What is he best known for?
The fields of study he is best known for:
- Internal medicine
- Artificial intelligence
- Neuroscience
The scientist’s investigation covers issues in Neuroscience, Artificial intelligence, Brain mapping, Pattern recognition and Neuroimaging.
In most of his Neuroscience studies, his work intersects topics such as Stuttering.
Specifically, his work in Artificial intelligence is concerned with the study of Spatial normalization.
His Spatial normalization research includes elements of Talairach coordinates, Image processing, Activation likelihood estimation, Stereotaxic technique and Reference values.
His Brain mapping research incorporates themes from Schizophrenia, Functional Brain Imaging, Human brain and Neural system.
His studies in Pattern recognition integrate themes in fields like Image resolution, Thresholding and Brain atlas.
His most cited work include:
- Automated Talairach Atlas labels for functional brain mapping (2921 citations)
- Reciprocal limbic-cortical function and negative mood: converging PET findings in depression and normal sadness (1971 citations)
- A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM) (1671 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Neuroscience, Artificial intelligence, Brain mapping, Spatial normalization and Magnetic resonance imaging.
As part of his studies on Neuroscience, Jack L. Lancaster often connects relevant areas like Anatomy.
His studies deal with areas such as Computer vision and Pattern recognition as well as Artificial intelligence.
He works in the field of Pattern recognition, namely Segmentation.
His Spatial normalization research is multidisciplinary, incorporating perspectives in Brain atlas, Octree, Image warping and Brain size.
While the research belongs to areas of Magnetic resonance imaging, Jack L. Lancaster spends his time largely on the problem of Nuclear medicine, intersecting his research to questions surrounding Tomography.
He most often published in these fields:
- Neuroscience (26.32%)
- Artificial intelligence (17.67%)
- Brain mapping (11.28%)
What were the highlights of his more recent work (between 2010-2021)?
- Neuroscience (26.32%)
- Neuroimaging (10.15%)
- Magnetic resonance imaging (10.15%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Neuroscience, Neuroimaging, Magnetic resonance imaging, Internal medicine and Fractional anisotropy.
His study in Resting state fMRI, Motor control, Transcranial magnetic stimulation, Brain mapping and Functional connectivity are all subfields of Neuroscience.
He has researched Neuroimaging in several fields, including Voxel-based morphometry, Software, Inference, Meta-analysis and Voxel.
His Magnetic resonance imaging study combines topics from a wide range of disciplines, such as Clinical psychology, Insular cortex and Human brain.
Jack L. Lancaster performs multidisciplinary studies into Scale and Artificial intelligence in his work.
His Artificial intelligence study incorporates themes from Spatial variability, Precuneus, Inferior frontal gyrus and Pattern recognition.
Between 2010 and 2021, his most popular works were:
- Identification of common variants associated with human hippocampal and intracranial volumes (511 citations)
- Fractional anisotropy of water diffusion in cerebral white matter across the lifespan (249 citations)
- The BrainMap strategy for standardization, sharing, and meta-analysis of neuroimaging data (159 citations)
In his most recent research, the most cited papers focused on:
- Internal medicine
- Artificial intelligence
- Neuroscience
Jack L. Lancaster focuses on Neuroscience, Neuroimaging, Software, Meta-analysis and Internal medicine.
He interconnects Fractional anisotropy, Diffusion MRI and SMA* in the investigation of issues within Neuroscience.
His research integrates issues of Genetics, Cortical morphology, Gyrification and Source code in his study of Neuroimaging.
Jack L. Lancaster works mostly in the field of Software, limiting it down to concerns involving Data science and, occasionally, Standardization, Functional neuroimaging and Multiple comparisons problem.
The various areas that Jack L. Lancaster examines in his Meta-analysis study include Metadata, Data mining, Voxel-based morphometry, Anatomic Location and Voxel.
Jack L. Lancaster has included themes like Endocrinology and Posterior cingulate in his Internal medicine study.
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