alexa
Reach Us +1-218-451-2974
Mark H Sundman | OMICS International
ISSN: 2161-0460

Journal of Alzheimers Disease & Parkinsonism
Open Access

Like us on:

Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)
Recommended Conferences

14th International Conference on Alzheimer s Disease & Dementia

Zurich, Switzerland

12th World Congress on Alzheimers Disease & Dementia

Budapest, Hungary
Share This Page

Mark H Sundman

Mark H Sundman Brain Imaging and Analysis Center Duke University Medical Center Durham USA

Biography

Dr. Mark H Sundman Research Fellow at Duke University Medical Center: Brain Imaging and Analysis Center He has extended his valuable services and has been a recipient of many award and grants. Currently, he is working as an Research Assistant for Harvard Medical School: Center for Regenerative Medicine. He is Working in the Brain Imaging and Analysis Center as the clinical research coordinator for a neuroimaging study investigating the structural and functional connectivity of the brain in Parkinson's disease (PD) patients. The two primary imaging modalities used in our study are resting state function MRI and diffusion tensor imaging (DTI). Our research is employing magnetic resonance imaging (MRI) as a means of investigating the underlying neural mechanisms of comorbidity in PD, including motor symptoms, depression, and cognitive decline. Specifically, through measuring the inter-subject correlation between 1) MRI based neuronal connectivity measures and 2) neuropsychological and motor function assessments, we aim to identify the neuronal networks that are best correlated with each of the co-existing disease phenotypes of PD. We developed a phenotype-based connectivity analysis (PBCA) to characterize the associations among a) ICN patterns; b) major disease phenotypes (e.g., motor function decline, cognitive decline and depression); and c) the progression of Parkinson’s disease. This new technique will allow the assessment of mechanistic connection, at the level of neuronal network, between multiple coexisting phenotypes of neurological diseases.

 

Publications

Global Speakers in the subject

Global Experts in the subject

Top