Ravi D. Mill

1.9k total citations
26 papers, 1.0k citations indexed

About

Ravi D. Mill is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Experimental and Cognitive Psychology. According to data from OpenAlex, Ravi D. Mill has authored 26 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Cognitive Neuroscience, 4 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Experimental and Cognitive Psychology. Recurrent topics in Ravi D. Mill's work include Functional Brain Connectivity Studies (17 papers), Neural dynamics and brain function (14 papers) and EEG and Brain-Computer Interfaces (7 papers). Ravi D. Mill is often cited by papers focused on Functional Brain Connectivity Studies (17 papers), Neural dynamics and brain function (14 papers) and EEG and Brain-Computer Interfaces (7 papers). Ravi D. Mill collaborates with scholars based in United States, United Kingdom and Netherlands. Ravi D. Mill's co-authors include Michael W. Cole, Takuya Ito, Douglas H. Schultz, Carrisa V. Cocuzza, Richard H. Chen, Richard J. Chen, Rebecca Knight, Hugo J. Spiers, Amir‐Homayoun Javadi and Yichao Yu and has published in prestigious journals such as Nature Communications, Nature Neuroscience and NeuroImage.

In The Last Decade

Ravi D. Mill

22 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ravi D. Mill United States 14 946 198 170 92 53 26 1.0k
Alfred B. Yu United States 10 535 0.6× 143 0.7× 101 0.6× 72 0.8× 19 0.4× 17 837
Jingwei Li China 18 1.3k 1.4× 534 2.7× 389 2.3× 76 0.8× 130 2.5× 46 1.9k
Stephanie A. McMains United States 12 1.3k 1.4× 73 0.4× 214 1.3× 51 0.6× 47 0.9× 18 1.4k
Alessio Fracasso Netherlands 20 948 1.0× 360 1.8× 121 0.7× 69 0.8× 21 0.4× 65 1.3k
Lorena Deuker Germany 14 1.4k 1.5× 80 0.4× 279 1.6× 435 4.7× 66 1.2× 15 1.5k
Shahin Nasr United States 16 947 1.0× 134 0.7× 150 0.9× 76 0.8× 25 0.5× 47 1.1k
Marcelo G. Mattar United States 16 952 1.0× 101 0.5× 227 1.3× 169 1.8× 9 0.2× 29 1.1k
Mark Jarmasz Canada 8 444 0.5× 166 0.8× 62 0.4× 52 0.6× 104 2.0× 15 642
Jascha D. Swisher United States 14 1.3k 1.4× 82 0.4× 276 1.6× 98 1.1× 15 0.3× 19 1.4k
Jv Haxby United States 3 1.2k 1.3× 132 0.7× 244 1.4× 33 0.4× 23 0.4× 5 1.3k

Countries citing papers authored by Ravi D. Mill

Since Specialization
Citations

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

Fields of papers citing papers by Ravi D. Mill

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ravi D. Mill. 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 Ravi D. Mill. The network helps show where Ravi D. Mill may publish in the future.

Co-authorship network of co-authors of Ravi D. Mill

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

All Works

20 of 20 papers shown
1.
2.
Mill, Ravi D. & Michael W. Cole. (2025). Dynamically shifting from compositional to conjunctive brain representations supports cognitive task learning. Nature Communications. 16(1). 10084–10084.
3.
Sánchez-Romero, Rubén, et al.. (2025). Regularized partial correlation provides reliable functional connectivity estimates while correcting for widespread confounding. Imaging Neuroscience. 3. 1 indexed citations
4.
Reid, Andrew, Yu Zhang, Ravi D. Mill, et al.. (2025). Right posterior theta reflects human parahippocampal phase resetting by salient cues during goal-directed navigation. Imaging Neuroscience. 3.
5.
Mill, Ravi D., et al.. (2024). Acute psychosocial stress modulates neural and behavioral substrates of cognitive control. Human Brain Mapping. 45(8). e26716–e26716. 3 indexed citations
6.
7.
Cocuzza, Carrisa V., Rubén Sánchez-Romero, Takuya Ito, et al.. (2024). Distributed network flows generate localized category selectivity in human visual cortex. PLoS Computational Biology. 20(10). e1012507–e1012507. 1 indexed citations
8.
Sánchez-Romero, Rubén, Takuya Ito, Ravi D. Mill, Stephen José Hanson, & Michael W. Cole. (2023). Causally informed activity flow models provide mechanistic insight into network-generated cognitive activations. NeuroImage. 278. 120300–120300. 6 indexed citations
9.
Keane, Brian P., Bart Krekelberg, Ravi D. Mill, et al.. (2022). Dorsal attention network activity during perceptual organization is distinct in schizophrenia and predictive of cognitive disorganization. European Journal of Neuroscience. 57(3). 458–478. 8 indexed citations
10.
Mill, Ravi D., et al.. (2022). Network modeling of dynamic brain interactions predicts emergence of neural information that supports human cognitive behavior. PLoS Biology. 20(8). e3001686–e3001686. 8 indexed citations
11.
Keane, Brian P., Deanna M. Barch, Ravi D. Mill, et al.. (2021). Brain network mechanisms of visual shape completion. NeuroImage. 236. 118069–118069. 14 indexed citations
12.
Hearne, Luke J., Ravi D. Mill, Brian P. Keane, et al.. (2021). Activity flow underlying abnormalities in brain activations and cognition in schizophrenia. Science Advances. 7(29). 22 indexed citations
13.
Ito, Takuya, Scott L. Brincat, Markus Siegel, et al.. (2020). Task-evoked activity quenches neural correlations and variability across cortical areas. PLoS Computational Biology. 16(8). e1007983–e1007983. 64 indexed citations
14.
Mill, Ravi D., Brian A. Gordon, David A. Balota, & Michael W. Cole. (2020). Predicting dysfunctional age-related task activations from resting-state network alterations. NeuroImage. 221. 117167–117167. 25 indexed citations
15.
Reid, Andrew, Drew B. Headley, Ravi D. Mill, et al.. (2019). Advancing functional connectivity research from association to causation. Nature Neuroscience. 22(11). 1751–1760. 194 indexed citations
16.
Ito, Takuya, Kaustubh Kulkarni, Douglas H. Schultz, et al.. (2017). Cognitive task information is transferred between brain regions via resting-state network topology. Nature Communications. 8(1). 1027–1027. 121 indexed citations
17.
Mill, Ravi D., Takuya Ito, & Michael W. Cole. (2017). From connectome to cognition: The search for mechanism in human functional brain networks. NeuroImage. 160. 124–139. 72 indexed citations
18.
Mill, Ravi D., Akira R. O’Connor, & Ian G. Dobbins. (2016). Pupil dilation during recognition memory: Isolating unexpected recognition from judgment uncertainty. Cognition. 154. 81–94. 21 indexed citations
19.
Javadi, Amir‐Homayoun, et al.. (2014). The Hippocampus and Entorhinal Cortex Encode the Path and Euclidean Distances to Goals during Navigation. Current Biology. 24(12). 1331–1340. 185 indexed citations
20.
Mill, Ravi D. & Akira R. O’Connor. (2014). Question format shifts bias away from the emphasised response in tests of recognition memory. Consciousness and Cognition. 30. 91–104. 10 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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