49 research outputs found
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)reliableāhow preciseāeach respective modality is in a given context. However, perceptual
experiments in other modalities suggest that the weights assigned to sensory cues are also modulated ātop-downā by
attention. Here, we asked whether during action, attention can likewise modulate the weights (i.e., precision) assigned to
visual versus proprioceptive information about body position. Participants controlled a virtual hand (VH) via a data glove,
matching either the VH or their (unseen) real hand (RH) movements to a target, and thus adopting a āvisualā or
āproprioceptiveā attentional set, under varying levels of visuo-proprioceptive congruence and visibility. Functional magnetic
resonance imaging (fMRI) revealed increased activation of the multisensory superior parietal lobe (SPL) during the VH task
and increased activation of the secondary somatosensory cortex (S2) during the RH task. Dynamic causal modeling (DCM)
showed that these activity changes were the result of selective, diametrical gain modulations in the primary visual cortex
(V1) and the S2. These results suggest that endogenous attention can balance the gain of visual versus proprioceptive brain
areas, thus contextualizing their inf luence on multisensory areas representing the body for action
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. Here, we asked whether increasing attention to (i.e., the precision of) vision or proprioception would enhance performance in a hand-target phase matching task, in which visual and proprioceptive cues about hand posture were incongruent. We show that in a simple simulated agent-based on predictive coding formulations of active inference-increasing the expected precision of vision or proprioception improved task performance (target matching with the seen or felt hand, respectively) under visuo-proprioceptive conflict. Moreover, we show that this formulation captured the behaviour and self-reported attentional allocation of human participants performing the same task in a virtual reality environment. Together, our results show that selective attention can balance the impact of (conflicting) visual and proprioceptive cues on action-rendering attention a key mechanism for a flexible body representation for action
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). Thus, we rendered visual information either task-relevant or a (to-be-ignored) distractor. Under visuo-proprioceptive incongruence, occipital beta power decreased (relative to congruence) when vision was task-relevant but increased when it had to be ignored. Dynamic causal modelling (DCM) revealed that this interaction was best explained by diametrical, task-dependent changes in visual gain. These novel results suggest a crucial role for beta oscillations in the contextual gating (i.e., gain or precision control) of visual vs proprioceptive action feedback, depending on concurrent behavioral demands
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. This means neural dynamics can be framed as generating actions to ensure sensations are consistent with these predictions-and adjusting predictions when they are not. We illustrate the significance of this formulation for clinical neurology through simulating a clinical examination of the motor system; i.e. an upper limb coordination task. Specifically, we show how tendon reflexes emerge naturally under the right kind of generative model. Through simulated perturbations, pertaining to prior probabilities of this model's variables, we illustrate the emergence of hyperreflexia and pendular reflexes, reminiscent of neurological lesions in the corticospinal tract and cerebellum. We then turn to the computational lesions causing hypokinesia and deficits of coordination. This in silico lesion-deficit analysis provides an opportunity to revisit classic neurological dichotomies (e.g. pyramidal versus extrapyramidal systems) from the perspective of modern approaches to theoretical neurobiology-and our understanding of the neurocomputational architecture of movement control based on first principles
I overthinkāTherefore I am not: An active inference account of altered sense of self and agency in depersonalisation disorder
I overthinkāTherefore I am not: An active inference account of altered sense of self and agency in depersonalisation disorder
I overthinkāTherefore 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. We then turn to sensory attenuation and the phenomenal consequences of (pathophysiological) failures to attenuate or modulate sensory precision. We then consider this failure in the context of depersonalisation disorder. The key idea here is that depersonalisation disorder reflects the remarkable capacity to explain perceptual engagement with the world via the hypothesis that "I am an embodied perceiver, but I am not in control of my perception". We suggest that individuals with depersonalisation may believe that 'another agent' is controlling their thoughts, perceptions or actions, while maintaining full insight that the 'other agent' is 'me' (the self). Finally, we rehearse the predictions of this formal analysis, with a special focus on the psychophysical and physiological abnormalities that may underwrite the phenomenology of depersonalisation
