Jean-Pascal Pfister

2.4k total citations
34 papers, 1.4k citations indexed

About

Jean-Pascal Pfister is a scholar working on Cognitive Neuroscience, Electrical and Electronic Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Jean-Pascal Pfister has authored 34 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Cognitive Neuroscience, 15 papers in Electrical and Electronic Engineering and 14 papers in Cellular and Molecular Neuroscience. Recurrent topics in Jean-Pascal Pfister's work include Neural dynamics and brain function (25 papers), Advanced Memory and Neural Computing (15 papers) and Neuroscience and Neuropharmacology Research (7 papers). Jean-Pascal Pfister is often cited by papers focused on Neural dynamics and brain function (25 papers), Advanced Memory and Neural Computing (15 papers) and Neuroscience and Neuropharmacology Research (7 papers). Jean-Pascal Pfister collaborates with scholars based in Switzerland, United Kingdom and Japan. Jean-Pascal Pfister's co-authors include Wulfram Gerstner, Taro Toyoizumi, Walter Senn, David Barber, Kazuyuki Aihara, Julijana Gjorgjieva, Claudia Clopath, José Brea, Mirko Santello and Thomas Nevian and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and Nature Neuroscience.

In The Last Decade

Jean-Pascal Pfister

33 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jean-Pascal Pfister Switzerland 15 1.1k 897 782 267 121 34 1.4k
Samuel A. Neymotin United States 23 1.0k 1.0× 227 0.3× 708 0.9× 65 0.2× 67 0.6× 60 1.3k
Mahmood Amiri Iran 20 853 0.8× 365 0.4× 535 0.7× 129 0.5× 19 0.2× 73 1.3k
Magnus J. E. Richardson United Kingdom 22 1.3k 1.2× 368 0.4× 816 1.0× 73 0.3× 82 0.7× 45 1.6k
Dong Song United States 25 1.7k 1.6× 639 0.7× 1.6k 2.0× 181 0.7× 26 0.2× 190 2.4k
Maurizio Mattia Italy 23 1.8k 1.6× 387 0.4× 839 1.1× 145 0.5× 13 0.1× 67 2.0k
Piotr J. Franaszczuk United States 27 2.5k 2.3× 131 0.1× 767 1.0× 135 0.5× 82 0.7× 82 2.9k
Arvind Kumar Germany 22 1.4k 1.3× 342 0.4× 1.1k 1.4× 105 0.4× 22 0.2× 72 1.8k
Alberto Bernacchia United States 12 1.4k 1.3× 149 0.2× 314 0.4× 224 0.8× 31 0.3× 25 1.6k
Hans‐Rudolf Lüscher Switzerland 14 956 0.9× 245 0.3× 707 0.9× 78 0.3× 30 0.2× 15 1.2k
Christian Tetzlaff Germany 16 553 0.5× 299 0.3× 422 0.5× 107 0.4× 19 0.2× 49 832

Countries citing papers authored by Jean-Pascal Pfister

Since Specialization
Citations

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

Fields of papers citing papers by Jean-Pascal Pfister

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean-Pascal Pfister. 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 Jean-Pascal Pfister. The network helps show where Jean-Pascal Pfister may publish in the future.

Co-authorship network of co-authors of Jean-Pascal Pfister

This figure shows the co-authorship network connecting the top 25 collaborators of Jean-Pascal Pfister. A scholar is included among the top collaborators of Jean-Pascal Pfister 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 Jean-Pascal Pfister. Jean-Pascal Pfister 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.
Pfister, Jean-Pascal, et al.. (2025). Scaling of Ventral Hippocampal Activity during Anxiety. Journal of Neuroscience. 45(12). e1128242025–e1128242025. 2 indexed citations
2.
Delvendahl, Igor, et al.. (2023). Efficient sampling-based Bayesian Active Learning for synaptic characterization. PLoS Computational Biology. 19(8). e1011342–e1011342. 2 indexed citations
3.
Aitchison, Laurence, et al.. (2021). Synaptic plasticity as Bayesian inference. Nature Neuroscience. 24(4). 565–571. 50 indexed citations
4.
Herzog, Michael H., et al.. (2020). Bayesian regression explains how human participants handle parameter uncertainty. PLoS Computational Biology. 16(5). e1007886–e1007886. 1 indexed citations
5.
Pfister, Jean-Pascal & Arko Ghosh. (2020). Generalized priority-based model for smartphone screen touches. Physical review. E. 102(1). 12307–12307. 7 indexed citations
6.
Pfister, Jean-Pascal, et al.. (2020). S1 Appendix -. Figshare. 7 indexed citations
7.
Pfister, Jean-Pascal, et al.. (2020). Identifiability of a Binomial Synapse. Frontiers in Computational Neuroscience. 14. 558477–558477. 5 indexed citations
8.
Bird, Alex D., et al.. (2019). Model-Based Inference of Synaptic Transmission. Frontiers in Synaptic Neuroscience. 11. 21–21. 13 indexed citations
9.
Henning, Christian, et al.. (2018). Approximating the Predictive Distribution via Adversarially-Trained Hypernetworks. Zurich Open Repository and Archive (University of Zurich). 5 indexed citations
10.
Sprekeler, Henning, et al.. (2017). Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception. Scientific Reports. 7(1). 8722–8722. 21 indexed citations
11.
Pfister, Jean-Pascal, et al.. (2015). A Statistical Model for In Vivo Neuronal Dynamics. PLoS ONE. 10(11). e0142435–e0142435. 2 indexed citations
12.
Sprekeler, Henning, et al.. (2015). Approximate nonlinear filtering with a recurrent neural network. BMC Neuroscience. 16(S1).
13.
Pfister, Jean-Pascal, et al.. (2014). Nerve Injury-Induced Neuropathic Pain Causes Disinhibition of the Anterior Cingulate Cortex. Journal of Neuroscience. 34(17). 5754–5764. 126 indexed citations
14.
Brea, Johanni, Walter Senn, & Jean-Pascal Pfister. (2011). Sequence learning with hidden units in spiking neural networks. Bern Open Repository and Information System (University of Bern). 24. 1422–1430. 20 indexed citations
15.
Hennequin, Guillaume, Wulfram Gerstner, & Jean-Pascal Pfister. (2010). STDP in Adaptive Neurons Gives Close-To-Optimal Information Transmission. Frontiers in Computational Neuroscience. 4. 143–143. 23 indexed citations
16.
Pfister, Jean-Pascal, Peter Dayan, & Máté Lengyel. (2009). Know Thy Neighbour: A Normative Theory of Synaptic Depression. MPG.PuRe (Max Planck Society). 22. 1464–1472. 10 indexed citations
17.
Pfister, Jean-Pascal, Taro Toyoizumi, David Barber, & Wulfram Gerstner. (2006). Optimal Spike-Timing-Dependent Plasticity for Precise Action Potential Firing in Supervised Learning. Neural Computation. 18(6). 1318–1348. 169 indexed citations
18.
Pfister, Jean-Pascal & Wulfram Gerstner. (2006). Triplets of Spikes in a Model of Spike Timing-Dependent Plasticity. Journal of Neuroscience. 26(38). 9673–9682. 428 indexed citations
19.
Pfister, Jean-Pascal & Wulfram Gerstner. (2005). Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency Effects. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 18. 1081–1088. 11 indexed citations
20.
Toyoizumi, Taro, Jean-Pascal Pfister, Kazuyuki Aihara, & Wulfram Gerstner. (2004). Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 17. 1409–1416. 13 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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