Gordon Pipa

4.6k total citations · 1 hit paper
90 papers, 2.9k citations indexed

About

Gordon Pipa is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Artificial Intelligence. According to data from OpenAlex, Gordon Pipa has authored 90 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Cognitive Neuroscience, 22 papers in Cellular and Molecular Neuroscience and 19 papers in Artificial Intelligence. Recurrent topics in Gordon Pipa's work include Neural dynamics and brain function (52 papers), Advanced Memory and Neural Computing (15 papers) and Neuroscience and Neural Engineering (15 papers). Gordon Pipa is often cited by papers focused on Neural dynamics and brain function (52 papers), Advanced Memory and Neural Computing (15 papers) and Neuroscience and Neural Engineering (15 papers). Gordon Pipa collaborates with scholars based in Germany, United States and Netherlands. Gordon Pipa's co-authors include Michael Wibral, Raúl Vicente, Michael Lindner, Raúl Vicente, Wolf Singer, Peter König, Cláudio R. Mirasso, Sergio Neuenschwander, Leonardo L. Gollo and Ingo Fischer and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Gordon Pipa

84 papers receiving 2.9k citations

Hit Papers

Transfer entropy—a model-free measure of effective connec... 2010 2026 2015 2020 2010 200 400 600
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.

  1. Transfer entropy—a model-free measure of effective connectivity for the neurosciences
    2010 669 citations Michael Wibral, Gordon Pipa et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gordon Pipa Germany 23 2.2k 572 367 282 255 90 2.9k
Rubén Moreno‐Bote Spain 26 2.3k 1.0× 668 1.2× 462 1.3× 219 0.8× 117 0.5× 62 2.6k
Eric Brown United States 7 1.3k 0.6× 213 0.4× 261 0.7× 164 0.6× 251 1.0× 7 1.9k
Murray Shanahan United Kingdom 34 1.5k 0.7× 473 0.8× 133 0.4× 1.2k 4.4× 387 1.5× 93 3.9k
Rafał Bogacz United Kingdom 38 4.4k 2.0× 1.6k 2.8× 196 0.5× 543 1.9× 101 0.4× 121 6.6k
Demian Battaglia France 20 1.3k 0.6× 578 1.0× 247 0.7× 151 0.5× 185 0.7× 52 2.0k
Viola Priesemann Germany 25 1.9k 0.9× 585 1.0× 402 1.1× 288 1.0× 120 0.5× 70 3.2k
Yonatan Loewenstein Israel 24 1.3k 0.6× 749 1.3× 96 0.3× 194 0.7× 52 0.2× 65 2.0k
Peter J. Thomas United States 23 852 0.4× 404 0.7× 406 1.1× 142 0.5× 243 1.0× 101 1.8k
Mark D. Humphries United Kingdom 24 2.2k 1.0× 1.2k 2.0× 292 0.8× 185 0.7× 99 0.4× 59 3.4k
Michael Wibral Germany 41 5.2k 2.4× 1.2k 2.0× 495 1.3× 480 1.7× 164 0.6× 97 6.9k

Countries citing papers authored by Gordon Pipa

Since Specialization
Citations

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

Fields of papers citing papers by Gordon Pipa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gordon Pipa

