Lift observation conveys object weight distribution but partly enhances predictive lift planning

Observation of object lifting allows updating of internal object representations for object weight, in turn enabling accurate scaling of fingertip forces when lifting the same object. Here, we investigated whether lift observation also enables updating of internal representations for an object's weight distribution. We asked participants to lift an inverted T-shaped manipulandum, of which the weight distribution could be changed, in turns with an actor. Participants were required to minimize object roll (i.e. 'lift performance') during lifting and were allowed to place their fingertips at self-chosen locations. The center of mass changed unpredictably every third to sixth trial performed by the actor and participants were informed that they would always lift the same weight distribution as the actor. Participants observed either erroneous (i.e. object rolling towards its heavy side) or skilled (i.e. minimized object roll) lifts. Lifting performance after observation was compared to lifts without prior observation and to lifts after active lifting, which provided haptic feedback about the weight distribution. Our results show that observing both skilled and erroneous lifts convey an object's weight distribution similar to active lifting, resulting in altered digit positioning strategies. However, minimizing object roll on novel weight distributions was only improved after observing error lifts and not after observing skilled lifts. In sum, these findings suggest that although observing motor errors and skilled motor performance enables updating of digit positioning strategy, only observing error lifts enables changes in predictive motor control when lifting objects with unexpected weight distributions.

Role of Post-Trial Visual Feedback on Unintentional Force Drift During Isometric Finger Force Production Tasks

A reduction in fingertip forces during a visually occluded isometric task is called unintentional drift. In this study, unintentional drift was studied for two conditions, with and without “epilogue.” We define epilogue as the posttrial visual feedback in which the outcome of the just-concluded trial is shown before the start of the next trial. For this study, 14 healthy participants were recruited and were instructed to produce fingertip forces to match a target line at 15% maximum voluntary contraction. The results showed a significant reduction in unintentional drift in the epilogue condition. This reduction is probably due to the difference in the shift in λ, the threshold of the tonic stretch reflex, the hypothetical control variable that the central controller can set.

Lift observation conveys object weight distribution but partly enhances predictive lift planning

Observation of object lifting allows updating of internal object representations for object weight, in turn enabling accurate scaling of fingertip forces when lifting the same object. Here, we investigated whether lift observation also enables updating of internal representations for an object’s weight distribution. We asked participants to lift an inverted T-shaped manipulandum, of which the weight distribution could be changed, in turns with an actor. Participants were required to minimize object roll (i.e. ‘lift performance’) during lifting and were allowed to place their fingertips at self-chosen locations. The center of mass changed unpredictably every third to sixth trial performed by the actor and participants were informed that they would always lift the same weight distribution as the actor. Participants observed either erroneous (i.e. object rolling towards its heavy side) or skilled (i.e. minimized object roll) lifts. Lifting performance after observation was compared to lifts without prior observation and to lifts after active lifting, which provided haptic feedback about the weight distribution. Our results show that observing both skilled and erroneous lifts convey an object’s weight distribution similar to active lifting, resulting in altered digit positioning strategies. However, minimizing object roll on novel weight distributions was only improved after observing error lifts and not after observing skilled lifts. In sum, these findings suggest that although observing motor errors and skilled motor performance enables updating of digit positioning strategy, only observing error lifts enables changes in predictive motor control when lifting objects with unexpected weight distributions.New and noteworthyIndividuals are able to extract an object’s size and weight by observing interactions with objects and subsequently integrate this information in their own motor repertoire. Here, we show that this ability extrapolates to weight distributions. Specifically, we highlighted that individuals can perceive an object’s weight distribution during lift observation but can only partially embody this information when planning their own actions.

Overt and Covert Object Features Mediate Timing of Patterned Brain Activity during Motor Planning

Humans are seamless in their ability to efficiently and reliably generate fingertip forces to gracefully interact with objects. Such interactions rarely end in awkward outcomes like spilling, crushing, or tilting given advanced motor planning. Here we combine multiband imaging with deconvolution- and Bayesian pattern component modeling of functional magnetic resonance imaging data and in-scanner kinematics, revealing compelling evidence that the human brain differentially represents preparatory information for skillful object interactions depending on the saliency of visual cues. Earlier patterned activity was particularly evident in ventral visual processing stream-, but also selectively in dorsal visual processing stream and cerebellum in conditions of heightened uncertainty when an object’s superficial shape was incompatible rather than compatible with a key underlying object feature.

