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& The representations that mediate the coding of spatial position were examined by comparing the behavior of patients with left hemispatial neglect with that of nonneurological control subjects. To determine the spatial coordinate system(s) used to define ‘‘left’ ’ and ‘‘right,’ ’ eye movements were measured for targets that appeared at 58, 108, and 158 to the relative left or right defined with respect to the midline of the eyes, head, or midsaggital plane of the trunk. In the baseline condition, in which the various egocentric midlines were all aligned with the environmental midline, patients were disproportionately slower at initiating saccades to left than right targets, relative to the controls. When either the trunk or the head was rotated and the midline aligned with the most peripheral position while the eyes remained aligned with the midline of the environment, the results did not differ from the baseline condition. However, when the eyes were rotated and the midline aligned with the peripheral position, saccadic reaction time (SRT) differed significantly from the baseline, especially when the eyes were rotated to the right. These findings suggest that target position is coded relative to the current position of gaze (oculocentrically) and that this eyecentered coding is modulated by orbital position (eye-in-head signal). The findings dovetail well with results from existing neurophysiological studies and shed further light on the spatial representations mediated by the human parietal cortex. &

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Humans build representations of objects and their locations by integrating imperfect information from multiple perceptual modalities (e.g., visual, haptic). Since sensory information is specified in different frames of reference (i.e. eye- and body-centered), it must be remapped into a common coordinate frame before integration and storage in memory. Such transformations require an understanding of body articulation, which is estimated through noisy sensory data. Consequently, target information acquires additional coordinate transformation uncertainty (CTU) during remapping due to errors in joint angle sensing. As a result, CTU creates differences in the reliability of target information depending on the reference frame used for storage. This paper explores whether the brain represents and compensates for CTU when making grasping movements. To address this question, we varied eye position in the head, while participants reached to grasp a spatially fixed object, both when the object was in view and when it was occluded. Varying eye position changes CTU between eye and head, producing additional uncertainty in remapped information away from forward view. The results demonstrate that people adjust their maximum grip aperture to compensate both for changes in visual information and for changes in CTU when the target is occluded. Moreover, the amount of compensation is predicted by a Bayesian model for location inference that employs eye-centered storage.

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 hand-held object locations for saccades, and what intrinsic coordinate system(s) are used in this transformation. We measured radial saccades beginning from a central light-emitting diode to sixteen target locations arranged peripherally in eight directions and two eccentricities on a horizontal plane in front of subjects. Target locations were either indicated by 1) a visual flash, 2) by subject actively moving the hand-held central target to a peripheral location, 3) by the experimenter passively moving the subject’s hand, 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, while 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

The study of capabilities a perceptual system can acquire from systematic exposure to sensorimotor correlations, i.e. the regular co-occurrence of motor patterns and sensory states, has become a major research trend in current cognitive science. Defendants of the sensorimotor approach have claimed that the study of sensorimotor learning can provide a coherent and parsimonious framework for understanding how specific perceptual capabilities are acquired and used. Yet, lacking a solid characterization of key theoretical notions like ‘sensorimotor invariant’, these alternative approaches can hardly provide more accurate explanations than those of mainstream perceptual research. In this paper, we fix a number of general constraints that any sensorimotor theory must meet in order to provide a valid alternative to traditional models. By focusing on the case-study of spatial competence, i.e. what knowledge a system must possess in order to behave spatially, we address the issue of what distinguishes sensorimotor theories from traditional approaches. We show how, in the case of spatial cognition, the sensorimotor approach can provide a viable and promising scientific programme for explaining the acquisition and use of

In this paper, we present a case study showing why the modeling effort of computational neuro-sciences must call upon interactions with an environment when developmental phenomena are investigated. More specifically, in the context of a model of the spatial organization of a repertoire of postures, we show that calling upon a realistic simulation of the human kinematics (i) results in raising the question of the nature of information encoded in this repertoire; and (ii) reveals that some previous assumptions about the functional organization of this repertoire were not necessary. Finally, we point out that conversely, robotics can benefit from such studies by using the suggested principles to design more adaptive control architectures.