D-Index & Metrics Best Publications

D-Index & Metrics 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.

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 45 Citations 8,418 173 World Ranking 3914 National Ranking 157

Overview

What is he best known for?

The fields of study he is best known for:

  • Neuroscience
  • Internal medicine
  • Electroencephalography

Olivier David spends much of his time researching Neuroscience, Electroencephalography, Artificial intelligence, Magnetoencephalography and Epilepsy. His Neuroscience research is multidisciplinary, relying on both Coupling and Deep brain stimulation. His work carried out in the field of Electroencephalography brings together such families of science as Neuroimaging and Brain mapping.

His Artificial intelligence study integrates concerns from other disciplines, such as Algorithm and Dynamic causal modelling. His research integrates issues of Cerebral cortex, Machine learning, Visual attention and Nonlinear system in his study of Magnetoencephalography. The various areas that Olivier David examines in his Epilepsy study include Anesthesia, Magnetic resonance imaging, Functional magnetic resonance imaging, Stimulation and Animal model.

His most cited work include:

  • A neural mass model for MEG/EEG: coupling and neuronal dynamics. (532 citations)
  • Dynamic causal modeling of evoked responses in EEG and MEG (476 citations)
  • Identifying neural drivers with functional MRI: an electrophysiological validation. (439 citations)

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

Olivier David mainly focuses on Neuroscience, Electroencephalography, Epilepsy, Deep brain stimulation and Stimulation. His studies link Subthalamic nucleus with Neuroscience. His work in the fields of Electroencephalography, such as Magnetoencephalography, intersects with other areas such as Context.

His Epilepsy research is multidisciplinary, incorporating elements of Hippocampal formation and Somatosensory system. His Stimulation research integrates issues from Biomedical engineering and Cognition, Stroop effect. His Artificial intelligence research also works with subjects such as

  • Machine learning that intertwine with fields like Pattern recognition,
  • Dynamic causal modelling together with Inference.

He most often published in these fields:

  • Neuroscience (85.53%)
  • Electroencephalography (60.53%)
  • Epilepsy (34.21%)

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

  • Neuroscience (85.53%)
  • Epilepsy (34.21%)
  • Stimulation (35.09%)

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

The scientist’s investigation covers issues in Neuroscience, Epilepsy, Stimulation, Stereoelectroencephalography and Deep brain stimulation. His Epilepsy research includes elements of Electrophysiology, Somatosensory system and Neuroimaging. His Stimulation study combines topics in areas such as Current pulse, Cognition, Audiology and Electroencephalography.

His Cognition study combines topics from a wide range of disciplines, such as Probabilistic logic, Relation and Brain mapping. Electroencephalography and Experimental control are two areas of study in which he engages in interdisciplinary research. His research investigates the connection with Deep brain stimulation and areas like Reticular formation which intersect with concerns in Cholinergic, MPTP, Cholinergic neuron, Dopamine and Brainstem.

Between 2018 and 2021, his most popular works were:

  • Reproducibility in TMS–EEG studies: A call for data sharing, standard procedures and effective experimental control (36 citations)
  • iEEG-BIDS, extending the Brain Imaging Data Structure specification to human intracranial electrophysiology. (30 citations)
  • Deep Brain Stimulation of the Pedunculopontine Nucleus Area in Parkinson Disease: MRI-Based Anatomoclinical Correlations and Optimal Target (21 citations)

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

  • Neuroscience
  • Internal medicine
  • Statistics

Olivier David spends much of his time researching Deep brain stimulation, Audiology, Stimulation, Electrophysiology and Neuroscience. His work on Pedunculopontine nucleus as part of general Deep brain stimulation study is frequently linked to Midbrain, therefore connecting diverse disciplines of science. The Audiology study combines topics in areas such as Motor cortex, Transcranial magnetic stimulation, Mood disorders and Electroencephalography.

Olivier David has researched Electroencephalography in several fields, including Primary motor cortex and Reproducibility. His Stimulation research includes themes of Valence, Arousal, Subthalamic nucleus and Cognition, Cognitive bias. Olivier David combines Neuroscience and Genetic model in his studies.

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

A neural mass model for MEG/EEG: coupling and neuronal dynamics.

Olivier David;Karl J. Friston.
NeuroImage (2003)

867 Citations

Dynamic causal modeling of evoked responses in EEG and MEG

Olivier David;Stefan J. Kiebel;Lee M. Harrison;Jérémie Mattout.
NeuroImage (2006)

666 Citations

Identifying neural drivers with functional MRI: an electrophysiological validation.

Olivier David;Isabelle Guillemain;Sandrine Saillet;Sebastien Reyt.
PLOS Biology (2008)

536 Citations

Evaluation of different measures of functional connectivity using a neural mass model.

Olivier David;Diego Cosmelli;Karl J. Friston.
NeuroImage (2004)

402 Citations

Modelling event-related responses in the brain.

Olivier David;Lee M. Harrison;Karl J. Friston.
NeuroImage (2005)

390 Citations

Mechanisms of evoked and induced responses in MEG/EEG

Olivier David;James M. Kilner;Karl J. Friston.
NeuroImage (2006)

324 Citations

Dynamic causal modelling: a critical review of the biophysical and statistical foundations.

Jean Daunizeau;Olivier David;Klaas E. Stephan;Klaas E. Stephan.
NeuroImage (2011)

311 Citations

Dynamic causal models of neural system dynamics: current state and future extensions

Klaas E Stephan;Lee M Harrison;Lee M Harrison;Stefan J Kiebel;Stefan J Kiebel;Olivier David.
Journal of Biosciences (2007)

270 Citations

Dynamic causal modelling of evoked responses in EEG/MEG with lead field parameterization

Stefan J. Kiebel;Olivier David;Karl J. Friston.
NeuroImage (2006)

203 Citations

Rapid interactions between the ventral visual stream and emotion-related structures rely on a two-pathway architecture.

David Rudrauf;Olivier David;Jean-Philippe Lachaux;Christopher K. Kovach.
The Journal of Neuroscience (2008)

165 Citations

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