Neural Evidence of Hierarchical Cognitive Control during Haptic Processing: An fMRI Study

Interacting with our immediate surroundings requires constant manipulation of objects. Dexterous manipulation depends on comparison between actual and predicted sensory input, with these predictions calculated by means of lower- and higher-order corollary discharge signals. However, there is still scarce knowledge about the hierarchy in the neural architecture supporting haptic monitoring during manipulation. The present study aimed to assess this issue focusing on the cross talk between lower- order sensory and higher-order associative regions. We used functional magnetic resonance imaging in humans during a haptic discrimination task in which participants had to judge whether a touched shape or texture corresponded to an expected stimulus whose name was previously presented. Specialized haptic regions identified with an independent localizer task did not differ between expected and unexpected conditions, suggesting their lack of involvement in tactile monitoring. When presented stimuli did not match previous expectations, the left supramarginal gyrus (SMG), middle temporal, and medial prefrontal cortices were activated regardless of the nature of the haptic mismatch (shape/texture). The left primary somatosensory area (SI) responded differently to unexpected shapes and textures in line with a specialized detection of haptic mismatch. Importantly, connectivity analyses revealed that the left SMG and SI were more functionally coupled during unexpected trials, emphasizing their interaction. The results point for the first time to a hierarchical organization in the neural substrates underlying haptic monitoring during manipulation with the SMG as a higher-order hub comparing actual and predicted somatosensory input, and SI as a lower- order site involved in the detection of more specialized haptic mismatch

Experimental Evaluation of the Projection-based Force Reflection Algorithms for Haptic Interaction with Virtual Environment

Haptic interaction with virtual environments is currently a major and growing area of research with a number of emerging applications, particularly in the field of robotics. Digital implementation of the virtual environments, however, introduces errors which may result in instability of the haptic displays. This thesis deals with experimental investigation of the Projection-Based Force Reflection Algorithms (PFRAs) for haptic interaction with virtual environments, focusing on their performance in terms of stability and transparency. Experiments were performed to compare the PFRA in terms of performance for both non-delayed and delayed haptic interactions with more conventional haptic rendering methods, such as the Virtual Coupling (VC) and Wave Variables (WV). The results demonstrated that the PFRA is more stable, guarantees higher levels of transparency, and is less sensitive to decrease in update rates

Touching is believing: creating illusions and feeling of embodiment with mid-air haptic technology

Over the last two decades, the sense of touch has received new attention from the scientific community.Several haptic devices have been developed to address the complexity of the sense of touch, the latest addition being mid-air (contactless) haptic technology. An interesting series of previous research has suggested an easier way to tackle the complexity of designing convincing tactile sensations by exploiting tactile illusions. Tactile illusions rely on perceptual shortcuts based on the psychophysics of the tactile receptors. Currently, studies exploring the perceptual space of mid-air haptics and its applicability in the tactile illusions field are still limited in number. This thesis aims to contribute to the field of Human-Computer Interaction (HCI) by investigating the perceptual design space of ultrasonic mid-air haptics technology. Specifically, in a first set of three studies, we investigate the absolute thresholds (minimal amount of a property of astimulus that a user can detect) for control points (CP) at different frequencies on the hand and arm (Study 1). Then we investigate the optimal sampling rate needed to drive the device in an optimal fashion and its relationship with shape size (Study 2). Next, we apply a new technique to increase users’ performance in a shape discrimination task (Study 3). In Study 4, we start the exploration of a tactile illusion of movement using contact touch and later, we apply a similar procedure to investigate the feasibility of creating a tactile illusion of movement between the two non-interconnected hands by using mid-air touch (Study 5). Finally, in Study 6, we explore our sense of touch in VR, while providing an illusion of rain drops through mid-air haptics, to recreate a virtual hand illusion (VHI) to explore the boundaries of our sense of embodiment. Therefore, the contribution of this work is threefold: a) we contribute by adding new knowledge on the psychophysical space for mid-air haptics, b) we test the potential to create realistic tactile sensations by exploiting tactile illusions with mid-air haptic technology, and c) we demonstrate how tactile illusions mediated by mid-air haptics can convey a sense of embodiment in VR environments

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Human adaptive haptic sensing

