Megan A. Miller

673 total citations
17 papers, 493 citations indexed

About

Megan A. Miller is a scholar working on Endocrine and Autonomic Systems, Experimental and Cognitive Psychology and Molecular Biology. According to data from OpenAlex, Megan A. Miller has authored 17 papers receiving a total of 493 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Endocrine and Autonomic Systems, 5 papers in Experimental and Cognitive Psychology and 3 papers in Molecular Biology. Recurrent topics in Megan A. Miller's work include Circadian rhythm and melatonin (9 papers), Sleep and related disorders (4 papers) and Sleep and Wakefulness Research (3 papers). Megan A. Miller is often cited by papers focused on Circadian rhythm and melatonin (9 papers), Sleep and related disorders (4 papers) and Sleep and Wakefulness Research (3 papers). Megan A. Miller collaborates with scholars based in United States and United Kingdom. Megan A. Miller's co-authors include Kathryn A. Roecklein, Shannon D. Donofry, Yvette P. Conley, Amy K. Wagner, Joelle M. Scanlon, Dianxu Ren, Patricia Wong, Stephen B. Manuck, Brant P. Hasler and Brenna N. Renn and has published in prestigious journals such as PLoS ONE, Neuroscience & Biobehavioral Reviews and Psychological Medicine.

In The Last Decade

Megan A. Miller

17 papers receiving 483 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Megan A. Miller United States 12 153 144 101 95 92 17 493
Eveline Hagebeuk Netherlands 12 223 1.5× 195 1.4× 108 1.1× 40 0.4× 235 2.6× 20 709
Catherine Hatfield United Kingdom 5 165 1.1× 144 1.0× 55 0.5× 45 0.5× 152 1.7× 9 455
Yoichi Nakazawa Japan 16 166 1.1× 175 1.2× 95 0.9× 44 0.5× 247 2.7× 58 688
Simone Maria Kagerbauer Germany 11 120 0.8× 99 0.7× 54 0.5× 89 0.9× 28 0.3× 29 576
Cüneyt Demiralay Germany 13 52 0.3× 108 0.8× 48 0.5× 54 0.6× 60 0.7× 33 516
Elsa Lindgren United States 5 182 1.2× 213 1.5× 75 0.7× 130 1.4× 342 3.7× 7 778
Christine M. Walsh United States 11 110 0.7× 146 1.0× 72 0.7× 71 0.7× 279 3.0× 19 523
Peter K. Thanos United States 12 69 0.5× 111 0.8× 98 1.0× 78 0.8× 242 2.6× 18 769
Matthew T. Scharf United States 12 258 1.7× 248 1.7× 73 0.7× 49 0.5× 411 4.5× 18 860
Irene Kürten Germany 15 115 0.8× 92 0.6× 121 1.2× 31 0.3× 73 0.8× 25 727

Countries citing papers authored by Megan A. Miller

Since Specialization
Citations

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

Fields of papers citing papers by Megan A. Miller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Megan A. Miller

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

All Works

17 of 17 papers shown
1.
Franzen, Peter L., Brant P. Hasler, Megan A. Miller, et al.. (2021). Elusive hypersomnolence in seasonal affective disorder: actigraphic and self-reported sleep in and out of depressive episodes. Psychological Medicine. 53(4). 1313–1322. 7 indexed citations
2.
Roecklein, Kathryn A., Peter L. Franzen, Brant P. Hasler, et al.. (2021). Melanopsin-driven pupil response in summer and winter in unipolar seasonal affective disorder. Journal of Affective Disorders. 291. 93–101. 15 indexed citations
3.
Miller, Megan A., et al.. (2019). Sleepless in the hospital: A systematic review of non-pharmacological sleep interventions. General Hospital Psychiatry. 59. 58–66. 43 indexed citations
4.
Smagula, Stephen F., Megan A. Miller, Robert T. Krafty, et al.. (2018). Rest-activity rhythms characteristics and seasonal changes in seasonal affective disorder. Chronobiology International. 35(11). 1553–1559. 9 indexed citations
5.
Miller, Megan A.. (2018). Lack of associations between rest/activity rhythms and cognition in healthy middle-aged and young adults. D-Scholarship@Pitt (University of Pittsburgh). 1 indexed citations
6.
Donofry, Shannon D., Kathryn A. Roecklein, Jennifer E. Wildes, Megan A. Miller, & Kirk I. Erickson. (2016). Alterations in emotion generation and regulation neurocircuitry in depression and eating disorders: A comparative review of structural and functional neuroimaging studies. Neuroscience & Biobehavioral Reviews. 68. 911–927. 44 indexed citations
7.
Miller, Megan A., Regina L. Leckie, Shannon D. Donofry, et al.. (2014). Photoperiod is associated with hippocampal volume in a large community sample. Hippocampus. 25(4). 534–543. 17 indexed citations
8.
Miller, Megan A., Scott D. Rothenberger, Brant P. Hasler, et al.. (2014). Chronotype predicts positive affect rhythms measured by ecological momentary assessment. Chronobiology International. 32(3). 376–384. 48 indexed citations
9.
Donofry, Shannon D., Kathryn A. Roecklein, Jennifer E. Wildes, et al.. (2014). COMT met allele differentially predicts risk versus severity of aberrant eating in a large community sample. Psychiatry Research. 220(1-2). 513–518. 11 indexed citations
10.
Failla, Michelle D., Megan A. Miller, Joelle M. Scanlon, et al.. (2013). Variants of SLC6A4 in depression risk following severe TBI. Brain Injury. 27(6). 696–706. 30 indexed citations
11.
Roecklein, Kathryn A., Patricia Wong, Peter L. Franzen, et al.. (2012). Melanopsin Gene Variations Interact With Season to Predict Sleep Onset and Chronotype. Chronobiology International. 29(8). 1036–1047. 37 indexed citations
12.
Miller, Megan A., et al.. (2012). Genetic variability in glutamic acid decarboxylase genes: Associations with post-traumatic seizures after severe TBI. Epilepsy Research. 103(2-3). 180–194. 49 indexed citations
13.
Roecklein, Kathryn A., Julie A. Schumacher, Megan A. Miller, & Natalie C. Ernecoff. (2012). Cognitive and Behavioral Predictors of Light Therapy Use. PLoS ONE. 7(6). e39275–e39275. 7 indexed citations
14.
Wagner, Amy K., Joelle M. Scanlon, Christian Niyonkuru, et al.. (2012). Association of KIBRA rs17070145 polymorphism and episodic memory in individuals with severe TBI. Brain Injury. 26(13-14). 1658–1669. 18 indexed citations
15.
Roecklein, Kathryn A., et al.. (2012). Melanopsin, photosensitive ganglion cells, and seasonal affective disorder. Neuroscience & Biobehavioral Reviews. 37(3). 229–239. 63 indexed citations
16.
Miller, Megan A., Yvette P. Conley, Joelle M. Scanlon, et al.. (2010). APOE genetic associations with seizure development after severe traumatic brain injury. Brain Injury. 24(12). 1468–1477. 27 indexed citations
17.
Wagner, Amy K., Megan A. Miller, Joelle M. Scanlon, et al.. (2010). Adenosine A1 receptor gene variants associated with post-traumatic seizures after severe TBI. Epilepsy Research. 90(3). 259–272. 67 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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