Ladan Shams

10.4k total citations · 3 hit papers
85 papers, 6.8k citations indexed

About

Ladan Shams is a scholar working on Experimental and Cognitive Psychology, Cognitive Neuroscience and Sensory Systems. According to data from OpenAlex, Ladan Shams has authored 85 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 72 papers in Experimental and Cognitive Psychology, 64 papers in Cognitive Neuroscience and 32 papers in Sensory Systems. Recurrent topics in Ladan Shams's work include Multisensory perception and integration (70 papers), Visual perception and processing mechanisms (43 papers) and Olfactory and Sensory Function Studies (32 papers). Ladan Shams is often cited by papers focused on Multisensory perception and integration (70 papers), Visual perception and processing mechanisms (43 papers) and Olfactory and Sensory Function Studies (32 papers). Ladan Shams collaborates with scholars based in United States, United Kingdom and Japan. Ladan Shams's co-authors include Shinsuke Shimojo, Aaron R. Seitz, Yukiyasu Kamitani, Ulrik Beierholm, David R. Wozny, Robyn Kim, Wei Ji, Steven R. Quartz, Joshua B. Tenenbaum and Konrad P. Körding and has published in prestigious journals such as Nature, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Ladan Shams

81 papers receiving 6.6k citations

Hit Papers

What you see is what you hear 2000 2026 2008 2017 2000 2007 2008 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. What you see is what you hear
    2000 852 citations Ladan Shams, Yukiyasu Kamitani et al. profile →
  2. Causal Inference in Multisensory Perception
    2007 739 citations Ulrik Beierholm, Ladan Shams et al. PLoS ONE profile →
  3. Benefits of multisensory learning
    2008 672 citations Ladan Shams, Aaron R. Seitz profile →

Peers

Ladan Shams
Salvador Soto‐Faraco Spain
Jamie Ward United Kingdom
Vilayanur S. Ramachandran United States
Jean Vroomen Netherlands
David Alais Australia
Fiona N. Newell Ireland
Uta Noppeney United Kingdom
Edward M. Hubbard United States
Jon Driver United Kingdom
Lawrence E. Marks United States
Salvador Soto‐Faraco Spain
Ladan Shams
Citations per year, relative to Ladan Shams Ladan Shams (= 1×) peers Salvador Soto‐Faraco

Countries citing papers authored by Ladan Shams

Since Specialization
Citations

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

Fields of papers citing papers by Ladan Shams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ladan Shams. 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 Ladan Shams. The network helps show where Ladan Shams may publish in the future.

Co-authorship network of co-authors of Ladan Shams

This figure shows the co-authorship network connecting the top 25 collaborators of Ladan Shams. A scholar is included among the top collaborators of Ladan Shams 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 Ladan Shams. Ladan Shams 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.
Beierholm, Ulrik, et al.. (2024). BCI Toolbox: An open-source python package for the Bayesian causal inference model. PLoS Computational Biology. 20(7). e1011791–e1011791.
2.
Shams, Ladan, et al.. (2023). Big number, big body: Jersey numbers alter body size perception. PLoS ONE. 18(9). e0287474–e0287474. 1 indexed citations
3.
Shams, Ladan, et al.. (2023). Improving memory for unusual events with wakeful reactivation. Frontiers in Psychology. 14. 1092408–1092408. 1 indexed citations
4.
Samad, Majed, Christina Ralph‐Nearman, Gerhard Hellemann, et al.. (2019). Disturbed Eating and Body Dysmorphic Symptoms in a Young Adult Sample Are Separable Constructs That Each Show a Mixture of Distributions. Assessment. 28(3). 890–898. 7 indexed citations
5.
Odegaard, Brian, Ulrik Beierholm, Jason M. Carpenter, & Ladan Shams. (2018). Prior expectation of objects in space is dependent on the direction of gaze. Cognition. 182. 220–226. 6 indexed citations
6.
Abney, Drew H., Dima Amso, Anthony Chemero, et al.. (2016). Perception, as you make it. Behavioral and Brain Sciences. 39. e260–e260. 12 indexed citations
7.
Samad, Majed, Albert Jin Chung, & Ladan Shams. (2015). Perception of Body Ownership Is Driven by Bayesian Sensory Inference. PLoS ONE. 10(2). e0117178–e0117178. 234 indexed citations
8.
Samad, Majed & Ladan Shams. (2015). Visual–somatotopic interactions in spatial perception. Neuroreport. 27(3). 180–185. 10 indexed citations
9.
Peters, Megan A. K., Benjamin Thompson, Lotfi B. Merabet, Allan D. Wu, & Ladan Shams. (2013). Anodal tDCS to V1 blocks visual perceptual learning consolidation. Neuropsychologia. 51(7). 1234–1239. 59 indexed citations
10.
Odegaard, Brian, David R. Wozny, & Ladan Shams. (2012). The effects of selective and divided attention on sensory integration. Journal of Vision. 12(9). 658–658. 1 indexed citations
11.
Wozny, David R. & Ladan Shams. (2011). Computational Characterization of Visually Induced Auditory Spatial Adaptation. Frontiers in Integrative Neuroscience. 5. 75–75. 44 indexed citations
12.
Wozny, David R. & Ladan Shams. (2011). Recalibration of Auditory Space following Milliseconds of Cross-Modal Discrepancy. Journal of Neuroscience. 31(12). 4607–4612. 100 indexed citations
13.
Shams, Ladan, David R. Wozny, Robyn Kim, & Aaron R. Seitz. (2011). Influences of Multisensory Experience on Subsequent Unisensory Processing. Frontiers in Psychology. 2. 264–264. 83 indexed citations
14.
Beierholm, Ulrik, et al.. (2009). Comparing Bayesian models for multisensory cue combination without mandatory integration. CaltechAUTHORS (California Institute of Technology). 29 indexed citations
15.
Jacobs, Robert A. & Ladan Shams. (2009). Visual Learning in Multisensory Environments. Topics in Cognitive Science. 2(2). 217–225. 7 indexed citations
16.
Natarajan, Rama, Iain Murray, Ladan Shams, & Richard S. Zemel. (2008). Characterizing response behavior in multi-sensory perception with conflicting cues. ERA. 21. 1153–1160. 6 indexed citations
17.
Wozny, David R., Ulrik Beierholm, & Ladan Shams. (2008). Human trimodal perception follows optimal statistical inference. Journal of Vision. 8(3). 24–24. 129 indexed citations
18.
Shimojo, Shinsuke, et al.. (2005). Touch-induced visual illusion. Neuroreport. 16(10). 1107–1110. 92 indexed citations
19.
Shams, Ladan & Christoph von der Malsburg. (2002). The role of complex cells in object recognition. Vision Research. 42(22). 2547–2554. 40 indexed citations
20.
Shams, Ladan, Yukiyasu Kamitani, Samuel B. Thompson, & Shinsuke Shimojo. (2001). Sound alters visual evoked potentials in humans. Neuroreport. 12(17). 3849–3852. 151 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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