Events

Feb 17, 2016
12:00 PM
149 13th Street (Building 149), main second floor seminar room (2204)

Susan Whitfield-Gabrieli, PhD

Research Scientist, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology

Research Scientist, Martinos Imaging Center, McGovern Institute for Brain Research

Title: Clinical Applications of Resting State Networks: Clinical Characterization, Novel Treatments and Prediction of Clinical Outcome 

Abstract: Neuroimaging has revealed brain differences in clinical disorders, but it has not yet fundamentally altered how patients are diagnosed or treated. However, the intrinsic functional architecture of the human brain as elucidated by resting state functional connectivity holds great promise for clinical translation.  I will describe how resting state networks (RSNs), provide information for (1) clinical characterization, (2) evaluating/developing novel treatments, and (3) predicting clinical outcome. We find that patients with schizophrenia and individuals with risk for schizophrenia and depression exhibit default mode network (DMN) hyperconnectivity which is positively correlated with symptom severity, and reductions in DMN anticorrelations, associated with impaired executive function. I will describe ways in which novel pharmacological (cannabinoid) and behavioral interventions (mindfulness meditation and real-time DMN feedback) ameliorate/normalize this DMN functional pathology. The finding that the DMN is plastic and can be altered by such interventions offers hope that effective treatments may help patients mitigate symptoms and potentially augment their cognitive function. In a study of patients with disorders of consciousness, such as minimally conscious state and vegetative state/unresponsive wakefulness syndrome (VS/UWS), individual differences in DMN anticorrelations predicted clinical outcomes more accurately than initial diagnosis. Finally, we used pre-treatment RSNs in patients with social anxiety disorder to predict subsequent clinical response to cognitive behavioral therapy. The intrinsic connectivity measures yielded a fivefold improvement in predicting treatment response relative to the clinical measure of initial anxiety.   These results suggest that RSNs may provide biomarkers that substantially improve predictions for success of clinical interventions, and suggest that such biomarkers may offer evidence-based, personalized/precision medicine approaches for optimally selecting treatment options.

Feb 24, 2016
12:00 PM
149 13th Street (Building 149), main second floor seminar room (2204)

Daniel S. Reich, MD, PhD

Chief, Translational Neuroradiology Unit

Division of Neuroimmunology and Neurovirology

National Institute of Neurological Disorders and Stroke

National Institutes of Health

Talk tile: Imaging the Lesion in Multiple Sclerosis

Abstract: How, and how well, do acute white matter lesions heal in multiple sclerosis (MS)? Can tissue repair be characterized in vivo? And how might we test emerging treatments to promote such repair in early phase clinical trials? After more than a century of research into the pathology of MS, and 35 years since MRI was first applied in the disease, the answers to these questions still elude us. Yet emerging data from epidemiological studies seem to confirm our intuition that tissue destruction within lesions may be highly relevant to the long-term accumulation of disability that occurs in progressive MS. At the same time, treatments that are most effective in reducing the chance of new lesion formation can also be dangerously immunosuppressive. Fortunately, there is now convincing experimental evidence that extensive endogenous repair, including remyelination, can occur soon after a lesion first appears, raising the possibility that therapeutic promotion of such repair might have both short-term and long-lasting benefits. In this talk, I will present data from our group’s studies in the radiology and pathology of active MS1,2 and primate experimental autoimmune encephalomyelitis3 that together provide a framework for the spatiotemporal evolution of new white matter lesions. I will discuss how the blood-brain barrier is altered in distinct ways at different stages of lesion formation, and in particular how these alterations are reflected in magnetic susceptibility changes detectable using ultra-high-field (7 tesla) MRI. I will further show how such changes can be used to monitor and predict the extent of lesion repair, even over periods of several months. The ability to image these processes leads naturally to a set of efficient trial designs for short-term, proof-of-concept clinical trials to assess lesion repair,4 potentially opening the way for the development of add-on agents that may limit the amount of tissue damage that occurs within new white matter lesions.

 

Mar 02, 2016
12:00 PM
149 13th Street (Building 149), main second floor seminar room (2204)

Zeynep Saygin, PhD

Postdoctoral Researcher, Department of Brain and Cognitive Sciences, MIT

Mar 09, 2016
12:00 PM
149 13th Street (Building 149), main second floor seminar room (2204)

Yi-Fen Yen, PhD

Assistant in Biomedical Engineering, Massachusetts General Hospital

Apr 20, 2016
12:00 PM
149 13th Street (Building 149), main second floor seminar room (2204)