Jean-Pascal Pfister

2.4k citations
34 papers · 1.4k · h-index 15

Impact in

Papers in

Jean-Pascal Pfister

33 papers receiving 1.4k citations

Peers

Jean-Pascal Pfister
Comparison fields: 5 of 97
  • Cognitive Neuroscience 1.1k
  • Cellular and Molecular Neuroscience 782
  • Electrical and Electronic Engineering 897
  • Artificial Intelligence 267
  • Statistical and Nonlinear Physics 84
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Citations per year

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-authors

The 25 scholars most cited alongside Jean-Pascal Pfister, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jean-Pascal Pfister Line = papers co-authored together Jean-Pascal Pfister links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006428
2 2006169
3 2011137
4 2014126
5 200586
6 201383
7 201055
8 202150
9 198441
10 201039
11 200739
12 201023
13 201721
14
Sequence learning with hidden units in spiking neural networks
201120
15 201920
16
Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model
200413
17 201913
18
Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency Effects
200511
19
Know Thy Neighbour: A Normative Theory of Synaptic Depression
200910
20 20189

About Jean-Pascal Pfister

Jean-Pascal Pfister is a scholar working on Cognitive Neuroscience, Electrical and Electronic Engineering, Cellular and Molecular Neuroscience, Artificial Intelligence and Molecular Biology, having authored 34 papers that have together received 1.4k indexed citations. Recurring topics across this work include Neural dynamics and brain function (25 papers), Advanced Memory and Neural Computing (15 papers), Neuroscience and Neuropharmacology Research (7 papers), Neuroscience and Neural Engineering (5 papers), Neural Networks and Reservoir Computing (3 papers), Photoreceptor and optogenetics research (3 papers), Neural Networks and Applications (2 papers) and Electrochemical Analysis and Applications (2 papers). The work is most often cited by research in Cognitive Neuroscience (1.1k citations), Cellular and Molecular Neuroscience (782 citations), Electrical and Electronic Engineering (897 citations), Artificial Intelligence (267 citations) and Statistical and Nonlinear Physics (84 citations). Jean-Pascal Pfister has collaborated with scholars based in Switzerland, United Kingdom and Japan. Frequent co-authors include Wulfram Gerstner, Taro Toyoizumi, Walter Senn, David Barber, Kazuyuki Aihara, Claudia Clopath, Julijana Gjorgjieva, José Brea, Thomas Nevian and Mirko Santello. Their work appears in journals such as Journal of Neuroscience, PLoS Computational Biology, Nature Neuroscience, Neural Computation and Proceedings of the National Academy of Sciences.

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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