Improving spatial updating accuracy in absence of external feedback

Two Neural Circuits to Point Towards Home Position After Passive Body Displacements

A challenge in motor control research is to understand the mechanisms underlying the transformation of sensory information into arm motor commands. Here, we investigated these transformation mechanisms for movements whose targets were defined by information issued from body rotations in the dark (i.e., idiothetic information). Immediately after being rotated, participants reproduced the amplitude of their perceived rotation using their arm (Experiment 1). The cortical activation during movement planning was analyzed using electroencephalography and source analyses. Task-related activities were found in regions of interest (ROIs) located in the prefrontal cortex (PFC), dorsal premotor cortex, dorsal region of the anterior cingulate cortex (ACC) and the sensorimotor cortex. Importantly, critical regions for the cognitive encoding of space did not show significant task-related activities. These results suggest that arm movements were planned using a sensorimotor-type of spatial representation. However, when a 8 s delay was introduced between body rotation and the arm movement (Experiment 2), we found that areas involved in the cognitive encoding of space [e.g., ventral premotor cortex (vPM), rostral ACC, inferior and superior posterior parietal cortex (PPC)] showed task-related activities. Overall, our results suggest that the use of a cognitive-type of representation for planning arm movement after body motion is necessary when relevant spatial information must be stored before triggering the movement.

Causal inference for spatial constancy across whole body motion

The brain uses self-motion information to internally update egocentric representations of locations of remembered world-fixed visual objects. If a discrepancy is observed between this internal update and reafferent visual feedback, this could be either due to an inaccurate update or because the object has moved during the motion. To optimally infer the object's location it is therefore critical for the brain to estimate the probabilities of these two causal structures and accordingly integrate and/or segregate the internal and sensory estimates. To test this hypothesis, we designed a spatial updating task involving passive whole body translation. Participants, seated on a vestibular sled, had to remember the world-fixed position of a visual target. Immediately after the translation, the reafferent visual feedback was provided by flashing a second target around the estimated "updated" target location, and participants had to report the initial target location. We found that the participants' responses were systematically biased toward the position of the second target position for relatively small but not for large differences between the "updated" and the second target location. This pattern was better captured by a Bayesian causal inference model than by alternative models that would always either integrate or segregate the internally updated target location and the visual feedback. Our results suggest that the brain implicitly represents the posterior probability that the internally updated estimate and the visual feedback come from a common cause and uses this probability to weigh the two sources of information in mediating spatial constancy across whole body motion. NEW & NOTEWORTHY When we move, egocentric representations of object locations require internal updating to keep them in register with their true world-fixed locations. How does this mechanism interact with reafferent visual input, given that objects typically do not disappear from view? Here we show that the brain implicitly represents the probability that both types of information derive from the same object and uses this probability to weigh their contribution for achieving spatial constancy across whole body motion.