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.
The specific aims are: I. To characterize sensory coupling and reweighting properties of postural sway. Three experiments will precisely define the information that sensory modalities (vision & touch) provide and how the modalities interact through reweighting. We hypothesize: a) strong velocity coupling and weak position coupling; b) uniform reweighting across frequency; and c) reweighting that is dependent upon the root mean square (RMS) velocity of sensory input; II. To characterize the dynamics of multisensory reweighting. The time scale over which the nervous system reweights sensory information within a modality and between modalities is not well known. Two experiments will investigate reweighting dynamics by: 1) adding or removing a sensory modality within a trial; 2) changing the amplitude of environmental motion within a trial. We hypothesize that reweighting is: i) a relatively slow process; and ii) dependent upon the amplitude of a newly added sensory input; and Ill. To determine how estimation and control differ in individuals with bilateral vestibular loss (BVL) and healthy subjects. It is not known whether the loss of vestibular information influences estimation and/or control. Differences in the dynamic characteristics of postural sway will be compared in BVL and healthy subjects with two experiments using visual and touch input and fixed or sway-referenced support surfaces. Our hypothesis is that the loss of vestibular function influences properties of estimation, rather than control. The implications of this proposal are: 1) to enhance rehabilitation of individuals with BVL; and 2) to develop a mechanistic model that will explicitly link underlying physiological subsystems to postural control. Future work will address other patient populations with similar techniques to determine the basis of their balance deficits.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Research Project (R01)
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Special Emphasis Panel (ZRG1-BBBP-7 (01))
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Kleitman, Naomi
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University of Maryland College Park
Schools of Public Health
College Park
United States
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Hwang, Sungjae; Agada, Peter; Grill, Stephen et al. (2016) A central processing sensory deficit with Parkinson's disease. Exp Brain Res 234:2369-79
Hwang, Sungjae; Agada, Peter; Kiemel, Tim et al. (2016) Identification of the Unstable Human Postural Control System. Front Syst Neurosci 10:22
Hwang, Sungjae; Agada, Peter; Kiemel, Tim et al. (2014) Dynamic reweighting of three modalities for sensor fusion. PLoS One 9:e88132
Logan, David; Kiemel, Tim; Jeka, John J (2014) Asymmetric sensory reweighting in human upright stance. PLoS One 9:e100418
Polastri, Paula F; Barela, José A; Kiemel, Tim et al. (2012) Dynamics of inter-modality re-weighting during human postural control. Exp Brain Res 223:99-108
Kiemel, Tim; Zhang, Yuanfen; Jeka, John J (2011) Identification of neural feedback for upright stance in humans: stabilization rather than sway minimization. J Neurosci 31:15144-53
Kiemel, Tim; Zhang, Yuanfen; Jeka, John J (2011) Visual flow is interpreted relative to multisegment postural control. J Mot Behav 43:237-46
Jeka, John J; Allison, Leslie K; Kiemel, Tim (2010) The dynamics of visual reweighting in healthy and fall-prone older adults. J Mot Behav 42:197-208
Carver, Sean G; Kiemel, Tim; Cowan, Noah J et al. (2009) Optimal motor control may mask sensory dynamics. Biol Cybern 101:35-42
Jeka, John J; Oie, Kelvin S; Kiemel, Tim (2008) Asymmetric adaptation with functional advantage in human sensorimotor control. Exp Brain Res 191:453-63

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