Great expectations: a predictive processing account of human balance control
Funder
None
Value
N/A
Team:
Collaborators
Dr. Toby Ellmers, Imperial College London
Prof Stephen Lord, Neuroscience Research Australia, University of Sydney
Duration
Ongoing
Project overview
For much of history, scientists have believed that the way we experience the world (our perception) is a result of our brain passively receiving incoming sensory stimuli. According to a revolutionary new theory (“Predictive Processing”), human brains are prediction machines. That is, the way we perceive and experience the world is as much to do with our prior expectations and predictions as it is the incoming sensory information.
This programme of research is focused on understanding ways in which we can deliberately “manipulate” our predictive brains by using various interventions (i.e. placebo effect, false feedback, reappraisal/reframing, priming, illusions) to modify our beliefs/expectations about an important perceptual-motor skill such as balance tasks.
This research fundamentally alters the way we think about managing balance problems (i.e. individuals with distorted perceptions of instability and maladaptive cognitive biases) with the ultimate ambition of reducing the occurrence and impact of falls.
Project Objectives
Understanding the importance of our expectations in the context of balance control systems in both healthy older adults and clinical populations.
Testing the efficacy of different procedures to modify expectations and exploring how such changes can influence human balance control systems and fear of falling.
Identifying the neurophysiological mechanisms driving these results (neural and muscular activity).
Exploring the factors that moderate the effects of expectations on balance perception and performance.
Project Outputs
- Russell, K., Duncan, M., Price, M., Mosewich, A., Ellmers, T., & Hill, M. (2022). A comparison of placebo and nocebo effects on objective and subjective postural stability: a double-edged sword? Frontiers in Human Neuroscience, 16, 967722.
