Conor Houghton

1.3k total citations
48 papers, 719 citations indexed

About

Conor Houghton is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Conor Houghton has authored 48 papers receiving a total of 719 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Cognitive Neuroscience, 14 papers in Statistical and Nonlinear Physics and 13 papers in Cellular and Molecular Neuroscience. Recurrent topics in Conor Houghton's work include Neural dynamics and brain function (20 papers), Black Holes and Theoretical Physics (8 papers) and stochastic dynamics and bifurcation (7 papers). Conor Houghton is often cited by papers focused on Neural dynamics and brain function (20 papers), Black Holes and Theoretical Physics (8 papers) and stochastic dynamics and bifurcation (7 papers). Conor Houghton collaborates with scholars based in United Kingdom, Ireland and United States. Conor Houghton's co-authors include Paul Sutcliffe, N. S. Manton, Thomas Kreuz, Emma Robinson, Daniel Chicharro, Ralph G. Andrzejak, Florian Mormann, Barak A. Pearlmutter, Peter Lynch and Nina Kazanina and has published in prestigious journals such as PLoS ONE, The Journal of Physiology and Journal of Neurophysiology.

In The Last Decade

Conor Houghton

43 papers receiving 696 citations

Peers

Conor Houghton

NHEP

SNP

CMN

Luca Mazzucato United States

Marcus K. Benna United States

James Vickers United Kingdom

B. Tirozzi Italy

Jakob Heinzle Germany

H. Kröger Canada

Gordon Chalmers United States

Joseph Snider United States

Sébastien Leurent France

G. Mennessier France

Luca Mazzucato United States

Conor Houghton

224 ×0.8

NHEP

288 ×1.2

169 ×1.1

SNP

146 ×1.2

CMN

129 ×1.4

Citations per year, relative to Conor Houghton Conor Houghton (= 1×) peers Luca Mazzucato

Countries citing papers authored by Conor Houghton

Since Specialization

Citations

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

Fields of papers citing papers by Conor Houghton

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Conor Houghton

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

All Works

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20 of 20 papers shown

Houghton, Conor, et al.. (2025). Modeling nonlinear oscillator networks using physics-informed hybrid reservoir computing. Scientific Reports. 15(1). 22497–22497. 2 indexed citations

Palacios, Ensor Rafael, Paul Chadderton, Karl Friston, & Conor Houghton. (2024). Cerebellar state estimation enables resilient coupling across behavioural domains. Scientific Reports. 14(1). 6641–6641. 1 indexed citations

O’Donnell, Cian, et al.. (2023). Signatures of Bayesian inference emerge from energy-efficient synapses. eLife. 12. 1 indexed citations

Gritton, Howard J., et al.. (2023). A robust and compact population code for competing sounds in auditory cortex. Journal of Neurophysiology. 130(3). 775–787. 1 indexed citations

O’Donnell, Cian, et al.. (2023). Bayesian analysis of phase data in EEG and MEG. eLife. 12. 4 indexed citations

Houghton, Conor, et al.. (2023). Beyond the limitations of any imaginable mechanism: Large language models and psycholinguistics. Behavioral and Brain Sciences. 46. e395–e395. 2 indexed citations

Kazanina, Nina, et al.. (2023). Reward conditioning may not have an effect on category-specific memory. Scientific Reports. 13(1). 22297–22297.

Houghton, Conor, et al.. (2022). A Scalar Poincaré Map for Anti-phase Bursting in Coupled Inhibitory Neurons With Synaptic Depression. Frontiers in Applied Mathematics and Statistics. 8. 822782–822782. 1 indexed citations

Perkins, Adam M., et al.. (2022). Objective measures of reward sensitivity and motivation in people with high v. low anhedonia. Psychological Medicine. 53(10). 4324–4332. 14 indexed citations

10.

Kazanina, Nina, et al.. (2022). Syllable-Initial Phonemes Affect Neural Entrainment to Consonant-Vowel Syllables. Frontiers in Neuroscience. 16. 826105–826105. 2 indexed citations

11.

Kazanina, Nina, et al.. (2021). Grammatical category and the neural processing of phrases. Scientific Reports. 11(1). 2446–2446. 20 indexed citations

12.

Bird, Alex D., et al.. (2019). Model-Based Inference of Synaptic Transmission. Frontiers in Synaptic Neuroscience. 11. 21–21. 13 indexed citations

13.

Houghton, Conor. (2018). Calculating the Mutual Information between Two Spike Trains. Neural Computation. 31(2). 330–343. 7 indexed citations

14.

Houghton, Conor, et al.. (2017). Behavioural and computational methods reveal differential effects for how delayed and rapid onset antidepressants effect decision making in rats. European Neuropsychopharmacology. 27(12). 1268–1280. 29 indexed citations

15.

Houghton, Conor. (2016). Dentate gyrus and hilar region revisited. Behavioral and Brain Sciences. 39. e210–e210. 3 indexed citations

16.

Houghton, Conor, et al.. (2015). Parameter estimation of neuron models using in-vitro and in-vivo electrophysiological data. Frontiers in Neuroinformatics. 9. 10–10. 15 indexed citations

17.

Gillespie, James B. & Conor Houghton. (2010). A metric space approach to the information channel capacity of spike trains. Journal of Computational Neuroscience. 30(1). 201–209. 2 indexed citations

18.

Houghton, Conor & James B. Gillespie. (2010). A metric space approach to the information capacity of spike trains. Arrow@dit (Dublin Institute of Technology). 1 indexed citations

19.

Houghton, Conor. (2008). Studying spike trains using a van Rossum metric with a synapse-like filter. Journal of Computational Neuroscience. 26(1). 149–155. 17 indexed citations

20.

Houghton, Conor, N. S. Manton, & Paul Sutcliffe. (1998). Rational maps, monopoles and skyrmions. Nuclear Physics B. 510(3). 507–537. 211 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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