Spyridon Chavlis

1.2k total citations
15 papers, 480 citations indexed

About

Spyridon Chavlis is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Electrical and Electronic Engineering. According to data from OpenAlex, Spyridon Chavlis has authored 15 papers receiving a total of 480 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cognitive Neuroscience, 8 papers in Cellular and Molecular Neuroscience and 6 papers in Electrical and Electronic Engineering. Recurrent topics in Spyridon Chavlis's work include Neural dynamics and brain function (10 papers), Advanced Memory and Neural Computing (6 papers) and Memory and Neural Mechanisms (6 papers). Spyridon Chavlis is often cited by papers focused on Neural dynamics and brain function (10 papers), Advanced Memory and Neural Computing (6 papers) and Memory and Neural Mechanisms (6 papers). Spyridon Chavlis collaborates with scholars based in Greece, United States and Bulgaria. Spyridon Chavlis's co-authors include Panayiota Poirazi, Panagiotis C. Petrantonakis, Attila Losonczy, Max Ladow, Gergely F. Turi, Nathan Danielson, Boris V. Zemelman, Wenke Li, Andres Grosmark and Justin K. O’Hare and has published in prestigious journals such as Nature Communications, Neuron and Current Opinion in Neurobiology.

In The Last Decade

Spyridon Chavlis

14 papers receiving 474 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Spyridon Chavlis Greece	9	356	342	71	61	60	15	480
George Kastellakis Greece	9	375 1.1×	373 1.1×	63 0.9×	105 1.7×	78 1.3×	13	528
Megha Sehgal United States	6	311 0.9×	233 0.7×	86 1.2×	44 0.7×	102 1.7×	10	497
Sachin P Vaidya United States	6	535 1.5×	485 1.4×	60 0.8×	65 1.1×	132 2.2×	6	652
William Mau United States	11	369 1.0×	451 1.3×	65 0.9×	21 0.3×	36 0.6×	12	518
Kishore V. Kuchibhotla United States	8	298 0.8×	349 1.0×	39 0.5×	42 0.7×	108 1.8×	12	505
Jeffrey P. Gavornik United States	13	458 1.3×	484 1.4×	50 0.7×	69 1.1×	190 3.2×	24	747
Daigo Takeuchi Japan	10	415 1.2×	593 1.7×	43 0.6×	29 0.5×	44 0.7×	12	713
Jeehyun Kwag South Korea	10	319 0.9×	311 0.9×	35 0.5×	68 1.1×	56 0.9×	24	438
Nitzan Geva Israel	7	400 1.1×	480 1.4×	56 0.8×	16 0.3×	47 0.8×	7	566
Mark Sheffield United States	10	540 1.5×	491 1.4×	102 1.4×	53 0.9×	107 1.8×	17	677

Countries citing papers authored by Spyridon Chavlis

Since Specialization

Citations

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

Fields of papers citing papers by Spyridon Chavlis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Spyridon Chavlis

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

All Works

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15 of 15 papers shown

1.

Chavlis, Spyridon & Panayiota Poirazi. (2025). Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning. Nature Communications. 16(1). 943–943. 9 indexed citations

2.

Chavlis, Spyridon, et al.. (2023). Introducing the Dendrify framework for incorporating dendrites to spiking neural networks. Nature Communications. 14(1). 131–131. 28 indexed citations

3.

Chavlis, Spyridon, et al.. (2023). Delay-Sensitive Local Plasticity in Echo State Networks. Ghent University Academic Bibliography (Ghent University). 1–8. 1 indexed citations

4.

Chavlis, Spyridon, et al.. (2023). Synaptic turnover promotes efficient learning in bio-realistic spiking neural networks. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations

5.

Chavlis, Spyridon, et al.. (2023). Lateral entorhinal cortex inputs modulate hippocampal dendritic excitability by recruiting a local disinhibitory microcircuit. Cell Reports. 42(1). 111962–111962. 18 indexed citations

6.

Chavlis, Spyridon, et al.. (2023). Synaptic turnover promotes efficient learning in bio-realistic spiking neural networks. Zenodo (CERN European Organization for Nuclear Research). 942–949. 1 indexed citations

7.

Chavlis, Spyridon & Panayiota Poirazi. (2022). Modeling Dendrites and Spatially-Distributed Neuronal Membrane Properties. Advances in experimental medicine and biology. 1359. 25–67. 2 indexed citations

8.

Chavlis, Spyridon & Panayiota Poirazi. (2021). Drawing inspiration from biological dendrites to empower artificial neural networks. Current Opinion in Neurobiology. 70. 1–10. 34 indexed citations

9.

Chavlis, Spyridon, et al.. (2021). Evolutionary models of amino acid substitutions based on the tertiary structure of their neighborhoods. Proteins Structure Function and Bioinformatics. 89(11). 1565–1576.

10.

Geiller, Tristan, Satoshi Terada, Spyridon Chavlis, et al.. (2020). Large-Scale 3D Two-Photon Imaging of Molecularly Identified CA1 Interneuron Dynamics in Behaving Mice. Neuron. 108(5). 968–983.e9. 79 indexed citations

11.

Turi, Gergely F., Wenke Li, Spyridon Chavlis, et al.. (2019). Vasoactive Intestinal Polypeptide-Expressing Interneurons in the Hippocampus Support Goal-Oriented Spatial Learning. Neuron. 101(6). 1150–1165.e8. 115 indexed citations

12.

Chavlis, Spyridon & Panayiota Poirazi. (2017). Pattern separation in the hippocampus through the eyes of computational modeling. Synapse. 71(6). 14 indexed citations

13.

Danielson, Nathan, Gergely F. Turi, Max Ladow, et al.. (2017). In Vivo Imaging of Dentate Gyrus Mossy Cells in Behaving Mice. Neuron. 93(3). 552–559.e4. 121 indexed citations

14.

Dollas, Apostolos, Ioannis Papaefstathiou, Dionisios Pnevmatikatos, et al.. (2017). An Architecture for the Acceleration of a Hybrid Leaky Integrate and Fire SNN on the Convey HC-2ex FPGA-Based Processor. 345. 56–63. 5 indexed citations

15.

Chavlis, Spyridon, Panagiotis C. Petrantonakis, & Panayiota Poirazi. (2016). Dendrites of dentate gyrus granule cells contribute to pattern separation by controlling sparsity. Hippocampus. 27(1). 89–110. 52 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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