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.

Buccello-Stout, RR, Bloomberg, JJ, Cohen, HS, Whorton, EB, Weaver, GD, & Cromwell, RL. Effects of sensorimotor adaptation training on functional mobility in older adults. J Gerontol B Psychol Sci Soc Sci. 63(5): 295-300. 2008.

Buccello-Stout RR, Cromwell RL, Bloomberg JJ, Whorton EB. Effects of sensorimotor adaptation training on head stability movement control in response to a lateral perturbation in older adults. The Journal of Aging and Physical Activity. 21: 272-289. 2013.

Dr. Mulavara is currently conducting a complementary National Space Biomedical Research Institute (NSBRI) study titled Developing Personalized Countermeasures for Sensorimotor Adaptability: A Bed Rest Study. This study will recall subjects who participated in the recent bed rest CFT70 campaign and spaceflight subjects (Functional Task Test) to investigate if predictive metrics based on behavioral, brain, and genetic markers can be used to retrospectively predict sensorimotor adaptability in post bed rest and spaceflight subjects. To aid this effort and to develop a complete set of predictive metrics we added several new behavioral measures. We also added genetic tests previously used to detect sensorimotor adaptability as possible metrics of adaptability. We called back our original subjects and tested them on these new metrics, which were added to the original set of potential predictive metrics obtained previously. During this reporting period data collection analysis was completed.

Data Collection at Azusa Pacific University (APU): The focus of the data collection at Dr. Wood's APU laboratory was to expand the set of behavioral predictive measures capable of identifying individual differences in the ability to adapt to novel discordant sensory environments. In the APU study the inter-subject variability during adaption to visual distortion lenses was measured in 27 subjects over 3 sessions. During this reporting period data collection analysis for the studies at APU was completed.

During this reporting period the following manuscripts were published:

Seidler RD, Mulavara AP, Bloomberg JJ, Peters BT. Individual predictors of sensorimotor adaptability. Front. Syst. Neurosci. 9:100. doi: 10.3389/fnsys.2015.00100, 2015.

Bloomberg JJ, Peters BT, Cohen HS and Mulavara AP. Enhancing astronaut performance using sensorimotor adaptability training. Front. Syst. Neurosci. 9:129.doi: 10.3389/fnsys.2015.00129, 2015.

In addition, during this reporting period 17 presentations at meetings were completed.

See also Bibliography section below.

To achieve these goals we have the following specific aims:

Specific Aim 1: Determine whether behavioral metrics of individual sensory bias predict sensorimotor adaptability. Subjects show individual variation in the degree to which sensory inputs are weighted and reorganized to produce motor output during exposure to discordant sensory conditions. These individual sensory biases may serve as predictors of adaptability. For this aim, subjects will perform tests that will delineate individual sensory biases in tests of visual, vestibular, and proprioceptive function. They will then be tested to determine if these metrics predict how quickly they adapt to a novel discordant sensory environment.

Specific Aim 2: Determine if individual capability for strategic and plastic-adaptive responses predicts sensorimotor adaptability. The transition from one sensorimotor state to another consists of two main mechanisms: strategic and plastic-adaptive. Strategic modifications represent immediate and transitory changes in control that are employed to deal with short-term changes in the prevailing environment. If these changes are prolonged then plastic-adaptive changes are evoked that modify central nervous system function to automate new behavioral responses. For this aim, each subject's strategic and plastic-adaptive abilities will be assessed using a test of locomotor function designed specifically to delineate both mechanisms. Subjects will then be tested to determine if these measures predict how quickly they adapt to a novel discordant sensory environment.

Specific Aim 3: Develop predictors of sensorimotor adaptability using brain structural and functional metrics. We will measure individual differences in regional brain volumes (structural magnetic resonance imaging, or MRI), white matter integrity (diffusion tensor imaging, or DTI), functional network integrity (resting state functional connectivity MRI), and sensorimotor adaptation task-related functional brain activation (functional MRI). Subjects will then be tested to determine if these metrics predict how quickly they behaviorally adapt to a novel discordant sensory environment.

Specific Aim 4: Determine if individualized training prescriptions based on predictive metrics can be used to optimize sensorimotor adaptability training countermeasures. To determine if predictive adaptability metrics can be used to design individualized training programs we will examine a test case focusing on improving adaptive performance of visually dependent subjects. Subjects who are identified in Experiment 1, as being visually dependent with reduced adaptive capability, will receive individualized training prescriptions designed to reduce their dependence on vision and increase their ability to use vestibular information for control of movement. The training program will have two components. 1) Subjects will walk on a treadmill-motion base system while viewing discordant visual scenes to reduce dependency on vision along with support-surface motion to challenge gait stability. 2) During this training subjects will receive stimuli (vestibular stochastic resonance) to enhance vestibular signal detection. We anticipate that these two components will act in synergy during training to both reduce visual dependency while increasing dependence on vestibular information. Training efficacy will be assessed by comparing the performance of trained and control visually dependent subjects on how quickly they adapt to a novel discordant sensory environment.

