This article has multiple issues. Please help improve it or discuss these issues on the talk page . (Learn how and when to remove these template messages)
|
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. [2] [3] He is the founding Director of the Center for Multimodal Imaging Genetics (CMIG) at UCSD. [4]
Dale founded and initially developed the brain imaging analysis software FreeSurfer as a graduate student at UCSD. [5] He later co-developed FreeSurfer at Massachusetts General Hospital/Harvard Medical School with Bruce Fischl. [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. [13] These genetic pleiotropy methods have provided valuable insights across a number of diseases and identified novel single nucleotide polymorphisms associated with increased risk for schizophrenia, bipolar disorder, [14] Alzheimer's disease, [15] Parkinson's disease, frontotemporal dementia, [16] corticobasal degeneration, [17] hypertension, hypercholesterolemia and coronary artery disease. [18] In collaboration with Rahul Desikan and Chun Fan, Dale has developed a polygenic score for quantifying the 'personalized' risk for quantifying Alzheimer's disease age of onset. [19]
Dale was born in Norway in 1964 to Major General Torstein Dale and Unn Søiland Dale. He went to college at the University of Texas from 1983 to 1985 and earned a B.A. in Computer Science, after which he served in the Norwegian Air Force. He then ran a small control systems consulting company. From 1989 to 1990 he went to Harvard and MIT on a Fulbright Fellowship, and received an M.S. in Engineering Science. He then pursued graduate studies at UCSD from 1989 to 1994.
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 pioneered methods of combining EEG, MEG, and MRI tests to localize brain activity. He also did important work in surface-based MRI data analysis and in the mapping of the visual cortex. He received a Ph.D. in Cognitive Science in 1994, becoming one of the first graduates of UCSD's Cognitive Science Department. [3] [20] [21]
In a 2003 interview, Dale explained that he had “always been interested in using quantitative modeling methods and simulations to answer biological questions, ”and that as a Harvard student he had been “interested in approaching connectionist neural networks from a more biological angle.” When he went to UCSD to continue his graduate work his interest “shifted to learning how to test models of how the brain works. Ideally you'd like to test your models not in anesthetized animals and brain slices, but by measuring brain activity in humans non-invasively. I wanted to study normal people doing normal tasks. That was what brought me to imaging. My goal was to see what kind of things we can measure non-invasively that can be quantitatively related to the models we want to build....I wanted to know what exactly we are measuring, how can you model it, and how can you relate the signal to what is going on in the brain physiologically...at a level that say you could measure invasively and that you could relate to parameters of quantitative models.” His thesis work at UCSD, he said, “was on the EEG and MEG forward and inverse problems, and how to use anatomical information to constrain the solutions. It is clear that if you only use EEG or MEG measures, the spatial precision is not good enough to make inferences at a scale that's most useful to neuroscience. That led us into trying to use information with higher spatial resolution to constrain or bias our estimations of the signal sources in the brain.” [20]
After completing his postgraduate work at UCSD, Dale returned to the Boston area, where from 1996 to 2004 he was an associate professor of radiology at Harvard University and associate director of the Athinoula A. Martinos Center for Biomedical Imaging, which is jointly operated by the Massachusetts General Hospital, Harvard Medical School, and MIT. During this period at Harvard, Dale continued to develop noninvasive imaging technologies and used structural MRI to diagnose neurological disorders. [3] [20] [21] It was toward the end of his graduate-student days at Harvard and during his postdoctoral stay at UCSD, Dale later said, that he began working with MRI and fMRI. “The field had just gotten started,” he explained. “We tried to use cortical surface reconstruction from MRI to constrain the localization of EEG and MEG signals. We also used those geometrical representations of the cortex, combined with functional MRI, to look for maps in the visual cortex. Steve Engel at Stanford had just developed the phase-encoded stimulus paradigm. 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. We thought up the idea of looking at these maps on the cortical surface, because the maps are actually two-dimensional. Although the topology of these maps is simple, their folding makes them complex in volume. In order to visualize and analyze the patterns of brain activity, you really need to take into account the individual geometry of the cortex. So we decided to do an experiment. We went to Massachusetts General Hospital, and tried our little experiment on a weekend....It worked very well and the results got into Science.” [20]
During this period, Dale and Bruce Fischl, a colleague at Harvard Medical School and Massachusetts General Hospital, continued to develop the brain imaging analysis software known as FreeSurfer, which Dale had begun working on at UCSD.
