The long-term goal of this research is to understand how the nervous system fuses information from multiple sensory systems for the control of upright stance. The ability to select and reweight alternative orientation references adaptively is considered a critical factor for postural control in patient and elderly populations. Despite the importance of multisensory reweighting, little is known about how it is achieved. We have developed a new experimental paradigm that simultaneously manipulates two sensory inputs (vision and touch) to probe the properties of multisensory integration. In parallel, we have developed a unique two-step modeling approach using time series techniques and mechanistic models to determine which characteristics of postural sway can: i) be attributed to estimation or control; and ii) distinguish different mechanisms of estimation used for multisensory reweighting. Here we focus on modeling the process of multisensory reweighting in changing sensory environments. The goal is to develop a mechanistic model that will explicitly link underlying physiological subsystems to postural control. Future work will address patient populations with similar techniques to determine the basis of their balance deficits.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
1R01NS046065-01
Application #
6641869
Study Section
Special Emphasis Panel (ZRG1-IFCN-5 (50))
Program Officer
Talley, Edmund M
Project Start
2002-09-30
Project End
2006-08-31
Budget Start
2002-09-30
Budget End
2003-08-31
Support Year
1
Fiscal Year
2002
Total Cost
$87,807
Indirect Cost
Name
University of Maryland College Park
Department
Miscellaneous
Type
Schools of Public Health
DUNS #
City
College Park
State
MD
Country
United States
Zip Code
20742
Carver, Sean G; Kiemel, Tim; Cowan, Noah J et al. (2009) Optimal motor control may mask sensory dynamics. Biol Cybern 101:35-42
Kiemel, Tim; Elahi, Alexander J; Jeka, John J (2008) Identification of the plant for upright stance in humans: multiple movement patterns from a single neural strategy. J Neurophysiol 100:3394-406
Saffer, Mark; Kiemel, Tim; Jeka, John (2008) Coherence analysis of muscle activity during quiet stance. Exp Brain Res 185:215-26
Zhang, Yuanfen; Kiemel, Tim; Jeka, John (2007) The influence of sensory information on two-component coordination during quiet stance. Gait Posture 26:263-71
Scholz, J P; Schoner, G; Hsu, W L et al. (2007) Motor equivalent control of the center of mass in response to support surface perturbations. Exp Brain Res 180:163-79
Kiemel, Tim; Oie, Kelvin S; Jeka, John J (2006) Slow dynamics of postural sway are in the feedback loop. J Neurophysiol 95:1410-8
Carver, Sean; Kiemel, Tim; Jeka, John J (2006) Modeling the dynamics of sensory reweighting. Biol Cybern 95:123-34
Jeka, John; Allison, Leslie; Saffer, Mark et al. (2006) Sensory reweighting with translational visual stimuli in young and elderly adults: the role of state-dependent noise. Exp Brain Res 174:517-27
Creath, Robert; Kiemel, Tim; Horak, Fay et al. (2005) A unified view of quiet and perturbed stance: simultaneous co-existing excitable modes. Neurosci Lett 377:75-80
Carver, Sean; Kiemel, Tim; van der Kooij, Herman et al. (2005) Comparing internal models of the dynamics of the visual environment. Biol Cybern 92:147-63

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