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Developing Predictive Measures of Sensorimotor Adaptability to Produce Customized Countermeasure Prescriptions

Completed Technology Project
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Project Description

Developing Predictive Measures of Sensorimotor Adaptability to Produce Customized Countermeasure Prescriptions
Astronauts experience sensorimotor disturbances during the initial exposure to microgravity and during the readaptation phase following a return to an Earth-gravitational environment. These alterations may lead to disruption in the ability to perform mission critical functional tasks required during these gravitational transitions. Astronauts show significant inter-subject variation in adaptive capability following gravitational transitions. The ability to predict the manner and degree to which each individual astronaut will be affected would improve the effectiveness of a countermeasure comprised of a training program designed to enhance sensorimotor adaptability. Therefore the goal of this project was to develop a set of predictive measures capable of identifying individual differences in sensorimotor adaptability to aid in the design of sensorimotor adaptability training countermeasures that are customized for each crewmember's individual sensory bias and adaptive capacity.

To achieve these goals we pursued the following specific aims:

Specific Aim 1: Determine whether behavioral metrics of individual sensory bias predicts strategic responses and sensorimotor adaptability to novel sensory environments.

Specific Aim 2: Develop predictors of strategic responses and sensorimotor adaptability using brain structural and functional metrics.

Specific Aim 3: Determine whether specific genetic polymorphisms are associated with individual differences in strategic responses and sensorimotor adaptability to novel sensory environments.

Subjects performed behavioral tests that delineated individual sensory bias in tests of visual, vestibular, and proprioceptive function. Subjects were also tested for individual differences in brain white matter integrity (using diffusion tensor imaging, or DTI), functional network integrity (using resting state functional connectivity MRI), and functional MRI activation associated with sensorimotor adaptation task performance. We also determined whether specific genotypes were associated with individual differences in sensorimotor adaptability. Three distinct motor learning tests were used to characterize individual behavioral strategic responses and motor learning capability. The Locomotor Balance Test characterized the strategic initial locomotor responses to a novel walking environment. The Adaptive Functional Mobility Test (AFMT) and the Adaptive Manual Control Test represented tasks producing plastic-adaptive response to a novel sensory environment. Subjects performed these tests to determine if behavioral, neuroimaging and genetic metrics predicted individual strategic and motor learning capability. Behavioral metrics related to proprioceptive function, visual dependency, and sensory integration served as the best predictors of individual strategic and motor learning capability. Behavioral results indicated that performance and adaptability are specific to the environment being tested.

This study explored relationships between behavioral parameters and performance on three different types of adaptation tasks. Each task had a different combination of significant parameters and no single parameter was significant for all three motor learning tasks. Diffusion Tensor Imaging (DTI) is an MRI technique used to assess white matter quality in the brain. The DTI results indicated that white matter microstructural integrity plays a role in how well individuals are able to respond to novel sensorimotor disturbances. Importantly, the white matter integrity of the corpus callosum was associated with enhanced performance suggesting that intact inter-hemispheric connectivity is an important factor for optimal responsiveness to novel changes in the sensory environment. Resting state functional connectivity MRI (fcMRI) was used to investigate individual differences in large-scale brain networks. These results demonstrated that specific patterns of functional connectivity between resting state networks involved in motor control and cognition are associated with individual differences in sensorimotor adaptation. The fMRI results indicated that a variety of frontal, temporal, and cingulate cortical and subcortical areas in which activation was predictive of individual differences in adaptability during a manual adaptation task. This suggests that some people might be more proficient at recruiting neural areas that allow for efficient adaptation learning. We determined whether genotypes for COMT, DRD2, BDNF, and Alpha 2 adrenergic receptor (DraI) single nucleotide polymorphisms (SNPs) were associated with individual differences in strategic responses and sensorimotor adaptability to novel sensory environments. The DraI and COMT SNPs showed a trend towards distinguishing subjects who exhibit faster or slower responses and adaptation rates on two locomotor tasks. These findings were limited by small sample size, but show promising initial results that may be improved upon by collecting more subject data.

In conclusion this study revealed that behavioral, neuroimaging, and genetic metrics can predict individual responses to novel sensory environments and motor learning capability. Predictive power may be enhanced using composite measures composed of a mix of behavioral, neuroimaging, and genetic metrics. Further investigations with astronauts in actual spaceflight conditions will serve to further validate potential predictive metrics of adaptability. These results have important implications for adaptation training programs that facilitate astronaut adaptation to novel environments and for rehabilitation. Specifically, the prospect of identifying people who will likely have difficulty with sensorimotor adaptation would allow for more targeted training programs.

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