What is she best known for?
The fields of study she is best known for:
- Neuroscience
- Artificial intelligence
- Functional magnetic resonance imaging
Petra Ritter mainly investigates Neuroscience, Rhythm, Electroencephalography, Resting state fMRI and Brain mapping.
In general Rhythm study, her work on Beta Rhythm often relates to the realm of State dependence, Multistability and Hopf bifurcation, thereby connecting several areas of interest.
Her study in Electroencephalography is interdisciplinary in nature, drawing from both Somatosensory system, Functional magnetic resonance imaging and Cortex.
Her Functional magnetic resonance imaging study incorporates themes from Functional imaging and Near-infrared spectroscopy.
Her research in Resting state fMRI intersects with topics in Diffusion MRI, Connectome, Connectomics and Default mode network.
The study incorporates disciplines such as Dynamic functional connectivity, Functional connectivity, Developmental psychology, Mood disorders and Major depressive disorder in addition to Brain mapping.
Her most cited work include:
- Correlates of alpha rhythm in functional magnetic resonance imaging and near infrared spectroscopy. (489 citations)
- Rolandic alpha and beta EEG rhythms' strengths are inversely related to fMRI-BOLD signal in primary somatosensory and motor cortex (308 citations)
- Simultaneous EEG-fMRI. (214 citations)
What are the main themes of her work throughout her whole career to date?
Neuroscience, Electroencephalography, Artificial intelligence, Resting state fMRI and Neuroimaging are her primary areas of study.
Her work focuses on many connections between Neuroscience and other disciplines, such as Rhythm, that overlap with her field of interest in Alpha rhythm.
Her Electroencephalography research incorporates themes from Speech recognition, Somatosensory system, Functional magnetic resonance imaging and Diffusion MRI.
Her Artificial intelligence study integrates concerns from other disciplines, such as Machine learning, Cognitive science, Computer vision and Pattern recognition.
Her work in the fields of Resting state fMRI, such as Dynamic functional connectivity, overlaps with other areas such as Variance.
Her Neuroimaging course of study focuses on Connectome and Neurophysiology and Brain function.
She most often published in these fields:
- Neuroscience (55.35%)
- Electroencephalography (30.82%)
- Artificial intelligence (27.04%)
What were the highlights of her more recent work (between 2018-2021)?
- Neuroscience (55.35%)
- Neuroimaging (23.27%)
- Dementia (5.66%)
In recent papers she was focusing on the following fields of study:
Her primary scientific interests are in Neuroscience, Neuroimaging, Dementia, Electroencephalography and Artificial intelligence.
In her research, Petra Ritter undertakes multidisciplinary study on Neuroscience and Neuregulin 1.
The concepts of her Neuroimaging study are interwoven with issues in Movement disorders, Statistical classification and Myoclonus.
Her research integrates issues of Cognitive psychology, Information processing, Audiology, Functional magnetic resonance imaging and Human brain in her study of Electroencephalography.
Her Functional magnetic resonance imaging research integrates issues from Nerve conduction velocity, Diffusion MRI and Electrophysiology.
Petra Ritter combines subjects such as Machine learning, Connectome, Functional connectivity and Pattern recognition with her study of Artificial intelligence.
Between 2018 and 2021, her most popular works were:
- A macaque connectome for large-scale network simulations in TheVirtualBrain. (16 citations)
- Subject specificity of the correlation between large-scale structural and functional connectivity (16 citations)
- Linking Molecular Pathways and Large-Scale Computational Modeling to Assess Candidate Disease Mechanisms and Pharmacodynamics in Alzheimer's Disease. (15 citations)
In her most recent research, the most cited papers focused on:
- Neuroscience
- Artificial intelligence
- Functional magnetic resonance imaging
Petra Ritter mainly focuses on Functional connectivity, Connectome, Neuroscience, Artificial intelligence and Randomness.
Her Functional connectivity study frequently draws connections to adjacent fields such as Resting state fMRI.
Her research in Resting state fMRI intersects with topics in Electrophysiology, Brain simulation, Nerve conduction velocity, Diffusion MRI and Functional magnetic resonance imaging.
Petra Ritter has included themes like Neurology, Cognitive neuroscience and Electroencephalography in her Connectome study.
Her studies in Electroencephalography integrate themes in fields like Memantine and Amyloid beta.
The various areas that Petra Ritter examines in her Artificial intelligence study include Machine learning, Neuroimaging, Macaque and Pattern recognition.
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