John B. Meixner

633 total citations
22 papers, 364 citations indexed

About

John B. Meixner is a scholar working on Social Psychology, Cognitive Neuroscience and Clinical Psychology. According to data from OpenAlex, John B. Meixner has authored 22 papers receiving a total of 364 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Social Psychology, 7 papers in Cognitive Neuroscience and 6 papers in Clinical Psychology. Recurrent topics in John B. Meixner's work include Deception detection and forensic psychology (16 papers), Psychopathy, Forensic Psychiatry, Sexual Offending (6 papers) and Adversarial Robustness in Machine Learning (6 papers). John B. Meixner is often cited by papers focused on Deception detection and forensic psychology (16 papers), Psychopathy, Forensic Psychiatry, Sexual Offending (6 papers) and Adversarial Robustness in Machine Learning (6 papers). John B. Meixner collaborates with scholars based in United States, Philippines and Netherlands. John B. Meixner's co-authors include J. Peter Rosenfeld, Elena Labkovsky, Giorgio Ganis, Rogier Kievit, Haline E. Schendan, Michael R. Winograd, Xiaoqing Hu, Shari Seidman Diamond, Mary R. Rose and Alexander W. Sokolovsky and has published in prestigious journals such as NeuroImage, Psychological Science and Psychophysiology.

In The Last Decade

John B. Meixner

18 papers receiving 337 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
John B. Meixner United States	9	288	219	114	110	28	22	364
Alysha Baker Canada	8	178 0.6×	106 0.5×	97 0.9×	40 0.4×	83 3.0×	12	283
Elena Labkovsky United States	10	397 1.4×	300 1.4×	152 1.3×	187 1.7×	32 1.1×	18	431
Ryan J. Fitzgerald Canada	10	197 0.7×	276 1.3×	36 0.3×	45 0.4×	21 0.8×	35	342
Victoria Tepe Nasman United States	6	193 0.7×	234 1.1×	88 0.8×	66 0.6×	21 0.8×	9	320
Jackie Hillman United Kingdom	12	399 1.4×	166 0.8×	277 2.4×	96 0.9×	160 5.7×	15	419
David Mallard Australia	9	73 0.3×	110 0.5×	37 0.3×	35 0.3×	29 1.0×	15	262
Maria A. Carlson United States	10	177 0.6×	249 1.1×	12 0.1×	56 0.5×	21 0.8×	23	295
Markus Spitzer Germany	9	43 0.1×	77 0.4×	61 0.5×	35 0.3×	17 0.6×	33	305
Danilo Fum Italy	9	31 0.1×	103 0.5×	28 0.2×	122 1.1×	14 0.5×	23	321
Yujia Peng United States	10	72 0.3×	164 0.7×	22 0.2×	21 0.2×	24 0.9×	32	284

Countries citing papers authored by John B. Meixner

Since Specialization

Citations

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

Fields of papers citing papers by John B. Meixner

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John B. Meixner. 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 John B. Meixner. The network helps show where John B. Meixner may publish in the future.

Co-authorship network of co-authors of John B. Meixner

This figure shows the co-authorship network connecting the top 25 collaborators of John B. Meixner. A scholar is included among the top collaborators of John B. Meixner 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 John B. Meixner. John B. Meixner 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

Meixner, John B.. (2020). Neuroscience and Mental Competency: Current Uses and Future Potential. eYLS (Yale Law School). 1 indexed citations

Meixner, John B.. (2018). Neuroscience and Mental Competency: Current Uses and Future Potential.. PubMed. 81(3). 995–1026. 2 indexed citations

Meixner, John B.. (2016). The use of neuroscience evidence in criminal proceedings. Journal of Law and the Biosciences. 3(2). 330–335. 8 indexed citations

Koehler, Jonathan J. & John B. Meixner. (2016). An Empirical Research Agenda for the Forensic Sciences. eYLS (Yale Law School). 106(1). 1–34.

Meixner, John B.. (2015). Liar, Liar, Jury's the Trier? The Future of Neuroscience-Based Credibility Assessment in the Court. Northwestern University law review. 106(3). 1451–1488. 3 indexed citations

Meixner, John B. & Shari Seidman Diamond. (2014). The Hidden Daubert Factor: How Judges Use Error Rates in Assessing Scientific Evidence. eYLS (Yale Law School). 1 indexed citations

Meixner, John B. & J. Peter Rosenfeld. (2014). Detecting Knowledge of Incidentally Acquired, Real-World Memories Using a P300-Based Concealed-Information Test. eYLS (Yale Law School). 24 indexed citations

Meixner, John B. & J. Peter Rosenfeld. (2014). Detecting Knowledge of Incidentally Acquired, Real-World Memories Using a P300-Based Concealed-Information Test. Psychological Science. 25(11). 1994–2005. 34 indexed citations

Meixner, John B., Elena Labkovsky, J. Peter Rosenfeld, et al.. (2013). P900: A Putative Novel ERP Component that Indexes Countermeasure Use in the P300-Based Concealed Information Test. Applied Psychophysiology and Biofeedback. 38(2). 121–132. 6 indexed citations

10.

Rosenfeld, J. Peter, Xiaoqing Hu, Elena Labkovsky, John B. Meixner, & Michael R. Winograd. (2013). Review of recent studies and issues regarding the P300-based complex trial protocol for detection of concealed information. International Journal of Psychophysiology. 90(2). 118–134. 69 indexed citations

11.

Sokolovsky, Alexander W., et al.. (2011). A novel countermeasure against the reaction time index of countermeasure use in the P300-based complex trial protocol for detection of concealed information. International Journal of Psychophysiology. 81(1). 60–63. 16 indexed citations

12.

Diamond, Shari Seidman, et al.. (2011). Damage Anchors on Real Juries. Journal of Empirical Legal Studies. 8(s1). 148–178. 20 indexed citations

13.

Meixner, John B.. (2011). Liar, Liar, Jury's the Trier? The Future of Neuroscience-Based Credibility Assessment and the Court. eYLS (Yale Law School). 3 indexed citations

14.

Ganis, Giorgio, J. Peter Rosenfeld, John B. Meixner, Rogier Kievit, & Haline E. Schendan. (2010). Lying in the scanner: Covert countermeasures disrupt deception detection by functional magnetic resonance imaging. NeuroImage. 55(1). 312–319. 89 indexed citations

15.

Meixner, John B. & J. Peter Rosenfeld. (2010). A mock terrorism application of the P300‐based concealed information test. Psychophysiology. 48(2). 149–154. 64 indexed citations

16.

Ganis, Giorgio, J. Peter Rosenfeld, John B. Meixner, Rogier Kievit, & Haline E. Schendan. (2010). Lying in the Scanner: Covert Countermeasures Disrupt Deception Detection ByFunctional Magnetic Resonance Imaging. 1 indexed citations

17.

Meixner, John B. & J. Peter Rosenfeld. (2010). A Mock Terrorism Application of the P300-Based Concealed Information Test. eYLS (Yale Law School).

18.

Meixner, John B. & J. Peter Rosenfeld. (2009). Countermeasure mechanisms in a P300-based concealed information test. Psychophysiology. 47(1). 57–65.

19.

Rosenfeld, J. Peter, Mónica Tang, John B. Meixner, Michael R. Winograd, & Elena Labkovsky. (2009). The effects of asymmetric vs. symmetric probability of targets following probe and irrelevant stimuli in the complex trial protocol for detection of concealed information with P300. Physiology & Behavior. 98(1-2). 10–16. 18 indexed citations

20.

Meixner, John B.. (1987). Frequencies and Possibility. 13. 73–77. 1 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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