Maya Jay
Impact in
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- Neurotransmitter Receptor Influence on Behavior
- Neuroscience and Neuropharmacology Research
- Neurobiology and Insect Physiology Research
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- Neural dynamics and brain function
- Memory and Neural Mechanisms
Papers in
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- Neuroscience and Neuropharmacology Research 1
- Neurotransmitter Receptor Influence on Behavior 1
- Neurobiology and Insect Physiology Research 1
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- Neural dynamics and brain function 2
- Memory and Neural Mechanisms 1
- Co-authors
- Scott W. Linderman (2 shared papers)Mohammed Abdal Monium Osman (2 shared papers)Caleb Weinreb (2 shared papers)Sandeep Robert Datta (2 shared papers)Winthrop F. Gillis (2 shared papers)David H. Brann (1 shared paper)Tomasz Kula (1 shared paper)Dorothy Koveal (1 shared paper)
- Partner nations
- United StatesSwitzerland
In The Last Decade
Maya Jay
3 papers receiving 142 citations
Maya Jay's Hit Papers
Peers
Comparison fields: 5 of 43
- Cellular and Molecular Neuroscience 70
- Cognitive Neuroscience 63
- Cell Biology 27
- Behavioral Neuroscience 4
- Developmental Biology 2
Countries citing papers authored by Maya Jay
This map shows the geographic impact of Maya Jay'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 Maya Jay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maya Jay more than expected).
Fields of papers citing papers by Maya Jay
This network shows the impact of papers produced by Maya Jay. 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 Maya Jay. The network helps show where Maya Jay may publish in the future.
Co-authors
The 25 scholars most cited alongside Maya Jay, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Spontaneous behaviour is structured by reinforcement without explicit reward Hit paper breakdown → | 2023 | 90 |
| 2 | Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics Hit paper breakdown → | 2024 | 48 |
| 3 | 2022 | 7 |
About Maya Jay
Maya Jay is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience, Cell Biology, Ecology, Evolution, Behavior and Systematics and Infectious Diseases, having authored 3 papers that have together received 145 indexed citations. Recurring topics across this work include Zebrafish Biomedical Research Applications (2 papers), Neural dynamics and brain function (2 papers), Memory and Neural Mechanisms (1 paper), Neuroscience and Neuropharmacology Research (1 paper), Neurotransmitter Receptor Influence on Behavior (1 paper), Animal Behavior and Reproduction (1 paper) and Neurobiology and Insect Physiology Research (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (70 citations), Cognitive Neuroscience (63 citations), Cell Biology (27 citations), Behavioral Neuroscience (4 citations) and Developmental Biology (2 citations). Maya Jay has collaborated with scholars based in United States and Switzerland. Frequent co-authors include Scott W. Linderman, Mohammed Abdal Monium Osman, Caleb Weinreb, Sandeep Robert Datta, Winthrop F. Gillis, David H. Brann, Tomasz Kula, Dorothy Koveal, Bernardo L. Sabatini and Jeffrey J. Wood. Their work appears in journals such as Nature Methods, Nature and Psychopharmacology.
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.