Anders Martin Dale is a prominent neuroscientist and professor of radiology, neurosciences, psychiatry, and cognitive science at the University of California, San Diego (UCSD),[1] and is one of the world's leading developers of sophisticated computational neuroimaging techniques.
[6] In addition to FreeSurfer, his major scientific contributions include developing: a) event related functional magnetic resonance imaging (fMRI) (with Randy Buckner at Harvard),[7] b) an in vivo method to quantify the gray matter thickness of the cerebral cortex using MRI images (with Bruce Fischl at Harvard),[8] c) an analysis platform to combine fMRI with magnetoencephalography (MEG),[9] d) computational morphometry to automatically label brain regions using MRI scans (with Bruce Fischl at Harvard and Rahul Desikan and Ron Killiany at Boston University),[10][11] and e) MRI-based methodologies to quantify longitudinal change in brain regions (with Dominic Holland at UCSD).
[12] Since 2013, in collaboration with Ole Andreassen at the University of Oslo, and using GWAS summary statistics (p-values and odds ratios), Dale has developed and validated methods for evaluating genetic overlap (pleiotropy) across diseases and phenotypes.
It was during this period at UCSD that Dale began working on the development of accurate and automated algorithms for head segmentation, which is vital to the correct modeling of EEG/MEG and optical signals.
He showed that if you present subjects with expanding annulus and rotating wedges, you can apply Fourier analysis to fMRI signals on a voxel-by-voxel basis, and obtain a delay map, or an estimate of the retinotopic representation.
Dale has been professor of radiology, neurosciences, psychiatry, and cognitive science at UCSD since 2004, and is the founding co-director of UCSD's Multi-Modal Imaging Laboratory (MMIL), which the university's website describes as “an interdisciplinary initiative of the Departments of Neurosciences and Radiology.” Dale is “the designated point person” in both departments “for integrating the various modes and methods of collecting imaging data, including functional MRI (fMRI), magnetoencephalography (MEG), electroencephalography (EEG), and optical imaging.” Dale's efforts, the website states, “are directed in three areas: continuing development and refinement of accurate and automated algorithms for evaluation subjects using multimodality approaches to data collection; statistical analysis of data; and conducting studies in animal models using optical imaging, high field fMRI, and electrophysiological recordings to enhance the interpretation of neuroimaging studies.” His work has “resulted in the development of software tools that enable the automated segmentation of the entire head and brain, including the neocortex and subcortical structures, from MRI data.” Most recently, Dale and his laboratory colleagues have been using the methods they have developed to assess regional morphometric alterations resulting from aging and from such afflictions as schizophrenia, Alzheimer's disease, and Huntington's disease.
This technology, developed for the Alzheimer’s Disease Neuroimaging Initiative (ADNI), involves longitudinal MRI and PET scans as well as CSF biomarkers in a large number of patients.” Dale has also initiated a number of “collaborative efforts using neuroimaging methods to study the genetic and environmental influences on brain structure and development” and that an “FDA-approved version of his automated segmentation technology is now in routine use for quantitative assessment of regional atrophy in patients under clinical evaluation for AD/MCI at UCSD.”[21] In 2009, the National Institute on Drug Abuse (NIDA), a part of the National Institutes of Health (NIH).
awarded a grant of $8,950,590 under the American Recovery and Reinvestment Act (ARRA) to fund a project at UCSD, the Pediatric Imaging, Neurocognition, and Genetics Study (PING), in which Dale played a major role.
It is our mission to effectively translate the fruits of such research into routine clinical practice.” CorTechs's website explains that it “is currently bringing to market our next-generation clinical brain morphometry product, NeuroQuant®,” a device that “automatically derives critical quantitative anatomical from brain MRIs and compares them to data from healthy individuals, in rough analogy to the normative information that quantitative reports from blood tests provide about molecular markers.
This tool can also provide sensitive imaging biomarkers that may reduce the expense and duration of clinical trials.” In addition, CorTechs has been provided with funding by the U.S. National Institute of Aging “to use data collected from the NIH and pharmaceutical-industry co-sponsored Alzheimer's Disease Neuroimaging Initiative (ADNI) project, to establish an indication for use for NeuroQuant® as an adjunctive tool in the assessment of patients with AD.”[23] NeuroQuant® has since been studied in a variety of neurological pathologies beyond its initial intended purpose for Alzheimer's Disease such as traumatic brain injury (TBI) and epilepsy.