The self and the Bayesian brain: Testing probabilistic models of body ownership through a self-localization task

The Many Roles of Precision in Action

Active inference describes (Bayes-optimal) behaviour as being motivated by the minimisation of surprise of one's sensory observations, through the optimisation of a generative model (of the hidden causes of one's sensory data) in the brain. One of active inference's key appeals is its conceptualisation of precision as biasing neuronal communication and, thus, inference within generative models. The importance of precision in perceptual inference is evident-many studies have demonstrated the importance of ensuring precision estimates are correct for normal (healthy) sensation and perception. Here, we highlight the many roles precision plays in action, i.e., the key processes that rely on adequate estimates of precision, from decision making and action planning to the initiation and control of muscle movement itself. Thereby, we focus on the recent development of hierarchical, "mixed" models-generative models spanning multiple levels of discrete and continuous inference. These kinds of models open up new perspectives on the unified description of hierarchical computation, and its implementation, in action. Here, we highlight how these models reflect the many roles of precision in action-from planning to execution-and the associated pathologies if precision estimation goes wrong. We also discuss the potential biological implementation of the associated message passing, focusing on the role of neuromodulatory systems in mediating different kinds of precision.

Biases in hand perception are driven by somatosensory computations, not a distorted hand model

To sense and interact with objects in the environment, we effortlessly configure our fingertips at desired locations. It is therefore reasonable to assume that the underlying control mechanisms rely on accurate knowledge about the structure and spatial dimensions of our hand and fingers. This intuition, however, is challenged by years of research showing drastic biases in the perception of finger geometry.1,2,3,4,5 This perceptual bias has been taken as evidence that the brain's internal representation of the body's geometry is distorted,6 leading to an apparent paradox regarding the skillfulness of our actions.7 Here, we propose an alternative explanation of the biases in hand perception-they are the result of the Bayesian integration of noisy, but unbiased, somatosensory signals about finger geometry and posture. To address this hypothesis, we combined Bayesian reverse engineering with behavioral experimentation on joint and fingertip localization of the index finger. We modeled the Bayesian integration either in sensory or in space-based coordinates, showing that the latter model variant led to biases in finger perception despite accurate representation of finger length. Behavioral measures of joint and fingertip localization responses showed similar biases, which were well fitted by the space-based, but not the sensory-based, model variant. The space-based model variant also outperformed a distorted hand model with built-in geometric biases. In total, our results suggest that perceptual distortions of finger geometry do not reflect a distorted hand model but originate from near-optimal Bayesian inference on somatosensory signals.

Hierarchical and dynamic relationships between body part ownership and full-body ownership

What is the relationship between experiencing individual body parts and the whole body as one's own? We theorised that body part ownership is driven primarily by the perceptual binding of visual and somatosensory signals from specific body parts, whereas full-body ownership depends on a more global binding process based on multisensory information from several body segments. To examine this hypothesis, we used a bodily illusion and asked participants to rate illusory changes in ownership over five different parts of a mannequin's body and the mannequin as a whole, while we manipulated the synchrony or asynchrony of visual and tactile stimuli delivered to three different body parts. We found that body part ownership was driven primarily by local visuotactile synchrony and could be experienced relatively independently of full-body ownership. Full-body ownership depended on the number of synchronously stimulated parts in a nonlinear manner, with the strongest full-body ownership illusion occurring when all parts received synchronous stimulation. Additionally, full-body ownership influenced body part ownership for nonstimulated body parts, and skin conductance responses provided physiological evidence supporting an interaction between body part and full-body ownership. We conclude that body part and full-body ownership correspond to different processes and propose a hierarchical probabilistic model to explain the relationship between part and whole in the context of multisensory awareness of one's own body.

Temporal visuomotor synchrony induces embodiment towards an avatar with biomechanically impossible arm movements

Visuomotor synchrony in time and space induces a sense of embodiment towards virtual bodies experienced in first-person view using Virtual Reality (VR). Here, we investigated whether temporal visuomotor synchrony affects avatar embodiment even when the movements of the virtual arms are spatially altered from those of the user in a non-human-like manner. In a within-subjects design VR experiment, participants performed a reaching task controlling an avatar whose lower arms bent in inversed and biomechanically impossible directions from the elbow joints. They performed the reaching task using this "unnatural avatar" as well as a "natural avatar," whose arm movements and positions spatially matched the user. The reaching tasks were performed with and without a one second delay between the real and virtual movements. While the senses of body ownership and agency towards the unnatural avatar were significantly lower compared to those towards the natural avatar, temporal visuomotor synchrony did significantly increase the sense of embodiment towards the unnatural avatar as well as the natural avatar. These results suggest that temporal visuomotor synchrony is crucial for inducing embodiment even when the spatial match between the real and virtual limbs is disrupted with movements outside the pre-existing cognitive representations of the human body.

Feasibility and Validation of a Robotic-Based Multisensory Integration Assessment in Healthy Controls and a Stroke Patient

After experiencing brain damage, stroke patients commonly suffer from motor and sensory impairments that impact their ability to perform volitional movements. Visuo-proprioceptive integration is a critical component of voluntary movement, allowing for accurate movements and a sense of ownership over one's body. While recent studies have increased our understanding of the balance between visual compensation and proprioceptive deficits in stroke patients, quantitative methods for studying multisensory integration are still lacking. This study aimed to evaluate the feasibility of adapting a 3D visuo-proprioceptive disparity (VPD) task into a 2D setting using an upper-limb robotic platform for moderate to severe chronic stroke patients. To assess the implementation of the 2D task, a cohort of unimpaired healthy participants performed the VPD task in both a 3D and 2D environment. We used a computational Bayesian model to predict errors in visuo-proprioceptive integration and compared the model's predictions to real behavioral data. Our findings indicated that the behavioral trends observed in the 2D and 3D tasks were similar, and the model accurately predicted behavior. We then evaluated the feasibility of our task to assess post-stroke deficits in a patient with severe motor and sensory deficits. Ultimately, this work may help to improve our understanding of the significance of visuo-proprioceptive integration and aid in the development of better rehabilitation therapies for improving sensorimotor outcomes in stroke patients.