Malcolm P. Young

5.3k total citations
50 papers, 3.8k citations indexed

About

Malcolm P. Young is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Molecular Biology. According to data from OpenAlex, Malcolm P. Young has authored 50 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Cognitive Neuroscience, 10 papers in Cellular and Molecular Neuroscience and 5 papers in Molecular Biology. Recurrent topics in Malcolm P. Young's work include Neural dynamics and brain function (31 papers), Visual perception and processing mechanisms (24 papers) and Functional Brain Connectivity Studies (14 papers). Malcolm P. Young is often cited by papers focused on Neural dynamics and brain function (31 papers), Visual perception and processing mechanisms (24 papers) and Functional Brain Connectivity Studies (14 papers). Malcolm P. Young collaborates with scholars based in United Kingdom, United States and Germany. Malcolm P. Young's co-authors include Claus C. Hilgetag, Gully Burns, Shigeru Yamane, Jack W. Scannell, Mark A. O’Neill, Rolf Kötter, Klaas Ε. Stephan, Péter Földiák, Anthony P. Cohen and Kun Guo and has published in prestigious journals such as Nature, Science and NeuroImage.

In The Last Decade

Malcolm P. Young

48 papers receiving 3.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Malcolm P. Young United Kingdom 30 2.9k 493 458 447 299 50 3.8k
G Tononi United States 6 2.2k 0.7× 233 0.5× 320 0.7× 170 0.4× 300 1.0× 7 2.7k
Marcus Kaiser United Kingdom 37 4.2k 1.4× 1.3k 2.6× 682 1.5× 487 1.1× 493 1.6× 135 5.8k
Mark D. Humphries United Kingdom 24 2.2k 0.8× 344 0.7× 1.2k 2.5× 300 0.7× 295 1.0× 59 3.4k
Joaquín Goñi United States 33 3.5k 1.2× 1.8k 3.7× 346 0.8× 502 1.1× 627 2.1× 91 4.9k
Murray Shanahan United Kingdom 34 1.5k 0.5× 206 0.4× 473 1.0× 129 0.3× 225 0.8× 93 3.9k
Gully Burns United States 18 1.2k 0.4× 332 0.7× 186 0.4× 437 1.0× 97 0.3× 67 2.0k
Joshua Wilson United States 27 3.0k 1.0× 1.8k 3.7× 228 0.5× 661 1.5× 419 1.4× 72 5.9k
Walter Freeman United States 45 4.1k 1.4× 134 0.3× 1.4k 3.1× 374 0.8× 231 0.8× 186 6.3k
Mária Ercsey-Ravasz Romania 21 1.3k 0.4× 361 0.7× 290 0.6× 256 0.6× 81 0.3× 47 2.3k
Klaus Obermayer Germany 31 2.4k 0.8× 121 0.2× 1.3k 2.8× 564 1.3× 85 0.3× 159 3.5k

Countries citing papers authored by Malcolm P. Young

Since Specialization
Citations

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

Fields of papers citing papers by Malcolm P. Young

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Malcolm P. Young. 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 Malcolm P. Young. The network helps show where Malcolm P. Young may publish in the future.

Co-authorship network of co-authors of Malcolm P. Young

This figure shows the co-authorship network connecting the top 25 collaborators of Malcolm P. Young. A scholar is included among the top collaborators of Malcolm P. Young 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 Malcolm P. Young. Malcolm P. Young 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.
Koutsoukas, Alexios, B. T. Simms, Johannes Kirchmair, et al.. (2011). From in silico target prediction to multi-target drug design: Current databases, methods and applications. Journal of Proteomics. 74(12). 2554–2574. 204 indexed citations
2.
Guo, Kun, R. G. H. Robertson, Ángel Nevado, et al.. (2007). Spatio‐temporal prediction and inference by V1 neurons. European Journal of Neuroscience. 26(4). 1045–1054. 31 indexed citations
3.
András, Péter, et al.. (2007). Ecological network analysis: an application to the evaluation of effects of pesticide use in an agricultural environment. Pest Management Science. 63(10). 943–953. 6 indexed citations
4.
Kaiser, Marcus, Robert L. Martin, Péter András, & Malcolm P. Young. (2007). Simulation of robustness against lesions of cortical networks. European Journal of Neuroscience. 25(10). 3185–3192. 171 indexed citations
5.
Guo, Kun, Sasan Mahmoodi, R. G. H. Robertson, & Malcolm P. Young. (2005). Longer fixation duration while viewing face images. Experimental Brain Research. 171(1). 91–98. 50 indexed citations
6.
Guo, Kun, et al.. (2004). Effects on orientation perception of manipulating the spatio–temporal prior probability of stimuli. Vision Research. 44(20). 2349–2358. 30 indexed citations
7.
Nevado, Ángel, Malcolm P. Young, & Stefano Panzeri. (2004). Functional imaging and neural information coding. NeuroImage. 21(3). 1083–1095. 22 indexed citations
8.
Guo, Kun, R. G. H. Robertson, Sasan Mahmoodi, Yoav Tadmor, & Malcolm P. Young. (2003). How do monkeys view faces?—a study of eye movements. Experimental Brain Research. 150(3). 363–374. 72 indexed citations
9.
Golledge, Huw, Stefano Panzeri, Jack W. Scannell, et al.. (2003). Correlations, feature-binding and population coding in primary visual cortex. Neuroreport. 14(7). 1045–1050. 41 indexed citations
10.
Panzeri, Stefano, et al.. (2002). A critical assessment of different measures of the information carried by correlated neuronal firing. Biosystems. 67(1-3). 177–185. 20 indexed citations
11.
Petroni, Filippo, Stefano Panzeri, Claus C. Hilgetag, Rolf Kötter, & Malcolm P. Young. (2001). Simultaneity of responses in a hierarchical visual network. Neuroreport. 12(12). 2753–2759. 31 indexed citations
12.
Young, Malcolm P.. (2000). The architecture of visual cortex and inferential processes in vision. Spatial Vision. 13(2-3). 137–146. 56 indexed citations
13.
Földiák, Péter & Malcolm P. Young. (1998). Sparse coding in the primate cortex. St Andrews Research Repository (St Andrews Research Repository). 895–898. 128 indexed citations
14.
Young, Malcolm P., et al.. (1997). Neural coding schemes for sensory representation: theoretical proposals and empirical evidence. 58. 146–92. 5 indexed citations
15.
Young, Malcolm P., et al.. (1994). Analysis of Connectivity: Neural Systems in the Cerebral Cortex. Reviews in the Neurosciences. 5(3). 227–50. 141 indexed citations
16.
Young, Malcolm P.. (1994). Visual Attention: Turn on, tune in and drop out. Current Biology. 4(1). 51–53. 2 indexed citations
17.
Scannell, Jack W. & Malcolm P. Young. (1993). The connectional organization of neural systems in the cat cerebral cortex. Current Biology. 3(4). 191–200. 80 indexed citations
18.
Young, Malcolm P.. (1992). Objective analysis of the topological organization of the primate cortical visual system. Nature. 358(6382). 152–155. 326 indexed citations
19.
Young, Malcolm P. & Michael D. Rugg. (1992). Word Frequency and Multiple Repetition as Determinants of the Modulation of Event‐Related Potentials in a Semantic Classification Task. Psychophysiology. 29(6). 664–676. 65 indexed citations
20.
Young, Malcolm P. & Shigeru Yamane. (1992). Sparse Population Coding of Faces in the Inferotemporal Cortex. Science. 256(5061). 1327–1331. 460 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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