Action Enhances Predicted Touch

It is widely believed that predicted tactile action outcomes are perceptually attenuated. The present experiments determined whether predictive mechanisms necessarily generate attenuation or, instead, can enhance perception—as typically observed in sensory cognition domains outside of action. We manipulated probabilistic expectations in a paradigm often used to demonstrate tactile attenuation. Adult participants produced actions and subsequently rated the intensity of forces on a static finger. Experiment 1 confirmed previous findings that action outcomes are perceived less intensely than passive stimulation but demonstrated more intense perception when active finger stimulation was removed. Experiments 2 and 3 manipulated prediction explicitly and found that expected touch during action is perceived more intensely than unexpected touch. Computational modeling suggested that expectations increase the gain afforded to expected tactile signals. These findings challenge a central tenet of prominent motor control theories and demonstrate that sensorimotor predictions do not exhibit a qualitatively distinct influence on tactile perception.

Sensory Attenuation in the Auditory Modality as a Window Into Predictive Processing

Self-generated auditory input is perceived less loudly than the same sounds generated externally. The existence of this phenomenon, called Sensory Attenuation (SA), has been studied for decades and is often explained by motor-based forward models. Recent developments in the research of SA, however, challenge these models. We review the current state of knowledge regarding theoretical implications about the significance of Sensory Attenuation and its role in human behavior and functioning. Focusing on behavioral and electrophysiological results in the auditory domain, we provide an overview of the characteristics and limitations of existing SA paradigms and highlight the problem of isolating SA from other predictive mechanisms. Finally, we explore different hypotheses attempting to explain heterogeneous empirical findings, and the impact of the Predictive Coding Framework in this research area.

Simultaneous mnemonic and predictive representations in the auditory cortex

Recent studies have shown that stimulus history can be decoded via the use of broadband sensory impulses to reactivate mnemonic representations. It has also been shown that predictive mechanisms in the auditory system demonstrate similar tonotopic organization of neural activity as that elicited by the perceived stimuli. However, it remains unclear if the mnemonic and predictive information can be decoded from cortical activity simultaneously and from overlapping neural populations. Here, we recorded neural activity using electrocorticography (ECoG) in the auditory cortex of anesthetized rats while exposed to repeated stimulus sequences, where events within the sequence were occasionally replaced with a broadband noise burst or omitted entirely. We show that both stimulus history and predicted stimuli can be decoded from neural responses to broadband impulse at overlapping latencies but linked to largely independent neural populations. We also demonstrate that predictive representations are learned over the course of stimulation at two distinct time scales, reflected in two dissociable time windows of neural activity. These results establish a valuable tool for investigating the neural mechanisms of passive sequence learning, memory encoding, and prediction mechanisms within a single paradigm, and provide novel evidence for learning predictive representations even under anaesthesia.

A transfer-learning approach for corrosion prediction in pipeline infrastructures

Pipeline infrastructures, carrying either gas or oil, are often affected by internal corrosion, which is a dangerous phenomenon that may cause threats to both the environment (due to potential leakages) and the human beings (due to accidents that may cause explosions in presence of gas leakages). For this reason, predictive mechanisms are needed to detect and address the corrosion phenomenon. Recently, we have seen a first attempt at leveraging Machine Learning (ML) techniques in this field thanks to their high ability in modeling highly complex phenomena. In order to rely on these techniques, we need a set of data, representing factors influencing the corrosion in a given pipeline, together with their related supervised information, measuring the corrosion level along the considered infrastructure profile. Unfortunately, it is not always possible to access supervised information for a given pipeline since measuring the corrosion is a costly and time-consuming operation. In this paper, we will address the problem of devising a ML-based predictive model for internal corrosion under the assumption that supervised information is unavailable for the pipeline of interest, while it is available for some other pipelines that can be leveraged through Transfer Learning (TL) to build the predictive model itself. We will cover all the methodological steps from data set creation to the usage of TL. The whole methodology will be experimentally validated on a set of real-world pipelines.

EXPRESS: Taking apart what brings us together: the role of action prediction, perspective-taking, and theory of mind in joint action

The ability to act together with others to achieve common goals is crucial in life, yet there is no full consensus on the underlying cognitive skills. While influential theoretical accounts suggest that interaction requires sophisticated insights into others’ minds, alternative views propose that high-level social skills might not be necessary because interactions are grounded on sensorimotor predictive mechanisms. At present, empirical evidence is insufficient to decide between the two. This study addressed this issue and explored the association between performance at joint action tasks and cognitive abilities in three domains - action prediction, perspective-taking, and theory of mind - in healthy adults (N=58). We found that, while perspective-taking played a role in reading the behaviour of others independently of the social context, action prediction abilities specifically influenced the agents’ performance in an interactive task but not in a control (social but non-interactive) task. In our study, performance at a theory of mind test did not play any role, as confirmed by Bayesian analyses. The results suggest that, in adults, sensorimotor predictive mechanisms might play a significant and specific role in supporting interpersonal coordination during motor interactions. We discuss the implications of our findings for the contrasting theoretical views described above and propose a way they might be partly reconciled.

