The neural foundations of handedness: insights from a rare case of deafferentation

Abstract

The role of proprioceptive feedback on motor lateralization remains unclear. We asked whether motor lateralization is dependent on proprioceptive feedback by examining a rare case of proprioceptive deafferentation (GL). Motor lateralization is thought to arise from asymmetries in neural organization, particularly at the cortical level. For example, we have previously provided evidence that the left hemisphere mediates optimal motor control that allows execution of smooth and efficient arm trajectories, while the right hemisphere mediates impedance control that can achieve stable and accurate final arm postures. The role of proprioception in both of these processes has previously been demonstrated empirically, bringing into question whether loss of proprioception will disrupt lateralization of motor performance. In this study, we assessed whether the loss of online sensory information produces deficits in integrating specific control contributions from each hemisphere by using a reaching task to examine upper limb kinematics in GL and five age-matched controls. Behavioral findings revealed differential deficits in the control of the left and right hands in GL and performance deficits in each of GL's hands compared with controls. Computational simulations can explain the behavioral results as a disruption in the integration of postural and trajectory control mechanisms when no somatosensory information is available. This rare case of proprioceptive deafferentation provides insights into developing a more accurate understanding of handedness that emphasizes the role of proprioception in both predictive and feedback control mechanisms.NEW & NOTEWORTHY The role of proprioceptive feedback on the lateralization of motor control mechanisms is unclear. We examined upper limb kinematics in a rare case of peripheral deafferentation to determine the role of sensory information in integrating motor control mechanisms from each hemisphere. Our empirical findings and computational simulations showed that the loss of somatosensory information results in an impaired integration of control mechanisms, thus providing support for a complementary dominance hypothesis of handedness.

Keywords: complementary dominance; lateralization; motor control; proprioception.

Conflict of interest statement

No conflicts of interest, financial or otherwise, are declared by the authors.

Figures

Fig. 1.

Experimental setup. A: an illustration of the KineReach setup showing a participant seated in front of a table with an inverted HD monitor that displayed the task on a mirrorized screen placed at chin level; this screen occluded direct view of the hands. Sensors placed on the hand and upper arm collected data used to compute orientation and location of the wrist, elbow, and shoulder joints. Each hand was supported on an air sled that produced continuous pressurized air to reduce the mechanical effects of friction and gravity. B: schematic of the unilateral reaching task showing movement of a cursor (representing the position of the hand) to the middle target (1 target presented per trial). Participants were asked to move the cursor to the target (appearing in 1 of 3 directions in a pseudorandom manner) within 1 s. The task consisted of 90 trials performed with each of the left and right hands separately. Visual feedback of the cursor was removed upon moving beyond the start circle.

Fig. 2.

Different behaviors exhibited by each hand in the absence of somatosensation. Substantial performance differences between hands are evident in the deafferented patient’s (GL) movements but not in those of neurologically intact control participants. A and B: hand paths and velocity profiles are shown in a representative participant in the control group (A) and in GL (B). Scale bars = 2-cm hand movement. C and D: mean initial direction error (C) and mean error at movement’s end (D) are displayed for each hand of control participants and GL (woman). Error bars in control data represent 1 SD from the mean (n = 5, 4 women). Mean values for each control participant are plotted as purple squares [left hand (L)] or yellow triangles [right hand (R)]. Crawford and Howell modified t test was used: *P < 0.001, statistically significant difference.

Fig. 3.

Serial activation of a dual-controller system describes differences in movement. Simulations of reaching movements show that 2 poorly tuned controllers can predict deafferented patient’s (GL’s) behavior. Hand paths and velocity profiles (insets) are shown for simulations of right arm movements involving pure trajectory control (A), pure postural control in a system with low joint damping (B), activation of the postural controller at peak velocity (C), late activation of postural control in a system with typical joint stiffness and damping values (E), and early (D) and late (F) activation of postural control in a system with joint stiffness and damping values similar to GL’s. Scale bars for trajectories = 2-cm simulated hand movement. Scale bars for velocity profiles represent 0.5 m/s.