Rapid adaptation of multisensory integration in vestibular pathways

In sensorimotor integration, sensory input and motor output signals are combined to provide an internal estimate of the state of both the world and one's own body. Although a single perceptual and motor snapshot can provide information about the current state, computational models show that the state can be optimally estimated by a recursive process in which an internal estimate is maintained and updated by the current sensory and motor signals. These models predict that an internal state estimate is maintained or stored in the brain. Here we report a patient with a lesion of the superior parietal lobe who shows both sensory and motor deficits consistent with an inability to maintain such an internal representation between updates. Our findings suggest that the superior parietal lobe is critical for sensorimotor integration, by maintaining an internal representation of the body's state.

The ability to distinguish sensory signals that register unexpected events (exafference) from those generated by voluntary actions (reafference) during self-motion is essential for accurate perception and behavior. The cerebellum is most commonly considered in relation to its contributions to the fine tuning of motor commands and sensorimotor calibration required for motor learning. During unexpected motion, however, the sensory prediction errors that drive motor learning potentially provide a neural basis for the computation underlying the distinction between reafference and exafference. Recording from monkeys during voluntary and applied self-motion, we demonstrate that individual cerebellar output neurons encode an explicit and selective representation of unexpected self-motion by means of an elegant computation that cancels the reafferent sensory effects of self-generated movements. During voluntary self-motion, the sensory responses of neurons that robustly encode unexpected movement are canceled. Neurons with vestibular and proprioceptive responses to applied head and body movements are unresponsive when the same motion is self-generated. When sensory reafference and exafference are experienced simultaneously, individual neurons provide a precise estimate of the detailed time course of exafference. These results provide an explicit solution to the longstanding problem of understanding mechanisms by which the brain anticipates the sensory consequences of our voluntary actions. Specifically, by revealing a striking computation of a sensory prediction error signal that effectively distinguishes between the sensory consequences of self-generated and externally produced actions, our findings overturn the conventional thinking that the sensory errors coded by the cerebellum principally contribute to the fine tuning of motor activity required for motor learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

Astronauts returning from space flight and performing Earth-bound activities must rapidly transition from the microgravity-adapted sensorimotor state to that of Earth's gravity. The goal of the current study was to assess locomotor dysfunction and recovery of function after long-duration space flight using a test of functional mobility. Eighteen International Space Station crewmembers experiencing an average flight duration of 185 days performed the functional mobility test (FMT) pre-flight and post-flight. To perform the FMT, subjects walked at a self selected pace through an obstacle course consisting of several pylons and obstacles set up on a base of 10-cm-thick, medium-density foam for a total of six trials per test session. The primary outcome measure was the time to complete the course (TCC, in seconds). To assess the long-term recovery trend of locomotor function after return from space flight, a multilevel exponential recovery model was fitted to the log-transformed TCC data. All crewmembers exhibited altered locomotor function after space flight, with a median 48% increase in the TCC. From the fitted model we calculated that a typical subject would recover to 95% of his/her pre-flight level at approximately 15 days post-flight. In addition, to assess the early motor learning responses after returning from space flight, we modeled performance over the six trials during the first post-flight session by a similar multilevel exponential relation. We found a significant positive correlation between measures of long-term recovery and early motor learning (P < 0.001) obtained from the respective models. We concluded that two types of recovery processes influence an astronaut's ability to re-adapt to Earth's gravity environment. Early motor learning helps astronauts make rapid modifications in their motor control strategies during the first hours after landing. Further, this early motor learning appears to reinforce the adaptive realignment, facilitating re-adaptation to Earth's 1-g environment on return from space flight.