What is he best known for?
The fields of study he is best known for:
- Neuroscience
- Statistics
- Functional magnetic resonance imaging
His main research concerns Cognitive psychology, Functional magnetic resonance imaging, Cognition, Neuroscience and Superior temporal sulcus. His research in Cognitive psychology is mostly focused on Lateralization of brain function. His study in the field of Brain activation also crosses realms of Wada test.
Mohamed L. Seghier combines subjects such as Visual perception, Semantic matching and Neuroimaging with his study of Cognition. His work on Face perception, Thalamus and Blindsight is typically connected to Cortical blindness and Systems neuroscience as part of general Neuroscience study, connecting several disciplines of science. His Superior temporal sulcus study incorporates themes from Emotional prosody, Prosody and Brain mapping.
His most cited work include:
- The Angular Gyrus: Multiple Functions and Multiple Subdivisions (778 citations)
- A network of occipito-temporal face-sensitive areas besides the right middle fusiform gyrus is necessary for normal face processing. (534 citations)
- The voices of wrath: brain responses to angry prosody in meaningless speech (357 citations)
What are the main themes of his work throughout his whole career to date?
Mohamed L. Seghier mainly focuses on Cognitive psychology, Neuroscience, Functional magnetic resonance imaging, Lateralization of brain function and Audiology. His studies in Cognitive psychology integrate themes in fields like Perception, Cognition, Speech production, Laterality and Brain mapping. His Cognition study combines topics from a wide range of disciplines, such as Neuroimaging and Artificial intelligence.
The Brain mapping study combines topics in areas such as Magnetic resonance imaging and Superior temporal sulcus. His research investigates the link between Functional magnetic resonance imaging and topics such as Functional imaging that cross with problems in Transcranial magnetic stimulation. His studies examine the connections between Lateralization of brain function and genetics, as well as such issues in Speech perception, with regards to Working memory.
He most often published in these fields:
- Cognitive psychology (41.79%)
- Neuroscience (36.57%)
- Functional magnetic resonance imaging (31.34%)
What were the highlights of his more recent work (between 2016-2021)?
- Audiology (26.87%)
- Lateralization of brain function (27.61%)
- Lesion (13.43%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Audiology, Lateralization of brain function, Lesion, Functional magnetic resonance imaging and Speech perception. His Audiology research integrates issues from Fusiform gyrus, Visual processing, Sulcus, Visual perception and Semantic memory. His Lateralization of brain function research is multidisciplinary, incorporating perspectives in Precentral gyrus, Laterality and Random variable.
His studies deal with areas such as Working memory and Magnetic resonance imaging as well as Functional magnetic resonance imaging. His research in Speech perception intersects with topics in Memory span and Aphasia. His research is interdisciplinary, bridging the disciplines of Functional neuroimaging and Cognitive psychology.
Between 2016 and 2021, his most popular works were:
- Interpreting and Utilising Intersubject Variability in Brain Function (98 citations)
- Large-scale DCMs for resting-state fMRI (88 citations)
- A guide to group effective connectivity analysis, part 2: Second level analysis with PEB. (59 citations)
In his most recent research, the most cited papers focused on:
- Neuroscience
- Statistics
- Functional magnetic resonance imaging
Mohamed L. Seghier spends much of his time researching Neuroimaging, Machine learning, Artificial intelligence, Cognitive psychology and Cognition. His Neuroimaging research is multidisciplinary, relying on both Physical medicine and rehabilitation, Artificial neural network, Transcranial magnetic stimulation, Functional imaging and Multivariate statistics. His Machine learning research includes themes of Prior probability, Dynamic causal modelling, Bayes' theorem and Parametric statistics.
His work on Bayesian inference as part of general Artificial intelligence research is often related to Graph theory, thus linking different fields of science. His study in Cognitive psychology is interdisciplinary in nature, drawing from both Precentral gyrus and Functional magnetic resonance imaging. Cognition and Brain function are frequently intertwined in his study.
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