Andreas Galka

1.4k total citations
50 papers, 926 citations indexed

About

Andreas Galka is a scholar working on Cognitive Neuroscience, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Andreas Galka has authored 50 papers receiving a total of 926 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Cognitive Neuroscience, 23 papers in Signal Processing and 9 papers in Artificial Intelligence. Recurrent topics in Andreas Galka's work include Blind Source Separation Techniques (21 papers), EEG and Brain-Computer Interfaces (21 papers) and Neural dynamics and brain function (17 papers). Andreas Galka is often cited by papers focused on Blind Source Separation Techniques (21 papers), EEG and Brain-Computer Interfaces (21 papers) and Neural dynamics and brain function (17 papers). Andreas Galka collaborates with scholars based in Germany, Japan and United States. Andreas Galka's co-authors include Tohru Ozaki, Ulrich Stephani, Okito Yamashita, R. Biscay, Pedro A. Valdés‐Sosa, Hiltrud Muhle, Ulrich Heute, Gerold Baier, Markus Müller and Michael Siniatchkin and has published in prestigious journals such as PLoS ONE, NeuroImage and Scientific Reports.

In The Last Decade

Andreas Galka

48 papers receiving 892 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andreas Galka Germany 16 553 218 142 138 120 50 926
R. Biscay Cuba 22 836 1.5× 197 0.9× 125 0.9× 41 0.3× 138 1.1× 60 1.4k
Lutz Leistritz Germany 20 732 1.3× 106 0.5× 243 1.7× 36 0.3× 122 1.0× 85 1.2k
M. Eiselt Germany 22 735 1.3× 122 0.6× 208 1.5× 48 0.3× 55 0.5× 77 1.6k
Anahita Adeli United States 12 718 1.3× 162 0.7× 47 0.3× 61 0.4× 97 0.8× 14 1.1k
Matthias Winterhalder Germany 14 1.2k 2.1× 392 1.8× 35 0.2× 142 1.0× 142 1.2× 22 1.5k
Raúl Vicente Germany 14 1.1k 1.9× 86 0.4× 80 0.6× 227 1.6× 287 2.4× 22 2.0k
L. Sendur United States 10 373 0.7× 122 0.6× 213 1.5× 85 0.6× 42 0.3× 14 1.7k
Christian Rummel Switzerland 23 1.3k 2.3× 255 1.2× 197 1.4× 165 1.2× 85 0.7× 94 1.9k
Wolfram Hesse Germany 10 637 1.2× 100 0.5× 65 0.5× 43 0.3× 74 0.6× 18 794
Andreas Ziehe Germany 20 830 1.5× 1.0k 4.7× 75 0.5× 49 0.4× 314 2.6× 30 1.9k

Countries citing papers authored by Andreas Galka

Since Specialization
Citations

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

Fields of papers citing papers by Andreas Galka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andreas Galka

