Director: David Eidelberg, M.D.
Title: Functional Brain Networks: A Novel Approach to Address Clinical Challenges in PD
The Udall Center at The Feinstein Institute for Medical Research employs rigorously validated Parkinson’s disease (PD)-related
networks to address vital issues that impact heavily on the care of today’s PD patients.
Because dopaminergic treatment is generally so effective for the motor symptoms of PD, at least early on, it is easy to dismiss the very real problems that ultimately develop: levodopa-induced dyskinesias and cognitive and behavioral changes for some patients. Understanding these phenomena should not only help us improve the lives of patients, but will provide unique insight into the pathophysiology of PD and perhaps other neurodegenerative disorders. Likewise, the validation of an automated pattern-based method for early diagnosis will help streamline trials of new therapies for PD as well as for atypical parkinsonian syndromes.
The Udall Center at The Feinstein Institute for Medical Research focuses on a unique patient-oriented approach using validated functional brain networks to develop novel approaches/solutions to basic problems of diagnosis and management confronted each day by Parkinson’s disease (PD) patients, clinicians and caretakers. Findings from Center projects will shed light on the relationship between functional brain organization in the resting state (PET, rest state fMRI) and neural activation during cognitive processing (event-related fMRI), and provide unique information on how both interact to shape performance in PD patients and healthy people. Project 1 addresses the serious clinical problem of levodopa-induced dyskinesias, which ultimately affect nearly all PD patients. Project 2 examines the network basis for individual differences in the cognitive response to dopaminergic treatment with a view to predicting which patients will develop untoward cognitive side effects under different treatment conditions. Project 3 aims to establish the feasibility of a new network-based algorithm for providing earlier and more accurate differential diagnosis than is currently possible.
Six cores support the research activities of three Projects: the Administrative, Clinical, Cognitive and Behavioral, Statistics
and Data Management, Imaging, and Training and Education cores. The activities of each core are independent. That said, these
activities are highly coordinated across the Clinical, Cognitive and Behavioral, and Imaging Cores in that the data output
of these cores are entered into a database created in the Statistics and Data Management core.
The specialized Udall Center mechanism allows Feinstein investigators to collaborate with scientific leaders in important translational research areas. For instance, the involvement of Dr. Angela Cenci-Nilsson at Lund University (Sweden) offers a true translational collaboration in the study of the role of the microvasculature in the pathogenesis of levodopa-induced dyskinesias (LID). Professor Cenci-Nilsson’s unique expertise provides the basis for a unique collaboration spanning the gap between experimental animal studies and human investigation in Parkinson’s disease. Similarly, investigators in Dr. Eidelberg’s laboratory have developed a productive working relationship with Dr. Mark Gluck and his team at Rutgers University (Newark, NJ) in the area of cognitive processing in Parkinson’s disease. Over the past five years, this collaboration has developed further during the course of the fMRI/behavioral studies of probabilistic category learning and neuro-economic decision making. Moreover, studies conducted at the sleep disorders centers at North Shore – LIJ Health System, Stanford University, and the University of Pennsylvania offer insights into the network abnormalities that appear in individuals at risk for PD prior to the onset of motor symptoms.
Project 1: Microvascular Changes in PD: Relationship to Levodopa-Induced Dyskinesia
In aggregate, data from both human subjects and rodents support the proposed hypotheses. If validated, the results of these
studies may lead to new therapeutic strategies for LID and related side-effects of PD treatment.
Project 2: Metabolic Networks and the Cognitive Treatment Response in Parkinson's Disease
We have previously characterized a specific metabolic network abnormality associated with cognitive dysfunction in non-demented PD subjects. In recent studies from the Udall Center at the Feinstein Institute, we have validated this PD cognition-related covariance pattern (PDCP) in an independent patient population. In addition to correlating consistently with performance on tests of executive function, PDCP expression related specifically to changes in dopaminergic input to the caudate nucleus (rather than the putamen). These findings create the basis for developing circuit-specific interventions for cognitive dysfunction in PD patients, with the PDCP modulation as a quantitative biomarker of treatment efficacy.
Project 3: Early Differential Diagnosis of Parkinsonism with Metabolic Imaging and Pattern Analysis
Animal Models: Rat model of L-dopa-induced dyskinesia (LID) at Lund University.
Other Resources: Clinical ratings (off-state UPDRS), a standardized neuropsychological testing battery, off-state FDG PET data, off-state, routine anatomical MRI, DNA banking, and brain donation/banking.
Project 1: (1) We plan to continue increasing our recruitment efforts for Aims 1 and 2 of the project. We will update the interim analyses on the newly collected data, particularly for local vasoreactivity in drug-naïve patients; (2) In the coming year, we will establish a microPET method to measure blood flow and glucose metabolism in rats utilizing the same multi-tracer approach as already performed in the human PET studies. This task is currently being carried out at the Feinstein Institute.
Project 2: (1) We will focus on recruitment in this project as well as perform interim analyses on the data and present the results in the next annual progress report; (2) We also plan to improve the sequence learning tasks and collect behavioral and imaging data with the modified tasks in PD patients and healthy controls for interim analysis.
Project 3: (1) We expect to complete recruitment for Aim 2 and will continue to enroll subjects for Aims 1 and 3. (2) We will further develop the automated diagnostic approach by adding a cortical basal ganglionic degeneration (CBGD) pattern to the classification algorithm. We will then apply the updated algorithm to the subjects enrolled in this Project. (3) Network analysis will be performed on REM behavior disorder (RBD) and healthy control subjects to identify potential metabolic covariance patterns relating specifically to prodromal disease states. As more RBD subjects return for follow-up imaging and sufficient longitudinal scan data become available, we will search for specific "preclinical" progression-related metabolic topographies. Such patterns may be particularly valuable as biomarkers in disease modification trials targeting individuals with early/preclinical disease.
Parkinson's disease cognitive network correlates with caudate dopamine.
Niethammer M, Tang CC, Ma Y, Mattis PJ, Ko JH, Dhawan V, Eidelberg D.
Neuroimage. 2013 Sep;78:204-9. PMID: 23578575
Identification of disease-related spatial covariance patterns using neuroimaging data.
Spetsieris P, Ma Y, Peng S, Ko JH, Dhawan V, Tang CC,
J Vis Exp. 2013 Jun 26;(76). PMID: 23851955
Parkinson's disease: increased motor network activity in the absence of movement.
Ko JH, Mure H, Tang CC, Ma Y, Dhawan V, Spetsieris P, Eidelberg D.
J Neurosci. 2013 Mar 6;33(10):4540-9..PMID: 23467370 Free PMC Article
Dissociating the cognitive effects of levodopa versus dopamine agonists in a neurocomputational model of learning in Parkinson's
Moustafa AA, Herzallah MM, Gluck MA.
Neurodegener Dis. 2013;11(2):102-11. PMID: 23128796
Collaboration with Other Udall Centers
PD Research Collaborations
Last updated October 30, 2013