John Porrill

3.8k total citations
87 papers, 2.7k citations indexed

About

John Porrill is a scholar working on Cognitive Neuroscience, Neurology and Computer Vision and Pattern Recognition. According to data from OpenAlex, John Porrill has authored 87 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Cognitive Neuroscience, 35 papers in Neurology and 29 papers in Computer Vision and Pattern Recognition. Recurrent topics in John Porrill's work include Vestibular and auditory disorders (35 papers), Visual perception and processing mechanisms (19 papers) and Advanced Vision and Imaging (19 papers). John Porrill is often cited by papers focused on Vestibular and auditory disorders (35 papers), Visual perception and processing mechanisms (19 papers) and Advanced Vision and Imaging (19 papers). John Porrill collaborates with scholars based in United Kingdom, Sweden and United States. John Porrill's co-authors include Paul Dean, James V. Stone, Henrik Jörntell, C.‐F. Ekerot, J. P. Frisby, Jim Ivins, Stephen Pollard, Sean Anderson, J. E. W. Mayhew and Noah Porter and has published in prestigious journals such as Nature, Nature reviews. Neuroscience and PLoS ONE.

In The Last Decade

John Porrill

84 papers receiving 2.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John Porrill United Kingdom 27 1.2k 784 570 383 327 87 2.7k
Peter W. Dicke Germany 22 1.5k 1.2× 559 0.7× 414 0.7× 211 0.6× 262 0.8× 49 2.4k
Richard D. Rabbitt United States 35 657 0.5× 1.1k 1.4× 701 1.2× 1.0k 2.7× 558 1.7× 100 3.7k
Laurence R. Young United States 38 2.9k 2.3× 1.9k 2.4× 237 0.4× 190 0.5× 177 0.5× 166 5.5k
Stan Gielen Netherlands 27 1.6k 1.3× 292 0.4× 402 0.7× 104 0.3× 404 1.2× 64 3.0k
Stefan Glasauer Germany 42 2.8k 2.3× 2.4k 3.1× 184 0.3× 574 1.5× 481 1.5× 222 5.9k
Leland S. Stone United States 33 2.5k 2.0× 672 0.9× 500 0.9× 205 0.5× 501 1.5× 102 3.1k
Laurence R. Harris Canada 35 3.0k 2.4× 538 0.7× 315 0.6× 311 0.8× 259 0.8× 190 3.9k
Casper J. Erkelens Netherlands 36 3.7k 3.0× 723 0.9× 572 1.0× 111 0.3× 169 0.5× 100 4.5k
Charles M. Oman United States 29 1.2k 1.0× 1.1k 1.4× 147 0.3× 282 0.7× 79 0.2× 111 3.0k
Markus Lappe Germany 46 5.4k 4.4× 637 0.8× 1.4k 2.4× 122 0.3× 431 1.3× 220 7.2k

Countries citing papers authored by John Porrill

Since Specialization
Citations

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

Fields of papers citing papers by John Porrill

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Porrill

This figure shows the co-authorship network connecting the top 25 collaborators of John Porrill. A scholar is included among the top collaborators of John Porrill 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 John Porrill. John Porrill 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.
Anderson, Sean, et al.. (2019). Sensorimotor maps can be dynamically calibrated using an adaptive-filter model of the cerebellum. PLoS Computational Biology. 15(7). e1007187–e1007187. 4 indexed citations
2.
Assaf, Tareq, Martin J. Pearson, Jonathan Rossiter, et al.. (2016). Cerebellar-inspired algorithm for adaptive control of nonlinear dielectric elastomer-based artificial muscle. Journal of The Royal Society Interface. 13(122). 20160547–20160547. 25 indexed citations
3.
Rössert, Christian, Paul Dean, & John Porrill. (2015). At the Edge of Chaos: How Cerebellar Granular Layer Network Dynamics Can Provide the Basis for Temporal Filters. PLoS Computational Biology. 11(10). e1004515–e1004515. 39 indexed citations
4.
Dean, Paul & John Porrill. (2014). Decorrelation Learning in the Cerebellum. Progress in brain research. 210. 157–192. 16 indexed citations
5.
Porrill, John, Paul Dean, & Sean Anderson. (2012). Adaptive filters and internal models: Multilevel description of cerebellar function. Neural Networks. 47. 134–149. 55 indexed citations
6.
Menzies, John, John Porrill, Mayank B. Dutia, & Paul Dean. (2010). Synaptic Plasticity in Medial Vestibular Nucleus Neurons: Comparison with Computational Requirements of VOR Adaptation. PLoS ONE. 5(10). e13182–e13182. 38 indexed citations
7.
Dean, Paul, John Porrill, C.‐F. Ekerot, & Henrik Jörntell. (2009). The cerebellar microcircuit as an adaptive filter: experimental and computational evidence. Nature reviews. Neuroscience. 11(1). 30–43. 269 indexed citations
8.
Porrill, John & Paul Dean. (2008). Silent Synapses, LTP, and the Indirect Parallel-Fibre Pathway: Computational Consequences of Optimal Cerebellar Noise-Processing. PLoS Computational Biology. 4(5). e1000085–e1000085. 26 indexed citations
9.
Anderson, Sean, Paul Dean, Visakan Kadirkamanathan, Chris R. S. Kaneko, & John Porrill. (2007). System Identification From Multiple Short-Time-Duration Signals. IEEE Transactions on Biomedical Engineering. 54(12). 2205–2213. 1 indexed citations
10.
Lepora, Nathan F., et al.. (2006). Response linearity determined by recruitment strategy in detailed model of nictitating membrane control. Biological Cybernetics. 96(1). 39–57. 11 indexed citations
11.
Porrill, John, et al.. (2005). Evidence for wide range of time scales in oculomotor plant dynamics: Implications for models of eye-movement control. Vision Research. 45(12). 1525–1542. 36 indexed citations
12.
Porrill, John, et al.. (1999). The variation of torsion with vergence and elevation. Vision Research. 39(23). 3934–3950. 26 indexed citations
13.
Porrill, John, et al.. (1999). Instability of torsion during smooth asymmetric vergence. Vision Research. 39(5). 993–1009. 4 indexed citations
14.
Porrill, John, John P. Frisby, Wendy J. Adams, & David Buckley. (1999). Robust and optimal use of information in stereo vision. Nature. 397(6714). 63–66. 23 indexed citations
15.
Dean, Paul & John Porrill. (1998). Pseudo-inverse control in biological systems: a learning mechanism for fixation stability. Neural Networks. 11(7-8). 1205–1218. 13 indexed citations
16.
Porrill, John, et al.. (1998). Kinematic Coordination of Reach and Balance. Journal of Motor Behavior. 30(3). 217–233. 6 indexed citations
17.
Mayhew, John E. W., Ying Zheng, John Porrill, et al.. (1996). Cerebral Vasomotion: A 0.1-Hz Oscillation in Reflected Light Imaging of Neural Activity. NeuroImage. 4(3). 183–193. 260 indexed citations
18.
Porrill, John. (1995). Optimal combination and constraints for geometrical sensor data. Ablex Publishing Corp. eBooks. 261–282. 23 indexed citations
19.
Frisby, John P., et al.. (1995). Interaction of stereo and texture cues in the perception of three-dimensional steps. Vision Research. 35(10). 1463–1472. 19 indexed citations
20.
McLauchlan, Philip F., et al.. (1991). Parallel 3D vision for vehicle navigation and control. Journal of Pharmacological Sciences. 110(2). 48–67. 4 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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