Mark N. Miller

1.1k total citations
8 papers, 825 citations indexed

About

Mark N. Miller is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Neurology. According to data from OpenAlex, Mark N. Miller has authored 8 papers receiving a total of 825 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cellular and Molecular Neuroscience, 5 papers in Cognitive Neuroscience and 2 papers in Neurology. Recurrent topics in Mark N. Miller's work include Neuroscience and Neuropharmacology Research (5 papers), Neural dynamics and brain function (3 papers) and Memory and Neural Mechanisms (2 papers). Mark N. Miller is often cited by papers focused on Neuroscience and Neuropharmacology Research (5 papers), Neural dynamics and brain function (3 papers) and Memory and Neural Mechanisms (2 papers). Mark N. Miller collaborates with scholars based in United States. Mark N. Miller's co-authors include Sacha B. Nelson, Chris M. Hempel, Ken Sugino, Benjamin W. Okaty, Z. Josh Huang, Peter A. Shapiro, Alexis M. Hattox, Andrey E. Ryabinin, Carrie S. McKinnon and Abraham A. Palmer and has published in prestigious journals such as Nature Communications, Journal of Neuroscience and Nature Neuroscience.

In The Last Decade

Mark N. Miller

8 papers receiving 812 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mark N. Miller United States	8	514	381	310	106	100	8	825
Chae‐Seok Lim South Korea	15	631 1.2×	401 1.1×	370 1.2×	111 1.0×	92 0.9×	37	1.1k
Stephen M. Taubenfeld United States	9	669 1.3×	395 1.0×	484 1.6×	163 1.5×	80 0.8×	11	1.1k
Maximiliano José Nigro Norway	10	391 0.8×	279 0.7×	296 1.0×	78 0.7×	74 0.7×	16	641
Alberto Cruz‐Martín United States	10	456 0.9×	444 1.2×	347 1.1×	158 1.5×	98 1.0×	19	965
Ivan Marchionni Italy	16	750 1.5×	277 0.7×	446 1.4×	110 1.0×	101 1.0×	20	979
Nathan G. Hedrick United States	10	569 1.1×	283 0.7×	334 1.1×	98 0.9×	115 1.1×	13	891
Karin E. Sorra United States	9	916 1.8×	365 1.0×	366 1.2×	160 1.5×	202 2.0×	10	1.1k
Astrid Rollenhagen Germany	18	696 1.4×	279 0.7×	352 1.1×	136 1.3×	142 1.4×	34	1.1k
André Marques–Smith United Kingdom	11	577 1.1×	257 0.7×	310 1.0×	130 1.2×	129 1.3×	12	819
Mio Nonaka Japan	17	878 1.7×	698 1.8×	351 1.1×	112 1.1×	120 1.2×	23	1.3k

Countries citing papers authored by Mark N. Miller

Since Specialization

Citations

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

Fields of papers citing papers by Mark N. Miller

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark N. Miller

This figure shows the co-authorship network connecting the top 25 collaborators of Mark N. Miller. A scholar is included among the top collaborators of Mark N. 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 Mark N. Miller. Mark N. 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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8 of 8 papers shown

1.

Miller, Mark N., Chung Yan Cheung, & Michael S. Brainard. (2017). Vocal learning promotes patterned inhibitory connectivity. Nature Communications. 8(1). 2105–2105. 20 indexed citations

2.

Miller, Mark N., et al.. (2010). Activity‐dependent changes in the firing properties of neocortical fast‐spiking interneurons in the absence of large changes in gene expression. Developmental Neurobiology. 71(1). 62–70. 29 indexed citations

3.

Okaty, Benjamin W., Mark N. Miller, Ken Sugino, Chris M. Hempel, & Sacha B. Nelson. (2009). Transcriptional and Electrophysiological Maturation of Neocortical Fast-Spiking GABAergic Interneurons. Journal of Neuroscience. 29(21). 7040–7052. 221 indexed citations

4.

Miller, Mark N., Benjamin W. Okaty, & Sacha B. Nelson. (2008). Region-Specific Spike-Frequency Acceleration in Layer 5 Pyramidal Neurons Mediated by Kv1 Subunits. Journal of Neuroscience. 28(51). 13716–13726. 53 indexed citations

5.

Sugino, Ken, Chris M. Hempel, Mark N. Miller, et al.. (2005). Molecular taxonomy of major neuronal classes in the adult mouse forebrain. Nature Neuroscience. 9(1). 99–107. 409 indexed citations

6.

Palmer, Abraham A., Mark N. Miller, Carrie S. McKinnon, & Tamara J. Phillips. (2002). Sensitivity to the locomotor stimulant effects of ethanol and allopregnanolone is influenced by common genes.. Behavioral Neuroscience. 116(1). 126–137. 24 indexed citations

7.

Ryabinin, Andrey E., et al.. (2002). Effects of acute alcohol administration on object recognition learning in C57BL/6J mice. Pharmacology Biochemistry and Behavior. 71(1-2). 307–312. 48 indexed citations

8.

Palmer, Abraham A., Mark N. Miller, Carrie S. McKinnon, & Tamara J. Phillips. (2002). Sensitivity to the locomotor stimulant effects of ethanol and allopregnanolone is influenced by common genes.. Behavioral Neuroscience. 116(1). 126–137. 21 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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