The relationship between the behavioral deficits and anatomical damage produced by a stroke is only partial, since physiological dsyfunction can be measured in brain regions far removed from the lesion. These non-local physiological deficits can be assessed using functional connectivity magnetic resonance imaging (fcMRl), which measures the temporal correlation between brain regions in the blood-oxygenation-level-dependent (BOLD) signal. Studies of fcMRl in healthy adults have identified distributed brain networks that underlie different behavioral functions, such as attention, motor control, and language. Our previous work on stroke patients with spatial neglect has shown that fcMRl deficits within the attention network correlate with a patient's deficit in the neglected field. This grant proposes that fcMRl can be used more broadly to understand the deficits produced by stroke across behavioral domains. We will measure fcMRl in a large, heterogeneous sample of stroke patients, and test several hypotheses of how strokes produce dysfunction in brain networks and how this dysfunction correlates with behavioral deficits. We predict that decreases in inter-hemispheric connectivity in motor and attention networks, which are bilaterally organized, will correlate with corresponding behavioral deficits and that these correlations will show functional specificity. For example, connectivity within an arm-defined motor network will predict upper-extremity function better than lower-extremity function. We determine the correlation between connectivity and behavior in an asymmetrically organized network, language, and compare the importance of inter-hemispheric vs intra-hemispheric connectivity. We examine how the functioning of multiple brain networks interact to produce a single behavioral deficit, and hypothesize that the connectivity of some networks, such as attention, correlates with behavior across domains. We measure fcMRl longtitudinally to determine if connectivity recovers in different networks at different rates and whether that recovery correlates with behavioral recovery. Finally, we study how changes in connectivity produced by a stroke depend on the type of tracts that are structurally damaged.

Public Health Relevance

The goal of this proposal is to understand the effects of a stroke on the physiology of the brain and how they relate to the behavioral deficits produced by the stroke. We plan to measure these physiological effects in stroke patients using a novel method that will allow us to simultaneously assess the functioning of many different brain networks that are thought to underlie our ability to use language, attend in the environment, perform motor acts, and so forth. We will measure the ability of stroke patients to carry out these activities at different time points following their stroke, allowing us to understand how recovery of the patient's behavioral functions possibly relate to recovery of their physiological function.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Research Project (R01)
Project #
5R01HD061117-09
Application #
8488454
Study Section
Acute Neural Injury and Epilepsy Study Section (ANIE)
Program Officer
Michel, Mary E
Project Start
2009-08-20
Project End
2014-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
9
Fiscal Year
2013
Total Cost
$495,713
Indirect Cost
$169,586
Name
Washington University
Department
Neurology
Type
Schools of Medicine
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Lin, Leanne Y; Ramsey, Lenny; Metcalf, Nicholas V et al. (2018) Stronger prediction of motor recovery and outcome post-stroke by cortico-spinal tract integrity than functional connectivity. PLoS One 13:e0202504
Siegel, Joshua S; Seitzman, Benjamin A; Ramsey, Lenny E et al. (2018) Re-emergence of modular brain networks in stroke recovery. Cortex 101:44-59
Ramsey, L E; Siegel, J S; Lang, C E et al. (2017) Behavioural clusters and predictors of performance during recovery from stroke. Nat Hum Behav 1:
Hacker, Carl D; Snyder, Abraham Z; Pahwa, Mrinal et al. (2017) Frequency-specific electrophysiologic correlates of resting state fMRI networks. Neuroimage 149:446-457
Siegel, Joshua S; Mitra, Anish; Laumann, Timothy O et al. (2017) Data Quality Influences Observed Links Between Functional Connectivity and Behavior. Cereb Cortex 27:4492-4502
Siegel, Joshua Sarfaty; Ramsey, Lenny E; Snyder, Abraham Z et al. (2016) Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke. Proc Natl Acad Sci U S A 113:E4367-76
Patel, Kevin R; Ramsey, Lenny E; Metcalf, Nicholas V et al. (2016) Early diffusion evidence of retrograde transsynaptic degeneration in the human visual system. Neurology 87:198-205
Baldassarre, Antonello; Capotosto, Paolo; Committeri, Giorgia et al. (2016) Magnetic stimulation of visual cortex impairs perceptual learning. Neuroimage 143:250-255
Siegel, Joshua S; Snyder, Abraham Z; Ramsey, Lenny et al. (2016) The effects of hemodynamic lag on functional connectivity and behavior after stroke. J Cereb Blood Flow Metab 36:2162-2176
Ramsey, Lenny E; Siegel, Joshua S; Baldassarre, Antonello et al. (2016) Normalization of network connectivity in hemispatial neglect recovery. Ann Neurol 80:127-41

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