astronomy

Larry Abbott

Larry Abbott is a astronomy topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Larry Abbott rather than just read about it. In short: Laurence Frederick Abbott (born 1950) is an American theoretical neuroscientist, who is currently the William Bloor Professor of Theoretical Neuroscience at Columbia University, where he helped create the Center for Theoretical Neuroscience. He is widely regarded as one of the leaders of theoretical neuroscience, and is coauthor, along with Peter Dayan, on the first comprehensive textbook on theoretical neuroscience…

Key takeaways

Larry Abbott belongs to astronomy; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Larry Abbott to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Larry Abbott from memory before moving on to harder problems.

Reference excerpt

Laurence Frederick Abbott (born 1950) is an American theoretical neuroscientist, who is currently the William Bloor Professor of Theoretical Neuroscience at Columbia University, where he helped create the Center for Theoretical Neuroscience. He is widely regarded as one of the leaders of theoretical neuroscience, and is coauthor, along with Peter Dayan, on the first comprehensive textbook on theoretical neuroscience, which is considered to be the standard text for students and researchers entering theoretical neuroscience. He helped invent the dynamic clamp method alongside Eve Marder. Abbott has received numerous awards for his work in the field, including memberships in the National Academy of Sciences and the American Academy of Arts and Sciences. In 2010, he received the Swartz Prize for Theoretical and Computational Neuroscience. In 2022 he was awarded the Gruber Neuroscience Prize. In 2024, he was awarded The Brain Prize for contributions to theoretical neuroscience, alongside Terrence Sejnowski and Haim Sompolinsky.

Biography Abbott attended Oberlin College from 1968 to 1971, where he received a bachelor's degree in physics. He subsequently attended graduate school at Brandeis University from 1973 to 1977, where he received his Ph.D. in physics.

Scientific career He subsequently worked in theoretical particle physics, serving as research associate at Stanford Linear Accelerator Center from 1977 to 1979, as a Scientific Associate at the Theory division at CERN from 1980 to 1981, and as a tenure track professor in the physics department at Brandeis from 1979 to 2005. Abbott began his transition to neuroscience research in 1989, joined the Department of Biology at Brandeis in 1993, and was the co-director of Brandeis Sloan Center for Theoretical Neurobiology from 1994 to 2002, the director of the Volen National Center for Complex Systems at Brandeis from 1997 to 2002, and a visiting faculty at UCSF Sloan Center for Theoretical Neuroscience from 1994 to 2002. At Brandeis, he held the position of the Nancy Lurie Marks Professor of Neuroscience from 1997 to 2002 and the Zalman Abraham Kekst Professor of Neuroscience from 2003 to 2005. In 2005, he joined the faculty of Columbia University, where he is currently a member of the Department of Neuroscience, and the Department of Physiology and Cellular Biophysics. He is co-director of the Center for Theoretical Neuroscience. He has been a senior fellow at HHMI Janelia Farm Research Campus since 2015.

Select publications

Abbott, L. F.; Varela, J. A.; Sen, Kamal; Nelson, S. B. (10 January 1997). "Synaptic Depression and Cortical Gain Control". Science. 275 (5297): 221–224. doi:10.1126/science.275.5297.221. ISSN 0036-8075. PMID 8985017. Song, Sen; Miller, Kenneth D.; Abbott, L. F. (September 2000). "Competitive Hebbian learning through spike-timing-dependent synaptic plasticity". Nature Neuroscience. 3 (9): 919–926. doi:10.1038/78829. ISSN 1546-1726. PMID 10966623. Sussillo, David; Abbott, L.F. (August 2009). "Generating Coherent Patterns of Activity from Chaotic Neural Networks". Neuron. 63 (4): 544–557. doi:10.1016/j.neuron.2009.07.018. PMC 2756108. PMID 19709635. Rajan, Kanaka; Abbott, L. F.; Sompolinsky, Haim (7 July 2010). "Stimulus-dependent suppression of chaos in recurrent neural networks". Physical Review E. 82 (1) 011903. arXiv:0912.3513. Bibcode:2010PhRvE..82a1903R. doi:10.1103/PhysRevE.82.011903. PMC 10683875. PMID 20866644. S2CID 946870. Vogels, T. P.; Abbott, L. (2009-03-22). "Gating multiple signals through detailed balance of excitation and inhibition in spiking networks". Nature Neuroscience. 12 (4): 483–491. doi:10.1038/nn.2276. PMC 2693069. PMID 19305402. Rajan, Kanaka; Abbott, L. F. (2 November 2006). "Eigenvalue Spectra of Random Matrices for Neural Networks" (PDF). Physical Review Letters. 97 (18) 188104. Bibcode:2006PhRvL..97r8104R. doi:10.1103/PhysRevLett.97.188104. PMID 17155583.

Awards, honors, and memberships

Published works Prinz, Astrid A.; Abbott, L.F.; Marder, Eve (April 2004). "The dynamic clamp comes of age" (PDF). Trends in Neurosciences. 27 (4). Elsevier: 218–224. doi:10.1016/j.tins.2004.02.004. PMID 15046881. S2CID 11246529. Archived from the original (PDF) on May 8, 2014. Retrieved May 15, 2015.

References

External links

Columbia Profile page Columbia Neurotheory page Simons Foundation Profile page National Academy of Science Member page

Worked examples

Example 1 — a first encounter with Larry Abbott

Start with the simplest possible case. Write down what Larry Abbott claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In astronomy, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Larry Abbott before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Larry Abbott ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Larry Abbott

In research: Larry Abbott appears in astronomy research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Larry Abbott in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Larry Abbott is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1950 births, American neuroscientists, American physicists, so understanding it makes those chapters shorter.
In everyday life: Look for Larry Abbott outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Larry Abbott in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Larry Abbott means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Larry Abbott out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Larry Abbott in simple terms?

Why does Larry Abbott matter?

Because it connects several astronomy ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Larry Abbott?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Larry Abbott.