Justin D. Lieber

716 total citations
9 papers, 419 citations indexed

About

Justin D. Lieber is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Biophysics. According to data from OpenAlex, Justin D. Lieber has authored 9 papers receiving a total of 419 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cognitive Neuroscience, 1 paper in Experimental and Cognitive Psychology and 1 paper in Biophysics. Recurrent topics in Justin D. Lieber's work include Tactile and Sensory Interactions (8 papers), Visual perception and processing mechanisms (8 papers) and Neural dynamics and brain function (7 papers). Justin D. Lieber is often cited by papers focused on Tactile and Sensory Interactions (8 papers), Visual perception and processing mechanisms (8 papers) and Neural dynamics and brain function (7 papers). Justin D. Lieber collaborates with scholars based in United States, Belgium and Taiwan. Justin D. Lieber's co-authors include Sliman J. Bensmaı̈a, Alison I. Weber, Ju‐Wen Cheng, Louise R. Manfredi, Hannes P. Saal, John F. Dammann, Charles M. Greenspon, Benoit P. Delhaye, Najib J. Majaj and J. Anthony Movshon and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Neurophysiology.

In The Last Decade

Justin D. Lieber

9 papers receiving 415 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Justin D. Lieber United States	8	395	120	102	73	53	9	419
Louise R. Manfredi United States	6	534 1.4×	175 1.5×	129 1.3×	135 1.8×	82 1.5×	10	597
J. Cortney Bradford United States	6	249 0.6×	99 0.8×	28 0.3×	62 0.8×	28 0.5×	13	325
Sung-Phil Kim South Korea	9	341 0.9×	275 2.3×	47 0.5×	89 1.2×	33 0.6×	16	534
Matthias Witkowski Italy	11	611 1.5×	224 1.9×	23 0.2×	251 3.4×	62 1.2×	12	726
Giulia Corniani United States	3	127 0.3×	71 0.6×	29 0.3×	14 0.2×	37 0.7×	10	207
Simona Bufalari Italy	6	362 0.9×	45 0.4×	36 0.4×	168 2.3×	87 1.6×	9	407
Heather E. Wheat Australia	7	297 0.8×	94 0.8×	50 0.5×	47 0.6×	26 0.5×	9	324
Ali Bülent Uşaklı Türkiye	7	355 0.9×	72 0.6×	14 0.1×	104 1.4×	252 4.8×	16	432
Chia‐Yen Yang Taiwan	9	242 0.6×	133 1.1×	21 0.2×	56 0.8×	62 1.2×	25	389
David Gueorguiev France	8	399 1.0×	62 0.5×	100 1.0×	13 0.2×	54 1.0×	21	455

Countries citing papers authored by Justin D. Lieber

Since Specialization

Citations

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

Fields of papers citing papers by Justin D. Lieber

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Justin D. Lieber. 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 Justin D. Lieber. The network helps show where Justin D. Lieber may publish in the future.

Co-authorship network of co-authors of Justin D. Lieber

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

All Works

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9 of 9 papers shown

Lieber, Justin D., et al.. (2023). Sensitivity to naturalistic texture relies primarily on high spatial frequencies. Journal of Vision. 23(2). 4–4. 2 indexed citations

Lieber, Justin D. & Sliman J. Bensmaı̈a. (2022). The neural basis of tactile texture perception. Current Opinion in Neurobiology. 76. 102621–102621. 7 indexed citations

Lieber, Justin D., et al.. (2022). Texture is encoded in precise temporal spiking patterns in primate somatosensory cortex. Nature Communications. 13(1). 1311–1311. 17 indexed citations

Greenspon, Charles M., et al.. (2020). Effect of scanning speed on texture-elicited vibrations. Journal of The Royal Society Interface. 17(167). 20190892–20190892. 21 indexed citations

Lieber, Justin D. & Sliman J. Bensmaı̈a. (2019). Emergence of an Invariant Representation of Texture in Primate Somatosensory Cortex. Cerebral Cortex. 30(5). 3228–3239. 15 indexed citations

Lieber, Justin D. & Sliman J. Bensmaı̈a. (2019). High-dimensional representation of texture in somatosensory cortex of primates. Proceedings of the National Academy of Sciences. 116(8). 3268–3277. 35 indexed citations

Delhaye, Benoit P., et al.. (2019). Feeling fooled: Texture contaminates the neural code for tactile speed. PLoS Biology. 17(8). e3000431–e3000431. 21 indexed citations

Lieber, Justin D., et al.. (2017). The neural code for tactile roughness in the somatosensory nerves. Journal of Neurophysiology. 118(6). 3107–3117. 26 indexed citations

Weber, Alison I., Hannes P. Saal, Justin D. Lieber, et al.. (2013). Spatial and temporal codes mediate the tactile perception of natural textures. Proceedings of the National Academy of Sciences. 110(42). 17107–17112. 275 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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