Estimating Fingertip Forces, Torques, and Local Curvatures from Fingernail Images

SUMMARYThe study of dexterous manipulation has provided important insights into human sensorimotor control as well as inspiration for manipulation strategies in robotic hands. Previous work focused on experimental environment with restrictions. Here, we describe a method using the deformation and color distribution of the fingernail and its surrounding skin to estimate the fingertip forces, torques, and contact surface curvatures for various objects, including the shape and material of the contact surfaces and the weight of the objects. The proposed method circumvents limitations associated with sensorized objects, gloves, or fixed contact surface type. In addition, compared with previous single finger estimation in an experimental environment, we extend the approach to multiple finger force estimation, which can be used for applications such as human grasping analysis. Four algorithms are used, c.q., Gaussian process, convolutional neural networks, neural networks with fast dropout, and recurrent neural networks with fast dropout, to model a mapping from images to the corresponding labels. The results further show that the proposed method has high accuracy to predict force, torque, and contact surface.

Musculoskeletal models of a human and bonobo finger: parameter identification and comparison to in vitro experiments

Introduction Knowledge of internal finger loading during human and non-human primate activities such as tool use or knuckle-walking has become increasingly important to reconstruct the behaviour of fossil hominins based on bone morphology. Musculoskeletal models have proven useful for predicting these internal loads during human activities, but load predictions for non-human primate activities are missing due to a lack of suitable finger models. The main goal of this study was to implement both a human and a representative non-human primate finger model to facilitate comparative studies on metacarpal bone loading. To ensure that the model predictions are sufficiently accurate, the specific goals were: (1) to identify species-specific model parameters based on in vitro measured fingertip forces resulting from single tendon loading and (2) to evaluate the model accuracy of predicted fingertip forces and net metacarpal bone loading in a different loading scenario. Materials & Methods Three human and one bonobo (Pan paniscus) fingers were tested in vitro using a previously developed experimental setup. The cadaveric fingers were positioned in four static postures and load was applied by attaching weights to the tendons of the finger muscles. For parameter identification, fingertip forces were measured by loading each tendon individually in each posture. For the evaluation of model accuracy, the extrinsic flexor muscles were loaded simultaneously and both the fingertip force and net metacarpal bone force were measured. The finger models were implemented using custom Python scripts. Initial parameters were taken from literature for the human model and own dissection data for the bonobo model. Optimized model parameters were identified by minimizing the error between predicted and experimentally measured fingertip forces. Fingertip forces and net metacarpal bone loading in the combined loading scenario were predicted using the optimized models and the remaining error with respect to the experimental data was evaluated. Results The parameter identification procedure led to minor model adjustments but considerably reduced the error in the predicted fingertip forces (root mean square error reduced from 0.53/0.69 N to 0.11/0.20 N for the human/bonobo model). Both models remained physiologically plausible after the parameter identification. In the combined loading scenario, fingertip and net metacarpal forces were predicted with average directional errors below 6° and magnitude errors below 12%. Conclusions This study presents the first attempt to implement both a human and non-human primate finger model for comparative palaeoanthropological studies. The good agreement between predicted and experimental forces involving the action of extrinsic flexors—which are most relevant for forceful grasping—shows that the models are likely sufficiently accurate for comparisons of internal loads occurring during human and non-human primate manual activities.

The observation of explicit and implicit visuomotor cues can drive predictive motor control

Recent studies have highlighted that the observation of hand-object interactions can influence perceptual weight judgements made by an observer. Moreover, observing explicit motor errors during object lifting allows individuals to update their internal sensorimotor representation about object weight. Embodying observed visuomotor cues for the planning of a motor command further enables individuals to accurately scale their fingertip forces when subsequently lifting the same object. However, it is still unknown whether observation of a skilled lift is equally able to mediate predictive motor control in the observer. Here, we tested this hypothesis by asking participants to grasp and lift a manipulandum after observing an actor’s lift. The object weight changed unpredictably (light or heavy) every third to sixth trial performed by the actor. Participants were informed that they would always lift the same weight as the actor and that, based on the experimental condition, they would have to observe skilled or erroneously performed lifts. Our results revealed that the observation of both skilled and erroneously performed lifts allows participants to update their internal sensorimotor object representation, in turn enabling them to predict force scaling accurately. These findings suggest that the observation of explicit as well as implicit visuomotor cues are embodied in the observer’s motor repertoire and can drive changes in predictive motor control.