Stephanie Nelli

653 total citations · 1 hit paper
6 papers, 307 citations indexed

About

Stephanie Nelli is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Artificial Intelligence. According to data from OpenAlex, Stephanie Nelli has authored 6 papers receiving a total of 307 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Cognitive Neuroscience, 2 papers in Cellular and Molecular Neuroscience and 2 papers in Artificial Intelligence. Recurrent topics in Stephanie Nelli's work include Neural dynamics and brain function (4 papers), Neural Networks and Applications (2 papers) and Visual perception and processing mechanisms (2 papers). Stephanie Nelli is often cited by papers focused on Neural dynamics and brain function (4 papers), Neural Networks and Applications (2 papers) and Visual perception and processing mechanisms (2 papers). Stephanie Nelli collaborates with scholars based in United Kingdom, United States and Canada. Stephanie Nelli's co-authors include Christopher Summerfield, Andrew Saxe, John T. Serences, Ramesh Srinivasan, Sirawaj Itthipuripat, Hannah Sheahan, Fabrice Luyckx, Tsvetomira Dumbalska, Antoniette M. Maldonado‐Devincci and Danielle Morrow and has published in prestigious journals such as Nature Communications, Neuron and Nature reviews. Neuroscience.

In The Last Decade

Stephanie Nelli

6 papers receiving 302 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

If deep learning is the answer, what is the question?

2020 208 citations Andrew Saxe, Stephanie Nelli et al. Nature reviews. Neuroscience profile →

Peers

Stephanie Nelli

CN

AI

CMN

CVPR

EEE

Dhruva Tirumala United Kingdom

Chang Cai China

S. Pravin Kumar India

Dimitrije Marković Germany

Xuyun Wen China

Stephanie C. Y. Chan United States

Luca Ambrogioni Netherlands

Jacob M.J. Murre Netherlands

Christian Huyck United Kingdom

Martí Sánchez-Fibla Spain

Dhruva Tirumala United Kingdom

Stephanie Nelli

229 ×1.2

CN

109 ×1.3

AI

52 ×1.6

CMN

16 ×0.5

CVPR

39 ×1.8

EEE

Citations per year, relative to Stephanie Nelli Stephanie Nelli (= 1×) peers Dhruva Tirumala

Countries citing papers authored by Stephanie Nelli

Since Specialization

Citations

This map shows the geographic impact of Stephanie Nelli'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 Stephanie Nelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephanie Nelli more than expected).

Fields of papers citing papers by Stephanie Nelli

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephanie Nelli. 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 Stephanie Nelli. The network helps show where Stephanie Nelli may publish in the future.

Co-authorship network of co-authors of Stephanie Nelli

This figure shows the co-authorship network connecting the top 25 collaborators of Stephanie Nelli. A scholar is included among the top collaborators of Stephanie Nelli 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 Stephanie Nelli. Stephanie Nelli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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6 of 6 papers shown

1.

Nelli, Stephanie, et al.. (2023). Neural knowledge assembly in humans and neural networks. Neuron. 111(9). 1504–1516.e9. 18 indexed citations

2.

Sheahan, Hannah, et al.. (2021). Neural state space alignment for magnitude generalization in humans and recurrent networks. Neuron. 109(7). 1214–1226.e8. 28 indexed citations

3.

Nelli, Stephanie, et al.. (2021). Individual Alpha Frequency Determines the Impact of Bottom-Up Drive on Visual Processing. Cerebral Cortex Communications. 2(2). tgab032–tgab032. 3 indexed citations

4.

Saxe, Andrew, Stephanie Nelli, & Christopher Summerfield. (2020). If deep learning is the answer, what is the question?. Nature reviews. Neuroscience. 22(1). 55–67. 208 indexed citations breakdown →

5.

Nelli, Stephanie, Sirawaj Itthipuripat, Ramesh Srinivasan, & John T. Serences. (2017). Fluctuations in instantaneous frequency predict alpha amplitude during visual perception. Nature Communications. 8(1). 2071–2071. 39 indexed citations

6.

Nelli, Stephanie, et al.. (2014). Ethanol Alters Local Cellular Levels of (3α,5α)-3-Hydroxypregnan-20-one (3α,5α-THP) Independent of the Adrenals in Subcortical Brain Regions. Neuropsychopharmacology. 39(8). 1978–1987. 11 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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