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Research conducted by the Sensorimotor Research Group at the German Primate Center sheds light on how the brain manages movement under conditions of visual uncertainty. Published in Nature Communications, the study used rhesus monkeys to explore how varying types of visual uncertainty affect movement precision.
Consider the scenario of reaching for a glass of water in a dimly lit room. In such situations, the brain must rely on estimations of both the glass's location and the position of the hand, which can lead to imprecise movements due to unclear visual cues. This study aims to dissect the brain's response to two forms of uncertainty: target uncertainty and feedback uncertainty.
In the experiment, monkeys were tasked with controlling a cursor on a screen using a joystick. The researchers manipulated the visual environment to create two types of uncertainty. The first type, target uncertainty, involved presenting the target as multiple scattered objects, making it difficult for the monkeys to pinpoint the exact target location. The second type, feedback uncertainty, involved obscuring the cursor's position with scattered small objects, complicating the monkeys' awareness of their hand's location.
Additionally, the study examined how feedback uncertainty impacted the monkeys when they controlled the cursor through a brain-computer interface (BCI). In this setup, the monkeys relied solely on visual feedback to gauge their movements, unlike natural arm movements, which are guided by a combination of sensory inputs.
The findings indicate that the brain's response to uncertainty differs based on its type. Target uncertainty primarily influences the planning phase and initiation of movement, resulting in less precise movements right from the start, as evidenced by the motor cortex's neuronal activity. In contrast, feedback uncertainty mainly affected movement execution, particularly when the monkeys depended entirely on visual feedback, as seen during BCI usage.
The research team discovered that the motor cortex reflects both types of uncertainty, yet these are processed in separate phases of movement control. This suggests that the brain integrates information about the target and the hand's position at different stages of the movement process.
These insights are particularly relevant for improving brain-computer interfaces, which allow paralyzed individuals to control devices with their thoughts. Since BCI users rely heavily on visual feedback, they may be more vulnerable to inaccuracies in their perception of movement. The integration of additional sensory signals, such as tactile feedback through vibration motors, may enhance the precision and intuitiveness of neuroprosthetic control.
According to the researchers, the ability of the brain to compensate for uncertainties when provided with alternative information sources is crucial for advancing BCI technology. By incorporating supplementary sensory stimuli, it may be possible to improve the control of neuroprosthetics for individuals with motor impairments.
This study advances the understanding of how the brain navigates sensory uncertainty, paving the way for the development of technologies aimed at assisting those with movement disabilities.
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