Population Neural Models
Population Neural Models is a computational framework in neural system modeling that characterizes the collective dynamics of large groups of neurons through aggregated variables, distinguishing itself from single-neuron or circuit-level models by focusing on statistical population behaviors and emergent network properties.
248
Publications
24K
Citations
636
Authors
334
Institutions
Publications per year
2017–2026
80
Parents
248
Weak pairwise correlations imply strongly correlated network states in a neural population
Elad Schneidman, Michael J. Berry, Ronen Segev et al. · Nature · 2006 · 1.9K citations · Full text
Designing neural networks through neuroevolution
Kenneth O. Stanley, Jeff Clune, Joel Lehman et al. · Nature Machine Intelligence · 2018 · 689 citations
1–5 of 248
636
7
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Courant Institute of Mathematical Sciences, United States
6 publications · 491 citations
6
h-index
5
h-index
5
h-index
1–5 of 636
334
Princeton University
Princeton, United States
11 h-index
23 publications
4.8K citations

Howard Hughes Medical Institute
Chevy Chase, United States
10 h-index
25 publications
4.4K citations

Centre National de la Recherche Scientifique
Paris, France
10 h-index
20 publications
1.5K citations
New York University
New York, United States
9 h-index
19 publications
1.7K citations
University College London
London, United Kingdom
8 h-index
15 publications
1.5K citations
University of Chicago
Chicago, United States
8 h-index
14 publications
9.3K citations
Harvard University
Cambridge, United States
8 h-index
13 publications
2K citations

Sorbonne Université
Paris, France
8 h-index
13 publications
513 citations
1–8 of 334
16 publications · 1K citations
14
h-index
12 publications · 489 citations
12
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Repository · 9 publications · 260 citations
9
h-index
8 publications · 577 citations
8
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8 publications · 2.5K citations
8
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1–5