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 37 Citations 5,965 209 World Ranking 5482 National Ranking 153

Overview

What is she best known for?

The fields of study she is best known for:

  • Internal medicine
  • Neuroscience
  • Surgery

Natasha M. Maurits mostly deals with Neuroscience, Electroencephalography, Brain activity and meditation, Functional magnetic resonance imaging and Human brain. Her work on EEG-fMRI and Eriksen flanker task as part of general Electroencephalography study is frequently linked to Relevant information and Mental fatigue, therefore connecting diverse disciplines of science. Her Brain activity and meditation research incorporates elements of Index finger, Primary motor cortex and Brain mapping.

She has included themes like Mirror neuron, Voxel, Somatosensory system and Cortex in her Functional magnetic resonance imaging study. In Prefrontal cortex, Natasha M. Maurits works on issues like SMA*, which are connected to Physical medicine and rehabilitation. Her work deals with themes such as Aging brain and Default mode network, which intersect with Working memory.

Her most cited work include:

  • A Brain-Wide Study of Age-Related Changes in Functional Connectivity (349 citations)
  • The dynamic mean-field density functional method and its application to the mesoscopic dynamics of quenched block copolymer melts (262 citations)
  • Correlating the alpha rhythm to BOLD using simultaneous EEG/fMRI: Inter-subject variability (248 citations)

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

Her primary areas of investigation include Physical medicine and rehabilitation, Electroencephalography, Neuroscience, Audiology and Artificial intelligence. Her Physical medicine and rehabilitation research incorporates themes from Physical therapy, Movement disorders, Parkinson's disease and Rating scale. She usually deals with Electroencephalography and limits it to topics linked to Motor learning and Motor skill.

Her study in Neuroscience concentrates on Essential tremor, Functional magnetic resonance imaging, Brain activity and meditation, Primary motor cortex and Aging brain. Her Essential tremor research integrates issues from Cerebellum and Electromyography. Her work carried out in the field of Artificial intelligence brings together such families of science as Multichannel eeg, Coherence, Computer vision and Pattern recognition.

She most often published in these fields:

  • Physical medicine and rehabilitation (19.93%)
  • Electroencephalography (21.40%)
  • Neuroscience (19.19%)

What were the highlights of her more recent work (between 2016-2021)?

  • Physical medicine and rehabilitation (19.93%)
  • Electroencephalography (21.40%)
  • Artificial intelligence (9.96%)

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

Natasha M. Maurits focuses on Physical medicine and rehabilitation, Electroencephalography, Artificial intelligence, Audiology and Neuroscience. Her Physical medicine and rehabilitation study incorporates themes from Rehabilitation, Ataxia and Movement disorders. Her Electroencephalography study integrates concerns from other disciplines, such as Motor cortex and Motor learning.

Her Artificial intelligence research is multidisciplinary, incorporating elements of Multichannel eeg, Spatial analysis and Pattern recognition. Her Audiology study combines topics from a wide range of disciplines, such as Auditory oddball, Neural correlates of consciousness, Cognition, Event-related potential and Brain mapping. Cognitive skill is closely connected to Cognitive decline in her research, which is encompassed under the umbrella topic of Neuroscience.

Between 2016 and 2021, her most popular works were:

  • Monitoring of Optimal Cerebral Perfusion Pressure in Traumatic Brain Injured Patients Using a Multi-Window Weighting Algorithm (25 citations)
  • Scaled Subprofile Modeling and Convolutional Neural Networks for the Identification of Parkinson's Disease in 3D Nuclear Imaging Data. (23 citations)
  • Best Practices in Data Analysis and Sharing in Neuroimaging using MEEG (21 citations)

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

  • Internal medicine
  • Neuroscience
  • Surgery

Natasha M. Maurits mainly investigates Electroencephalography, Neuroscience, Motor learning, Physical medicine and rehabilitation and Dreyfus model of skill acquisition. She has researched Electroencephalography in several fields, including Motor cortex, Hearing loss, Neuroimaging and Cochlear implant. As part of her studies on Neuroscience, Natasha M. Maurits often connects relevant areas like Cognitive decline.

Her Motor learning research is multidisciplinary, incorporating perspectives in Functional magnetic resonance imaging, Motor skill and Brain mapping. Her research investigates the connection between Physical medicine and rehabilitation and topics such as Ataxia that intersect with issues in Rehabilitation, Rating scale, Classifier and Motor coordination. Her work focuses on many connections between Upper limb and other disciplines, such as Micrographia, that overlap with her field of interest in Set and Artificial intelligence.

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 Brain-Wide Study of Age-Related Changes in Functional Connectivity

Linda Geerligs;Remco J. Renken;Emi Saliasi;Natasha M. Maurits.
Cerebral Cortex (2015)

594 Citations

The dynamic mean-field density functional method and its application to the mesoscopic dynamics of quenched block copolymer melts

J. G. E. M. Fraaije;B. A. C. van Vlimmeren;N. M. Maurits;M. Postma.
Journal of Chemical Physics (1997)

451 Citations

Correlating the alpha rhythm to BOLD using simultaneous EEG/fMRI: inter-subject variability.

S.I. Gonçalves;J.C. de Munck;P.J.W. Pouwels;R. Schoonhoven.
NeuroImage (2006)

369 Citations

Reference values of maximum isometric muscle force obtained in 270 children aged 4-16 years by hand-held dynamometry.

Eac Beenakker;van der Johannes Hoeven;Johanna Fock;Natasha Maurits.
Neuromuscular Disorders (2001)

302 Citations

μ-Suppression during Action Observation and Execution Correlates with BOLD in Dorsal Premotor, Inferior Parietal, and SI Cortices

Dan Arnstein;Fang Cui;Christian Keysers;Natasha M. Maurits.
The Journal of Neuroscience (2011)

278 Citations

Admitting acute ischemic stroke patients to a stroke care monitoring unit versus a conventional stroke unit: a randomized pilot study.

Geert Sulter;Jan Willem Elting;Marc Langedijk;Natasha M Maurits.
Stroke (2003)

266 Citations

Mental Fatigue Affects Visual Selective Attention

Léon G. Faber;Natasha M. Maurits;Monicque M. Lorist.
PLOS ONE (2012)

224 Citations

Best Practices in Data Analysis and Sharing in Neuroimaging using MEEG

Cyril Pernet;Marta Garrido;Alexandre Gramfort;Natasha Maurits.
(2018)

207 Citations

Reduced Specificity of Functional Connectivity in the Aging Brain During Task Performance

Linda Geerligs;Linda Geerligs;Natasha M. Maurits;Remco J. Renken;Monicque M. Lorist;Monicque M. Lorist.
Human Brain Mapping (2014)

201 Citations

The influence of mental fatigue and motivation on neural network dynamics; an EEG coherence study

Monicque M. Lorist;Eniko Bezdan;Michael ten Caat;Mark M. Span.
Brain Research (2009)

193 Citations

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