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. [3] [21]
According to a UCSD website, the work of Dale's laboratory at UCSD has yield several other technological developments, including “a method for tracking and correcting for head motion, in real time, during MRI scans; a fully automated method for identifying white matter tracts from MRI scans; and a method for quantifying longitudinal anatomical change from serial MRI scans.” In addition, the laboratory has produced “a free software program that aids in the study of anatomical changes associated with early stages of Alzheimer’s disease and Mild Cognitive Impairment (MCI). 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. The study made use of “sophisticated gene-mapping tools and imaging technology to collect a wealth of data about brain development in children.” Dale said that “Our major aim is to create a database – essentially a map depicting the genomic landscape of the developing human brain – as a resource for the scientific community. [2] As a result of the PING project, Dale and his fellow researchers “developed a multidimensional set of brain measurements that, when taken together, can accurately assess a child’s age with 92 percent accuracy.” [22]
In 2001 Dale co-founded with Áine Behan the neuroimaging company CorTechs Labs Incorporated in La Jolla, California, for which he serves as Chief Scientific Advisor. [3] [20] [21]
CorTechs Labs describes itself as “a group of scientists, engineers, business professionals, and clinical specialists dedicated to bringing cutting edge brain image analysis technologies to the commercial market.” These technologies “may help physicians to more effectively diagnose and treat serious neurological disorders that affect millions of patients worldwide. 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. Neurologists, neuroradiologists, and other experts in the diagnosis and treatment of CNS disorders can use this product to derive adjunctive information that may aid in the detection and treatment of disease processes in individual patients. 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. [24] [25]
Dale was on the consulting faculty of the NIMH Training Program in Cognitive Neuroscience 2011–2012. [26]
Dale has published articles across numerous scientific and medical disciplines, in a wide range of journals including Science, Nature, Neuron, PNAS, PLOS Genetics, Plos Medicine, Molecular Psychiatry, Annals of Neurology, Acta Neuropathologica, Radiology, and Circulation. [21]
The entorhinal cortex (EC) is an area of the brain's allocortex, located in the medial temporal lobe, whose functions include being a widespread network hub for memory, navigation, and the perception of time. The EC is the main interface between the hippocampus and neocortex. The EC-hippocampus system plays an important role in declarative (autobiographical/episodic/semantic) memories and in particular spatial memories including memory formation, memory consolidation, and memory optimization in sleep. The EC is also responsible for the pre-processing (familiarity) of the input signals in the reflex nictitating membrane response of classical trace conditioning; the association of impulses from the eye and the ear occurs in the entorhinal cortex.
Magnetoencephalography (MEG) is a functional neuroimaging technique for mapping brain activity by recording magnetic fields produced by electrical currents occurring naturally in the brain, using very sensitive magnetometers. Arrays of SQUIDs are currently the most common magnetometer, while the SERF magnetometer is being investigated for future machines. Applications of MEG include basic research into perceptual and cognitive brain processes, localizing regions affected by pathology before surgical removal, determining the function of various parts of the brain, and neurofeedback. This can be applied in a clinical setting to find locations of abnormalities as well as in an experimental setting to simply measure brain activity.
A gamma wave or gamma rhythm is a pattern of neural oscillation in humans with a frequency between 25 and 140 Hz, the 40 Hz point being of particular interest. Gamma rhythms are correlated with large-scale brain network activity and cognitive phenomena such as working memory, attention, and perceptual grouping, and can be increased in amplitude via meditation or neurostimulation. Altered gamma activity has been observed in many mood and cognitive disorders such as Alzheimer's disease, epilepsy, and schizophrenia.
Functional integration is the study of how brain regions work together to process information and effect responses. Though functional integration frequently relies on anatomic knowledge of the connections between brain areas, the emphasis is on how large clusters of neurons – numbering in the thousands or millions – fire together under various stimuli. The large datasets required for such a whole-scale picture of brain function have motivated the development of several novel and general methods for the statistical analysis of interdependence, such as dynamic causal modelling and statistical linear parametric mapping. These datasets are typically gathered in human subjects by non-invasive methods such as EEG/MEG, fMRI, or PET. The results can be of clinical value by helping to identify the regions responsible for psychiatric disorders, as well as to assess how different activities or lifestyles affect the functioning of the brain.
Neuroimaging is the use of quantitative (computational) techniques to study the structure and function of the central nervous system, developed as an objective way of scientifically studying the healthy human brain in a non-invasive manner. Increasingly it is also being used for quantitative research studies of brain disease and psychiatric illness. Neuroimaging is highly multidisciplinary involving neuroscience, computer science, psychology and statistics, and is not a medical specialty. Neuroimaging is sometimes confused with neuroradiology.
The posterior cingulate cortex (PCC) is the caudal part of the cingulate cortex, located posterior to the anterior cingulate cortex. This is the upper part of the "limbic lobe". The cingulate cortex is made up of an area around the midline of the brain. Surrounding areas include the retrosplenial cortex and the precuneus.
FreeSurfer is a brain imaging software package originally developed by Bruce Fischl, Anders Dale, Martin Sereno, and Doug Greve. Development and maintenance of FreeSurfer is now the primary responsibility of the Laboratory for Computational Neuroimaging at the Athinoula A. Martinos Center for Biomedical Imaging. FreeSurfer contains a set of programs with a common focus of analyzing magnetic resonance imaging (MRI) scans of brain tissue. It is an important tool in functional brain mapping and contains tools to conduct both volume based and surface based analysis. FreeSurfer includes tools for the reconstruction of topologically correct and geometrically accurate models of both the gray/white and pial surfaces, for measuring cortical thickness, surface area and folding, and for computing inter-subject registration based on the pattern of cortical folds.
