The role of visual processing on tactile suppression

How visuomotor predictability and task demands affect tactile sensitivity on a moving limb during object interaction in a virtual environment

Tactile sensitivity is decreased on a moving limb compared to the same static limb. This tactile suppression likely reflects an interplay between sensorimotor predictions and sensory feedback. Here, we examined how visuomotor predictability influences tactile suppression. Participants were instructed to hit an approaching virtual object, with the object either never rotating, or always rotating, or rotating unpredictably, prompting related movement adjustments. We probed tactile suppression by delivering a vibrotactile stimulus of varying intensities to the moving hand briefly after the object's rotation and asked participants to indicate if they had felt a vibration. We hypothesized that Unpredictable Rotations would require upweighting of somatosensory feedback from the hand and therefore decrease suppression. Instead, we found stronger suppression with unpredictable than Predictable Rotations. This finding persisted even when visual input from the moving hand was removed and participants had to rely solely on somatosensory feedback of their hand. Importantly, we found a correlation between task demand and tactile suppression in both experiments, indicating that task load can amplify tactile suppression, possibly by downweighting task-irrelevant somatosensory feedback signals to allow for successful task performance when visuomotor task demands are high.

Sensorimotor memories influence movement kinematics but not associated tactile processing

When interacting with objects, we often rely on visual information. However, vision is not always the most reliable sense for determining relevant object properties. For example, when the mass distribution of an object cannot be inferred visually, humans may rely on predictions about the object's dynamics. Such predictions may not only influence motor behavior but also associated processing of movement-related afferent information, leading to reduced tactile sensitivity during movement. We examined whether predictions based on sensorimotor memories influence grasping kinematics and associated tactile processing. Participants lifted an object of unknown mass distribution and reported whether they detected a tactile stimulus on their grasping hand during the lift. In Experiment 1, the mass distribution could change from trial to trial, whereas in Experiment 2, we intermingled longer with shorter parts of constant and variable mass distributions, while also providing implicit or explicit information about the trial structure. In both experiments, participants grasped the object by predictively choosing contact points that would compensate the mass distribution experienced in the previous trial. Tactile suppression during movement, however, was invariant across conditions. These results suggest that predictions based on sensorimotor memories can influence movement kinematics but not associated tactile perception.

A Survey of Multifingered Robotic Manipulation: Biological Results, Structural Evolvements, and Learning Methods

Multifingered robotic hands (usually referred to as dexterous hands) are designed to achieve human-level or human-like manipulations for robots or as prostheses for the disabled. The research dates back 30 years ago, yet, there remain great challenges to effectively design and control them due to their high dimensionality of configuration, frequently switched interaction modes, and various task generalization requirements. This article aims to give a brief overview of multifingered robotic manipulation from three aspects: a) the biological results, b) the structural evolvements, and c) the learning methods, and discuss potential future directions. First, we investigate the structure and principle of hand-centered visual sensing, tactile sensing, and motor control and related behavioral results. Then, we review several typical multifingered dexterous hands from task scenarios, actuation mechanisms, and in-hand sensors points. Third, we report the recent progress of various learning-based multifingered manipulation methods, including but not limited to reinforcement learning, imitation learning, and other sub-class methods. The article concludes with open issues and our thoughts on future directions.

