory of coupled neuronal-synaptic dynamics2302.08985v2 · David G. Clark, L.F. Abbott2023 · 46 citationsarXiv
Dimension of activity in random neural networks2207.12373v3 · David G. Clark, L.F. Abbott, Ashok Litwin-Kumar2022 · 54 citationsPhys. Rev. Lett. 131, 118401 (2023)
Emergent neural dynamics and geometry for generalization in a transitive inference task10.1101/2022.10.10.511448v3 · Kay, K., Biderman, N., Khajeh, R. et al.2022 · 15 citationsbioRxiv
Hue selectivity from recurrent circuitry in Drosophila10.1101/2023.07.12.548573v1 · Christenson, M. P., Sanz Diez, A., Heath, S. L. et al.2023 · 21 citationsbioRxiv
The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks.36630961 · DePasquale, Brian, Sussillo, David, Abbott, L F et al.2023 · 64 citationsNeuron. 2023;111(5):631-649.e10
Converting an allocentric goal into an egocentric steering signal10.1101/2022.11.10.516026v1 · Mussells Pires, P., Abbott, L. F., Maimon, G.2022 · 118 citationsbioRxiv
Flexible neural control of motor units.36216998 · Marshall, Najja J, Glaser, Joshua I, Trautmann, Eric M et al.2022 · 121 citationsNature neuroscience. 2022;25(11):1492-1504
Building an allocentric travelling direction signal via vector computation.34912112 · Lyu, Cheng, Abbott, L F, Maimon, Gaby2022 · 215 citationsNature. 2022;601(7891):92-97
Flexible neural control of motor units10.1101/2021.05.05.442653v2 · Marshall, N. J., Glaser, J. I., Trautmann, E. M. et al.2021 · 121 citationsbioRxiv
Thalamic control of cortical dynamics in a model of flexible motor sequencing.34077721 · Logiaco, Laureline, Abbott, L F, Escola, Sean2022 · 163 citationsCell reports. 2021;35(9):109090
Neural population geometry: An approach for understanding biological and artificial neural networks2104.07059v3 · SueYeon Chung, L. F. Abbott2021 · 309 citationsCurrent Opinion in Neurobiology, Volume 70, October 2021, Pages 137-144
Meta-learning local synaptic plasticity for continual familiarity detection10.1101/2021.03.21.436287v1 · Tyulmankov, D., Yang, G. R., Abbott, L.2021 · 8 citationsbioRxiv
Neural Trajectories in the Supplementary Motor Area and Motor Cortex Exhibit Distinct Geometries, Compatible with Different Classes of Computation.32516573 · Russo, Abigail A, Khajeh, Ramin, Bittner, Sean R et al.2020 · 172 citationsNeuron. 2020;107(4):745-758.e6
Lyapunov spectra of chaotic recurrent neural networks2006.02427v1 · Rainer Engelken, Fred Wolf, L.F. Abbott2020 · 74 citationsarXiv
Generation of stable heading representations in diverse visual scenes.31748750 · Kim, Sung Soo, Hermundstad, Ann M, Romani, Sandro et al.2020 · 206 citationsNature. 2019;576(7785):126-131
Generalization of learned responses in the mormyrid electrosensory lobe.30860480 · Dempsey, Conor, Abbott, L F, Sawtell, Nathaniel B2020 · 15 citationseLife. 2019;8
Storage capacity of generalized networks.9898773 · Abbott, Arian2019 · 45 citationsPhysical review. A, General physics. 1987;36(10):5091-5094
Asynchronous states in networks of pulse-coupled oscillators.9960738 · Abbott, van Vreeswijk C2019 · 509 citationsPhysical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 1993;48(2):1483-1490
Population subspaces reflect movement intention for arm and brain-machine interface control10.1101/688259v1 · Lalazar, H., Murray, J. M., Abbott, L. F. et al.2019 · 4 citationsbioRxiv
Tuning Curves for Arm Posture Control in Motor Cortex Are Consistent with Random Connectivity.27224735 · Lalazar, Hagai, Abbott, L F, Vaadia, Eilon2017 · 15 citationsPLoS computational biology. 2016;12(5):e1004910
LFADS - Latent Factor Analysis via Dynamical Systems1608.06315v1 · David Sussillo, Rafal Jozefowicz, L. F. Abbott et al.2016 · 71 citationsarXivon Valency
Bayesian Sparse Regression Analysis Documents the Diversity of Spinal Inhibitory Interneurons.26949187 · Gabitto, Mariano I, Pakman, Ari, Bikoff, Jay B et al.2016 · 81 citationsCell. 2016;165(1):220-233
Conceptual and technical advances define a key moment for theoretical neuroscience.26906500 · Churchland, Anne K, Abbott, L F2016 · 54 citationsNature neuroscience. 2016;19(3):348-9
Building functional networks of spiking model neurons.26906501 · Abbott, L F, DePasquale, Brian, Memmesheimer, Raoul-Martin2016 · 232 citationsNature neuroscience. 2016;19(3):350-5
Using Firing-Rate Dynamics to Train Recurrent Networks of Spiking Model Neurons1601.07620v1 · Brian DePasquale, Mark M. Churchland, L.F. Abbott2016 · 38 citationsarXiv
A computational model of motor neuron degeneration.25088365 · Le Masson, Gwendal, Przedborski, Serge, Abbott, L F2014 · 167 citationsNeuron. 2014;83(4):975-88
Pairwise analysis can account for network structures arising from spike-timing dependent plasticity.23436986 · Babadi, Baktash, Abbott, L F2013 · 60 citationsPLoS computational biology. 2013;9(2):e1002906
Beyond the edge of chaos: amplification and temporal integration by recurrent networks in the chaotic regime.22181445 · Toyoizumi, T, Abbott, L F2012 · 151 citationsPhysical review. E, Statistical, nonlinear, and soft matter physics. 2011;84(5 Pt 1):051908
Modular realignment of entorhinal grid cell activity as a basis for hippocampal remapping.21697391 · Monaco, Joseph D, Abbott, L F, Abbott, Larry F2011 · 124 citationsThe Journal of neuroscience : the official journal of the Society for Neuroscience. 2011;31(25):9414-25
Stimulus-dependent suppression of chaos in recurrent neural networks.20866644 · Rajan, Kanaka, Abbott, L F, Sompolinsky, Haim2011 · 308 citationsPhysical review. E, Statistical, nonlinear, and soft matter physics. 2010;82(1 Pt 1):011903
Stimulus-Dependent Suppression of Chaos in Recurrent Neural Networks0912.3513v2 · Kanaka Rajan, L F Abbott, Haim Sompolinsky2009 · 311 citationsPhysical Review E 82, 011903 (2010)on Valency
HCN hyperpolarization-activated cation channels inhibit EPSPs by interactions with M-type K(+) channels.19363490 · George, Meena S, Abbott, L F, Siegelbaum, Steven A2009 · 197 citationsNature neuroscience. 2009;12(5):577-84
Career total: 195 works. 85 are in this corpus.Showing the 50 most recent.
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