Tactile suppression stems from sensation-specific sensorimotor predictions

The ability to sample sensory information with our hands is crucial for smooth and efficient interactions with the world. Despite this important role of touch, tactile sensations on a moving hand are perceived weaker than when presented on the same but stationary hand.1-3 This phenomenon of tactile suppression has been explained by predictive mechanisms, such as forward models, that estimate future sensory states of the body on the basis of the motor command and suppress the associated predicted sensory feedback.4 The origins of tactile suppression have sparked a lot of debate, with contemporary accounts claiming that suppression is independent of predictive mechanisms and is instead akin to unspecific gating.5 Here, we target this debate and provide evidence for sensation-specific tactile suppression due to sensorimotor predictions. Participants stroked with their finger over textured surfaces that caused predictable vibrotactile feedback signals on that finger. Shortly before touching the texture, we applied external vibrotactile probes on the moving finger that either matched or mismatched the frequency generated by the stroking movement. We found stronger suppression of the probes that matched the predicted sensory feedback. These results show that tactile suppression is not limited to unspecific gating but is specifically tuned to the predicted sensory states of a movement.

The effect of self- vs. externally generated actions on timing, duration and amplitude of BOLD response for visual feedback processing

It has been widely assumed that internal forward models use efference copies to create predictions about the sensory consequences of our own actions. While these predictions had been frequently associated with reduced neural processing in sensory cortices, the timing and duration of the hemodynamic response of self-generated as opposed to externally generated movements is poorly investigated. In the present study we tested the hypothesis that predictive mechanisms for self-generated actions lead to early and shorter neural processing compared with externally generated movements. Using a first and second-order Taylor approximation in terms of the temporal (TD) and dispersion (DD) derivatives of a canonical hemodynamic response function, we investigated the timing and duration of activation for self-generated and externally generated movements using a custom-made fMRI-compatible movement device. Visual video feedback of the active and passive hand movements were presented in real time or with variable delays (0 - 417 ms). Participants had to judge, whether the feedback was delayed. We found earlier feedback processing for self-generated compared to externally generated movements in several regions including the supplementary motor area, cerebellum, subcortical structures such as the putamen and visual cortices. Shorter processing was found in areas, which show also lower blood oxygen level dependent (BOLD) amplitudes, such as the SMA, occipital and parietal cortex. Specifically, earlier activation in the putamen, of self-generated movements was associated with worse performance in detecting delays. These findings support our hypothesis, that efference copy based predictive mechanisms enable earlier processing of action feedback, as potential source for behavioral effects.

Towards a causal role of Broca's area in language: A TMS-EEG study on syntactic prediction

Categorical predictions have been proposed as the key mechanism supporting the fast pace of syntactic composition in human language. Accordingly, grammar-based expectations facilitate the analysis of incoming syntactic information - e.g., hearing the determiner 'the' enhances the prediction of a noun - which is then checked against a single or few other word categories. Previous functional neuroimaging studies point towards Broca's area in the left inferior frontal gyrus (IFG) as one fundamental cortical region involved in categorical prediction during on-line language processing. Causal evidence for this hypothesis is however still missing. In this study, we combined Electroencephalography (EEG) and Transcranial Magnetic Stimulation (TMS) to test whether Broca's area is functionally relevant in predictive mechanisms for language. Specifically, we transiently perturbed Broca's area during the categorical prediction phase in two-word constructions, while simultaneously measuring the Event-Related Potential (ERP) correlates of syntactic composition. We reasoned that if Broca's area is involved in predictive mechanisms for syntax, disruptive TMS during the processing of the first word (determiner/pronoun) would mitigate the difference in ERP responses for predicted and unpredicted categories when composing basic phrases and sentences. Contrary to our hypothesis, perturbation of Broca's area at the predictive stage did not affect the ERP correlates of basic composition. The correlation strength between the electrical field induced by TMS and the magnitude of the EEG response on the scalp further confirmed this pattern. We discuss the present results in light of an alternative account of the role of Broca's area in syntactic composition, namely the bottom-up integration of words into constituents.

Visuo-tactile predictive mechanisms of peripersonal space

Our daily living includes bodily contacts with objects and people. While this physical contact occurs naturally, it could also pose a risk of bodily harm—for example, when objects are sharp, or people have bad intentions. It is therefore imperative to have a mechanism that predicts the consequences of bodily contact before it occurs, to guide our interactions appropriately. Evidence from a range of studies suggests a neurofunctional coupling between external visual or auditory stimuli near the body and tactile stimuli on the body. While these multisensory peripersonal representations have been linked to spatial attention, motor control, and social behaviour, a discussion on whether these functions involve a similar mechanism has been missing. Here we suggest that prediction is central to this multimodal coding: visual or auditory stimuli near the body predict tactile consequences of bodily contact. This predictive mechanism is based on learned visuo-tactile associations and modulated by higher-order visual contextual information.

Why Are Acquired Search-Guiding Context Memories Resistant to Updating?

Looking for goal-relevant objects in our various environments is one of the most ubiquitous tasks the human visual system has to accomplish (Wolfe, 1998). Visual search is guided by a number of separable selective-attention mechanisms that can be categorized as bottom-up driven – guidance by salient physical properties of the current stimuli – or top-down controlled – guidance by observers' “online” knowledge of search-critical object properties (e.g., Liesefeld and Müller, 2019). In addition, observers' expectations based on past experience also play also a significant role in goal-directed visual selection. Because sensory environments are typically stable, it is beneficial for the visual system to extract and learn the environmental regularities that are predictive of (the location of) the target stimulus. This perspective article is concerned with one of these predictive mechanisms: statistical context learning of consistent spatial patterns of target and distractor items in visual search. We review recent studies on context learning and its adaptability to incorporate consistent changes, with the aim to provide new directions to the study of processes involved in the acquisition of search-guiding context memories and their adaptation to consistent contextual changes – from a three-pronged, psychological, computational, and neurobiological perspective.