Steven Greening: h-index, Total Citations, and Citation Map
Steven Greening's h-index is 27 (40 i10-index, 2,497+ total citations across 4+ publications) according to Google Scholar as of May 2026. Steven Greening is affiliated with Associate Professor, University of Manitoba.
Steven Greening is a researcher affiliated with Associate Professor, University of Manitoba, specializing in Affective Neuroscience, Cognitive Neuroscience, Social Neuroscience. Their work has been cited 2,497 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Steven Greening's Citation Metrics
Bibliometric impact based on 4 indexed publications.
- H-Index
- 27
- i10-Index
- 40
- Total Citations
- 2,497
- Citing Countries
- 10
As of May 2026.
Steven Greening has an h-index of 27 and 2,497 total citations across 4 publications, with research cited by institutions in 10 countries.
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Global Impact Map
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Top Cited Works
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Neuromelanin marks the spot: identifying a locus coeruleus biomarker of cognitive reserve in healthy aging
2016272
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Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
The researcher identified neuromelanin as a potential biomarker for cognitive reserve in healthy aging, establishing a novel link between locus coeruleus integrity and cognitive function.
The researcher advanced the understanding of emotional awareness by identifying multiple neural mechanisms, establishing a foundational framework for studying the neural correlates of consciousness.
The researcher pioneered the application of machine learning to characterize abstraction in neural representations through multivariate cross-classification, establishing a foundational methodological framework in cognitive neuroscience.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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