Jeffrey M. Miller

4.8k total citations · 1 hit paper
117 papers, 3.3k citations indexed

About

Jeffrey M. Miller is a scholar working on Cognitive Neuroscience, Pharmacology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Jeffrey M. Miller has authored 117 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Cognitive Neuroscience, 25 papers in Pharmacology and 19 papers in Cellular and Molecular Neuroscience. Recurrent topics in Jeffrey M. Miller's work include Functional Brain Connectivity Studies (31 papers), Treatment of Major Depression (24 papers) and Neurotransmitter Receptor Influence on Behavior (15 papers). Jeffrey M. Miller is often cited by papers focused on Functional Brain Connectivity Studies (31 papers), Treatment of Major Depression (24 papers) and Neurotransmitter Receptor Influence on Behavior (15 papers). Jeffrey M. Miller collaborates with scholars based in United States, China and Egypt. Jeffrey M. Miller's co-authors include J. John Mann, María A. Oquendo, M. Elizabeth Sublette, Ramin V. Parsey, R. Todd Ogden, Son V. Pham, Anne‐Catrin Uhlemann, Stephanie Cheung, Ariel Goldenthal and Graham D. Farquhar and has published in prestigious journals such as Journal of Clinical Oncology, NeuroImage and American Journal of Psychiatry.

In The Last Decade

Jeffrey M. Miller

115 papers receiving 3.2k citations

Hit Papers

align trajectories

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.

Systematic Review of Gut Microbiota and Major Depression

2019 426 citations Ariel Goldenthal, J. John Mann et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jeffrey M. Miller United States	30	676	658	553	429	414	117	3.3k
Xin‐Min Li Canada	37	414 0.6×	800 1.2×	486 0.9×	179 0.4×	738 1.8×	141	4.2k
Brent Myers United States	37	441 0.7×	524 0.8×	803 1.5×	197 0.5×	692 1.7×	76	5.0k
Helge Frieling Germany	35	398 0.6×	1.3k 2.0×	351 0.6×	394 0.9×	665 1.6×	215	4.2k
Carlo Altamura Italy	25	242 0.4×	302 0.5×	756 1.4×	282 0.7×	334 0.8×	56	2.8k
Michael Deuschle Germany	43	886 1.3×	509 0.8×	977 1.8×	430 1.0×	529 1.3×	191	6.7k
Élisabeth Lambert Australia	55	379 0.6×	657 1.0×	177 0.3×	346 0.8×	323 0.8×	226	9.3k
Renato Polimanti United States	33	220 0.3×	1.2k 1.8×	239 0.4×	195 0.5×	262 0.6×	187	3.7k
David E. Bush United States	41	1.1k 1.7×	458 0.7×	200 0.4×	232 0.5×	984 2.4×	79	8.2k
James Hill United States	46	677 1.0×	882 1.3×	297 0.5×	450 1.0×	1.3k 3.2×	170	7.0k
Hongxing Zhang China	37	992 1.5×	1.4k 2.1×	513 0.9×	348 0.8×	1.0k 2.5×	240	5.0k

Countries citing papers authored by Jeffrey M. Miller

Since Specialization

Citations

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

Fields of papers citing papers by Jeffrey M. Miller

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeffrey M. Miller. 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 Jeffrey M. Miller. The network helps show where Jeffrey M. Miller may publish in the future.

Co-authorship network of co-authors of Jeffrey M. Miller

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

All Works

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20 of 20 papers shown

Goldenthal, Ariel, Evan Lieberman, Mina Rizk, et al.. (2024). Relationships between serotonin 1A receptor DNA methylation, self-reported history of childhood abuse and gray matter volume in major depression. Journal of Affective Disorders. 367. 307–317. 1 indexed citations

Galer, Peter D., David Lewis‐Smith, Shridhar Parthasarathy, et al.. (2023). Enriching representation learning using 53 million patient notes through human phenotype ontology embedding. Artificial Intelligence in Medicine. 139. 102523–102523. 10 indexed citations

Bartlett, Elizabeth, et al.. (2023). Dynamic Human Brain Imaging with a Portable PET Camera: Comparison to a Standard Scanner. Journal of Nuclear Medicine. 65(2). 320–326. 1 indexed citations

Bartlett, Elizabeth, Francesca Zanderigo, Bárbara Stanley, et al.. (2023). In vivo serotonin transporter and 1A receptor binding potential and ecological momentary assessment (EMA) of stress in major depression and suicidal behavior. European Neuropsychopharmacology. 70. 1–13. 7 indexed citations

