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.

Forgetting ourselves in flow: an active inference account of flow states and how we experience ourselves within them.

Flow has been described as a state of optimal performance, experienced universally across a broad range of domains: from art to athletics, gaming to writing. However, its phenomenal characteristics can, at first glance, be puzzling. Firstly, individuals in flow supposedly report a loss of self-awareness, even though they perform in a manner which seems to evince their agency and skill.

Phasic modulation of beta power at movement-related frequencies during visuomotor conflict.

Rhythmic cortical activity is thought to underlie many cognitive functions including the flexible weighting of sensory information depending on the current behavioral context. Here, we tested for potential oscillatory alignment and power modulation at behaviorally relevant frequencies in magnetoencephalography (MEG) data acquired during a virtual reality-based, rhythmic hand-target phase matching task. The task contained conditions differing in terms of visuomotor incongruence and whether or not behavior (grasping movements) had to be adapted to keep vision aligned with the target.

I overthink-Therefore I am not: An active inference account of altered sense of self and agency in depersonalisation disorder.

This paper considers the phenomenology of depersonalisation disorder, in relation to predictive processing and its associated pathophysiology. To do this, we first establish a few mechanistic tenets of predictive processing that are necessary to talk about phenomenal transparency, mental action, and self as subject. We briefly review the important role of 'predicting precision' and how this affords mental action and the loss of phenomenal transparency.

Does temporal irregularity drive prediction failure in schizophrenia? temporal modelling of ERPs.

Schizophrenia subjects often suffer from a failure to properly predict incoming inputs; most notably, some patients exhibit impaired prediction of the sensory consequences of their own actions. The mechanisms underlying this deficit remain unclear, though. One possible mechanism could consist in aberrant predictive processing, as schizophrenic patients show relatively less attenuated neuronal activity to self-produced tones, than healthy controls.

A Crucial Role of the Frontal Operculum in Task-Set Dependent Visuomotor Performance Monitoring.

For adaptive goal-directed action, the brain needs to monitor action performance and detect errors. The corresponding information may be conveyed via different sensory modalities; for instance, visual and proprioceptive body position cues may inform about current manual action performance. Thereby, contextual factors such as the current task set may also determine the relative importance of each sensory modality for action guidance.

Precision control for a flexible body representation.

Adaptive body representation requires the continuous integration of multisensory inputs within a flexible 'body model' in the brain. The present review evaluates the idea that this flexibility is augmented by the contextual modulation of sensory processing 'top-down'; which can be described as precision control within predictive coding formulations of Bayesian inference. Specifically, I focus on the proposal that an attenuation of proprioception may facilitate the integration of conflicting visual and proprioceptive bodily cues.

The computational neurology of movement under active inference.

We propose a computational neurology of movement based on the convergence of theoretical neurobiology and clinical neurology. A significant development in the former is the idea that we can frame brain function as a process of (active) inference, in which the nervous system makes predictions about its sensory data. These predictions depend upon an implicit predictive (generative) model used by the brain.

Cortical beta oscillations reflect the contextual gating of visual action feedback.

In sensorimotor integration, the brain needs to decide how its predictions should accommodate novel evidence by 'gating' sensory data depending on the current context. Here, we examined the oscillatory correlates of this process by recording magnetoencephalography (MEG) data during a new task requiring action under intersensory conflict. We used virtual reality to decouple visual (virtual) and proprioceptive (real) hand postures during a task in which the phase of grasping movements tracked a target (in either modality).

Active inference under visuo-proprioceptive conflict: Simulation and empirical results.

It has been suggested that the brain controls hand movements via internal models that rely on visual and proprioceptive cues about the state of the hand. In active inference formulations of such models, the relative influence of each modality on action and perception is determined by how precise (reliable) it is expected to be. The 'top-down' affordance of expected precision to a particular sensory modality is associated with attention.

Attentional Modulation of Vision Versus Proprioception During Action.

To control our actions efficiently, our brain represents our body based on a combination of visual and proprioceptive cues, weighted according to how (un)reliable-how precise-each respective modality is in a given context. However, perceptual experiments in other modalities suggest that the weights assigned to sensory cues are also modulated "top-down" by attention. Here, we asked whether during action, attention can likewise modulate the weights (i.

Action-Dependent Processing of Touch in the Human Parietal Operculum and Posterior Insula.

Somatosensory input generated by one's actions (i.e., self-initiated body movements) is generally attenuated.

