Neuroimaging

I do neuroimaging, specifically fMRI and DTI. I am especially interested in brain networks and developments in neuroimaging software. We use independent component analysis to identify separate networks in the brain related to processing and learning language. My colleagues and I worked to improve fMRI analysis, display and data sharing options. Beginning with a web-based workbench designed for the dynamic exploration of map-based data, we worked to develop brain maps that could be similarly explored and demonstrated that this approach yielded results similar to those achieved by much more laborious and manual exploration techniques. This has improved our ability to streamline analyses, extract insights from our data and share data online. I have also worked on DWI analysis of the language system for the past 8 years. This has resulted in contributions to tract analyses (Wilson et al., 2011) and to the development of a novel technique (Patterson et al., 2015) to extract not only information about the properties of each tract but also information about the size and location of connected grey matter regions. We continue to explore the implications of these new measures. Keywords: fMRI, DWI, Language, Neuroimaging, MRI

My research program is centered on investigating the neurobiology of healthy language system, and changes in cognitive and language processing associated with stroke and neurological disorders. My interests include incorporating cognitive measures and multimodal neuroimaging methods, with a goal to understand the relationship between language and other aspects of cognition, as well as the neural dynamics related to brain damage, resilience, and recovery. My research efforts are directed towards identifying factors which affect language comprehension and production, and how these change with development and are influenced by aging, stroke, brain injury, and neurodegenerative disorders, including Primary Progressive Aphasia (PPA) and Alzheimer’s disease (AD). I study language processing at the multiple levels, using behavioral experiments and both structural (DTI, lesion-symptom mapping, voxel-based morphometry) and functional neuroimaging (fMRI, EEG, MEG). In addition, I am interested in neuroplasticity and application of noninvasive brain stimulation techniques (e.g., TMS, tDCS) to the treatment of aphasia and dementia. The long-term goal of my research is to understand the cognitive and neural processes that support recovery of cognitive and language functions after stroke. Keywords: stroke, aphasia, dementia, MRI, EEG, Language

Charles Higgins, PhD, is an Associate Professor in the Department of Neuroscience with a dual appointment in Electrical Engineering at the University of Arizona where he is also leader of the Higgins Lab. Though he started his career as an electrical engineer, his fascination with the natural world has led him to study insect vision and visual processing, while also trying to meld together the worlds of robotics and biology. His research ranges from software simulations of brain circuits to interfacing live insect brains with robots, but his driving interest continues to be building truly intelligent machines.Dr. Higgins’ lab conducts research in areas that vary from computational neuroscience to biologically-inspired engineering. The unifying goal of all these projects is to understand the representations and computational architectures used by biological systems. These projects are conducted in close collaboration with neurobiology laboratories that perform anatomical, electrophysiological, and histological studies, mostly in insects.More than three years ago he captured news headlines when he and his lab team demonstrated a robot they built which was guided by the brain and eyes of a moth. The moth, immobilized inside a plastic tube, was mounted on a 6-inch-tall wheeled robot. When the moth moved its eyes to the right, the robot turned in that direction, proving brain-machine interaction. While the demonstration was effective, Charles soon went to work to overcome the difficulty the methodology presented in keeping the electrodes attached to the brain of the moth while the robot was in motion. This has led him to focus his work on another insect species.

Dr. Allen’s research spans several areas, but the main focus is the etiology and treatment of mood and anxiety disorders. His work focuses on identifying risk factors for depression using electroencephalographic and autonomic psychophysiological measures, especially EEG asymmetry, resting state fMRI connectivity, and cardiac vagal control. Based on these findings, he is developing novel and neurally-informed treatments for mood and anxiety disorders, including Transcranial Ultrasound, EEG biofeedback, and Transcranial Direct Current and Transcranial Alternating Current stimulation. Other work includes understanding how emotion and emotional disorders influence the way we make decisions and monitor our actions. Keywords: Depression, Neuromodulation, EEG, Resting-state fMRI

Dr. Alexander is Professor in the Departments of Psychology and Psychiatry, the Evelyn F. McKnight Brain Institute, and the Neuroscience and Physiological Sciences Graduate Interdisciplinary Programs of the University of Arizona. He is Director of the Brain Imaging, Behavior and Aging Lab, a member of the Internal Scientific Advisory Committee for the Arizona Alzheimer’s Consortium, and a member of the Scientific Advisory Board for the Arizona Evelyn F. McKnight Brain Institute. He received his post-doctoral training in neuroimaging and neuropsychology at Columbia University Medical Center and the New York State Psychiatric Institute. Prior to coming to Arizona, Dr. Alexander was Chief of the Neuropsychology Unit in the Laboratory of Neurosciences in the Intramural Research Program at the National Institute on Aging. Dr. Alexander has over 20 years experience as a neuroimaging and neuropsychology researcher in the study of aging and age-related neurodegenerative disease. He is a Fellow of the Association for Psychological Science and the American Psychological Association (Division 40) Society for Clinical Neuropsychology. His research has been supported by grants from the National Institutes of Health, the Evelyn F. McKnight Brain Research Foundation, the State of Arizona, and the Alzheimer’s Association. He uses structural and functional magnetic resonance imaging (MRI) and positron emission tomography (PET) combined with measures of cognition and behavior to investigate the effects of multiple health and lifestyle factors on the brain changes associated with aging and the risk for Alzheimer’s disease. Keywords: "Aging/Age-Related Disease", "Brain Imaging", "Cognitive Neurosicence", "Alzheimer's Disease"