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 41 Citations 6,049 170 World Ranking 4608 National Ranking 389

Overview

What is he best known for?

The fields of study he is best known for:

  • Neuroscience
  • Internal medicine
  • Artificial intelligence

Marc Tittgemeyer mainly investigates Neuroscience, Magnetic resonance imaging, Diffusion MRI, Anatomy and Functional magnetic resonance imaging. His studies in Neuroscience integrate themes in fields like Tractography, Extreme capsule and Internal capsule. His Magnetic resonance imaging research integrates issues from Surgery and Computed tomography.

The Diffusion MRI study combines topics in areas such as Corpus callosum, Pathology and Brain mapping. His Anatomy study combines topics from a wide range of disciplines, such as Voxel, Diffusion Tractography and Macaque. His work carried out in the field of Functional magnetic resonance imaging brings together such families of science as Motion perception and Cognition.

His most cited work include:

  • Connectivity-Based Parcellation of Broca's Area (464 citations)
  • Towards a standard analysis for functional near-infrared imaging. (192 citations)
  • Posterior medial frontal cortex activity predicts post-error adaptations in task-related visual and motor areas (186 citations)

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

Marc Tittgemeyer focuses on Neuroscience, Parkinson's disease, Artificial intelligence, Magnetic resonance imaging and Internal medicine. His Neuroscience research includes elements of Tractography and White matter. Cerebral white matter is closely connected to Diffusion MRI in his research, which is encompassed under the umbrella topic of White matter.

His Parkinson's disease study combines topics in areas such as Anterior cingulate cortex and Resting state fMRI. His studies in Artificial intelligence integrate themes in fields like Machine learning, Computer vision and Pattern recognition. His research in Internal medicine intersects with topics in Endocrinology, Neuroimaging and Oncology.

He most often published in these fields:

  • Neuroscience (53.68%)
  • Parkinson's disease (18.95%)
  • Artificial intelligence (11.05%)

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

  • Neuroscience (53.68%)
  • Parkinson's disease (18.95%)
  • Dopaminergic (14.74%)

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

Marc Tittgemeyer mostly deals with Neuroscience, Parkinson's disease, Dopaminergic, Internal medicine and Dopamine. His Neuroscience study incorporates themes from Deep brain stimulation and Impulsivity. His Parkinson's disease research incorporates themes from Anterior cingulate cortex, Cognition and Resting state fMRI.

His Dopaminergic study integrates concerns from other disciplines, such as Obesity and Insulin. His Internal medicine research is multidisciplinary, relying on both Endocrinology, Neuroimaging and Oncology. His research in Dopamine tackles topics such as Human brain which are related to areas like Taste, Gut–brain axis, Affect, Striatum and Dopamine metabolism.

Between 2018 and 2021, his most popular works were:

  • Connectivity Profile Predictive of Effective Deep Brain Stimulation in Obsessive-Compulsive Disorder. (86 citations)
  • Current directions in the auricular vagus nerve stimulation I - A physiological perspective (39 citations)
  • Current directions in the auricular vagus nerve stimulation I - A physiological perspective (39 citations)

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

  • Neuroscience
  • Internal medicine
  • Artificial intelligence

Marc Tittgemeyer spends much of his time researching Neuroscience, Parkinson's disease, Dopaminergic, Dopamine and Internal medicine. His Neuroscience study frequently draws connections to other fields, such as Deep brain stimulation. His study in Deep brain stimulation is interdisciplinary in nature, drawing from both Ventral striatum, Impulsivity, Ventromedial prefrontal cortex and Disinhibition.

His study looks at the relationship between Dopaminergic and topics such as Human brain, which overlap with Stimulus and Extracellular dopamine. His research integrates issues of Pet imaging, Neuroimaging and Oncology in his study of Internal medicine. His studies deal with areas such as Hypersexuality, Anterior cingulate cortex, Resting state fMRI and Dopamine transporter as well as Nucleus accumbens.

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

Connectivity-Based Parcellation of Broca's Area

A Anwander;M Tittgemeyer;DY von Cramon;AD Friederici.
Cerebral Cortex (2006)

606 Citations

Allostatic Self-Efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression

Klaas Enno Stephan;Zina Mary Manjaly;Christoph Daniel Mathys;Lilian A.E. Weber.
Frontiers in Human Neuroscience (2016)

296 Citations

Posterior medial frontal cortex activity predicts post-error adaptations in task-related visual and motor areas

Claudia Danielmeier;Tom Eichele;Birte U. Forstmann;Marc Tittgemeyer.
The Journal of Neuroscience (2011)

281 Citations

Towards a standard analysis for functional near-infrared imaging.

Matthias L Schroeter;Markus M Bücheler;Karsten Müller;Kâmil Uludağ;Kâmil Uludağ.
NeuroImage (2004)

255 Citations

The brain in myotonic dystrophy 1 and 2: Evidence for a predominant white matter disease

Martina Minnerop;Bernd Weber;Jan-Christoph Schoene-Bake;Sandra Roeske.
Brain (2011)

232 Citations

The speed-accuracy tradeoff in the elderly brain: a structural model-based approach.

Birte U. Forstmann;Marc Tittgemeyer;Eric-Jan Wagenmakers;Jan Derrfuss.
The Journal of Neuroscience (2011)

226 Citations

Predicting errors from reconfiguration patterns in human brain networks

Matthias Ekman;Jan Derrfuss;Marc Tittgemeyer;Christian J. Fiebach.
Proceedings of the National Academy of Sciences of the United States of America (2012)

163 Citations

Connectivity Profile Predictive of Effective Deep Brain Stimulation in Obsessive-Compulsive Disorder.

Juan Carlos Baldermann;Corina Melzer;Alexandra Zapf;Sina Kohl.
Biological Psychiatry (2019)

159 Citations

Tractography-based priors for dynamic causal models

Klaas Enno Stephan;Marc Tittgemeyer;Thomas R. Knösche;Rosalyn J. Moran.
NeuroImage (2009)

158 Citations

Cognitive impairment in multiple sclerosis.

Stefanie Hoffmann;Marc Tittgemeyer;D. Yves von Cramon.
Current Opinion in Neurology (2007)

149 Citations

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