Christopher R. Cox

671 total citations
27 papers, 335 citations indexed

About

Christopher R. Cox is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Developmental and Educational Psychology. According to data from OpenAlex, Christopher R. Cox has authored 27 papers receiving a total of 335 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Cognitive Neuroscience, 5 papers in Artificial Intelligence and 5 papers in Developmental and Educational Psychology. Recurrent topics in Christopher R. Cox's work include Face Recognition and Perception (6 papers), Functional Brain Connectivity Studies (6 papers) and Neural dynamics and brain function (5 papers). Christopher R. Cox is often cited by papers focused on Face Recognition and Perception (6 papers), Functional Brain Connectivity Studies (6 papers) and Neural dynamics and brain function (5 papers). Christopher R. Cox collaborates with scholars based in United States, United Kingdom and Norway. Christopher R. Cox's co-authors include Timothy T. Rogers, Nikhil Rao, Alex S. Cohen, Robert D. Nowak, Matthew A. Lambon Ralph, Florian Kattner, C. Shawn Green, Ajay D. Halai, Eileen Haebig and Raymond P. Tucker and has published in prestigious journals such as Journal of Neuroscience, PLoS ONE and Brain.

In The Last Decade

Christopher R. Cox

25 papers receiving 330 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Christopher R. Cox United States 11 177 59 57 43 40 27 335
Björn Browatzki South Korea 4 121 0.7× 37 0.6× 51 0.9× 44 1.0× 29 0.7× 6 319
Meysam Asgari United States 12 174 1.0× 226 3.8× 119 2.1× 39 0.9× 67 1.7× 37 548
Kévin Bailly France 12 191 1.1× 46 0.8× 190 3.3× 29 0.7× 65 1.6× 32 546
Krishna Somandepalli United States 12 109 0.6× 107 1.8× 65 1.1× 21 0.5× 8 0.2× 46 408
Tongran Liu China 13 198 1.1× 67 1.1× 137 2.4× 55 1.3× 41 1.0× 39 414
Angelo Rega Italy 10 175 1.0× 13 0.2× 18 0.3× 12 0.3× 52 1.3× 40 299
Naoki Miura Japan 13 397 2.2× 24 0.4× 88 1.5× 113 2.6× 65 1.6× 27 547
Carsten Stahlhut Denmark 9 499 2.8× 14 0.2× 96 1.7× 173 4.0× 39 1.0× 18 618
Qiufang Fu China 11 249 1.4× 39 0.7× 89 1.6× 84 2.0× 113 2.8× 37 436

Countries citing papers authored by Christopher R. Cox

Since Specialization
Citations

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

Fields of papers citing papers by Christopher R. Cox

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher R. Cox. 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 Christopher R. Cox. The network helps show where Christopher R. Cox may publish in the future.

Co-authorship network of co-authors of Christopher R. Cox

This figure shows the co-authorship network connecting the top 25 collaborators of Christopher R. Cox. A scholar is included among the top collaborators of Christopher R. Cox 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 Christopher R. Cox. Christopher R. Cox 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.
Haebig, Eileen, et al.. (2025). Vocabulary development in autistic children: a network growth analysis. Journal of Child Psychology and Psychiatry.
2.
Dabbs, Kevin, et al.. (2024). A longitudinal evaluation of personalized intrinsic network topography and cognitive decline in Parkinson's disease. European Journal of Neuroscience. 60(1). 3795–3811.
3.
Cox, Christopher R., Timothy T. Rogers, Akihiro Shimotake, et al.. (2024). Representational similarity learning reveals a graded multidimensional semantic space in the human anterior temporal cortex. PubMed. 2. 1 indexed citations
4.
Halai, Ajay D., et al.. (2023). Decoding semantic representations in mind and brain. Trends in Cognitive Sciences. 27(3). 258–281. 28 indexed citations
5.
Haebig, Eileen, et al.. (2023). Interpretations of meaningful and ambiguous hand gestures in autistic and non-autistic adults: A norming study. Behavior Research Methods. 56(5). 5232–5245. 2 indexed citations
6.
Chiou, Rocco, Christopher R. Cox, & Matthew A. Lambon Ralph. (2022). Bipartite functional fractionation within the neural system for social cognition supports the psychological continuity of self versus other. Cerebral Cortex. 33(4). 1277–1299. 1 indexed citations
7.
Cox, Christopher R. & Eileen Haebig. (2022). Child-oriented word associations improve models of early word learning. Behavior Research Methods. 55(1). 16–37. 9 indexed citations
8.
Rogers, Timothy T., Christopher R. Cox, Qihong Lu, et al.. (2021). Evidence for a deep, distributed and dynamic code for animacy in human ventral anterior temporal cortex. eLife. 10. 22 indexed citations
9.
Cohen, Alex S., Christopher R. Cox, Raymond P. Tucker, et al.. (2021). Validating Biobehavioral Technologies for Use in Clinical Psychiatry. Frontiers in Psychiatry. 12. 503323–503323. 7 indexed citations
10.
Cohen, Alex S., Christopher R. Cox, Tovah Cowan, et al.. (2021). High Predictive Accuracy of Negative Schizotypy With Acoustic Measures. Clinical Psychological Science. 10(2). 310–323. 6 indexed citations
11.
Cox, Christopher R., Emma H. Moscardini, Alex S. Cohen, & Raymond P. Tucker. (2020). Machine learning for suicidology: A practical review of exploratory and hypothesis-driven approaches. Clinical Psychology Review. 82. 101940–101940. 28 indexed citations
12.
Cohen, Alex S., Christopher R. Cox, Thanh P. Le, et al.. (2020). Using machine learning of computerized vocal expression to measure blunted vocal affect and alogia. Schizophrenia. 6(1). 26–26. 31 indexed citations
13.
Cox, Christopher R. & Timothy T. Rogers. (2020). Finding Distributed Needles in Neural Haystacks. Journal of Neuroscience. 41(5). 1019–1032. 7 indexed citations
14.
Zhou, Shuo, Wenwen Li, Christopher R. Cox, & Haiping Lu. (2020). Side Information Dependence as a Regularizer for Analyzing Human Brain Conditions across Cognitive Experiments. Proceedings of the AAAI Conference on Artificial Intelligence. 34(4). 6957–6964. 3 indexed citations
15.
Cohen, Alex S., Christopher R. Cox, Michael D. Masucci, et al.. (2020). Digital Phenotyping Using Multimodal Data. Current Behavioral Neuroscience Reports. 7(4). 212–220. 16 indexed citations
16.
Kattner, Florian, et al.. (2017). Perceptual Learning Generalization from Sequential Perceptual Training as a Change in Learning Rate. Current Biology. 27(6). 840–846. 44 indexed citations
17.
Cox, Christopher R., et al.. (2016). Representational similarity learning with application to brain networks. Journal of Machine Learning Research. 1041–1049. 6 indexed citations
18.
Kattner, Florian, Christopher R. Cox, & C. Shawn Green. (2016). Transfer in Rule-Based Category Learning Depends on the Training Task. PLoS ONE. 11(10). e0165260–e0165260. 7 indexed citations
19.
Rao, Nikhil, et al.. (2013). Sparse Overlapping Sets Lasso for Multitask Learning and its Application to fMRI Analysis. arXiv (Cornell University). 26. 2202–2210. 21 indexed citations
20.
Mazzocco, Michèle M. M., et al.. (1999). Normative data for the contingency naming test (CNT). Archives of Clinical Neuropsychology. 14(8). 711–711. 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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