In an effort to increase efficiency and maximize the predictive power of our measures we are currently completing the data collection for Specific Aims 1, 2, and 3 simultaneously on the same subjects (n=15). This involves behavioral testing in our labs at NASA/Johnson Space Center and neuroimaging at the University of Texas Medical Branch Victory Lakes Facility, which is located offsite. This approach had a number of benefits including increased data capture. By having the same subject perform all three specific aims we can enhance our ability to detect how wider range factors and their grouping can predict adaptability in a specific individual. This provides a much richer data base and potentially a better understanding of the predictive power of the selected factors.

Buccello-Stout, RR, Bloomberg, JJ, Cohen, HS, Whorton, EB, Weaver, GD, & Cromwell, RL. Effects of sensorimotor adaptation training on functional mobility in older adults. J Gerontol B Psychol Sci Soc Sci. 63(5): 295-300. 2008.

Buccello-Stout RR, Cromwell RL, Bloomberg JJ, Whorton EB. Effects of sensorimotor adaptation training on head stability movement control in response to a lateral perturbation in older adults. The Journal of Aging and Physical Activity. 21: 272-289. 2013.

Significant improvements were made to our data-collection process for the Treadmill Visual Dependency and Novel Sensory Discordance tests. These tests require simultaneous data collection of video-based motion capture and analog data. We consolidated the data collection from three to two computers while still assuring that the video-based motion capture data and the analog data were synchronized. This allowed us to eliminate several post-processing steps to synchronize the data, saving up to an hour of analysis time per data collection session.

We have received approval from the NASA Institutional Review Board (IRB) and completed a NASA Test Readiness Review (TRR) to conduct the study supporting Specific Aim 4. We are currently conducting pilot testing and plan to begin data collection for Specific Aim 4 in Sept. 2014. Data Collection at Azusa Pacific University (APU): The focus of the data collection at Dr. Wood's APU laboratory is to expand the set of predictive measures capable of identifying individual differences in the ability to adapt to novel discordant sensory environments. As with the primary data collection at NASA Johnson Space Center (JSC), three sets of predictor tests have been implemented to delineate individual sensory biases or asymmetries in tests of visual, vestibular, and proprioceptive function. The ability to adapt to discordant sensory cues will be assessed by improvements in time-to-completion of an obstacle course over a foam surface while wearing visual distortion lenses. This past year five undergraduate students assisted Dr. Wood in implementing the tests (described in the Main Findings section). During the next phase, thirty students will be recruited to perform each of the following tests. We expect both the overlapping measures in another research setting as well as the unique features of the tests implemented at APU will enhance our ability to generalize results towards a comprehensive set of predictive tests to determine individual capability for rapid sensorimotor adaptation.

To achieve these goals we have the following specific aims:

Specific Aim 1: Determine whether behavioral metrics of individual sensory bias predicts sensorimotor adaptability. Subjects show individual variation in the degree to which sensory inputs are weighted and reorganized to produce motor output during exposure to discordant sensory conditions. These individual sensory biases may serve as predictors of adaptability. For this aim, subjects will perform tests that will delineate individual sensory biases in tests of visual, vestibular and proprioceptive function. They will then be tested to determine if these metrics predict how quickly they adapt to a novel discordant sensory environment.

Specific Aim 2: Determine if individual capability for strategic and plastic-adaptive responses predicts sensorimotor adaptability. The transition from one sensorimotor state to another consists of two main mechanisms: strategic and plastic-adaptive. Strategic modifications represent immediate and transitory changes in control that are employed to deal with short-term changes in the prevailing environment. If these changes are prolonged then plastic-adaptive changes are evoked that modify central nervous system function to automate new behavioral responses. For this aim, each subject's strategic and plastic-adaptive abilities will be assessed using two tests of locomotor function designed specifically to delineate both mechanisms. Subjects will then be tested to determine if these measures predict how quickly they adapt to a novel discordant sensory environment.

Specific Aim 3: Develop predictors of sensorimotor adaptability using brain structural and functional metrics. We will measure individual differences in regional brain volumes (structural MRI), white matter integrity (diffusion tensor imaging, or DTI), functional network integrity (resting state functional connectivity MRI), and sensorimotor adaptation task-related functional brain activation (functional MRI). Subjects will then be tested to determine if these metrics predict how quickly they behaviorally adapt to a novel discordant sensory environment.

