An illustration of antero-posterior (AP) and mediolateral (ML) sway

Postural Sway

An illustration of antero-posterior (AP) and mediolateral (ML) sway

Postural Sway

What is postural sway?

When humans stand upright, we are inherently unstable; we need to constantly make small adjustments to maintain upright stance. Most of the time we are unaware of these tiny adjustments (slightly more so when we close our eyes). However, there is a complex set of brain and body systems underpinning our ability to remain standing. I’m interested in measuring the output of these systems using relatively simple equipment and measures (a force plate that measures centre of pressure while people stand as still as possible). Can these simple measures help us detect underlying differences between healthy individuals and those with Parkinson’s disease, or multiple sclerosis, or schizoprhenia? Can we see the influence of long-term use of substances such as cannabis? Can individual differences in sway measures tell us something about how vision influences a person’s interpretation of the world (for instance, in judging self-motion)?

Deborah Apthorp
Senior Lecturer in Psychology

My research interests include visual perception, Parkinson’s disease, postural sway, and EEG.


Postural control deficits are well documented in schizophrenia. However, postural stability has not been assessed in first-degree relatives of individuals with schizophrenia to our knowledge. We analyzed postural sway in 27 controls (CTR) and 18 first-degree relatives (REL). The REL group was significantly impaired compared to CTR, with a larger mean sway area and longer mean sway path. These preliminary findings suggest a genetic contribution to postural control deficits observed in schizophrenia spectrum disorders. Future studies should, however, examine the contributions of shared environmental risk factors including stress, toxins, etc. to familial risk to dissociate them from shared genetic risk.

We measured postural sway in individuals diagnosed with Parkinson’s disease and age-matched controls. Individuals with Parkinson’s swayed more, as expected, especially when their eyes were closed. In the people with Parkinson’s, sway correlated strongly with cognitive measures, as well as with measures of quality of life and clinical status.

We measured postural sway in individuals diagnosed with schizotypal personality disorder, but otherwise free of medication and other comorbidities. They swayed significantly more than matched controls, and as much as people dignosed with schizophrenia, in all conditions.

A prominent effect of acute cannabis use is impaired motor coordination and driving performance. However, few studies have evaluated balance in chronic cannabis users, even though density of the CB1 receptor, which mediates the psychoactive effects of cannabis, is extremely high in brain regions critically involved in this fundamental behavior. The present study measured postural sway in regular cannabis users and used rambling and trembling analysis to quantify the integrity of central and peripheral nervous system contributions to the sway signal.Postural sway was measured in 42 regular cannabis users (CB group) and 36 non-cannabis users (N-CB group) by asking participants to stand as still as possible on a force platform in the presence and absence of motor and sensory challenges. Center of pressure (COP) path length was measured, and the COP signal was decomposed into rambling and trembling components. Exploratory correlational analyses were conducted between sway variables, cannabis use history, and neurocognitive function. The CB group had significantly increased path length and increased trembling in the anterior-posterior (AP) direction. Exploratory correlational analyses suggested that AP rambling was significantly inversely associated with visuo-motor processing speed. Regular cannabis use is associated with increased postural sway, and this appears to be predominantly due to the trembling component, which is believed to reflect the peripheral nervous system’s contribution to the sway signal.

Sounds are thought to contribute to the perceptions of self-motion, often via higher-level, cognitive mechanisms. This study examined whether illusory self-motion (i.e. vection) could be induced by auditory metaphorical motion stimulation (without providing any spatialized or low-level sensory information consistent with self-motion). Five different types of auditory stimuli were presented in mono to our 20 blindfolded, stationary participants (via a loud speaker array): (1) an ascending Shepard–Risset glissando; (2) a descending Shepard–Risset glissando; (3) a combined Shepard–Risset glissando; (4) a combined-adjusted (loudness-controlled) Shepard–Risset glissando; and (5) a white-noise control stimulus. We found that auditory vection was consistently induced by all four Shepard–Risset glissandi compared to the white-noise control. This metaphorical auditory vection appeared similar in strength to the vection induced by the visual reference stimulus simulating vertical self-motion. Replicating past visual vection findings, we also found that individual differences in postural instability appeared to significantly predict auditory vection strength ratings. These findings are consistent with the notion that auditory contributions to self-motion perception may be predominantly due to higher-level cognitive factors.

Visually-induced illusions of self-motion (vection) can be compelling for some people, but they are subject to large individual variations in strength. Do these variations depend, at least in part, on the extent to which people rely on vision to maintain their postural stability? We investigated by comparing physical posture measures to subjective vection ratings. Using a Bertec balance plate in a brightly-lit room, we measured 13 participants’ excursions of the centre of foot pressure (CoP) over a 60-second period with eyes open and with eyes closed during quiet stance. Subsequently, we collected vection strength ratings for large optic flow displays while seated, using both verbal ratings and online throttle measures. We also collected measures of postural sway (changes in anterior-posterior CoP) in response to the same visual motion stimuli while standing on the plate. The magnitude of standing sway in response to expanding optic flow (in comparison to blank fixation periods) was predictive of both verbal and throttle measures for seated vection. In addition, the ratio between eyes-open and eyes-closed CoP excursions during quiet stance (using the area of postural sway) significantly predicted seated vection for both measures. Interestingly, these relationships were weaker for contracting optic flow displays, though these produced both stronger vection and more sway. Next we used a non-linear analysis (recurrence quantification analysis, RQA) of the fluctuations in anterior-posterior position during quiet stance (both with eyes closed and eyes open); this was a much stronger predictor of seated vection for both expanding and contracting stimuli. Given the complex multisensory integration involved in postural control, our study adds to the growing evidence that non-linear measures drawn from complexity theory may provide a more informative measure of postural sway than the conventional linear measures.

This study asked whether individual differences in the influence of vision on postural stability could be used to predict the strength of subsequently induced visual illusions of self-motion (vection). In the experiment, we first measured spontaneous postural sway while subjects stood erect for 60 s with their eyes both open and both closed. We then showed our subjects two types of self-motion display: radially expanding optic flow (simulating constant velocity forwards self-motion) and vertically oscillating radially expanding optic flow (simulating constant velocity forwards self-motion combined with vertical head oscillation). As expected, subjects swayed more with their eyes closed (compared to open) and experienced more compelling illusions of self-motion with vertically oscillating (as opposed to smooth) radial flow. The extent to which participants relied on vision for postural stability—measured as the ratio of sway with eyes closed compared to that with eyes open—was found to predict vection strength. However, this was only the case for displays representing smooth self-motion. It seems that for oscillating displays, other factors, such as visual–vestibular interactions, may be more important.