Raphael T. Gerraty

3.0k total citations · 1 hit paper
12 papers, 2.0k citations indexed

About

Raphael T. Gerraty is a scholar working on Cognitive Neuroscience, Neurology and Molecular Biology. According to data from OpenAlex, Raphael T. Gerraty has authored 12 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cognitive Neuroscience, 2 papers in Neurology and 1 paper in Molecular Biology. Recurrent topics in Raphael T. Gerraty's work include Functional Brain Connectivity Studies (8 papers), Neural dynamics and brain function (5 papers) and Neural and Behavioral Psychology Studies (5 papers). Raphael T. Gerraty is often cited by papers focused on Functional Brain Connectivity Studies (8 papers), Neural dynamics and brain function (5 papers) and Neural and Behavioral Psychology Studies (5 papers). Raphael T. Gerraty collaborates with scholars based in United States, Germany and Russia. Raphael T. Gerraty's co-authors include Matthew M. Kurtz, Kosha Ruparel, Ruben C. Gur, James Loughead, Raquel E. Gur, Mark A. Elliott, Theodore D. Satterthwaite, Håkon Håkonarson, Daniel H. Wolf and Monica E. Calkins and has published in prestigious journals such as Journal of Neuroscience, NeuroImage and Human Brain Mapping.

In The Last Decade

Raphael T. Gerraty

11 papers receiving 2.0k citations

Hit Papers

An improved framework for confound regression and filteri... 2012 2026 2016 2021 2012 400 800 1.2k
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.

  1. An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data
    2012 1.3k citations Theodore D. Satterthwaite, Mark A. Elliott et al. NeuroImage profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Raphael T. Gerraty United States 9 1.5k 525 426 368 132 12 2.0k
Charles J. Lynch United States 19 1.9k 1.3× 454 0.9× 387 0.9× 242 0.7× 153 1.2× 27 2.1k
Raimon Pruim Netherlands 7 1.4k 0.9× 481 0.9× 277 0.7× 288 0.8× 107 0.8× 16 1.7k
Weidan Pu China 25 1.1k 0.7× 476 0.9× 405 1.0× 401 1.1× 183 1.4× 54 1.5k
Joseph W. Dubis United States 7 2.0k 1.3× 706 1.3× 265 0.6× 422 1.1× 153 1.2× 7 2.3k
Anita D. Barber United States 22 1.5k 1.0× 386 0.7× 405 1.0× 263 0.7× 149 1.1× 45 1.8k
Alberto Llera Netherlands 17 1.4k 1.0× 478 0.9× 250 0.6× 289 0.8× 102 0.8× 39 1.8k
Crystal Cooper United States 20 1.0k 0.7× 621 1.2× 314 0.7× 378 1.0× 108 0.8× 39 1.7k
Xiaoqian J. Chai United States 22 2.1k 1.4× 552 1.1× 370 0.9× 607 1.6× 157 1.2× 44 2.5k
William R. Shirer United States 11 2.0k 1.4× 589 1.1× 357 0.8× 422 1.1× 127 1.0× 15 2.5k
Zhang-Ye Dong China 9 1.8k 1.2× 650 1.2× 332 0.8× 408 1.1× 209 1.6× 9 2.1k

Countries citing papers authored by Raphael T. Gerraty

Since Specialization
Citations

This map shows the geographic impact of Raphael T. Gerraty'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 Raphael T. Gerraty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphael T. Gerraty more than expected).

Fields of papers citing papers by Raphael T. Gerraty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Raphael T. Gerraty. 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 Raphael T. Gerraty. The network helps show where Raphael T. Gerraty may publish in the future.

Co-authorship network of co-authors of Raphael T. Gerraty

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

All Works

12 of 12 papers shown
1.
Montaser‐Kouhsari, Leila, Jonathan Nicholas, Raphael T. Gerraty, & Daphna Shohamy. (2025). Differentiating Reinforcement Learning and Episodic Memory in Value-Based Decisions in Parkinson's Disease. Journal of Neuroscience. 45(21). e0911242025–e0911242025.
2.
Gerraty, Raphael T., Allison C. Provost, Lin Li, et al.. (2023). Machine learning within the Parkinson’s progression markers initiative: Review of the current state of affairs. Frontiers in Aging Neuroscience. 15. 1076657–1076657. 16 indexed citations
3.
Dundon, Neil M., Raphael T. Gerraty, J. Michael Tyszka, et al.. (2022). Reinforcement learning with associative or discriminative generalization across states and actions: fMRI at 3 T and 7 T. Human Brain Mapping. 43(15). 4750–4790. 7 indexed citations
4.
Gerraty, Raphael T., et al.. (2021). Hierarchical Bayesian models of reinforcement learning: Introduction and comparison to alternative methods. Journal of Mathematical Psychology. 105. 102602–102602. 6 indexed citations
5.
Gerraty, Raphael T., Juliet Y. Davidow, Karin Foerde, et al.. (2018). Dynamic Flexibility in Striatal-Cortical Circuits Supports Reinforcement Learning. Journal of Neuroscience. 38(10). 2442–2453. 64 indexed citations
6.
Liu, Xueqing, Raphael T. Gerraty, Jack Grinband, David Parker, & Qolamreza Razlighi. (2017). Brain atrophy can introduce age‐related differences in BOLD response. Human Brain Mapping. 38(7). 3402–3414. 12 indexed citations
7.
Gerraty, Raphael T., Juliet Y. Davidow, G. Elliott Wimmer, Itamar Kahn, & Daphna Shohamy. (2014). Transfer of Learning Relates to Intrinsic Connectivity between Hippocampus, Ventromedial Prefrontal Cortex, and Large-Scale Networks. Journal of Neuroscience. 34(34). 11297–11303. 60 indexed citations
8.
Roalf, David R., Kosha Ruparel, Raquel E. Gur, et al.. (2013). Neuroimaging predictors of cognitive performance across a standardized neurocognitive battery.. Neuropsychology. 28(2). 161–176. 52 indexed citations
9.
Falcone, Mary, E. Paul Wileyto, Kosha Ruparel, et al.. (2013). Age‐related differences in working memory deficits during nicotine withdrawal. Addiction Biology. 19(5). 907–917. 36 indexed citations
10.
Satterthwaite, Theodore D., Kosha Ruparel, James Loughead, et al.. (2012). Being right is its own reward: Load and performance related ventral striatum activation to correct responses during a working memory task in youth. NeuroImage. 61(3). 723–729. 107 indexed citations
11.
Satterthwaite, Theodore D., Mark A. Elliott, Raphael T. Gerraty, et al.. (2012). An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data. NeuroImage. 64. 240–256. 1302 indexed citations breakdown →
12.
Kurtz, Matthew M. & Raphael T. Gerraty. (2009). A meta-analytic investigation of neurocognitive deficits in bipolar illness: Profile and effects of clinical state.. Neuropsychology. 23(5). 551–562. 309 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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