The utilization of visual feedback from peripheral and ... - Research

May 4, 2004 - that are due to offline processing of visual feedback will result in a reduction in .... To ensure that participants did not move their eyes during the trials, a Sony CVX-VIP ...... Can J Exp Psychol 53:160–175. Abahnini K, Proteau L ...
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Exp Brain Res (2004) 158: 241–251 DOI 10.1007/s00221-004-1897-y

RESEARCH ARTICLES

Michael A. Khan . Gavin P. Lawrence . Ian M. Franks . Eric Buckolz

The utilization of visual feedback from peripheral and central vision in the control of direction Received: 14 July 2003 / Accepted: 7 March 2004 / Published online: 4 May 2004 # Springer-Verlag 2004

Abstract Past research has demonstrated that both peripheral and central vision play an important role in the control of movement direction. However, it has been unclear whether the benefits of these sources of information are due to adjustments in the limb trajectory during movement execution (i.e., online) or modification in motor commands prior to movement initiation (i.e., offline). In the present paper, we analyzed the variability in limb trajectories in a directional aiming task to examine the relative contributions of peripheral and central vision in both the planning and execution of movements. The point of gaze was manipulated to vary where in the limb trajectory information was gained from central and peripheral vision. Analysis of the variability in directional error at various stages of the movement revealed that participants utilized information from early in the trajectory during movement execution when it appeared in both peripheral and central visual fields. Information from late in the trajectory was used offline to improve the programming of subsequent movements regardless of where this information was available in the visual field. Keywords Aiming movements . Central vision . Peripheral vision

M. A. Khan (*) . G. P. Lawrence School of Sport, Health and Exercise Sciences, University of Wales, Bangor, George Building, Bangor, Gwynedd, Wales, LL57 2PX, UK e-mail: [email protected] Tel.: +44-1248-388275 Fax: +44-1248-371053 I. M. Franks School of Human Kinetics, University of British Columbia, Canada E. Buckolz School of Kinesiology, University of Western Ontario, Canada

Introduction When performing manual aiming movements to specific positions in space, individuals usually fixate on the target prior to movement initiation or relatively early in the trajectory of the limb (Abrams et al. 1990). This places the limb in the peripheral visual field during the initial stages of movement, whereas it enters the central visual field upon approaching the target. Paillard and Amblard (1985) have postulated that information from peripheral and central vision is processed via two semi-independent visual systems, each mediating a specific role in the control of goal-directed movement. The kinetic channel operates in the visual periphery and is said to play an important role in controlling the direction of movement. The static channel operates in central vision and is thought to be primarily responsible for the control of movement amplitude during the homing-in phase of the limb trajectory when limb velocities are relatively low. In support of Paillard and Amblard’s (1985) model, researchers have demonstrated that the accuracy of aiming tasks in which participants are required to move a specified distance is improved when central vision is available (Bard et al. 1990; Carlton 1981; Temprado et al. 1996), whereas peripheral vision has been shown to improve accuracy in tasks that require the control of direction (Abahnini and Proteau 1999; Abahnini et al. 1997; Bard et al. 1990). However, in contrast to Paillard and Amblard’s model, these latter studies have also revealed that central vision contributed to the directional accuracy of aiming movements. One interpretation that has been offered for this finding was that central vision was not used to adjust limb trajectories during movement execution (i.e., online). Instead, central vision was said to provide information on the terminal accuracy of movements, which was then used as a form of knowledge of results to improve the programming of subsequent movements (i.e., offline) (Abahnini and Proteau 1999; Abahnini et al. 1997). In support of this interpretation, it was noted that for the relatively fast movement times employed (