L. F. Abbott

18.2k total citations · 6 hit papers
121 papers, 12.5k citations indexed

About

L. F. Abbott is a scholar working on Cognitive Neuroscience, Nuclear and High Energy Physics and Cellular and Molecular Neuroscience. According to data from OpenAlex, L. F. Abbott has authored 121 papers receiving a total of 12.5k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Cognitive Neuroscience, 46 papers in Nuclear and High Energy Physics and 27 papers in Cellular and Molecular Neuroscience. Recurrent topics in L. F. Abbott's work include Neural dynamics and brain function (44 papers), Black Holes and Theoretical Physics (30 papers) and Particle physics theoretical and experimental studies (27 papers). L. F. Abbott is often cited by papers focused on Neural dynamics and brain function (44 papers), Black Holes and Theoretical Physics (30 papers) and Particle physics theoretical and experimental studies (27 papers). L. F. Abbott collaborates with scholars based in United States, Switzerland and France. L. F. Abbott's co-authors include Mark B. Wise, Wade G. Regehr, Sacha B. Nelson, S. Deser, Juan A. Varela, Kamal Sen, Carl van Vreeswijk, Edward Farhi, G. Bard Ermentrout and Eve Marder and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

L. F. Abbott

120 papers receiving 12.2k citations

Hit Papers

Synaptic Depression and Cortical Gain Control 1981 2026 1996 2011 1997 2004 1981 1982 1994 400 800 1.2k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
L. F. Abbott United States 50 5.5k 4.2k 4.1k 2.9k 2.3k 121 12.5k
P. A. Robinson Australia 57 7.3k 1.3× 1.3k 0.3× 1.8k 0.4× 3.7k 1.3× 1.7k 0.7× 446 14.0k
Vijay Balasubramanian United States 48 1.3k 0.2× 5.2k 1.2× 781 0.2× 4.5k 1.6× 2.9k 1.3× 166 8.2k
H. R. Wilson United Kingdom 45 1.2k 0.2× 7.5k 1.8× 291 0.1× 4.6k 1.6× 492 0.2× 179 9.0k
Fabrizio Gabbiani United States 37 2.2k 0.4× 1.3k 0.3× 2.1k 0.5× 207 0.1× 405 0.2× 88 5.0k
Daniel J. Amit Israel 32 4.5k 0.8× 261 0.1× 1.4k 0.3× 129 0.0× 1.7k 0.8× 84 8.0k
Joseph J. Atick United States 32 2.5k 0.5× 1.3k 0.3× 720 0.2× 540 0.2× 493 0.2× 44 5.2k
L. F. Abbott United States 4 1.5k 0.3× 1.9k 0.5× 1.2k 0.3× 1.4k 0.5× 161 0.1× 6 4.0k
Stiliyan Kalitzin Netherlands 29 2.1k 0.4× 844 0.2× 966 0.2× 337 0.1× 789 0.3× 87 3.5k
D. Horn Israel 33 848 0.2× 1.7k 0.4× 393 0.1× 101 0.0× 539 0.2× 205 5.9k
Partha P. Mitra United States 57 6.4k 1.2× 2.1k 0.5× 3.9k 0.9× 18 0.0× 560 0.2× 162 16.1k

Countries citing papers authored by L. F. Abbott

Since Specialization
Citations

This map shows the geographic impact of L. F. Abbott's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by L. F. Abbott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites L. F. Abbott more than expected).

Fields of papers citing papers by L. F. Abbott

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by L. F. Abbott. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by L. F. Abbott. The network helps show where L. F. Abbott may publish in the future.