Specific Aim 4: Determine if individualized training prescriptions based on predictive metrics can be used to optimize sensorimotor adaptability training countermeasures. To determine if predictive adaptability metrics can be used to design individualized training programs we will examine a test case focusing on improving adaptive performance of visually dependent subjects. Subjects who are identified in Experiment 1, as being visually dependent with reduced adaptive capability will receive individualized training prescriptions designed to reduce their dependence on vision and increase their ability to use vestibular information for control of movement. The training program will have two components. 1) Subjects will walk on a treadmill-motion base system while viewing discordant visual scenes to reduce dependency on vision along with support-surface motion to challenge gait stability. 2) During this training subjects will receive stimuli (vestibular stochastic resonance) to enhance vestibular signal detection. We anticipate that these two components will act in synergy during training to both reduce visual dependency while increasing dependence on vestibular information. Training efficacy will be assessed by comparing the performance of trained and control visually dependent subjects on how quickly they adapt to a novel discordant sensory environment.

In an effort to increase efficiency and data capture we are currently conducting data collection for Specific Aims 1, 3, and part of 2 simultaneously on the same subjects.

Buccello-Stout, RR, Bloomberg, JJ, Cohen, HS, Whorton, EB, Weaver, GD, & Cromwell, RL. Effects of sensorimotor adaptation training on functional mobility in older adults. J Gerontol B Psychol Sci Soc Sci. 63(5): 295-300. 2008.

Buccello-Stout RR, Cromwell RL, Bloomberg JJ, Whorton EB. Effects of sensorimotor adaptation training on head stability movement control in response to a lateral perturbation in older adults. The Journal of Aging and Physical Activity. 21: 272-289. 2013.

In order to perform this integrated data collection procedure the following activities were completed: 1) Institutional Review Board approval was obtained. 2) A NASA Test Readiness Review was completed. 3) Pilot experimental dry runs were conducted at the University of Texas Medical Branch (UTMB) Victory Lakes MRI facility to practice and finalize the neuroimaging procedures required for Specific Aim 3. 4) Procedures to measure proprioceptive acuity were developed that were superior to those described in the initial proposal. In collaboration with the NASA-JSC Exercise Physiology Lab a more accurate and repeatable measure of proprioceptive acuity was implemented entailing the use of an isokinetic dynamometer that measures an individual's ability to reproduce a predetermined joint angle after passively moving the limb.

To achieve these goals we will pursue the following specific aims:

Aim 1: Determine whether behavioral metrics of individual sensory bias predicts sensorimotor adaptability. For this aim, subjects will perform tests that will delineate individual sensory bias in tests of visual, vestibular and proprioceptive function. They will then be tested to determine if these metrics predict how quickly they adapt to a novel discordant sensory environment.

Aim 2: Determine if individual capability for strategic and plastic-adaptive responses predicts sensorimotor adaptability. The transition from one sensorimotor state to another consists of two main mechanisms: strategic and plastic-adaptive. Strategic modifications represent immediate and transitory changes in control that are employed to deal with short-term changes in the prevailing environment. If these changes are prolonged then plastic-adaptive changes are evoked that modify central nervous system function to automate new behavioral responses. For this aim, each subject’s strategic and plastic-adaptive motor learning abilities will be assessed using two tests of locomotor function designed specifically to delineate both mechanisms. Subjects will then be tested to determine if these measures predict how quickly they adapt to a novel discordant sensory environment.

Aim 3: Develop predictors of sensorimotor adaptability using brain structural and functional metrics. We will measure individual differences in regional brain volumes (structural MRI), white matter integrity (diffusion tensor imaging, or DTI), functional network integrity (resting state functional connectivity MRI), and sensorimotor adaptation task-related functional brain activation (functional MRI). Subjects will then be tested to determine if these metrics predict how fast they behaviorally adapt to a novel discordant sensory environment.

Aim 4: Determine if individualized training prescriptions based on predictive metrics can be used to optimize sensorimotor adaptability training countermeasures. To achieve this aim we will examine a test case focusing on improving adaptive performance of visually dependent subjects. Subjects identified in Aim 1 as being visually dependent with reduced adaptive capability will receive individualized training prescriptions designed to reduce their dependence on vision and increase their ability to use vestibular information for control of movement. As part of a specialized training program, subjects will walk on a treadmill-motion base system while experiencing discordant visual scenes along with increased support surface motion. During this training subjects will receive stimuli to enhance vestibular signal detection to aid in dynamic balance control. Training efficacy will be assessed by comparing the performance of trained and control subjects on how quickly they adapt to a novel discordant sensory environment.