How do humans physically interact with the environment or with other humans? It is well known that the nervous system can modify the body’s stiffness by selectively cocontracting muscles to shape the mechanical interaction with the environment, but how this influences haptic perception is not known. This thesis examines whether humans can adapt muscles’ activation to influence their perception of the physical interaction with the environment. This question is investigated by conducting behavioural experiments using dedicated robotic interfaces to study sensorimotor interactions in the presence of haptic and visual perturbations. Hypotheses about the underlying mechanism are then tested through mathematical modelling and simulations. Chapter 1 reviews related frameworks and introduces the most relevant questions addressed in this work. Chapter 2 then shows that the central nervous system (CNS) can voluntarily adapt muscle cocontraction to increase haptic sensitivity. In an experiment, participants tracked a randomly moving target with visual noise while being physically guided by a virtual elastic band, where the band’s stiffness was controlled by their muscle coactivation. The results show that participants learned to increase cocontraction with visual noise and decrease it when the guidance is incongruent with the visual target. The adaptation law governing the regulation of the body’s stiffness by the CNS is then derived through computational modelling. This model is designed to maximise visuo-haptic information while minimising metabolic cost, thus trading off sensory information with energy. Further, it is shown in Chapter 3 that when the subjects are coupled via a tuneable connection to a robotic guidance designed to hinder their tracking through perturbations at the turning points (where participants physiologically increase cocontraction), they adapted cocontraction to reduce the impact of perturbations on performance. These results highlight the CNS ability to modify the muscle activation patterns to improve performance with minimal effort. Chapter 4 tests the robustness of human adaptive haptic sensing introduced in the previous chapters for human-human physical interaction. For example, in tango dancing physical contact provides haptic information of the partner’s action required to coordinate the movements. During such physical interactions, should one keep the arms compliant so that the partner can correct the motion, or should one stiffen them to better keep along the planned movement? Using a tracking task in which a dyad is coupled via a rigid connection, subjects readily adapted the compliance of their limb depending on both the accuracy of the partner’s and their own movement. The same computational model introduced in Chapter 2 could explain these results and predict the experimentally observed cocontraction adaptation. This suggests that the minimisation of prediction error and energy is a general principle also holding in interpersonal interactions. Altogether, these findings shed light on how humans can adapt haptic sensing by changing body properties, and propose a novel framework to interpret visuo-haptic perception for interaction with the environment and other humans.Open Acces

Abstracts from CIP 2007: Segundo Congreso Ibérico de Percepción

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The Effects of Age-related Differences in State Estimation on Sensorimotor Control of the Arm in School-age Children

Previous research examining sensorimotor control of arm movements in school-age children has demonstrated age-related improvements in performance. A unifying, mechanistic explanation of these improvements is currently lacking. This dissertation systematically examined the processes involved in sensorimotor control of the arm to investigate the hypothesis that improvements in performance can be attributed, in part, to developmental changes in state estimation, defined as estimates computed by the central nervous system (CNS) that specify current and future hand positions and velocities (i.e., hand `state'). A series of behavioral experiments were employed in which 5- to 12-year-old children and adults executed goal-directed arm movements. Experiment 1 demonstrated that improvements in proprioceptive functioning resulted in an increased contribution of proprioception to the multisensory estimate of hand position, suggesting that the CNS of children flexibly integrates redundant sensorimotor feedback based on the accuracy of the individual inputs. Experiment 2 demonstrated that improvements in proprioceptive functioning for localizing initial hand position reduced the directional variability of goal-directed reaching, suggesting that improvements in static state estimation contribute to the age-related improvements in performance. Relying on sensory feedback to provide estimates of hand state during movement execution can result in erroneous movement trajectories due to delays in sensory processing. Research in adults has suggested that the CNS circumvents these delays by integrating sensory feedback with predictions of future hand states (i.e., dynamic state estimation), a finding that has not been investigated in children. Experiment 3 demonstrated that young children utilized delayed and unreliable state estimates to make on-line trajectory modifications, resulting in poor sensorimotor performance. Last, Experiment 4 hypothesized that if improvements in state estimation drive improvements in sensorimotor performance, then exposure to a perturbation that simulated the delayed and unreliable dynamic state estimation in young children would cause the adults to perform similarly to the young children (i.e., eliminating age-related improvements in performance). Results from this study were equivocal. Collectively, the results from these experiments: 1) characterized a developmental trajectory of state estimation across 5- to 12-year-old children; and, 2) demonstrated that the development of state estimation is one mechanism underlying the age-related improvements in sensorimotor performance