Co-authorship network of co-authors of L. F. Abbott

This figure shows the co-authorship network connecting the top 25 collaborators of L. F. Abbott. A scholar is included among the top collaborators of L. F. Abbott based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with L. F. Abbott. L. F. Abbott is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhang, Lingwei, et al.. (2024). Converting an allocentric goal into an egocentric steering signal. Nature. 626(8000). 808–818. 29 indexed citations
2.
Adachi, Atsuko, et al.. (2024). Hue selectivity from recurrent circuitry in Drosophila. Nature Neuroscience. 27(6). 1137–1147. 5 indexed citations
3.
Kay, Kenneth, et al.. (2024). A mathematical theory of relational generalization in transitive inference. Proceedings of the National Academy of Sciences. 121(28). e2314511121–e2314511121. 3 indexed citations
4.
DePasquale, Brian, David Sussillo, L. F. Abbott, & Mark M. Churchland. (2023). The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks. Neuron. 111(5). 631–649.e10. 25 indexed citations
5.
Lyu, Cheng, L. F. Abbott, & Gaby Maimon. (2021). Building an allocentric travelling direction signal via vector computation. Nature. 601(7891). 92–97. 93 indexed citations
6.
Abbott, L. F., Brian DePasquale, & Raoul-Martin Memmesheimer. (2016). Building functional networks of spiking model neurons. Nature Neuroscience. 19(3). 350–355. 137 indexed citations
7.
Gabitto, Mariano I., Ari Pakman, Jay B. Bikoff, et al.. (2016). Bayesian Sparse Regression Analysis Documents the Diversity of Spinal Inhibitory Interneurons. Cell. 165(1). 220–233. 55 indexed citations
8.
Rajan, Kanaka, L. F. Abbott, & Haim Sompolinsky. (2010). Stimulus-dependent suppression of chaos in recurrent neural networks. Physical Review E. 82(1). 11903–11903. 171 indexed citations
9.
George, Mark S., L. F. Abbott, & Steven A. Siegelbaum. (2009). HCN hyperpolarization-activated cation channels inhibit EPSPs by interactions with M-type K+ channels. Nature Neuroscience. 12(5). 577–584. 150 indexed citations
10.
Drew, Patrick J. & L. F. Abbott. (2003). Model of Song Selectivity and Sequence Generation in Area HVc of the Songbird. Journal of Neurophysiology. 89(5). 2697–2706. 37 indexed citations
11.
Chance, Frances S., Sacha B. Nelson, & L. F. Abbott. (1999). Complex cells as cortically amplified simple cells. Nature Neuroscience. 2(3). 277–282. 154 indexed citations
12.
O’Neil, Maggie, L. F. Abbott, Andrew A. Sharp, & Eve Marder. (1998). Dynamic clamp: computer-neural hybrids. MIT Press eBooks. 326–329. 3 indexed citations
13.
Liu, Zheng, Jorge Golowasch, Eve Marder, & L. F. Abbott. (1998). A Model Neuron with Activity-Dependent Conductances Regulated by Multiple Calcium Sensors. Journal of Neuroscience. 18(7). 2309–2320. 176 indexed citations
14.
Marom, Shimon & L. F. Abbott. (1994). Modeling state-dependent inactivation of membrane currents. Biophysical Journal. 67(2). 515–520. 49 indexed citations
15.
Abbott, L. F., Edward Farhi, & Sam Gutmann. (1991). The path integral for dendritic trees. Biological Cybernetics. 66(1). 49–60. 43 indexed citations
16.
Abbott, L. F. & Mark B. Wise. (1989). Wormholes and global symmetries. Nuclear Physics B. 325(3). 687–704. 128 indexed citations
17.
Abbott, L. F., et al.. (1988). Integral constraints in general relativity. Nuclear Physics B. 296(3). 710–716. 5 indexed citations
18.
Abbott, L. F. & Mark B. Wise. (1984). Gauge-invariant cosmological fluctuations of uncoupled fluids. Nuclear Physics B. 237(2). 226–236. 18 indexed citations
19.
Abbott, L. F., P. Sikivie, & Mark B. Wise. (1980). Constraints on charged-Higgs-boson couplings. Physical review. D. Particles, fields, gravitation, and cosmology/Physical review. D. Particles and fields. 21(5). 1393–1403. 122 indexed citations
20.
Abbott, L. F.. (1980). Choosing an Expansion Parameter for Quantum Chromodynamics. Physical Review Letters. 44(24). 1569–1572. 30 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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