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. Secondly, flow states are felt to be effortless, despite the prerequisite complexity of the tasks that engender them. In this paper, we unpick these features of flow, as well as others, through the active inference framework, which posits that action and perception are forms of active Bayesian inference directed at sustained self-organisation; i.e., the minimisation of variational free energy. We propose that the phenomenology of flow is rooted in the deployment of high precision weight over (i) the expected sensory consequences of action and (ii) beliefs about how action will sequentially unfold. This computational mechanism thus draws the embodied cognitive system to minimise the ensuing (i.e., expected) free energy through the exploitation of the pragmatic affordances at hand. Furthermore, given the challenging dynamics the flow-inducing situation presents, attention must be wholly focussed on the unfolding task whilst counterfactual planning is restricted, leading to the attested loss of the sense of self-as-object. This involves the inhibition of both the sense of self as a temporally extended object and higherāorder, meta-cognitive forms of self-conceptualisation. Nevertheless, we stress that self-awareness is not entirely lost in flow. Rather, it is pre-reflective and bodily. Our approach to bodily-action-centred phenomenology can be applied to similar facets of seemingly agentive experience beyond canonical flow states, providing insights into the mechanisms of so-called selfless experiences, embodied expertise and wellbeing
Action-Dependent Processing of Touch in the Human Parietal Operculum and Posterior Insula
Somatosensory input generated by oneās actions (i.e., self-initiated body movements) is generally attenuated. Conversely,
externally caused somatosensory input is enhanced, for example, during active touch and the haptic exploration of objects.
Here, we used functional magnetic resonance imaging (fMRI) to ask how the brain accomplishes this delicate weighting of
self-generated versus externally caused somatosensory components. Finger movements were either self-generated by our
participants or induced by functional electrical stimulation (FES) of the same muscles. During half of the trials,
electrotactile impulses were administered when the (actively or passively) moving finger reached a predefined f lexion
threshold. fMRI revealed an interaction effect in the contralateral posterior insular cortex (pIC), which responded more
strongly to touch during self-generated than during FES-induced movements. A network analysis via dynamic causal
modeling revealed that connectivity from the secondary somatosensory cortex via the pIC to the supplementary motor area
was generally attenuated during self-generated relative to FES-induced movementsāyet specifically enhanced by touch
received during self-generated, but not FES-induced movements. Together, these results suggest a crucial role of the
parietal operculum and the posterior insula in differentiating self-generated from externally caused somatosensory
information received from oneās moving limb
The role of the cerebellum in adaptation: ALE metaāanalyses on sensory feedback error
It is widely accepted that unexpected sensory consequences of selfāaction engage the cerebellum. However, we currently lack consensus on where in the cerebellum, we find fineāgrained differentiation to unexpected sensory feedback. This may result from methodological diversity in taskābased human neuroimaging studies that experimentally alter the quality of selfāgenerated sensory feedback. We gathered existing studies that manipulated sensory feedback using a variety of methodological approaches and performed activation likelihood estimation (ALE) metaāanalyses. Only half of these studies reported cerebellar activation with considerable variation in spatial location. Consequently, ALE analyses did not reveal significantly increased likelihood of activation in the cerebellum despite the broad scientific consensus of the cerebellum's involvement. In light of the high degree of methodological variability in published studies, we tested for statistical dependence between methodological factors that varied across the published studies. Experiments that elicited an adaptive response to continuously altered sensory feedback more frequently reported activation in the cerebellum than those experiments that did not induce adaptation. These findings may explain the surprisingly low rate of significant cerebellar activation across brain imaging studies investigating unexpected sensory feedback. Furthermore, limitations of functional magnetic resonance imaging to probe the cerebellum could play a role as climbing fiber activity associated with feedback error processing may not be captured by it. We provide methodological recommendations that may guide future studies