Body spatial orientation depends directly on a precise and continuous integration of visual, vestibular, and somatosensory inputs. The integration of these inputs supports the central nervous system (CNS) to create a time-to-time neural representation of the body configuration, and its relation with the surrounding environment [1, 2]. the accuracy of this internal representation is essential for the implementation of successful corrective adjustments to internal and external mechanical forces applied to the axial skeleton. The visual system, for example, uses fine oculomotor movements (such as smooth pursuit and saccadic movements) along with peripheral visual perception to provide a reference for body’s verticality, head/body orientation, and body’s relative velocity to the visual world [3-5].
The relative importance of visual inputs on postural control is commonly referred to as visual dependency, and its applications in both laboratory and clinical settings have grown in importance. This importance is rooted to its potential role on improving predictive models of higher risks of falling in adults. Historically, the term visual dependency was coined based on Witkin and Asch (1948), who introduced the analog rod-and-frame test as a subjective visual procedure to estimate one’s degree of reliance on visual information for spatial orientation [6]. An important find was the larger levels of perceptual errors in a percentage of the healthy persons studied, implying these persons might not rely on visual inputs to the same degree. These results suggest that part of our healthy population is naturally prone to higher risks of falling when their vision is impaired and/or obstructed. Although this higher risk of falling may be subclinical at younger ages, they are likely amplified by aging and/or neurological conditions. Based on this rationale, indices quantifying degrees of visual dependency could be used as an early indicator for increased fall risk. However, testing this rationale depends on the development and investigation of a multi-dimensional panel of indices representing multiple characteristics of human bipedal vertical control.
Along the past decades, the analog rod-and-frame test has been replaced by computerized methods with improved accuracy. For example, individuals are asked to adjust a projected laser bar, so the bar is perceived as either in its most vertical or horizontal position. The angular error between the bar placement and the true vertical or horizontal is computed (subjective visual vertical, SVV, and subjective visual horizontal, SVH, respectively). This valid otoneurologic clinical test has been successfully used to investigate the integrity of visual and vestibular otolithic information in different health conditions [7–9]. Despite improved accuracy and easy application, SVV and SVH tests have been limited to cases of severe impairments, such as vestibular neuritis, cerebellopontine angle tumor, posterior canal benign paroxysmal positional vertigo, and other peripheral and central vestibular lesions [10–17]. This limitation has hindered its utilization in mild and moderate cases. Therefore, less severe visual and vestibular impairments may go undetected and untreated.
Considering ample evidence suggesting human postural control as a complex series of neurophysiological processes involving several cortical and subcortical structures [18], the univariate nature of SVV/SDH testing outcomes seems to restrict its sensitivity. A potential method to improve SVV and SVH outcomes is the analysis of the body’s sway behavior (computerized stabilometry). This assessment is based on the recording of the body’s central of pressure (COP) coordinates on a force platform during the execution of quiet bipedal vertical stance [19, 20]. Once recorded, these signals are submitted to computational procedures for the extraction of multiple indices corresponding to characteristics belonging to multiple analytical domains, i.e., spatial, temporal, frequency, and structural domains [21, 22]. In fact, this principle has been utilized to investigate the effect of vision on postural control by analyzing body sway behavior during quiet stance with eyes open and closed [23–27]. Despite their importance, these investigations were not designed to establish an actual index representing the visual dependency during postural control, nor its potential modulation across the lifespan. Such gap in the scientific literature remains.
A plausible solution to overcome this gap is the development of postural indices dedicated to the quantification of visual dependency. For example, the computation of ratios between indices obtained from different conditions of visual inputs availability could be a potential marker for visual dependency. Under this approach, individuals showing larger visual dependency would likely develop ratios departing from the normative. The use of postural index ratios was introduced by Nashner and Peters (1990) as a concept for the sensory organization testing where major sensory modalities are manipulated for the establishment of ratio-based scores [28]. This method has been clinically used in the past decades. However, the ratios and scores (i.e. maximum amplitudes of body sway and COP’s shortest distances to the base of support’s boundary) still represent only a fraction of all indices reported in laboratory as sensitive to modulation of visual inputs [28–30].
The present study was designed to bridge this gap. Here, we introduced the use of a set of Visuo-Postural Dependency Index (VPDI) representing the normalized differences calculated for multiple variables of interest recorded via computerized stabilometry, and under different conditions of visual inputs availability. We investigated the modulation of each VPDI to establish their ability to capture the effects of changes in visual inputs, their potential modulation across the lifespan, their correlations to SVV and SVH testing results, and a potential gender effect. Our main hypothesis is centered on the expectancy that VPDIs representing multiple analytical domains would be sensitive to the modulation of visual inputs. We also hypothesized that visual dependency would decrease with age. This study represents a logical progression on the study of visuo-postural dependency by providing a comprehensive panel of postural behavioral quantities and establishing an initial set of normative data across the adult life span. Moreover, the present study will offer an initial analysis of the potential relationship between subjective visual testing and stabilometric indices.