Area:
brain stimulation, neuromodulation, neuroimaging, depression, treatment-resistant depression, transcranial magnetic stimulation, deep brain stimulation
We are testing a new system for linking grants to scientists.
The funding information displayed below comes from the
NIH Research Portfolio Online Reporting Tools and the
NSF Award Database.
The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
You can help! If you notice any innacuracies, please
sign in and mark grants as correct or incorrect matches.
Sign in to see low-probability grants and correct any errors in linkage between grants and researchers.
High-probability grants
According to our matching algorithm, Paul E. Holtzheimer is the likely recipient of the following grants.
| Years |
Recipients |
Code |
Title / Keywords |
Matching
score |
| 2011 — 2015 |
Holtzheimer, Paul E |
R01Activity Code Description:
To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Identifying Biomarkers For Treatment-Resistant Depression Using Neuroimaging
DESCRIPTION (provided by applicant): Treatment-resistant depression (TRD) is a prevalent, costly public health problem that affects at least 2% of the U.S. population. Little is known about the neurobiology of TRD, and practically nothing is known about what neurobiological abnormalities remain in TRD patients following adequate treatments that may alter neural functioning independent of antidepressant effects. As depression likely represents disruption within a distributed network of cortical and subcortical brain regions - rather than dysfunction of any single brain region - network-level analyses (e.g., functional and structural connectivity) may be better able to define its neuropathology. A converging database suggests that connectivity of the medial prefrontal cortex (MF10) may be associated with TRD. In this project, resting state functional magnetic resonance imaging (rfMRI) data will be obtained in 103 TRD individuals (depressed following two adequate antidepressant treatments) and 103 treatment-responsive individuals (in remission from depression following two adequate antidepressant treatments). Whole-brain functional connectivity (FC) and structural connectivity (SC) analyses will be performed. We hypothesize that whole-brain resting state FC of the MF10 will differ between TRD and treatment-responsive individuals and that SC (assessed via diffusion tensor imaging tomography and analysis of white matter integrity) will correlate with FC. In secondary analyses, the functional and structural connectivity of other regions of interest within this network (e.g., subcallosal cingulate cortex, dorsolateral prefrontal cortex, hippocampus, amygdala) will be assessed using univariate and multivariate analyses. Demographic and clinical characteristics of TRD and treatment-responsive individuals will be compared to clarify whether there is a phenomenological profile associated with TRD. This study will provide a cross-sectional analysis of neural network activity between TRD and treatment-responsive patients that controls for the effects of ongoing antidepressant treatment. These results will help guide further TRD research including the refinement of TRD biomarkers and the development of novel treatment strategies that may directly target abnormal functional (and/or structural) connectivity. PUBLIC HEALTH RELEVANCE: This project will investigate the neurobiology of treatment-resistant depression (TRD) using functional magnetic resonance imaging and diffusion tensor imaging. These findings will increase our understanding of the pathophysiology of TRD and will guide further research including the development of novel interventions for this prevalent and costly disorder.
|
1 |