|Project Team||Project Title & Description|
|Principal Investigator (PI): Hiroaki Matsunami, Professor, Molecular Genetics & Microbiology; Dennis Thiele, George Barth Geller Professor, Pharmacology & Cancer Biology; Kevin Franks, Assistant Professor, Neurobiology. All are affiliated with the School of Medicine.||
Smelling Sulfur in Wilson's Disease: How Does Copper Metabolism Affect Olfaction?
Wilson's disease is a genetic disease caused by mutations in the copper transporter gene ATP7A, resulting in toxic accumulation of copper in various organs. This progressive accumulation eventually leads to liver and kidney damage and various neurological problems, among other complications. One curious attribute of patients with Wilson's disease: They seem to be indifferent to sulfur-containing odors such as skunk spray, flatulence, and natural gas additive, which have a strong, disagreeable odor to most people. This suggests an unexpected link between copper metabolism and olfaction. We assembled a strong interdisciplinary team with complementary expertise in odor-receptor interactions (Matsunami) and odor-mediated behavior and odor coding in the brain (Franks), and copper transporters and copper metabolism (Thiele) to study this copper-dependent olfactory defect. We will test the hypothesis that copper-olfactory receptor-odorant interactions in the nasal mucosa are essential for sensitive detection and signaling of sulfur-containing odors, and copper maldistribution caused by Wilson's disease compromises olfactory sensory neuron responses and specific odorant detection. Our project will validate a novel mechanism underlying the fundamental biology of smell and, importantly, could lead to an innovative olfactory-based method to screen non-invasively Wilson's disease patients, enabling early interventions to reduce irreversible brain damage.
PI: Mike Tadross, Assistant Professor, Biomedical Engineering, Pratt School of Engineering; Kafui Dzirasa, Associate Professor, Psychiatry & Behavioral Sciences, School of Medicine
(Note: This project was selected by the DIBS External Advisory Board to honor the memory of Julie Rhodes, the first DIBS Communications Director, who died in August 2018.)
Deconstructing the Glutamatergic Basis of Depression
Major depressive disorder is the leading cause of disability in the world. Pharmacological treatments available fail to adequately treat the disorder in up to 50 percent of patients. Recent evidence indicates that ketamine, a drug with anesthetic and pain-killing properties, can effectively treat symptoms in this population. However, ketamine has many side effects that limit its broad clinical utility. In this study, we will use two groundbreaking technologies to uncover the mechanisms underlying ketamine's antidepressant effects. The first technology, Drugs Acutely Restricted by Tethering (DART), offers the unprecedented opportunity to deliver drugs to genetically defined cell types in the brain. The second technology, Whole-Brain Electome Mapping (WBEM), allows characterization of whole-brain dynamics in animal models of depression, offering the opportunity to observe mood-related brain states with a sensitivity and specificity surpassing all known behavioral correlates of disease. Successful completion of this work will yield a multi-scale understanding of depression, providing insight into how a precise pharmacological intervention, targeted to specific cells in the brain, propagates to affect whole-brain dynamics and behavior. The work has the potential to yield a new class of precision therapeutics to rapidly reverse depressive symptoms in a broad patient population.
|PI: Jörg Grandl, Assistant Professor, Neurobiology, School of Medicine; Stefan Zauscher, Sternberg Family Professor, Mechanical Engineering & Materials Science, Pratt School of Engineering||
Quantitative Investigation of the Specialization of Mechanotransduction Neurons
The sense of touch is crucial for our survival, and its malfunction is associated with inflammatory pain and chronic pain, for which medical treatments are still disappointingly inadequate. For this project, we will investigate how specific nerve cells are specialized to sense mechanical touch. Ample experimental evidence already suggests such a specialization. For example, some nerve cells only detect light mechanical indentation, whereas others respond exclusively to deeper indentation. We suspect that many additional types of specialization exist. However, a fundamental investigation and classification of nerve cells has never been performed, in part because this has not been technically possible. We will overcome this limitation by engineering a unique instrument that can measure precisely the electrical activity of nerve cells in response to a clearly defined mechanical stimulus. Next, we plan to use this instrument to measure and characterize hundreds of nerve cells, which will enable us for the first time to reveal exactly how they are specialized to sense mechanical touch. This knowledge would enable us to study the genes and molecules that determine the specialization of nerve cells for sensing mechanical touch and understand how the electrical response of neurons is changed in disease conditions, such as inflammatory pain.