Lewis, S.H., et al.. (2023). Nd:YAG Laser Capsulotomy: Efficacy and Outcomes Performed by Optometrists. Optometry and Vision Science. 100(10). 665–669. 3 indexed citations

Lan, Martin J., Francesca Zanderigo, Spiro P. Pantazatos, et al.. (2022). Serotonin 1A Receptor Binding of [11C]CUMI-101 in Bipolar Depression Quantified Using Positron Emission Tomography: Relationship to Psychopathology and Antidepressant Response. The International Journal of Neuropsychopharmacology. 25(7). 534–544. 3 indexed citations

Smart, Kelly, María A. Oquendo, J. John Mann, et al.. (2021). Data-driven analysis of kappa opioid receptor binding in major depressive disorder measured by positron emission tomography. Translational Psychiatry. 11(1). 602–602. 2 indexed citations

Tu, Tao, Jeffrey M. Miller, Francesca Zanderigo, et al.. (2020). Large-scale network dynamics in neural response to emotionally negative stimuli linked to serotonin 1A binding in major depressive disorder. Molecular Psychiatry. 26(6). 2393–2401. 15 indexed citations

Rubin‐Falcone, Harry, Jochen Weber, Ronit Kishon, et al.. (2019). Neural predictors and effects of cognitive behavioral therapy for depression: the role of emotional reactivity and regulation. Psychological Medicine. 50(1). 146–160. 29 indexed citations

10.

Rubin‐Falcone, Harry, R. Todd Ogden, Xuejing Lin, et al.. (2019). Antidepressant medication exposure and 5‐HT_1A autoreceptor binding in major depressive disorder. Synapse. 73(6). e22089–e22089. 16 indexed citations

11.

Doré, Bruce, Alexa Hubbard, Jochen Weber, et al.. (2018). Negative Autobiographical Memory in Depression Reflects Elevated Amygdala-Hippocampal Reactivity and Hippocampally Associated Emotion Regulation. Biological Psychiatry Cognitive Neuroscience and Neuroimaging. 3(4). 358–366. 36 indexed citations

12.

Michel, Jeremy J., Alexander G. Fiks, Stephanie L. Mayne, et al.. (2018). A Technology Driven Approach for Sharing Patient-Reported Outcomes in ADHD between Parents, Pediatricians and Teachers. PEDIATRICS. 142. 618–618. 1 indexed citations

13.

Miller, Jeffrey M., Seonjoo Lee, Harry Rubin‐Falcone, et al.. (2016). Omega-3 polyunsaturated fatty acid supplementation and white matter changes in major depression. Journal of Psychiatric Research. 75. 65–74. 52 indexed citations

14.

Sullivan, Gregory M., María A. Oquendo, Matthew S. Milak, et al.. (2014). Positron Emission Tomography Quantification of Serotonin_1AReceptor Binding in Suicide Attempters With Major Depressive Disorder. JAMA Psychiatry. 72(2). 169–169. 69 indexed citations

15.

Lan, Martin J., R. Todd Ogden, Yung‐yu Huang, et al.. (2014). Genetic variation in brain-derived neurotrophic factor val66met allele is associated with altered serotonin-1A receptor binding in human brain. NeuroImage. 94. 33–39. 10 indexed citations

16.

Miller, Jeffrey M., Natalie Hesselgrave, R. Todd Ogden, et al.. (2013). Positron Emission Tomography Quantification of Serotonin Transporter in Suicide Attempters with Major Depressive Disorder. Biological Psychiatry. 74(4). 287–295. 84 indexed citations

17.

Kikuchi, Toshiaki, et al.. (2012). Neural responses to incongruency in a blocked-trial Stroop fMRI task in major depressive disorder. Journal of Affective Disorders. 143(1-3). 241–247. 27 indexed citations

18.

Parsey, Ramin V., R. Todd Ogden, Jeffrey M. Miller, et al.. (2010). Higher Serotonin 1A Binding in a Second Major Depression Cohort: Modeling and Reference Region Considerations. Biological Psychiatry. 68(2). 170–178. 126 indexed citations

19.

Miller, Jeffrey M., Erin L. Kinnally, R. Todd Ogden, et al.. (2009). Reported childhood abuse is associated with low serotonin transporter binding in vivo in major depressive disorder. Synapse. 63(7). 565–573. 67 indexed citations

20.

Wilkinson, Alan, H. Albin Gritsch, Phuong‐Chi Pham, et al.. (2002). Monotherapy with the anti-cd20 monoclonal antibody rituximab in a kidney transplant recipient with posttransplant lymphoproliferative disease. Transplantation Proceedings. 34(4). 1178–1181. 14 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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