This figure shows the co-authorship network connecting the top 25 collaborators of Gordon Pipa. A scholar is included among the top collaborators of Gordon Pipa 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 Gordon Pipa. Gordon Pipa 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.
Pipa, Gordon, et al.. (2025). Potential role of developmental experience in the emergence of the parvo-magno distinction. Communications Biology. 8(1). 987–987.
2.
Pipa, Gordon, et al.. (2024). Spike synchrony as a measure of Gestalt structure. Scientific Reports. 14(1). 5910–5910.
3.
Kippenberger, Stefan, Gordon Pipa, Nadja Zöller, et al.. (2023). Learning in the Single-Cell Organism Physarum polycephalum: Effect of Propofol. International Journal of Molecular Sciences. 24(7). 6287–6287. 5 indexed citations
4.
Langguth, Michael, et al.. (2023). Deep learning models for generation of precipitation maps based on numerical weather prediction. Geoscientific model development. 16(5). 1467–1480. 7 indexed citations
5.
Pipa, Gordon, et al.. (2023). Dendritic plateau potentials can process spike sequences across multiple time-scales. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 2. 7 indexed citations
6.
7.
Che, Lin, et al.. (2021). Feasible and Adaptive Multimodal Trajectory Prediction with Semantic Maneuver Fusion. 8530–8536. 5 indexed citations
8.
Schultz, Martin, Felix Kleinert, Lukas Hubert Leufen, et al.. (2019). DeepRain - Improved local-scale prediction of precipitation through deep learning. EGU General Assembly Conference Abstracts. 13625. 1 indexed citations
9.
Gómez-Herrero, Germán, et al.. (2015). Assessing Coupling Dynamics from an Ensemble of Time Series. Entropy. 17(4). 1958–1970. 50 indexed citations
10.
Schmitz, S., et al.. (2015). Application of Parallel Factor Analysis (PARAFAC) to electrophysiological data. Frontiers in Neuroinformatics. 8. 84–84. 7 indexed citations
11.
Pipa, Gordon, et al.. (2014). Spatiotemporal Computations of an Excitable and Plastic Brain: Neuronal Plasticity Leads to Noise-Robust and Noise-Constructive Computations. PLoS Computational Biology. 10(3). e1003512–e1003512. 23 indexed citations
12.
Aru, Juhan, Jaan Aru, Viola Priesemann, et al.. (2014). Untangling cross-frequency coupling in neuroscience. Current Opinion in Neurobiology. 31. 51–61. 394 indexed citations
13.
Haslinger, Robert, Gordon Pipa, Bruss Lima, et al.. (2012). Context Matters: The Illusive Simplicity of Macaque V1 Receptive Fields. PLoS ONE. 7(7). e39699–e39699. 14 indexed citations
14.
Haslinger, Robert, et al.. (2012). Statistical modeling approach for detecting generalized synchronization. Physical Review E. 85(5). 56215–56215. 15 indexed citations
15.
Haslinger, Robert, Gordon Pipa, & Emery N. Brown. (2010). Discrete Time Rescaling Theorem: Determining Goodness of Fit for Statistical Models of Neural Spiking. DSpace@MIT (Massachusetts Institute of Technology). 1 indexed citations
16.
Scheller, Bertram, Gordon Pipa, Joachim R. Ehrlich, et al.. (2010). LOW HEMOGLOBIN LEVELS DURING NORMOVOLEMIA ARE ASSOCIATED WITH ELECTROCARDIOGRAPHIC CHANGES IN PIGS. Shock. 35(4). 375–381. 7 indexed citations
17.
Vicente, Raúl, Leonardo L. Gollo, Cláudio R. Mirasso, Ingo Fischer, & Gordon Pipa. (2008). Dynamical relaying can yield zero time lag neuronal synchrony despite long conduction delays. Proceedings of the National Academy of Sciences. 105(44). 17157–17162. 250 indexed citations
18.
Wu, Wei, et al.. (2008). Behavioral performance modulates spike field coherence in monkey prefrontal cortex. Neuroreport. 19(2). 235–238. 14 indexed citations
19.
Lazăr, Andreea, Gordon Pipa, & Jochen Triesch. (2006). The combination of STDP and intrinsic plasticity yields complex dynamics in recurrent spiking networks.. The European Symposium on Artificial Neural Networks. 647–652. 5 indexed citations
20.
Mureșan, Raul C., Gordon Pipa, Răzvan V. Florian, & Diek W. Wheeler. (2005). Coherence, Memory and Conditioning. International Conference on Neural Information Processing. 7(2). 19–28. 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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