Boosting and Decreasing Action Prediction Abilities Through Excitatory and Inhibitory tDCS of Inferior Frontal Cortex

Abstract

Influential theories suggest that humans predict others' upcoming actions by using their own motor system as an internal forward model. However, evidence that the motor system is causally essential for predicting others' actions is meager. Using transcranial direct current stimulation (tDCS), we tested the role of the inferior frontal cortex (IFC), in action prediction (AP). We devised a novel AP task where participants observed the initial phases of right-hand reaching-to-grasp actions and had to predict their outcome (i.e., the goal/object to be grasped). We found that suppression by cathodal (inhibitory) tDCS of the left IFC, but not the left superior temporal sulcus or the right IFC, selectively impaired performance on the AP task, but not on a difficulty-matched control task. Remarkably, anodal (excitatory) tDCS of the left IFC brought about a selective improvement in the AP task. These findings indicate that the left IFC is necessary for predicting the outcomes of observed human right-hand actions. Crucially, our study shows for the first time that down- and up-regulating excitability within the motor system can hinder and enhance AP abilities, respectively. These findings support predictive coding theories of action perception and have implications for enhancement of AP abilities.

Uncertainty in contextual and kinematic cues jointly modulate motor resonance in primary motor cortex

“…Evidence in support of this account comes from our combined results from Experiments 1 and 2 showing that grip-specific muscle-facilitation was significantly stronger when both informative cues and full-view movement kinematics are present compared to when only informative cues are accessible. Previous research has suggested that goals and outcomes of an observed action might be represented by a hierarchically organized network of areas in parietal and frontal cortex (Avenanti, Paracampo, Annella, Tidoni, & Aglioti, 2017;Hamilton & Grafton, 2006). Our study revealed physiological evidence that different aspects of action representations do ultimately converge onto M1 as predicted by hierarchical models of predictive coding (see Kilner et al 2007).…”

Blocking facial mimicry affects recognition of facial and body expressions

“…From an initial pool of 372 stimuli, we selected a total of 138 pictures (23 pictures for each combination of face/body medium and happy/neutral/fearful expression) based on the results of a first pilot study whose aim was to identify two sets of facial and body expressions matched for emotional intensity. We selected happy and fearful stimuli with relatively high, but not extreme, ratings, to ensure visual recognition was not trivial (see S1 Text and S1 Table), as sensorimotor simulation is thought to contribute to visual perception particularly when stimuli are relatively subtle [29,31,78,79].…”

Perceiving Hesitation requires both the Motor and Mentalizing systems

“…The larger the deviation, the higher the likelihood that the actor was hesitant. The somatosensory-motor grasping network has been shown to be essential for drawing non-mentalistic inferences from observed kinematics of a grasping action (Pobric and de C. Hamilton 2006;Michael et al 2014;Avenanti et al 2017;Valchev et al 2017), and the predictive coding models suggested to be implemented in the pMNS could provide an architecture to calculate the deviation from such prediction (Grèzes et al 2004;Keysers and Perrett 2004;Kilner et al 2007;Thomas et al 2018). This could explain why interfering with the pMNS slowed the ability to detect Hesitations in our data, and why this network is activated and feeds into the mentalizing network.…”