Different damping responses explain vertical endpoint error differences between visual conditions

Abstract

Upright people making goal-directed movements in dark environments often vertically undershoot remembered target locations when compared to performances in illuminated environments. In this study, we wanted to determine whether influences of the gravitational pull and/or type of muscle activation could explain differences in vertical endpoint precision between movements to visually remembered target locations with and without allocentric cues available. We also used a simple damping model for movement trajectories to describe potential differences in behavior between visual conditions. Subjects performed straight arm pointing movements to REAL target locations or remembered target locations in darkness (DARK) or normal room lighting (LIGHT). Performances were made from UPRIGHT and INVERTED (upside down) body orientations. Starting arm position (UP by the ear; DOWN on the thigh) also varied so that eccentric or concentric muscle contractions for arm flexion or extension movements occurred primarily along the earth-fixed vertical either with or against the gravitational pull. Effects of visual condition (LIGHT, DARK), body orientation (UPRIGHT, INVERTED), starting arm position (UP, DOWN), and target level (Near, Middle, Far) on elevation endpoint errors revealed that subject's errors in the DARK were more negative than those in the LIGHT. Errors correlated well with movement displacement to reveal the common vertical undershooting bias in darkness exacerbated by inverting the body or requiring greater movement excursions. Although influences of gravitational pull and muscle activation type could not explain differences between visual conditions, modeling revealed critically damped behavior in the DARK and under-damped behavior in the LIGHT to indicate muscle energy dissipation without vision.

A cross-species neural integration of gravity for motor optimisation

“…Given the richness of humans’ and monkeys’ motor repertoires, the study of mono-articular arm movements may seem restrictive. However, it is essential to point out that direction-dependent motor patterns have been observed for movements as varied as mono-articular arm (Crevecoeur et al, 2009; Gaveau and Papaxanthis, 2011; Gaveau et al, 2014, 2016; Gentili et al, 2007; Hondzinski et al, 2016; Sciutti et al, 2012; Le Seac’h and McIntyre, 2007), multi-articular arm (Berret et al, 2008; Papaxanthis et al, 1998a, 1998b; Yamamoto and Kushiro, 2014) and whole-body movements (Manckoundia et al, 2006; Papaxanthis et al, 2003). These results, along with the present findings, provide conceptual support for a general theory that the brain builds internal representations of the environmental and musculoskeletal dynamics to optimise motor planning and control (Franklin and Wolpert, 2011; Guigon et al, 2008; Izawa et al, 2008; Shadmehr and Wise, 2005; Shadmehr et al, 2010; Todorov, 2004; Wolpert and Ghahramani, 2000).…”

A cross-species neural integration of gravity for motor optimization

“…Given the richness of humans' and monkeys' motor repertoires, the study of monoarticular arm movements may seem restrictive. However, it is essential to point out that direction-dependent motor patterns have been observed for movements as varied as monoarticular upper limb (21,23,59), multiarticular upper limb (60,61), and wholebody movements (62). These direction-dependent motor patterns are optimal to save muscle effort and slowly reoptimize to newly experienced gravito-inertial fields (23,24,60).…”

Muscle effort is best minimized by the right-dominant arm in the gravity field

“…Investigating motor planning and control of the dominant arm/hemisphere, several studies proposed that the brain uses an internal representation of gravity to take advantage of its mechanical effects (Berret et al 2008;Crevecoeur et al 2009;Gaveau et al 2014Gaveau et al , 2016Gaveau et al , 2021. More specifically, studies investigating vertical arm reaching movements reported direction-dependent arm kinematics (Gaveau et al , 2014(Gaveau et al , 2016(Gaveau et al , 2021Gentili et al 2007;Hondzinski et al 2016;Papaxanthis et al 2005;Poirier et al 2020;Le Seac'h and McIntyre 2007;Yamamoto et al 2016Yamamoto et al , 2019Yamamoto and Kushiro 2014). Particularly, the time to peak acceleration and time to peak velocity were shorter and the curvature was greater for upward than for downward movements.…”