How visual information links to multijoint coordination during quiet standing

Abstract

The link between visual information and postural control was investigated based on a multi-degree-of-freedom model using the framework of the uncontrolled manifold (UCM) hypothesis. The hypothesis was that because visual information specifies the position of the body in space, it would couple preferentially into those combinations of degrees of freedom (DOFs) that move the body in space and not into combinations of DOFs that do not move the body in space. Subjects stood quietly in a virtual reality cave for 4-min trials with or without a 0.2, 2.0 Hz, or combined 0.2 and 2.0 Hz visual field perturbation that was below perceptual threshold. Motion analysis was used to compute six sagittal plane joint angles. Variance across time of the angular motion was partitioned into (1) variance associated with motion of the body and (2) variance reflecting the use of flexible joint combinations that keep the anterior-posterior positions of the head (HD(POS)) and center of mass (CM(POS)) invariant. UCM analysis was performed in the frequency domain in order to link the sensory perturbation to each variance component at different frequencies. As predicted, variance related to motion of the body was selectively increased at the 0.2-Hz drive frequency but not at other frequencies of sway for both CM(POS) and HD(POS). The dominant effect with the 2.0-Hz visual drive also was limited largely to variance related to motion of the body.

Inter-trial phase coherence of visually evoked postural responses in virtual reality

“…We observed visually evoked postural responses (VEPRs) coupled to sinusoidal moving room-perturbations in VR, consistent with preceding studies employing real world (Lee and Lishman 1975;Peterka and Benolken 1995;Loughlin and Redfern 2001;Redfern et al 2007;Cruz et al 2018) and virtual (Dijkstra et al 1994;Kuno et al 1999;Keshner and Kenyon 2000;Oie et al 2002;Sparto et al 2004;Musolino et al 2006;Scholz et al 2012;Hanssens et al 2013) stimulation. Especially with stimulation at 0.2 Hz, subjects exhibited a steady-state response in the trajectory of their COP containing high power in the frequency regime of the stimulus, which is estimated to be around the mean eigenfrequency of the postural system (Dijkstra et al 1994).…”

“…Stable balance is mainly achieved by controlling the body's center of mass (COM) and keeping it within a distinct area of stability which physically supports the upright human body (Horak and Macpherson 1996;Scholz et al 2007Scholz et al , 2012Sousa et al 2012). Locating the COM within the complex mass distribution of a human body is a difficult endeavor, which is why foot center of pressure (COP) is widely used to investigate postural sway and whole-body movements (Winter 1995;Winter et al 1996).…”

“…These include structure (van Asten et al 1988a;Tossavainen et al 2003), velocity (Stoffregen 1986;Kuno 1999;Barela et al 2009;Dokka et al 2009;Day et al 2016;Holten et al 2016) and predictability (Guerraz et al 2001;Musolino et al 2006;Barela et al 2009). For periodical stimuli in particular, the effect on posture and balance depends on the frequency (Dijkstra et al 1994;Oida et al 1995;Jeka et al 1998;Kuno et al 1999;Scholz et al 2012;Hanssens et al 2013) and amplitude (Peterka and Benolken 1995;Peterka 2002;O'Connor et al 2008) of the modulation.…”

“…Because of their simple implementation and analytically beneficial properties, periodical perturbations of the visual scene in the form of sinusoidal oscillations have become a common method of assessing the influence of vision on posture (e.g. Lee and Lishman 1975;Dijkstra et al 1994;Peterka and Benolken 1995;Keshner and Kenyon 2000;Loughlin and Redfern 2001;Oie et al 2002;Musolino et al 2006;Redfern et al 2007;Scholz et al 2012;Hanssens et al 2013;Cruz et al 2018). Being performed in such a way, these studies allow for insights into the adjustments of the postural control system to an ongoing stimulation over longer periods of time.…”

Biomechanics as a window into the neural control of movement

“…In particular, many studies used kinematic (such as joint rotations) and kinetic (such as joint torques and digit forces) variables to perform analyses of the structure of inter-trial variance to estimate stability of specific performance variables to which all the elemental variables contributed. So far, the method has proven to be very productive with the discovery of new phenomena, such as selective stabilization of only some of the performance variables (Scholz and Schöner, 1999; Scholz et al, 2002), anticipatory synergy adjustments (Olafsdottir et al, 2005), the involvement of many body joints in postural sway (Hsu et al, 2007; Scholz et al, 2012), and significant changes in task-specific stability in patients with subcortical disorders (reviewed in Latash and Huang, 2015). The method has also been extended to analyze the phenomenon of motor equivalence, large movements of the high-dimensional system of elemental variables in directions leading to no changes in salient performance variables (Mattos et al, 2011, 2015).…”