D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Neuroscience D-index 61 Citations 15,531 141 World Ranking 1366 National Ranking 115

Overview

What is he best known for?

The fields of study he is best known for:

  • Neuroscience
  • Cognition
  • Electroencephalography

Stefan Debener mainly focuses on Electroencephalography, Neuroscience, Cognition, Independent component analysis and Audiology. The study incorporates disciplines such as Speech recognition, Communication and Pattern recognition in addition to Electroencephalography. Many of his research projects under Neuroscience are closely connected to Committee report with Committee report, tying the diverse disciplines of science together.

He studied Cognition and Perception that intersect with Cognitive psychology, Stimulus and Developmental psychology. His Independent component analysis research is under the purview of Artificial intelligence. His studies in Audiology integrate themes in fields like Electrophysiology and Visual cortex.

His most cited work include:

  • Default-mode brain dysfunction in mental disorders: A systematic review (1201 citations)
  • Mining event-related brain dynamics. (1075 citations)
  • Trial-by-Trial Coupling of Concurrent Electroencephalogram and Functional Magnetic Resonance Imaging Identifies the Dynamics of Performance Monitoring (872 citations)

What are the main themes of his work throughout his whole career to date?

Electroencephalography, Audiology, Neuroscience, Speech recognition and Cognition are his primary areas of study. His Electroencephalography research incorporates themes from Stimulus and Independent component analysis, Artificial intelligence. His work deals with themes such as Computer vision and Pattern recognition, which intersect with Artificial intelligence.

His research integrates issues of Visual perception, Perception and Electrophysiology in his study of Audiology. His Cognition study frequently links to related topics such as Developmental psychology. His work in Auditory cortex tackles topics such as Evoked potential which are related to areas like N100.

He most often published in these fields:

  • Electroencephalography (66.84%)
  • Audiology (40.11%)
  • Neuroscience (18.72%)

What were the highlights of his more recent work (between 2018-2021)?

  • Electroencephalography (66.84%)
  • Audiology (40.11%)
  • Artificial intelligence (11.76%)

In recent papers he was focusing on the following fields of study:

His main research concerns Electroencephalography, Audiology, Artificial intelligence, Neurofeedback and Pattern recognition. His Electroencephalography research incorporates elements of Stimulus, Neural correlates of consciousness and Speech recognition. His study in Audiology is interdisciplinary in nature, drawing from both Forehead and Eeg data.

His Neurofeedback research is multidisciplinary, incorporating elements of Motor imagery and Cognition. His research in Cognition intersects with topics in Checklist and Applied psychology. In his work, Subspace topology and Independent component analysis is strongly intertwined with Artifact, which is a subfield of Pattern recognition.

Between 2018 and 2021, his most popular works were:

  • Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist) (60 citations)
  • A Riemannian Modification of Artifact Subspace Reconstruction for EEG Artifact Handling (44 citations)
  • Machine-learning-derived sleep-wake staging from around-the-ear electroencephalogram outperforms manual scoring and actigraphy. (33 citations)

In his most recent research, the most cited papers focused on:

  • Neuroscience
  • Cognition
  • Electroencephalography

His primary areas of investigation include Electroencephalography, Speech recognition, Neural correlates of consciousness, Audiology and Active listening. The study incorporates disciplines such as Subspace topology, Covariance and Audiogram in addition to Electroencephalography. Stefan Debener works mostly in the field of Speech recognition, limiting it down to topics relating to Stimulus and, in certain cases, Sentence, as a part of the same area of interest.

His Neural correlates of consciousness research is multidisciplinary, relying on both Recall, Free recall, Spatial contextual awareness, Landmark and Episodic memory. The various areas that Stefan Debener examines in his Audiology study include Electrophysiology and Frequency following response. His biological study spans a wide range of topics, including Cross modal plasticity, Noise, Cognitive resource theory and Presbycusis.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Default-mode brain dysfunction in mental disorders: A systematic review

Samantha J. Broyd;Charmaine Demanuele;Stefan Debener;Suzannah K. Helps.
Neuroscience & Biobehavioral Reviews (2009)

1654 Citations

Mining event-related brain dynamics.

Scott Makeig;Stefan Debener;Julie Onton;Arnaud Delorme.
Trends in Cognitive Sciences (2004)

1356 Citations

Trial-by-Trial Coupling of Concurrent Electroencephalogram and Functional Magnetic Resonance Imaging Identifies the Dynamics of Performance Monitoring

Stefan Debener;Markus Ullsperger;Markus Siegel;Katja Fiehler.
The Journal of Neuroscience (2005)

1064 Citations

How about taking a low-cost, small, and wireless EEG for a walk?

Stefan Debener;Falk Minow;Reiner Emkes;Katharina Gandras.
Psychophysiology (2012)

494 Citations

Prediction of human errors by maladaptive changes in event-related brain networks.

Tom Eichele;Stefan Debener;Vince D. Calhoun;Vince D. Calhoun;Vince D. Calhoun;Karsten Specht;Karsten Specht.
Proceedings of the National Academy of Sciences of the United States of America (2008)

474 Citations

Single-trial EEG–fMRI reveals the dynamics of cognitive function

Stefan Debener;Markus Ullsperger;Markus Siegel;Andreas K. Engel.
Trends in Cognitive Sciences (2006)

449 Citations

Committee report: Publication guidelines and recommendations for studies using electroencephalography and magnetoencephalography

Andreas Keil;Stefan Debener;Gabriele Gratton;Markus Junghöfer.
Psychophysiology (2014)

419 Citations

Is Resting Anterior EEG Alpha Asymmetry a Trait Marker for Depression

Stefan Debener;André Beauducel;Doreen Nessler;Burkhard Brocke.
Neuropsychobiology (2000)

414 Citations

What is novel in the novelty oddball paradigm? Functional significance of the novelty P3 event-related potential as revealed by independent component analysis.

Stefan Debener;Scott Makeig;Arnaud Delorme;Andreas K. Engel.
Cognitive Brain Research (2005)

333 Citations

Semi-automatic identification of independent components representing EEG artifact.

Filipa Campos Viola;Jeremy Thorne;Barrie Edmonds;Till Schneider.
Clinical Neurophysiology (2009)

313 Citations

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