🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

John M. Henderson

Atmospheric and Environmental Research

ORCID: 0000-0003-1975-4251

Also affiliated with University of California, Davis

NeuroscienceComputer ScienceEnvironmental Science

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 3%percentile

1.2Author DataRank

Indexed papers

1in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Why this DataRank?

An author's DataRank is the sum of the DataRanks of all 1 indexed paper attributed to them. A prolific author with many moderate-impact papers can outrank one with a single high-impact paper.

Author scores recompute whenever paper DataRanks are refreshed, so this number lags the underlying paper scores by at most one batch run.

Read the full methodology →

The highest-impact dataset this researcher has shared, ranked by DataRank — the single contribution doing the most to lift their data-sharing standing.

Eye Movements in Real-World Scene Photographs: General Characteristics and Effects of Viewing Task

Frontiers in Psychology(2020)10.3389/fpsyg.2019.02915

Top 17%

1.2DataRank

Top 17%52 citations

Elizabeth H. Hall, Jessica Goold, Taylor R. Hayes, John M. Henderson, Deborah Cronin

Papers

Driven by 17 papers — median percentile 83. Top paper: “Eye Movements in Real-World Scene Photographs: General Characteristics and Effects of Viewing Task”.

Eye Movements in Real-World Scene Photographs: General Characteristics and Effects of Viewing Task

Frontiers in Psychology(2020)10.3389/fpsyg.2019.02915

Top 17%

1.2DataRank

Top 17%52 citations

Elizabeth H. Hall, Jessica Goold, Taylor R. Hayes, John M. Henderson, Deborah Cronin

Deep saliency models learn low-, mid-, and high-level features to predict scene attention

Scientific Reports(2021)10.1038/s41598-021-97879-z

N/A

0.770DataRank · unranked

26 citations

John M. Henderson, Taylor R. Hayes

Developmental changes in natural scene viewing in infancy.

Developmental Psychology(2021)10.1037/dev0001020

N/A

0.762DataRank · unranked

30 citations

Taylor R. Hayes, Mee‐Kyoung Kwon, John M. Henderson, Lisa M. Oakes, Katherine I. Pomaranski

Meaning maps capture the density of local semantic features in scenes: A reply to Pedziwiatr, Kümmerer, Wallis, Bethge & Teufel (2021)

Cognition(2021)10.1016/j.cognition.2021.104742

N/A

0.724DataRank · unranked

18 citations

Taylor R. Hayes, Candace E. Peacock, Gwendolyn Rehrig, John M. Henderson

Meaning maps detect the removal of local semantic scene content but deep saliency models do not

Attention Perception & Psychophysics(2022)10.3758/s13414-021-02395-x

N/A

0.475DataRank · unranked

12 citations

John M. Henderson, Taylor R. Hayes

Center Bias Does Not Account for the Advantage of Meaning Over Salience in Attentional Guidance During Scene Viewing

Frontiers in Psychology(2020)10.3389/fpsyg.2020.01877

N/A

0.449DataRank · unranked

19 citations

Taylor R. Hayes, John M. Henderson, Candace E. Peacock

Eye movements dissociate between perceiving, sensing, and unconscious change detection in scenes

Psychonomic Bulletin & Review(2022)10.3758/s13423-022-02122-z

N/A

0.345DataRank · unranked

9 citations

John M. Henderson, Andrew P. Yonelinas, Michelle M. Ramey

Searching for meaning: Local scene semantics guide attention during natural visual search in scenes

Quarterly Journal of Experimental Psychology(2022)10.1177/17470218221101334

N/A

0.330DataRank · unranked

8 citations

Praveena Singh, Taylor R. Hayes, Gwendolyn Rehrig, John M. Henderson, Candace E. Peacock

When more is more: redundant modifiers can facilitate visual search

Cognitive Research Principles and Implications(2021)10.1186/s41235-021-00275-4

N/A

0DataRank · unranked

12 citations

Reese A. Cullimore, John M. Henderson, Fernanda Ferreira, Gwendolyn Rehrig

What do deep saliency models learn about where we look in scenes?

Research Square(2021)10.21203/rs.3.rs-420396/v1

N/A

0DataRank · unranked

0 citations

John M. Henderson, Taylor R. Hayes

Objects are selected for attention based upon meaning during passive scene viewing

Psychonomic Bulletin & Review(2023)10.3758/s13423-023-02286-2

N/A

0DataRank · unranked

3 citations

Elizabeth H. Hall, John M. Henderson, Candace E. Peacock

The role of local meaning in infants' fixations of natural scenes

Infancy(2024)10.1111/infa.12582

N/A

0DataRank · unranked

13 citations

Taylor R. Hayes, Shannon M. Klotz, Katherine I. Pomaranski, John M. Henderson, Lisa M. Oakes

Where the action could be: Speakers look at graspable objects and meaningful scene regions when describing potential actions.

Journal of Experimental Psychology Learning Memory and Cognition(2020)10.1037/xlm0000837

N/A

0DataRank · unranked

25 citations

Candace E. Peacock, Taylor R. Hayes, John M. Henderson, Fernanda Ferreira, Gwendolyn Rehrig

Episodic memory and semantic knowledge interact to guide eye movements during visual search in scenes: Distinct effects of conscious and unconscious memory

Psychonomic Bulletin & Review(2025)10.3758/s13423-025-02686-6

N/A

0DataRank · unranked

5 citations

John M. Henderson, Andrew P. Yonelinas, Michelle M. Ramey

Why do we retrace our visual steps? Semantic and episodic memory in gaze reinstatement

Learning & Memory(2020)10.1101/lm.051227.119

N/A

0DataRank · unranked

19 citations

Andrew P. Yonelinas, John M. Henderson, Michelle M. Ramey

Visual and verbal working memory loads interfere with scene-viewing

Attention Perception & Psychophysics(2020)10.3758/s13414-020-02076-1

N/A

0DataRank · unranked

26 citations

Candace E. Peacock, John M. Henderson, Deborah Cronin

The spatial distribution of attention predicts familiarity strength during encoding and retrieval.

Journal of Experimental Psychology General(2020)10.1037/xge0000758

N/A

0DataRank · unranked

20 citations

John M. Henderson, Andrew P. Yonelinas, Michelle M. Ramey