The Effect of Training on Brain Activity During Postural Tasks in Older Adults

Older people show deficits in dynamic weight-shifting, as the investigators found that more time is needed to perform weight-shifts and the movements became less fluent and accurate in older versus younger adults. Deficits with weight-shifting in the mediolateral (left-right) direction have been linked to balance and falls in ageing. Balance control can be improved with training. Virtual reality (VR) based training programs for improving balance are gaining ground, as it can provide both fun and challenging balance tasks, enhancing motivation. The investigators demonstrated earlier that older adults show an overloaded neural activation pattern compared to young adults when performing the same VR-based mediolateral weight-shifting task (wasp game). What is yet unclear, is whether improved balance capacity can be gained with training and whether such an intervention impacts the underlying neural mechanisms. Using a combination of behavioral assessments and functional Near-Infrared Spectrocopy (fNIRS), the primary aim of this study is to investigate the effects of a VR-based weight-shift training and its underlying neural imprint in older adults. Furthermore, as a previous study done by the investigators also showed that adding an extra cognitive task in a so-called dual-task (DT) negatively affects weight-shifting performance, a secondary aim will be to test whether weight-shift training will enhance performance during such DT conditions. The results of this study may contribute to the future design of technology-based rehabilitation programs.

For this study, 40 healthy older adults will be included. A previous fNIRS study done by the investigators (unpublished) revealed that our primary outcome, weight-shifting speed, improved from 0,0668 ± 0,0255 m/s to 0,0916 ± 0,0350 m/s. Based on Caljouw et al. (2016), the investigators expect a training effect size of 20%, resulting in a weight-shifting speed of 0.1094 ± 0,0418 m/s. Applying a power of 80% and alpha of 0.05 for a repeated measures ANOVA with a within-between interaction design (within: pre vs post; between: training vs control) the investigators calculated a total sample size of 40 participants (20 per group). Considering possible data exclusion due to fNIRS measurements, the collected fNIRS data will be monitored during recruitment, and more participants will be recruited if necessary.

Prior to training on day 1, participants will be screened for inclusion based on the Montreal Cognitive Assessment (MoCA). Other cognitive assessments include the Flanker (inhibition), Set-Shifting (shifting attention), and Benton Judgement of Line Orientation (visuospatial ability) test, which will be administered on day 2. The Falls Efficacy Scale International (FES-I), a sarcopenia questionnaire (SARC-F), and the Pittsburgh Sleep Quality Index (PSQI) will also be administered on day 2 to assess fear of falling, sarcopenia, and the quality of sleep of the night between day 1 and day 2 of the experiment, respectively.

For both weight-shifting assessment and training, the VR-based Wasp Game will be used. Before starting the Wasp Game, functional limits of stability (fLOS) will be assessed by asking the participant to move the Centre of Mass (CoM) as far as possible over its base of support in eight different directions by pushing a virtual bar away from the center position. Mean CoM shifts will be calculated and used for personalized scaling of the Wasp Game. The Wasp Game was developed and piloted to meet the requirements for balance training for older people and can capture weight-shifting speed and accuracy as learning outcomes. In the Wasp Game, the player is in the middle of an area infested by wasps. By moving the CoM towards a pre-defined 80% of the fLOS, a water stream will come on to hit the wasp. The Wasp Game single-task (WASP-ST) involves hitting wasps in the mediolateral (ML) direction only. During the Wasp Game dual-task (WASP-DT), a serial subtraction task is added as the secondary task, whereby the red ball (representing the CoM) will change color from red to white and white to red within a random interval between 2-5 seconds. A starting number will appear on the screen for 1.5 seconds at the beginning of each trial. Every time the ball changes its color, subtractions have to be made in threes. Subjects will indicate the correct number afterward, so as not to disturb the fNIRS recording.

During training on day 1, participants will perform 10 blocks of 2.5 min weight-shifting within the WASP-ST. Before, and 24h after training, balance performance will be assessed with the Mini Balance Evaluation Systems Test (MiniBEST), and weight-shifting ability with the fLOS, the WASP-ST, and WASP-DT. During the WASP-ST and WASP-DT, oxygenated (HbO2) and deoxygenated hemoglobin (HHb) will be assessed simultaneously by means of functional Near-Infrared Spectroscopy (fNIRS). To be able to compare HbO2 and HHb levels relative to a baseline, both the WASP-ST and WASP-DT will be offered in a block design of 20 sec standing still and looking at a screen capture of the Wasp Game and 20 sec of weight-shifting within the Wasp Game, alternating in 7 trials. Cortical regions assessed with fNIRS include the prefrontal cortex (PFC), frontal eye fields (FEF), premotor cortex (PMC), supplementary motor area (SMA), and supplementary sensory cortex (SSC). To ensure similar fNIRS recording on all test moments, the fNIRS cap and optodes will remain in place between pre and post-testing. Between post and retention testing, certain spots on the head (i.e. Cz) will be marked to guide cap placement on day 2. In a recent study, fNIRS was found to have adequate test-retest reliability.

Eligibility Criteria:
Inclusion Criteria:

* Being able to independently stand upright \> 5min

Exclusion Criteria:

* Visual impairment precluding following the targets on the screen
* Cognitive impairment (MoCA\<24/26?) / (MMSE\<24)?
* History of neurological disorders
* Balance impairments (i.e. vestibular disorders)
* Chronic musculoskeletal, cardiovascular and respiratory conditions
* Diabetes related polyneuropathy