Leo Zsembik

1.1k total citations
3 papers, 18 citations indexed

About

Leo Zsembik is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, Leo Zsembik has authored 3 papers receiving a total of 18 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Cognitive Neuroscience, 1 paper in Cellular and Molecular Neuroscience and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Leo Zsembik's work include Functional Brain Connectivity Studies (1 paper), Neuroscience and Neuropharmacology Research (1 paper) and Neural dynamics and brain function (1 paper). Leo Zsembik is often cited by papers focused on Functional Brain Connectivity Studies (1 paper), Neuroscience and Neuropharmacology Research (1 paper) and Neural dynamics and brain function (1 paper). Leo Zsembik collaborates with scholars based in United States. Leo Zsembik's co-authors include Dipanwita Pati, Takayuki Yoshida, Mahmoud Mostapha, John J. O’Malley, Martin Styner, Stephen M. Pizer, Aaron Limoges, Thomas L. Kash, Mio Nonaka and Andrew Holmes and has published in prestigious journals such as Nature, Nature Neuroscience and PubMed.

In The Last Decade

Leo Zsembik

2 papers receiving 18 citations

Peers

Countries citing papers authored by Leo Zsembik

Since Specialization

Citations

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

Fields of papers citing papers by Leo Zsembik

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leo Zsembik

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

All Works

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3 of 3 papers shown

#	Work	Indexed citations
1	Duration between rewards controls the rate of behavioral and dopaminergic learning 2026 ·Nature Neuroscience ·Dennis A. Burke, (unknown), Huijeong Jeong, (unknown), Leo Zsembik, (unknown), Joseph R Floeder, (unknown), Ritchie Chen, (unknown)	0
2	A distinct cortical code for socially learned threat 2024 ·Nature ·(unknown), (unknown), Olena Bukalo, Dipanwita Pati, (unknown), Aaron Limoges, Leo Zsembik, Takayuki Yoshida, John J. O’Malley, Ronald F. Paletzki, (unknown), Mio Nonaka, Karl Deisseroth, Charles R. Gerfen, Mario A. Penzo, Thomas L. Kash, Andrew Holmes	14
3	Non-Euclidean, convolutional learning on cortical brain surfaces 2018 ·PubMed ·Mahmoud Mostapha, (unknown), Guorong Wu, Leo Zsembik, Stephen M. Pizer, Martin Styner	4

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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