|PI: Jessica R. Lunsford-Avery, Assistant Professor, Psychiatry & Behavioral Science, School of Medicine; Matthew Engelhard, Senior Research Associate, Psychiatry & Behavioral Sciences, School of Medicine, and Electrical & Computer Engineering, Pratt School of Engineering; Scott Kollins, Professor, Psychiatry & Behavioral Sciences, School of Medicine; Ricardo Henao, Assistant Professor, Biostatistics & Bioinformatics, School of Medicine, and Electrical & Computer Engineering, Pratt School of Engineering; Sujay Kansagra, Assistant Professor, Pediatrics, School of Medicine||
Harnessing Sleep/Circadian Rhythm Data as a Biomarker to Mitigate Health Risks
Sleep is essential to sustaining health. Many individuals and their doctors know sleep is important, but they often do not identify sleep problems during routine doctors' visits, and as a result, the problems are not sufficiently addressed. One obstacle to the convenient measurement of sleep is its complexity. A good night's sleep depends on an individual's daily rest and activity rhythms, the length and quality of their sleep, time spent in sleep stages (e.g., deep sleep versus rapid eye movement sleep), and their behaviors, such as maintaining a consistent bedtime. We do not know the specific patterns of sleep that place people at risk for — or protect them from — health problems. In addition, traditional ways of identifying sleep problems, such as spending the night in a sleep clinic, are often expensive or unavailable to many. This study will use wearable sleep monitors (i.e., similar to Fitbits) to identify the patterns of sleep that increase risk for health problems. As a first step, our team — including psychiatry, engineering, neurology, and sleep medicine specialists — will identify patterns that increase risk for mental health problems among adolescents, who are especially vulnerable to both sleep and psychiatric problems. We will also examine patients' perceptions of the ease and acceptability of using wearable monitors to measure sleep in their health care setting. In the future, we hope to apply the patterns of sleep problems identified in this study to the detection of risk for a range of health problems for individuals of all ages.
|PI: John Pearson, Assistant Professor, Biostatistics & Bioinformatics; Eva Aimable Naumann, Assistant Professor, Neurobiology. Both are affiliated with the School of Medicine.||
Interrogation and Manipulation of Brain States through Real-time Analysis of Neural Activity
One of the great challenges in neuroscience is to understand how local groups of cells work together in circuits to generate complex behaviors. Historically, scientists have been limited to studying only a few of these cells at a time, yet new developments in microscope and imaging technology have recently made it possible to study much larger groups of cells. For some small animals such as the zebrafish, transparent in its larval state, it is possible to record the activity of nearly all brain cells at once. But there's a downside: These new experiments can generate up to a terabyte of data an hour, enough to fill several hard drives per experiment! And often, the data from one day must be analyzed overnight on a computer cluster before the next experiment can start. The goal of our project is to remove much of this data analysis burden by using newly developed data processing methods and computer hardware to analyze the incoming brain signals in real time. Our goal is to perform so-called closed-loop, all-optical experiments, in which the incoming data change the experiment as it's being run — a feedback loop. For example, will be be able to see how some neurons respond to visual information as the data are being collected and to stimulate these same neurons based on their response patterns. Methods like these promise to dramatically expand our understanding on how networks of brain cells function together, not only in healthy brains, but in those affected by neuropsychiatric diseases.
|PI: Elika Bergelson, Assistant Professor, Psychology & Neuroscience, Arts & Sciences (A&S); Marty Woldorff, Psychiatry & Behavioral Sciences, School of Medicine, and Psychology & Neuroscience, A&S; Sharon Freedman, Professor, Ophthalmology and Pediatrics, School of Medicine||
Early Language Development in the Visually Impaired
Children with high levels of hearing loss who receive late intervention usually have poor language outcomes, but children with high levels of vision loss generally attain language abilities akin to typically developing peers. Blind adults in older children have largely indistinguishable language abilities form sighted individuals, although research reports some brain differences in responses to auditory and linguistic stimuli; however, early language abilities in young blind children have been very little studied. This is significant, given that vision loss effects >75,000 children under age 4 in the U.S. One major roadblock to understanding early language abilities under visual impairment is the lack of methods that can be used across blind and sighted infants. Reports from parents can be informative, but they may be subject to parental opinion. Direct assessments provide a more accurate measure of children's receptive vocabulary; however, standard eye-tracking approaches (which measure the time infants spend looking at named objects) are not possible in blind infants. We propose to extend to blind infants the auditory-based electro-encephalography (EEG) paradigms that have been well-established with infants and toddlers developing typically. Uncovering how blind children learn and represent words will reveal how sensory impairment fundamentally shapes the developing brain, which will in turn inform our understanding of cognition and language more generally. These results also will inform potential training regimens that can mitigate language delays and deficits in both children and adults.