What is he best known for?
The fields of study he is best known for:
- Neuroscience
- Electroencephalography
- Artificial intelligence
His scientific interests lie mostly in Electroencephalography, Neuroscience, Artificial intelligence, Pattern recognition and Communication.
Electroencephalography is frequently linked to Scalp in his study.
His work on Auditory cortex, Electrophysiology, Evoked potential and Event-related potential as part of general Neuroscience research is frequently linked to Third order, bridging the gap between disciplines.
Michael Scherg has researched Artificial intelligence in several fields, including Brain activity and meditation and Brain mapping.
His Communication study integrates concerns from other disciplines, such as Orientation and Temporal lobe.
His Temporal lobe research focuses on Mismatch negativity and how it relates to Nuclear magnetic resonance.
His most cited work include:
- A source analysis of the late human auditory evoked potentials (648 citations)
- Evoked dipole source potentials of the human auditory cortex (646 citations)
- Two bilateral sources of the late AEP as identified by a spatio-temporal dipole model. (638 citations)
What are the main themes of his work throughout his whole career to date?
Electroencephalography, Neuroscience, Audiology, Magnetoencephalography and Artificial intelligence are his primary areas of study.
His Electroencephalography research is multidisciplinary, incorporating elements of Scalp, Speech recognition and Epilepsy.
His Speech recognition study combines topics in areas such as Equivalent dipole and Mismatch negativity.
His Audiology research focuses on Psychoacoustics and how it connects with Gap detection and Temporal resolution.
His Artificial intelligence research incorporates elements of Brain activity and meditation, Computer vision and Pattern recognition.
In his research on the topic of Pattern recognition, Temporal lobe and Orientation is strongly related with Communication.
He most often published in these fields:
- Electroencephalography (42.27%)
- Neuroscience (32.99%)
- Audiology (31.96%)
What were the highlights of his more recent work (between 2009-2019)?
- Electroencephalography (42.27%)
- Epilepsy (13.40%)
- Artificial intelligence (21.65%)
In recent papers he was focusing on the following fields of study:
Michael Scherg spends much of his time researching Electroencephalography, Epilepsy, Artificial intelligence, Ictal and Neuroscience.
Electroencephalography and Scalp are frequently intertwined in his study.
His studies examine the connections between Epilepsy and genetics, as well as such issues in Audiology, with regards to Magnetoencephalography, Sensitivity, Clinical neurophysiology and Gating.
The various areas that Michael Scherg examines in his Artificial intelligence study include Large skull and Pattern recognition.
His research investigates the link between Pattern recognition and topics such as Communication that cross with problems in Temporal lobe.
His work in the fields of Neuroscience, such as Frontal lobe, intersects with other areas such as Open peer review.
Between 2009 and 2019, his most popular works were:
- Influences of skull segmentation inaccuracies on EEG source analysis. (68 citations)
- Beyond the double banana: improved recognition of temporal lobe seizures in long-term EEG. (42 citations)
- Fast evaluation of interictal spikes in long-term EEG by hyper-clustering. (28 citations)
In his most recent research, the most cited papers focused on:
- Neuroscience
- Electroencephalography
- Artificial intelligence
Michael Scherg mainly investigates Electroencephalography, Epilepsy, Artificial intelligence, Magnetic resonance imaging and Ictal.
Michael Scherg has researched Epilepsy in several fields, including Communication and Pattern recognition.
He has included themes like Large skull and Scalp in his Artificial intelligence study.
His Scalp study combines topics in areas such as Acoustics, Human skull, Skull and Segmentation, Computer vision.
His biological study spans a wide range of topics, including Surgery, Source imaging, Nuclear medicine, Inverse solution and Epilepsy surgery.
His Ictal research is multidisciplinary, incorporating perspectives in Cluster analysis and Brain mapping.
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