In neuroscience, the default mode network (DMN), also known as the default network, default state network, or anatomically the medial frontoparietal network (M-FPN), is a large-scale brain network primarily composed of the dorsal medial prefrontal cortex, posterior cingulate cortex, precuneus and angular gyrus. It is best known for being active when a person is not focused on the outside world and the brain is at wakeful rest, such as during daydreaming and mind-wandering. It can also be active during detailed thoughts related to external task performance. Other times that the DMN is active include when the individual is thinking about others, thinking about themselves, remembering the past, and planning for the future.
Alzheimer's Disease Neuroimaging Initiative (ADNI) is a multisite study that aims to improve clinical trials for the prevention and treatment of Alzheimer's disease (AD). This cooperative study combines expertise and funding from the private and public sector to study subjects with AD, as well as those who may develop AD and controls with no signs of cognitive impairment. Researchers at 63 sites in the US and Canada track the progression of AD in the human brain with neuroimaging, biochemical, and genetic biological markers. This knowledge helps to find better clinical trials for the prevention and treatment of AD. ADNI has made a global impact, firstly by developing a set of standardized protocols to allow the comparison of results from multiple centers, and secondly by its data-sharing policy which makes available all at the data without embargo to qualified researchers worldwide. To date, over 1000 scientific publications have used ADNI data. A number of other initiatives related to AD and other diseases have been designed and implemented using ADNI as a model. ADNI has been running since 2004 and is currently funded until 2021.
The Human Connectome Project (HCP) is a five-year project sponsored by sixteen components of the National Institutes of Health, split between two consortia of research institutions. The project was launched in July 2009 as the first of three Grand Challenges of the NIH's Blueprint for Neuroscience Research. On September 15, 2010, the NIH announced that it would award two grants: $30 million over five years to a consortium led by Washington University in St. Louis and the University of Minnesota, with strong contributions from University of Oxford (FMRIB) and $8.5 million over three years to a consortium led by Harvard University, Massachusetts General Hospital and the University of California Los Angeles.
Resting state fMRI is a method of functional magnetic resonance imaging (fMRI) that is used in brain mapping to evaluate regional interactions that occur in a resting or task-negative state, when an explicit task is not being performed. A number of resting-state brain networks have been identified, one of which is the default mode network. These brain networks are observed through changes in blood flow in the brain which creates what is referred to as a blood-oxygen-level dependent (BOLD) signal that can be measured using fMRI.
Dynamic functional connectivity (DFC) refers to the observed phenomenon that functional connectivity changes over a short time. Dynamic functional connectivity is a recent expansion on traditional functional connectivity analysis which typically assumes that functional networks are static in time. DFC is related to a variety of different neurological disorders, and has been suggested to be a more accurate representation of functional brain networks. The primary tool for analyzing DFC is fMRI, but DFC has also been observed with several other mediums. DFC is a recent development within the field of functional neuroimaging whose discovery was motivated by the observation of temporal variability in the rising field of steady state connectivity research.
Randy L. Buckner is an American neuroscientist and psychologist whose research focuses on understanding how large-scale brain circuits support mental function and how dysfunction arises in illness.
The Ludwig-Boltzmann-Institute for functional Brain Topography was a research institute for the investigation of the function of brain areas. It was founded in 1993 in Vienna, Austria by Lüder Deecke. With his retirement in 2006 the institute was closed.
Dynamic causal modeling (DCM) is a framework for specifying models, fitting them to data and comparing their evidence using Bayesian model comparison. It uses nonlinear state-space models in continuous time, specified using stochastic or ordinary differential equations. DCM was initially developed for testing hypotheses about neural dynamics. In this setting, differential equations describe the interaction of neural populations, which directly or indirectly give rise to functional neuroimaging data e.g., functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG) or electroencephalography (EEG). Parameters in these models quantify the directed influences or effective connectivity among neuronal populations, which are estimated from the data using Bayesian statistical methods.
Rahul Desikan was an Indian-American neuroscientist and neuroradiologist. He was an Assistant Professor of Radiology & Biomedical Imaging, Neurology and Pediatrics at the University of California, San Francisco, and co-director of Laboratory for Precision Neuroimaging. Desikan's achievements became publicly known in a Washington Post article detailing his lifelong commitment to preventing and treating Alzheimer's disease and his continuing work as a scientist living with Amyotrophic lateral sclerosis (ALS). Desikan was vocal about the need for increased awareness and research funding for ALS, and voiced his unique perspective as both ALS researcher and ALS patient in op-ed articles appearing in a regular column in the Washington Post as well as in the San Francisco Chronicle and Scientific American.
Petra Ritter is a German neuroscientist and medical doctor at Charité in Berlin. Her field is computational neuroscience and her focus is developing brain simulations for individual people with neurological conditions, combining EEG and neuroimaging data.