SummaryThe human motor system is remarkably proficient in the online control of visually guided movements, adjusting to changes in the visual scene within 100 ms [1–3]. This is achieved through a set of highly automatic processes [4] translating visual information into representations suitable for motor control [5, 6]. For this to be accomplished, visual information pertaining to target and hand need to be identified and linked to the appropriate internal representations during the movement. Meanwhile, other visual information must be filtered out, which is especially demanding in visually cluttered natural environments. If selection of relevant sensory information for online control was achieved by visual attention, its limited capacity [7] would substantially constrain the efficiency of visuomotor feedback control. Here we demonstrate that both exogenously and endogenously cued attention facilitate the processing of visual target information [8], but not of visual hand information. Moreover, distracting visual information is more efficiently filtered out during the extraction of hand compared to target information. Our results therefore suggest the existence of a dedicated visuomotor binding mechanism that links the hand representation in visual and motor systems.

Goal-directed reaching movements are guided by visual feedback from both target and hand. The classical view is that the brain extracts information about target and hand positions from a visual scene, calculates a difference vector between them, and uses this estimate to control the movement. Here we show that during fast feedback control, this computation is not immediate, but evolves dynamically over time. Immediately after a change in the visual scene, the motor system generates independent responses to the errors in hand and target location. Only about 200 ms later, the changes in target and hand positions are combined appropriately in the response, slowly converging to the true difference vector. Therefore, our results provide evidence for the temporal evolution of spatial computations in the human visuomotor system, in which the accurate difference vector computation is first estimated by a fast approximation.

In visual suppression paradigms, transcranial magnetic stimulation (TMS) applied approximately 90 ms after visual stimulus presentation over occipital visual areas can robustly interfere with visual perception, thereby most likely affecting feedback activity from higher areas (Amassian VE, Cracco RQ, Maccabee PJ, Cracco JB, Rudell A, Eberle L. 1989. Suppression of visual perception by magnetic coil stimulation of human occipital cortex. Electroencephalogr Clin Neurophysiol 74:458-462.). It is speculated that the observed effects might stem primarily from the disruption of V1 activity. This hypothesis, although under debate, argues in favor of a special role of V1 in visual awareness. In this study, we combine TMS, functional magnetic resonance imaging, and calculation of the induced electric field to study the neural correlates of visual suppression. For parafoveal visual stimulation in the lower right half of the visual field, area V2d is shown to be the likely TMS target based on its anatomical location close to the skull surface. Furthermore, isolated stimulation of area V3 also results in robust visual suppression. Notably, V3 stimulation does not directly affect the feedback from higher visual areas that is relayed mainly via V2 to V1. These findings support the view that intact activity patterns in several early visual areas (rather than merely in V1) are likewise important for the perception of the stimulus.

The posterior parietal cortex (PPC) plays an important role in controlling voluntary movements by continuously integrating sensory information about body state and the environment. We tested which subregions of the PPC contribute to the processing of target- and body-related visual information while reaching for an object, using a reaching paradigm with 2 types of visual perturbation: displacement of the visual target and displacement of the visual feedback about the hand position. Initially, functional magnetic resonance imaging (fMRI) was used to localize putative target areas involved in online corrections of movements in response to perturbations. The causal contribution of these areas to online correction was tested in subsequent neuronavigated transcranial magnetic stimulation (TMS) experiments. Robust TMS effects occurred at distinct anatomical sites along the anterior intraparietal sulcus (aIPS) and the anterior part of the supramarginal gyrus for both perturbations. TMS over neighboring sites did not affect online control. Our results support the hypothesis that the aIPS is more generally involved in visually guided control of movements, independent of body effectors and nature of the visual information. Furthermore, they suggest that the human network of PPC subregions controlling goal-directed visuomotor processes extends more inferiorly than previously thought. Our results also point toward a good spatial specificity of the TMS effects.

Goal-directed movements are executed under the permanent supervision of the central nervous system, which continuously processes sensory afferents and triggers on-line corrections if movement accuracy seems to be compromised. For arm reaching movements, visual information about the hand plays an important role in this supervision, notably improving reaching accuracy. Here, we tested whether visual feedback of the hand affects the latency of on-line responses to an external perturbation when reaching for a visual target. Two types of perturbation were used: visual perturbation consisted in changing the spatial location of the target and kinesthetic perturbation in applying a force step to the reaching arm. For both types of perturbation, the hand trajectory and the electromyographic (EMG) activity of shoulder muscles were analysed to assess whether visual feedback of the hand speeds up on-line corrections. Without visual feedback of the hand, on-line responses to visual perturbation exhibited the longest latency. This latency was reduced by about 10% when visual feedback of the hand was provided. On the other hand, the latency of on-line responses to kinesthetic perturbation was independent of the availability of visual feedback of the hand. In a control experiment, we tested the effect of visual feedback of the hand on visual and kinesthetic two-choice reaction times -for which coordinate transformation is not critical. Two-choice reaction times were never facilitated by visual feedback of the hand. Taken together, our results suggest that visual feedback of the hand speeds up on-line corrections when the position of the visual target with respect to the body must be re-computed during movement execution. This facilitation probably results from the possibility to map hand-and target-related information in a common visual reference frame.