This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Galka. A scholar is included among the top collaborators of Andreas Galka 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 Andreas Galka. Andreas Galka 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.
Miwakeichi, Fumikazu & Andreas Galka. (2023). Comparison of Bootstrap Methods for Estimating Causality in Linear Dynamic Systems: A Review. Entropy. 25(7). 1070–1070. 2 indexed citations
2.
Arnrich, Bert, et al.. (2023). State Space Modeling of Event Count Time Series. Entropy. 25(10). 1372–1372. 1 indexed citations
3.
Miwakeichi, Fumikazu & Andreas Galka. (2023). Comparison of Bootstrap Methods for Estimating Causality in Linear Dynamic Systems: A Review. Preprints.org. 2 indexed citations
4.
Aydın, Ümit, Carsten H. Wolters, Jens Christian Claussen, et al.. (2020). Source imaging of deep-brain activity using the regional spatiotemporal Kalman filter. Computer Methods and Programs in Biomedicine. 200. 105830–105830. 5 indexed citations
5.
Zabel, Sebastian, Andreas Galka, J.‐M. Wagner, et al.. (2019). Magnetic particle mapping using magnetoelectric sensors as an imaging modality. Scientific Reports. 9(1). 2086–2086. 23 indexed citations
6.
Siniatchkin, Michael, Andreas Galka, Friederike Moeller, et al.. (2018). Multifocal epilepsy in children is associated with increased long-distance functional connectivity: An explorative EEG-fMRI study. European Journal of Paediatric Neurology. 22(6). 1054–1065. 11 indexed citations
7.
Siniatchkin, Michael, et al.. (2018). Pipeline for Forward Modeling and Source Imaging of Magnetocardiographic Recordings via Spatiotemporal Kalman Filtering. PubMed. 2018. 199–202. 1 indexed citations
8.
Muthalib, Makii, Stéphane Perrey, Andreas Galka, et al.. (2016). Effective Connectivity of Cortical Sensorimotor Networks During Finger Movement Tasks: A Simultaneous fNIRS, fMRI, EEG Study. Brain Topography. 29(5). 645–660. 104 indexed citations
9.
Wiegand, Gert, et al.. (2015). The performance of the spatiotemporal Kalman filter and LORETA in seizure onset localization. PubMed. 2015. 2741–2744. 2 indexed citations
10.
Muthalib, Makii, Stéphane Perrey, Andreas Galka, et al.. (2012). Directionality analysis on functional magnetic resonance imaging during motor task using Granger Causality. PubMed. 85. 2287–2290. 6 indexed citations
11.
Heute, Ulrich, et al.. (2012). Muscle artifact suppression using Independent-Component Analysis and State-Space Modeling. PubMed. 2012. 6500–6503. 3 indexed citations
12.
Galka, Andreas, Kin Foon Kevin Wong, Tohru Ozaki, et al.. (2010). Decomposition of Neurological Multivariate Time Series by State Space Modelling. Bulletin of Mathematical Biology. 73(2). 285–324. 15 indexed citations
13.
Bosch‐Bayard, Jorge, Rolando J. Biscay-Lirio, Kin Foon Kevin Wong, et al.. (2010). SPATIO-TEMPORAL CORRELATIONS FROM fMRI TIME SERIES BASED ON THE NN-ARx MODEL. Journal of Integrative Neuroscience. 9(4). 381–406.
14.
Galka, Andreas, Michael Siniatchkin, Ulrich Stephani, et al.. (2010). OPTIMAL HRF AND SMOOTHING PARAMETERS FOR FMRI TIME SERIES WITHIN AN AUTOREGRESSIVE MODELING FRAMEWORK. Journal of Integrative Neuroscience. 9(4). 429–452. 2 indexed citations
15.
Galka, Andreas, Tohru Ozaki, Hiltrud Muhle, Ulrich Stephani, & Michael Siniatchkin. (2008). A data-driven model of the generation of human EEG based on a spatially distributed stochastic wave equation. Cognitive Neurodynamics. 2(2). 101–113. 14 indexed citations
16.
Wong, Kin Foon Kevin, Andreas Galka, Okito Yamashita, & Tohru Ozaki. (2005). Modelling non-stationary variance in EEG time series by state space GARCH model. Computers in Biology and Medicine. 36(12). 1327–1335. 32 indexed citations
17.
Müller, Markus, Gerold Baier, Andreas Galka, Ulrich Stephani, & Hiltrud Muhle. (2005). Detection and characterization of changes of the correlation structure in multivariate time series. Physical Review E. 71(4). 46116–46116. 87 indexed citations
18.
Galka, Andreas, et al.. (2004). Recursive penalized least squares solution for dynamical inverse problems of EEG generation. Human Brain Mapping. 21(4). 221–235. 57 indexed citations
19.
Miwakeichi, Fumikazu, Andreas Galka, Sunao Uchida, et al.. (2004). Impulse response function based on multivariate AR model can differentiate focal hemisphere in temporal lobe epilepsy. Epilepsy Research. 61(1-3). 73–87. 6 indexed citations
20.
Galka, Andreas, Okito Yamashita, Tohru Ozaki, R. Biscay, & Pedro A. Valdés‐Sosa. (2004). A solution to the dynamical inverse problem of EEG generation using spatiotemporal Kalman filtering. NeuroImage. 23(2). 435–453. 112 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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