'Seeing the Dark': Grounding Phenomenal Transparency and Opacity in Precision Estimation for Active Inference.

One of the central claims of the Self-model Theory of Subjectivity is that the experience of being someone - even in a minimal form - arises through a transparent phenomenal self-model, which itself can in principle be reduced to brain processes. Here, we consider whether it is possible to distinguish between phenomenally transparent and opaque states in terms of active inference. We propose a relationship of phenomenal opacity to expected uncertainty or precision; i.

Fronto-Parietal Brain Responses to Visuotactile Congruence in an Anatomical Reference Frame.

Spatially and temporally congruent visuotactile stimulation of a fake hand together with one's real hand may result in an illusory self-attribution of the fake hand. Although this illusion relies on a representation of the two touched body parts in external space, there is tentative evidence that, for the illusion to occur, the seen and felt touches also need to be congruent in an anatomical reference frame. We used functional magnetic resonance imaging and a somatotopical, virtual reality-based setup to isolate the neuronal basis of such a comparison.

Different responses of the right superior temporal sulcus to visual movement feedback during self-generated vs. externally generated hand movements.

An important implication of several recent accounts of motor control is that sensory feedback from self-generated movements is relatively attenuated based on predictions issued by the agent's motor system. Such a relative attenuation of sensory information during actions has already been demonstrated in the somatosensory domain. Here, we used functional magnetic resonance imaging (fMRI) and a virtual reality-based setup to investigate a potential attenuation of brain responses to realistic visual movement feedback during active vs.

Posterior parietal cortex evaluates visuoproprioceptive congruence based on brief visual information.

To represent one's upper limbs for action, the brain relies on a combined position estimate based on visual and proprioceptive information. Monkey neurophysiology and human brain imaging suggest that the underlying operations are implemented in a network of fronto-parietal and occipitotemporal cortical areas. Recently, a potential hierarchical arrangement of these areas has been proposed, emphasizing the posterior parietal cortex (PPC) in early multisensory comparison and integration.

Neuronal correlates of continuous manual tracking under varying visual movement feedback in a virtual reality environment.

To accurately guide one's actions online, the brain predicts sensory action feedback ahead of time based on internal models, which can be updated by sensory prediction errors. The underlying operations can be experimentally investigated in sensorimotor adaptation tasks, in which moving under perturbed sensory action feedback requires internal model updates. Here we altered healthy participants' visual hand movement feedback in a virtual reality setup, while assessing brain activity with functional magnetic resonance imaging (fMRI).

Integration of Visual and Proprioceptive Limb Position Information in Human Posterior Parietal, Premotor, and Extrastriate Cortex.

Unlabelled: The brain constructs a flexible representation of the body from multisensory information. Previous work on monkeys suggests that the posterior parietal cortex (PPC) and ventral premotor cortex (PMv) represent the position of the upper limbs based on visual and proprioceptive information. Human experiments on the rubber hand illusion implicate similar regions, but since such experiments rely on additional visuo-tactile interactions, they cannot isolate visuo-proprioceptive integration.

That's not quite me: limb ownership encoding in the brain.

With congruent stimulation of one's limb together with a fake counterpart, an illusory self-attribution of the fake limb can be induced. Such illusions have brought profound insights into the cognitive and neuronal mechanisms underlying temporary changes in body representation, but to put them in perspective, they need to be compared with ownership as experienced for one's real body. We used functional magnetic resonance imaging (fMRI) to compare the neuronal correlates of touch under different degrees of body ownership.

Network activity underlying the illusory self-attribution of a dummy arm.

Neuroimaging has demonstrated that the illusory self-attribution of body parts engages frontal and intraparietal brain areas, and recent evidence further suggests an involvement of visual body-selective regions in the occipitotemporal cortex. However, little is known about the principles of information exchange within this network. Here, using automated congruent versus incongruent visuotactile stimulation of distinct anatomical locations on the participant's right arm and a realistic dummy counterpart in an fMRI scanner, we induced an illusory self-attribution of the dummy arm.

Proprioceptive drift in the rubber hand illusion is intensified following 1 Hz TMS of the left EBA.

The rubber hand illusion (RHI) is a paradigm used to induce an illusory feeling of owning a dummy hand through congruent multisensory stimulation. Thus, it can grant insights into how our brain represents our body as our own. Recent research has demonstrated an involvement of the extrastriate body area (EBA), an area of the brain that is typically implicated in the perception of non-face body parts, in illusory body ownership.