Sean M. Lane

1.5k total citations
30 papers, 1.0k citations indexed

About

Sean M. Lane is a scholar working on Cognitive Neuroscience, Social Psychology and Artificial Intelligence. According to data from OpenAlex, Sean M. Lane has authored 30 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Cognitive Neuroscience, 15 papers in Social Psychology and 7 papers in Artificial Intelligence. Recurrent topics in Sean M. Lane's work include Memory Processes and Influences (18 papers), Deception detection and forensic psychology (14 papers) and Face Recognition and Perception (3 papers). Sean M. Lane is often cited by papers focused on Memory Processes and Influences (18 papers), Deception detection and forensic psychology (14 papers) and Face Recognition and Perception (3 papers). Sean M. Lane collaborates with scholars based in United States, United Kingdom and Canada. Sean M. Lane's co-authors include Maria S. Zaragoza, Chunqiao Luo, Claire Advokat, Paul Atchley, Jonathan W. Schooler, Mara Mather, Christian A. Meissner, Jeffrey J. Starns, Ron Sun and Robert C. Mathews and has published in prestigious journals such as Psychological Science, Journal of Experimental Psychology Learning Memory and Cognition and Accident Analysis & Prevention.

In The Last Decade

Sean M. Lane

30 papers receiving 983 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sean M. Lane United States 17 751 535 189 167 155 30 1.0k
Friedrich Wilkening Switzerland 19 489 0.7× 280 0.5× 139 0.7× 662 4.0× 338 2.2× 33 1.6k
Michelle L. Meade United States 15 831 1.1× 510 1.0× 190 1.0× 410 2.5× 213 1.4× 28 1.2k
Ty W. Boyer United States 13 282 0.4× 217 0.4× 117 0.6× 344 2.1× 139 0.9× 33 1.1k
Stéphane Doyen Australia 12 354 0.5× 202 0.4× 176 0.9× 61 0.4× 173 1.1× 31 860
Elizabeth F. Loftus United States 8 672 0.9× 480 0.9× 181 1.0× 233 1.4× 157 1.0× 9 1.1k
Ainat Pansky Israel 12 730 1.0× 289 0.5× 91 0.5× 298 1.8× 259 1.7× 23 1.1k
Esperanza Báusela Herreras Spain 12 290 0.4× 139 0.3× 63 0.3× 125 0.7× 126 0.8× 115 990
Yana Weinstein United States 19 581 0.8× 130 0.2× 66 0.3× 263 1.6× 310 2.0× 34 1.2k
Jeffrey S. Neuschatz United States 22 1.5k 2.0× 1.2k 2.2× 220 1.2× 230 1.4× 185 1.2× 67 1.9k
Frédéric Nils Belgium 14 283 0.4× 469 0.9× 141 0.7× 68 0.4× 419 2.7× 33 1.1k

Countries citing papers authored by Sean M. Lane

Since Specialization
Citations

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

Fields of papers citing papers by Sean M. Lane

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sean M. Lane

This figure shows the co-authorship network connecting the top 25 collaborators of Sean M. Lane. A scholar is included among the top collaborators of Sean M. Lane 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 Sean M. Lane. Sean M. Lane 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.
Lane, Sean M. & Kate A. Houston. (2021). Understanding Eyewitness Memory. New York University Press eBooks. 2 indexed citations
2.
Lane, Sean M., et al.. (2019). The effect of statement type and repetition on deception detection. Cognitive Research Principles and Implications. 4(1). 38–38. 3 indexed citations
3.
Lane, Sean M., et al.. (2016). Context influences interpretation of eyewitness confidence statements.. Law and Human Behavior. 41(2). 180–190. 16 indexed citations
4.
Atchley, Paul, et al.. (2012). Stuck in the 70s: The role of social norms in distracted driving. Accident Analysis & Prevention. 48. 279–284. 72 indexed citations
5.
Mathews, Robert C., et al.. (2011). Getting it right generally, but not precisely: learning the relation between multiple inputs and outputs. Memory & Cognition. 39(6). 1133–1145. 1 indexed citations
6.
Lane, Sean M.. (2010). Collective Intelligence for Competitive Advantage: Crowdsourcing and Open Innovation. Scholars' Bank (University of Oregon). 8 indexed citations
7.
Lane, Sean M., et al.. (2008). Facilitative interactions of model- and experiencebased processes: Implications for type and flexibility of representation. Memory & Cognition. 36(1). 157–169. 5 indexed citations
8.
Lane, Sean M., et al.. (2008). Providing information about diagnostic features at retrieval reduces false recognition. Memory. 16(8). 836–851. 7 indexed citations
9.
Lane, Sean M., et al.. (2008). What Judges Know about What Jurors Know: Consistency of Beliefs about Eyewitness Memory. 2 indexed citations
10.
Lane, Sean M. & Maria S. Zaragoza. (2007). A little elaboration goes a long way: The role of generation in eyewitness suggestibility. Memory & Cognition. 35(6). 1255–1266. 17 indexed citations
11.
Mathews, Robert C., et al.. (2007). Developing rich and quickly accessed knowledge of an artificial grammar. Memory & Cognition. 35(8). 2118–2133. 16 indexed citations
12.
Lane, Sean M., et al.. (2007). Features and feedback: Enhancing metamnemonic knowledge at retrieval reduces source-monitoring errors.. Journal of Experimental Psychology Learning Memory and Cognition. 33(6). 1131–1142. 18 indexed citations
13.
Lane, Sean M.. (2006). Dividing attention during a witnessed event increases eyewitness suggestibility. Applied Cognitive Psychology. 20(2). 199–212. 36 indexed citations
14.
Starns, Jeffrey J., et al.. (2006). Metamnemonic control over the discriminability of memory evidence: A signal detection analysis of warning effects in the associative list paradigm. Journal of Memory and Language. 56(4). 592–607. 21 indexed citations
15.
Lane, Sean M. & Jonathan W. Schooler. (2004). Skimming the Surface. Psychological Science. 15(11). 715–719. 38 indexed citations
16.
Lane, Sean M., et al.. (2001). How events are reviewed matters: Effects of varied focus on eyewitness suggestibility. Memory & Cognition. 29(7). 940–947. 43 indexed citations
17.
Zaragoza, Maria S. & Sean M. Lane. (1998). Processing resources and eyewitness suggestibility. Legal and Criminological Psychology. 3(2). 305–320. 38 indexed citations
18.
Lane, Sean M. & Maria S. Zaragoza. (1995). The recollective experience of cross-modality confusion errors. Memory & Cognition. 23(5). 607–610. 28 indexed citations
19.
Zaragoza, Maria S. & Sean M. Lane. (1994). Source misattributions and the suggestibility of eyewitness memory.. Journal of Experimental Psychology Learning Memory and Cognition. 20(4). 934–945. 241 indexed citations
20.
Zaragoza, Maria S. & Sean M. Lane. (1994). Source misattributions and the suggestibility of eyewitness memory.. Journal of Experimental Psychology Learning Memory and Cognition. 20(4). 934–945. 184 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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