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D Y P Henriques

Publications and source records attributed to D Y P Henriques.

7 recordsLinked to original sources
PubMed2006

Proprioceptive guidance of saccades in eye-hand coordination.

The saccade generator updates memorized target representations for saccades during eye and head movements. Here, we tested if proprioceptive feedback from the arm can also update handheld object locations for saccades, and what intrinsic coordinate system(s) is used in this transformation. We measured radial saccades beginning from a central light-emitting diode to 16 target locations arranged peripherally in eight directions and two eccentricities on a horizontal plane in front of subjects. Target locations were either indicated 1) by a visual flash, 2) by the subject actively moving the handheld central target to a peripheral location, 3) by the experimenter passively moving the subject's hand, or 4) through a combination of the above proprioceptive and visual stimuli. Saccade direction was relatively accurate, but subjects showed task-dependent systematic overshoots and variable errors in radial amplitude. Visually guided saccades showed the smallest overshoot, followed by saccades guided by both vision and proprioception, whereas proprioceptively guided saccades showed the largest overshoot. In most tasks, the overall distribution of saccade endpoints was shifted and expanded in a gaze- or head-centered cardinal coordinate system. However, the active proprioception task produced a tilted pattern of errors, apparently weighted toward a limb-centered coordinate system. This suggests the saccade generator receives an efference copy of the arm movement command but fails to compensate for the arm's inertia-related directional anisotropy. Thus the saccade system is able to transform hand-centered somatosensory signals into oculomotor coordinates and combine somatosensory signals with visual inputs, but it seems to have a poorly calibrated internal model of limb properties.

Adult↗
PubMed2003

Geometric computations underlying eye-hand coordination: orientations of the two eyes and the head.

Eye-hand coordination is geometrically complex. To compute the location of a visual target relative to the hand, the brain must consider every anatomical link in the chain from retinas to fingertips. Here we focus on the first three links, studying how the brain handles information about the angles of the two eyes and the head. It is known that people, even in darkness, reach more accurately when the eye looks toward the target, rather than right or left of it. We show that reaching is also impaired when the binocular fixation point is displaced from the target in depth: reaching becomes not just sloppy, but systematically inaccurate. Surprisingly, though, in normal Gaze-On-Target reaching we found no strong correlations between errors in aiming the eyes and hand onto the target site. We also asked people to reach when the head was not facing the target. When the eyes were on-target, people reached accurately, but when gaze was off-target, performance degraded. Taking all these findings together, we suggest that the brain's computational networks have learned the complex geometry of reaching for well-practiced tasks, but that the networks are poorly calibrated for less common tasks such as Gaze-Off-Target reaching.

Adult↗
PubMed2003

Ocular kinematics and eye-hand coordination.

Eye-hand coordination is complicated by the fact that the eyes are constantly in motion relative to the head. This poses problems in interpreting the spatial information gathered from the retinas and using this to guide hand motion. In particular, eye-centered visual information must somehow be spatially updated across eye movements to be useful for future actions, and these representations must then be transformed into commands appropriate for arm motion. In this review, we present evidence that early visuomotor representations for arm movement are remapped relative to the gaze direction during each saccade. We find that this mechanism holds for targets in both far and near visual space. We then show how the brain incorporates the three-dimensional, rotary geometry of the eyes when interpreting retinal images and transforming these into commands for arm movement. Next, we explore the possibility that hand-eye alignment is optimized for the eye with the best field of view. Finally, we describe how head orientation influences the linkage between oculocentric visual frames and bodycentric motor frames. These findings are framed in terms of our 'conversion-on-demand' model, in which only those representations selected for action are put through the complex visuomotor transformations required for interaction with objects in personal space, thus providing a virtual on-line map of visuomotor space.

Biomechanical Phenomena↗
PubMed2002

Visuomotor transformations for eye-hand coordination.

In recent years the scientific community has come to appreciate that the early cortical representations for visually guided arm movements are probably coded in a visual frame, i.e. relative to retinal landmarks. While this scheme accounts for many behavioral and neurophysiological observations, it also poses certain problems for manual control. For example, how are these oculocentric representations updated across eye movements, and how are they then transformed into useful commands for accurate movements of the arm relative to the body? Also, since we have two eyes, which is used as the reference point in eye-hand alignment tasks like pointing? We show that patterns of errors in human pointing suggest that early oculocentric representations for arm movement are remapped relative to the gaze direction during each saccade. To then transform these oculocentric representations into useful commands for accurate movements of the arm relative to the body, the brain correctly incorporates the three-dimensional, rotary geometry of the eyes when interpreting retinal images. We also explore the possibility that the eye-hand coordination system uses a strategy like ocular dominance, but switches alignment between the left and right eye in order to maximize eye-hand coordination in the best field of view. Finally, we describe the influence of eye position on eye-hand alignment, and then consider how head orientation influences the linkage between oculocentric visual frames and bodycentric motor frames. These findings are framed in terms of our 'conversion-on-demand' model, which suggests a virtual representation of egocentric space, i.e. one in which only those representations selected for action are put through the complex visuomotor transformations required for interaction with actual objects in personal space.

Arm↗
PubMed2002

Role of eye, head, and shoulder geometry in the planning of accurate arm movements.

Eye-hand coordination requires the brain to integrate visual information with the continuous changes in eye, head, and arm positions. This is a geometrically complex process because the eyes, head, and shoulder have different centers of rotation. As a result, head rotation causes the eye to translate with respect to the shoulder. The present study examines the consequences of this geometry for planning accurate arm movements in a pointing task with the head at different orientations. When asked to point at an object, subjects oriented their arm to position the fingertip on the line running from the target to the viewing eye. But this eye-target line shifts when the eyes translate with each new head orientation, thereby requiring a new arm pointing direction. We confirmed that subjects do realign their fingertip with the eye-target line during closed-loop pointing across various horizontal head orientations when gaze is on target. More importantly, subjects also showed this head-position-dependent pattern of pointing responses for the same paradigm performed in complete darkness. However, when gaze was not on target, compensation for these translations in the rotational centers partially broke down. As a result, subjects tended to overshoot the target direction relative to current gaze; perhaps explaining previously reported errors in aiming the arm to retinally peripheral targets. These results suggest that knowledge of head position signals and the resulting relative displacements in the centers of rotation of the eye and shoulder are incorporated using open-loop mechanisms for eye-hand coordination, but these translations are best calibrated for foveated, gaze-on-target movements.

Adult↗