Daniel J. Strauß

1.7k total citations
163 papers, 1.2k citations indexed

About

Daniel J. Strauß is a scholar working on Cognitive Neuroscience, Signal Processing and Sensory Systems. According to data from OpenAlex, Daniel J. Strauß has authored 163 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 126 papers in Cognitive Neuroscience, 29 papers in Signal Processing and 28 papers in Sensory Systems. Recurrent topics in Daniel J. Strauß's work include Neural dynamics and brain function (61 papers), Hearing Loss and Rehabilitation (56 papers) and EEG and Brain-Computer Interfaces (36 papers). Daniel J. Strauß is often cited by papers focused on Neural dynamics and brain function (61 papers), Hearing Loss and Rehabilitation (56 papers) and EEG and Brain-Computer Interfaces (36 papers). Daniel J. Strauß collaborates with scholars based in Germany, United States and Malaysia. Daniel J. Strauß's co-authors include Farah I. Corona–Strauss, W. Delb, Yin Fen Low, Ronny Hannemann, Carlos Trenado, Alexander L. Francis, Harald Seidler, Roberto D’Amelio, Gabriele Steidl and Peter K. Plinkert and has published in prestigious journals such as NeuroImage, Journal of Neurophysiology and The Journal of the Acoustical Society of America.

In The Last Decade

Daniel J. Strauß

147 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel J. Strauß Germany 20 895 280 190 134 132 163 1.2k
Boris Gourévitch France 21 994 1.1× 383 1.4× 58 0.3× 97 0.7× 83 0.6× 48 1.3k
Bernhard Treutwein Germany 12 872 1.0× 53 0.2× 36 0.2× 34 0.3× 183 1.4× 19 1.1k
Pekcan Ungan Türkiye 18 799 0.9× 91 0.3× 102 0.5× 29 0.2× 144 1.1× 42 884
Konstantin Tziridis Germany 18 635 0.7× 464 1.7× 20 0.1× 110 0.8× 51 0.4× 49 965
Tom Francart Belgium 29 2.7k 3.1× 492 1.8× 1.2k 6.4× 675 5.0× 301 2.3× 132 3.0k
Caterina Cinel United Kingdom 18 756 0.8× 36 0.1× 49 0.3× 38 0.3× 111 0.8× 50 938
Jürgen Fell Germany 19 1.4k 1.6× 42 0.1× 80 0.4× 20 0.1× 128 1.0× 31 1.7k
Eduardo Martínez‐Montes Cuba 17 1.2k 1.3× 32 0.1× 268 1.4× 8 0.1× 113 0.9× 49 1.6k
Maie Bachmann Estonia 19 615 0.7× 14 0.1× 88 0.5× 40 0.3× 202 1.5× 53 1.1k
Mark E. Pflieger United States 11 753 0.8× 59 0.2× 52 0.3× 9 0.1× 149 1.1× 19 882

Countries citing papers authored by Daniel J. Strauß

Since Specialization
Citations

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

Fields of papers citing papers by Daniel J. Strauß

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel J. Strauß. 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 Daniel J. Strauß. The network helps show where Daniel J. Strauß may publish in the future.

Co-authorship network of co-authors of Daniel J. Strauß

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel J. Strauß. A scholar is included among the top collaborators of Daniel J. Strauß 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 Daniel J. Strauß. Daniel J. Strauß 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.
2.
Strauß, Daniel J., et al.. (2025). Unraveling the effects of selective auditory attention in ERPs: From the brainstem to the cortex. NeuroImage. 316. 121295–121295.
3.
Corona–Strauss, Farah I., et al.. (2025). Electromyographic correlates of effortful listening in the vestigial auriculomotor system. Frontiers in Neuroscience. 18. 1462507–1462507. 1 indexed citations
4.
Landgraeber, Stefan, et al.. (2025). Enhanced rehabilitation after total joint replacement using a wearable high-density surface electromyography system. Frontiers in Rehabilitation Sciences. 6. 1657543–1657543.
5.
Corona–Strauss, Farah I., et al.. (2024). The vestigial pinna-orienting system in humans briefly suppresses superior auricular muscle activity during reflexive orienting toward auditory stimuli. Journal of Neurophysiology. 132(2). 514–526. 1 indexed citations
6.
Landgraeber, Stefan, et al.. (2023). Neue Perspektiven in der Orthopädie. Die Orthopädie. 52(7). 547–551. 2 indexed citations
7.
Nomura, Shinobu, et al.. (2022). Software for non‐parametric image registration of 2‐photon imaging data. Journal of Biophotonics. 15(8). e202100330–e202100330. 9 indexed citations
8.
Schneider, E., et al.. (2022). Electrodermal Responses to Driving Maneuvers in a Motion Sickness Inducing Real-World Driving Scenario. IEEE Transactions on Human-Machine Systems. 52(5). 994–1003. 8 indexed citations
9.
Trenado, Carlos, et al.. (2021). Multimodal data acquisition at SARS‐CoV ‐2 drive through screening centers: Setup description and experiences in Saarland, Germany. Journal of Biophotonics. 14(8). e202000512–e202000512. 3 indexed citations
10.
Schneider, E., et al.. (2021). Motion Sickness Prediction in Self-Driving Cars Using the 6DOF-SVC Model. IEEE Transactions on Intelligent Transportation Systems. 23(8). 13582–13591. 10 indexed citations
11.
Kühn, Bernd, et al.. (2021). Fast variational alignment of non-flat 1D displacements for applications in neuroimaging. Journal of Neuroscience Methods. 353. 109076–109076. 2 indexed citations
12.
Strauß, Daniel J., et al.. (2020). Vestigial auriculomotor activity indicates the direction of auditory attention in humans. eLife. 9. 21 indexed citations
13.
Bennewitz, Roland, et al.. (2019). Friction in Passive Tactile Perception Induces Phase Coherency in Late Somatosensory Single Trial Sequences. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 27(2). 129–138. 3 indexed citations
14.
Corona–Strauss, Farah I., et al.. (2019). Implementation and Long-Term Evaluation of a Hearing Aid Supported Tinnitus Treatment Using Notched Environmental Sounds. IEEE Journal of Translational Engineering in Health and Medicine. 7. 1–9. 24 indexed citations
15.
Pfleger, Norbert, et al.. (2019). Electroencephalographic Phase–Amplitude Coupling in Simulated Driving With Varying Modality-Specific Attentional Demand. IEEE Transactions on Human-Machine Systems. 49(6). 589–598. 7 indexed citations
16.
Wagner, Eric F., et al.. (2018). Somatosensory Evoked Responses Elicited by Haptic Sensations in Midair. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 26(10). 2070–2077. 7 indexed citations
17.
Low, Yin Fen & Daniel J. Strauß. (2009). EEG phase reset due to auditory attention: an inverse time-scale approach. Physiological Measurement. 30(8). 821–832. 14 indexed citations
18.
Wallhäußer-Franke, Elisabeth, et al.. (2009). Modeling limbic influences on habituation deficits in chronic tinnitus aurium. PubMed. 2009. 4234–7. 12 indexed citations
19.
Delb, W., et al.. (2008). Extraction of habituation correlates in single-sweep sequences of late auditory evoked potentials using time-scale coherence: objective detection of uncomfortable loudness level. 83–87. 3 indexed citations
20.
Low, Yin Fen, Carlos Trenado, W. Delb, Farah I. Corona–Strauss, & Daniel J. Strauß. (2007). The Role of Attention in the Tinnitus Decompensation: Reinforcement of a Large-Scale Neural Decompensation Measure. Conference proceedings. 2007. 2485–2488. 9 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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