Linking Signal Relevancy and Intensity in Predictive Tactile Suppression

Predictable somatosensory feedback leads to a reduction in tactile sensitivity. This phenomenon, called tactile suppression, relies on a mechanism that uses an efference copy of motor commands to help select relevant aspects of incoming sensory signals. We investigated whether tactile suppression is modulated by (a) the task-relevancy of the predicted consequences of movement and (b) the intensity of related somatosensory feedback signals. Participants reached to a target region in the air in front of a screen; visual or tactile feedback indicated the reach was successful. Furthermore, tactile feedback intensity (strong vs. weak) varied across two groups of participants. We measured tactile suppression by comparing detection thresholds for a probing vibration applied to the finger either early or late during reach and at rest. As expected, we found an overall decrease in late-reach suppression, as no touch was involved at the end of the reach. We observed an increase in the degree of tactile suppression when strong tactile feedback was given at the end of the reach, compared to when weak tactile feedback or visual feedback was given. Our results suggest that the extent of tactile suppression can be adapted to different demands of somatosensory processing. Downregulation of this mechanism is invoked only when the consequences of missing a weak movement sequence are severe for the task. The decisive factor for the presence of tactile suppression seems not to be the predicted action effect as such, but the need to detect and process anticipated feedback signals occurring during movement.

Dynamic temporal modulation of somatosensory processing during reaching

Sensorimotor control of human action integrates feedforward policies that predict future body states with online sensory feedback. These predictions lead to a suppression of the associated feedback signals. Here, we examine whether somatosensory processing throughout a goal-directed movement is constantly suppressed or dynamically tuned so that online feedback processing is enhanced at critical moments of the movement. Participants reached towards their other hand in the absence of visual input and detected a probing tactile stimulus on their moving or static hand. Somatosensory processing on the moving hand was dynamically tuned over the time course of reaching, being hampered in early and late stages of the movement, but, interestingly, recovering around the time of maximal speed. This novel finding of temporal somatosensory tuning was further corroborated in a second experiment, in which larger movement amplitudes shifted the absolute time of maximal speed later in the movement. We further show that the release from suppression on the moving limb was temporally coupled with enhanced somatosensory processing on the target hand. We discuss these results in the context of optimal feedforward control and suggest that somatosensory processing is dynamically tuned during the time course of reaching by enhancing sensory processing at critical moments of the movement.

The influence of afferent input on somatosensory suppression during grasping

The processing of somatosensory information is hampered on a moving limb. This suppression has been widely attributed to sensorimotor predictions that suppress the associated feedback, though postdictive mechanisms are also involved. Here, we investigated the extent to which suppression on a limb is influenced by backward somatosensory signals, such as afferents associated with forces that this limb applies. Participants grasped and lifted objects of symmetric and asymmetric mass distributions using a precision grip. We probed somatosensory processing at the moment of the grasp by presenting a vibrotactile stimulus either on the thumb or index finger and asked participants to report if they felt this stimulus. Participants applied greater forces with the thumb and index finger for objects loaded to the thumb’s or index finger’s endpoint, respectively. However, suppression was not influenced by the different applied forces. Suppression on the digits remained constant both when grasping heavier objects, and thus applying even greater forces, and when probing suppression on the skin over the muscle that controlled force application. These results support the idea that somatosensory suppression is predictive in nature while backward masking may only play a minor role in somatosensory processing on the moving hand, at least in this context.

Age effects on sensorimotor predictions: What drives increased tactile suppression during reaching?

Tactile suppression refers to the phenomenon that tactile signals are attenuated during movement planning and execution when presented on a moving limb compared to rest. It is usually explained in the context of the forward model of movement control that predicts the sensory consequences of an action. Recent research suggests that aging increases reliance on sensorimotor predictions resulting in stronger somatosensory suppression. However, the mechanisms contributing to this age effect remain to be clarified. We measured age-related differences in tactile suppression during reaching and investigated the modulation by cognitive processes. A total of 23 younger (18-27 years) and 26 older (59-78 years) adults participated in our study. We found robust suppression of tactile signals when executing reaching movements. Age group differences corroborated stronger suppression in old age. Cognitive task demands during reaching, although overall boosting suppression effects, did not modulate the age effect. Across age groups, stronger suppression was associated with lower individual executive capacities. There was no evidence that baseline sensitivity had a prominent impact on the magnitude of suppression. We conclude that aging alters the weighting of sensory signals and sensorimotor predictions during movement control. Our findings suggest that individual differences in tactile suppression are critically driven by executive functions.