What is he best known for?
The fields of study he is best known for:
- Neuroscience
- Internal medicine
- Endocrinology
Nicolaas A.J. Puts mainly investigates Neuroscience, Nuclear magnetic resonance, GABAergic, Somatosensory system and Mega press.
Nicolaas A.J. Puts combines subjects such as Endocrinology and Internal medicine with his study of Neuroscience.
The various areas that he examines in his Nuclear magnetic resonance study include Macromolecular Substances, Echo time, Tissue segmentation, Nuclear medicine and Voxel.
The concepts of his Somatosensory system study are interwoven with issues in Stimulus, Sensory stimulation therapy, Autism, Autism spectrum disorder and Sensory threshold.
He interconnects Neurochemical, Age related and Biochemistry in the investigation of issues within Human brain.
His In vivo magnetic resonance spectroscopy research includes elements of Tissue distribution, Quantitative analysis, Occipital region, Artificial intelligence and Pattern recognition.
His most cited work include:
- Current practice in the use of MEGA-PRESS spectroscopy for the detection of GABA (305 citations)
- Current practice in the use of MEGA-PRESS spectroscopy for the detection of GABA (305 citations)
- Gannet: a batch-processing tool for the quantitative analysis of gamma-aminobutyric acid-edited MR spectroscopy spectra (275 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Neuroscience, Nuclear magnetic resonance, Internal medicine, Endocrinology and In vivo magnetic resonance spectroscopy.
His work on Neuroscience deals in particular with Somatosensory system, Human brain, GABAergic, Sensory stimulation therapy and Neuroplasticity.
His Nuclear magnetic resonance research integrates issues from White matter and Voxel.
Nicolaas A.J. Puts interconnects Healthy volunteers, Cerebrospinal fluid and Nuclear medicine in the investigation of issues within Voxel.
His work on Young adult and Neurochemical as part of general Internal medicine research is frequently linked to Glutamine, bridging the gap between disciplines.
His work on Inhibitory postsynaptic potential and Neurotransmitter as part of general Endocrinology study is frequently linked to Striatum and Cognitive decline, therefore connecting diverse disciplines of science.
He most often published in these fields:
- Neuroscience (65.69%)
- Nuclear magnetic resonance (47.45%)
- Internal medicine (34.31%)
What were the highlights of his more recent work (between 2019-2021)?
- Neuroscience (65.69%)
- Audiology (23.36%)
- Internal medicine (34.31%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Neuroscience, Audiology, Internal medicine, Endocrinology and In vivo magnetic resonance spectroscopy.
His Neuroscience research incorporates elements of Regression analysis and Individual participant data.
Nicolaas A.J. Puts combines topics linked to Somatosensory system with his work on Audiology.
Nicolaas A.J. Puts integrates several fields in his works, including Internal medicine and Glutamine.
His work on Inhibitory postsynaptic potential and Cerebellum as part of general Endocrinology research is often related to Glutathione and Population, thus linking different fields of science.
His In vivo magnetic resonance spectroscopy research is multidisciplinary, incorporating perspectives in Mean age, Nuclear medicine, Data set and Single voxel.
Between 2019 and 2021, his most popular works were:
- Brain GABA and glutamate levels across pain conditions: A systematic literature review and meta-analysis of 1H-MRS studies using the MRS-Q quality assessment tool. (21 citations)
- Reproducibility of flutter-range vibrotactile detection and discrimination thresholds. (8 citations)
- Reproducibility of flutter-range vibrotactile detection and discrimination thresholds. (8 citations)
In his most recent research, the most cited papers focused on:
- Neuroscience
- Internal medicine
- Psychiatry
Nicolaas A.J. Puts focuses on Algorithm, Nonlinear system, Residual, Frequency domain and Signal averaging.
Algorithm combines with fields such as Subtraction and Time domain in his research.
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.
