Steven J. Middleton

2.7k total citations · 1 hit paper
17 papers, 1.7k citations indexed

About

Steven J. Middleton is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, Steven J. Middleton has authored 17 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Cellular and Molecular Neuroscience, 15 papers in Cognitive Neuroscience and 5 papers in Molecular Biology. Recurrent topics in Steven J. Middleton's work include Neuroscience and Neuropharmacology Research (14 papers), Neural dynamics and brain function (9 papers) and Memory and Neural Mechanisms (9 papers). Steven J. Middleton is often cited by papers focused on Neuroscience and Neuropharmacology Research (14 papers), Neural dynamics and brain function (9 papers) and Memory and Neural Mechanisms (9 papers). Steven J. Middleton collaborates with scholars based in United States, Japan and United Kingdom. Steven J. Middleton's co-authors include Miles A. Whittington, Thomas J. McHugh, Mark O. Cunningham, Fiona E. N. LeBeau, Roger D. Traub, Hannah Monyer, Anita K. Roopun, Andrea Bibbig, Andrei Rozov and David M. Bannerman and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Steven J. Middleton

17 papers receiving 1.7k citations

Hit Papers

align trajectories

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.

Gamma Entrainment Binds Higher-Order Brain Regions and Offers Neuroprotection

2019 293 citations Chinnakkaruppan Adaikkan, Steven J. Middleton et al. Neuron profile →

Peers

Steven J. Middleton

CMN

NEURO

Pablo Fuentealba Chile

Timothy Spellman United States

Elke C. Fuchs Germany

Andrew J. D. Nelson United Kingdom

Brigitte Cosquer France

Leonid S. Krimer United States

Jonathan J. Couey Netherlands

Peter V. Massey United Kingdom

Livia de Hoz Germany

Hugo Lehmann Canada

Pablo Fuentealba Chile

Steven J. Middleton

1.3k ×1.1

1.5k ×1.2

CMN

343 ×1.1

285 ×1.1

NEURO

73 ×0.7

Citations per year, relative to Steven J. Middleton Steven J. Middleton (= 1×) peers Pablo Fuentealba

Countries citing papers authored by Steven J. Middleton

Since Specialization

Citations

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

Fields of papers citing papers by Steven J. Middleton

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Steven J. Middleton. 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 Steven J. Middleton. The network helps show where Steven J. Middleton may publish in the future.

Co-authorship network of co-authors of Steven J. Middleton

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

All Works

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17 of 17 papers shown

Adaikkan, Chinnakkaruppan, Justin Joseph, Georgios Foustoukos, et al.. (2024). Silencing CA1 pyramidal cells output reveals the role of feedback inhibition in hippocampal oscillations. Nature Communications. 15(1). 2190–2190. 7 indexed citations

Adaikkan, Chinnakkaruppan, Jun Wang, Steven J. Middleton, et al.. (2022). Alterations in a cross-hemispheric circuit associates with novelty discrimination deficits in mouse models of neurodegeneration. Neuron. 110(19). 3091–3105.e9. 11 indexed citations

Middleton, Steven J., et al.. (2021). Lateralization of CA1 assemblies in the absence of CA3 input. Nature Communications. 12(1). 6114–6114. 10 indexed citations

Chen, Shuo, Arthur Huang, Roman Boehringer, et al.. (2020). A hypothalamic novelty signal modulates hippocampal memory. Nature. 586(7828). 270–274. 135 indexed citations

Adaikkan, Chinnakkaruppan, Steven J. Middleton, Asaf Marco, et al.. (2019). Gamma Entrainment Binds Higher-Order Brain Regions and Offers Neuroprotection. Neuron. 102(5). 929–943.e8. 293 indexed citations breakdown →

Middleton, Steven J. & Thomas J. McHugh. (2019). CA2: A Highly Connected Intrahippocampal Relay. Annual Review of Neuroscience. 43(1). 55–72. 36 indexed citations

Middleton, Steven J., Shuo Chen, Ikuo Ogiwara, et al.. (2018). Altered hippocampal replay is associated with memory impairment in mice heterozygous for the Scn2a gene. Nature Neuroscience. 21(7). 996–1003. 49 indexed citations

Boehringer, Roman, Denis Polygalov, Arthur Huang, et al.. (2017). Chronic Loss of CA2 Transmission Leads to Hippocampal Hyperexcitability. Neuron. 94(3). 642–655.e9. 78 indexed citations

Middleton, Steven J. & Thomas J. McHugh. (2016). Silencing CA3 disrupts temporal coding in the CA1 ensemble. Nature Neuroscience. 19(7). 945–951. 87 indexed citations

10.

Kramer, Mark, et al.. (2014). A Unified Approach to Linking Experimental, Statistical and Computational Analysis of Spike Train Data. PLoS ONE. 9(1). e85269–e85269. 15 indexed citations

11.

Middleton, Steven J., Claudia Racca, Mark O. Cunningham, et al.. (2008). High-Frequency Network Oscillations in Cerebellar Cortex. Neuron. 58(5). 763–774. 102 indexed citations

12.

Traub, Roger D., Steven J. Middleton, Thomas Knöpfel, & Miles A. Whittington. (2008). Model of very fast (> 75 Hz) network oscillations generated by electrical coupling between the proximal axons of cerebellar Purkinje cells. European Journal of Neuroscience. 28(8). 1603–1616. 36 indexed citations

13.

Middleton, Steven J., Tilman Kispersky, Fiona E. N. LeBeau, et al.. (2008). NMDA receptor-dependent switching between different gamma rhythm-generating microcircuits in entorhinal cortex. Proceedings of the National Academy of Sciences. 105(47). 18572–18577. 96 indexed citations

14.

Bibbig, Andrea, Steven J. Middleton, Claudia Racca, et al.. (2007). Beta Rhythms (15–20 Hz) Generated by Nonreciprocal Communication in Hippocampus. Journal of Neurophysiology. 97(4). 2812–2823. 28 indexed citations

15.

Fuchs, Elke C., Aleksandar R. Zivkovic, Mark O. Cunningham, et al.. (2007). Recruitment of Parvalbumin-Positive Interneurons Determines Hippocampal Function and Associated Behavior. Neuron. 53(4). 591–604. 393 indexed citations

16.

Cunningham, Mark O., Steven J. Middleton, Fiona E. N. LeBeau, et al.. (2006). Region-Specific Reduction in Entorhinal Gamma Oscillations and Parvalbumin-Immunoreactive Neurons in Animal Models of Psychiatric Illness. Journal of Neuroscience. 26(10). 2767–2776. 133 indexed citations

17.

Roopun, Anita K., Steven J. Middleton, Mark O. Cunningham, et al.. (2006). A beta2-frequency (20–30 Hz) oscillation in nonsynaptic networks of somatosensory cortex. Proceedings of the National Academy of Sciences. 103(42). 15646–15650. 234 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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