Updating of visual orientation in a gravity-based reference frame.

The brain can use multiple reference frames to code line orientation, including head-, object-, and gravity-centered references. If these frames change orientation, their representations must be updated to keep register with actual line orientation. We tested this internal updating during head rotation in roll, exploiting the rod-and-frame effect: The illusory tilt of a vertical line surrounded by a tilted visual frame. If line orientation is stored relative to gravity, these distortions should also affect the updating process. Alternatively, if coding is head- or frame-centered, updating errors should be related to the changes in their orientation. Ten subjects were instructed to memorize the orientation of a briefly flashed line, surrounded by a tilted visual frame, then rotate their head, and subsequently judge the orientation of a second line relative to the memorized first while the frame was upright. Results showed that updating errors were mostly related to the amount of subjective distortion of gravity at both the initial and final head orientation, rather than to the amount of intervening head rotation. In some subjects, a smaller part of the updating error was also related to the change of visual frame orientation. We conclude that the brain relies primarily on a gravity-based reference to remember line orientation during head roll.

Predictive mechanisms in the control of contour following.

In haptic exploration, when running a fingertip along a surface, the control system may attempt to anticipate upcoming changes in curvature in order to maintain a consistent level of contact force. Such predictive mechanisms are well known in the visual system, but have yet to be studied in the somatosensory system. Thus, the present experiment was designed to reveal human capabilities for different types of haptic prediction. A robot arm with a large 3D workspace was attached to the index fingertip and was programmed to produce virtual surfaces with curvatures that varied within and across trials. With eyes closed, subjects moved the fingertip around elliptical hoops with flattened regions or Limaçon shapes, where the curvature varied continuously. Subjects anticipated the corner of the flattened region rather poorly, but for the Limaçon shapes, they varied finger speed with upcoming curvature according to the two-thirds power law. Furthermore, although the Limaçon shapes were randomly presented in various 3D orientations, modulation of contact force also indicated good anticipation of upcoming changes in curvature. The results demonstrate that it is difficult to haptically anticipate the spatial location of an abrupt change in curvature, but smooth changes in curvature may be facilitated by anticipatory predictions.

Time-integrated position error accounts for sensorimotor behavior in time-constrained tasks.

Several studies have shown that human motor behavior can be successfully described using optimal control theory, which describes behavior by optimizing the trade-off between the subject's effort and performance. This approach predicts that subjects reach the goal exactly at the final time. However, another strategy might be that subjects try to reach the target position well before the final time to avoid the risk of missing the target. To test this, we have investigated whether minimizing the control effort and maximizing the performance is sufficient to describe human motor behavior in time-constrained motor tasks. In addition to the standard model, we postulate a new model which includes an additional cost criterion which penalizes deviations between the position of the effector and the target throughout the trial, forcing arrival on target before the final time. To investigate which model gives the best fit to the data and to see whether that model is generic, we tested both models in two different tasks where subjects used a joystick to steer a ball on a screen to hit a target (first task) or one of two targets (second task) before a final time. Noise of different amplitudes was superimposed on the ball position to investigate the ability of the models to predict motor behavior for different levels of uncertainty. The results show that a cost function representing only a trade-off between effort and accuracy at the end time is insufficient to describe the observed behavior. The new model correctly predicts that subjects steer the ball to the target position well before the final time is reached, which is in agreement with the observed behavior. This result is consistent for all noise amplitudes and for both tasks.

Visuomotor coordination is different for different directions in three-dimensional space.

In most visuomotor tasks in which subjects have to reach to visual targets or move the hand along a particular trajectory, eye movements have been shown to lead hand movements. Because the dynamics of vergence eye movements is different from that of smooth pursuit and saccades, we have investigated the lead time of gaze relative to the hand for the depth component (vergence) and in the frontal plane (smooth pursuit and saccades) in a tracking task and in a tracing task in which human subjects were instructed to move the finger along a 3D path. For tracking, gaze leads finger position on average by 28 ± 6 ms (mean ± SE) for the components in the frontal plane but lags finger position by 95 ± 39 ms for the depth dimension. For tracing, gaze leads finger position by 151 ± 36 ms for the depth dimension. For the frontal plane, the mean lead time of gaze relative to the hand is 287 ± 13 ms. However, we found that the lead time in the frontal plane was inversely related to the tangential velocity of finger. This inverse relation for movements in the frontal plane could be explained by assuming that gaze leads the finger by a constant distance of ∼ 2.6 cm (range of 1.5-3.6 cm across subjects).

Modeling zinc regulation in small mammals.

Due to large zinc discharges into the global environment, both terrestrial and aquatic environments have been polluted with zinc. The embanked floodplains of the lower Rhine River in the Netherlands contain large amounts of heavy metals, including zinc. These large amounts of heavy metals may pose risks to flora and fauna by accumulation in food webs, and risk assessment may be required. However, toxicokinetic models for zinc metabolism in mammalian wildlife species are currently lacking. The present study describes the development of a zinc kinetics model that predicts internal zinc concentrations in small mammals by modeling zinc absorption and excretion dependent on the dietary zinc intake using adapted Michaelis-Menten equations. The equations were parameterized based on experimental data reported in the scientific literature. Within the dietary zinc range of 3 to 104 mg/kg dry weight, the model predicts internal zinc concentrations and shows that the internal zinc is regulated within this range. Outside this range, the model could not be calibrated due to a lack of data. Validation of the model with four small mammal species living in an embanked floodplain along a distributary of the Rhine River illustrated that the model predicts internal zinc concentrations differing up to a factor of 1.6 (Common shrew) to 1.7 (Common vole) from field measurements.