Abstract
Predicting intentions from observing another agent’s behaviours is often thought to depend on motor resonance – i.e., the motor system’s response to a perceived movement by the activation of its stored motor counterpart, but observers might also rely on prior expectations, especially when actions take place in perceptually uncertain situations. Here we assessed motor resonance during an action prediction task using transcranial magnetic stimulation to probe corticospinal excitability (CSE) and report that experimentally-induced updates in observers’ prior expectations modulate CSE when predictions are made under situations of perceptual uncertainty. We show that prior expectations are updated on the basis of both biomechanical and probabilistic prior information and that the magnitude of the CSE modulation observed across participants is explained by the magnitude of change in their prior expectations. These findings provide the first evidence that when observers predict others’ intentions, motor resonance mechanisms adapt to changes in their prior expectations. We propose that this adaptive adjustment might reflect a regulatory control mechanism that shares some similarities with that observed during action selection. Such a mechanism could help arbitrate the competition between biomechanical and probabilistic prior information when appropriate for prediction.
Highlights
Predicting and understanding other people’s behaviours is often thought to depend on processes of motor simulation or resonance[1,2,3,4,5,6,7,8,9,10,11]
As we hypothesize, the motor resonance system is sensitive to prior expectations and their updating – corticospinal excitability (CSE) should be modulated by the type of probabilistic bias and not the grip, and this effect should be greater for participants who update their prior expectations
To investigate whether participants updated their prior expectations in line with the probability distributions to which they were exposed, we analysed the mean Response Bias (RB) values collected during the bias block using a 2 × 3 repeated-measures ANOVA with ‘grip’ as a within-subject factor and ‘group’ as a between-subject factor
Summary
Predicting and understanding other people’s behaviours is often thought to depend on processes of motor simulation or resonance[1,2,3,4,5,6,7,8,9,10,11]. Tracking biomechanical and probabilistic information and solving the potential conflicts between them enables human observers to narrow the number of intentions (or goals) that compete to explain other people’s behaviour This results in the selection of intentions that the observed agent is more likely to pursue given their prior distributions[21,22,32], the biomechanical constraints of the effector[33], and the physical properties of the objects that might be used to achieve their goal[34]. Healthy adult participants were asked to make predictions about an agent’s final intentions or goals (in the following manuscript we will interchangeably use these two terms to refer to the mentalized and actualized end-state of the action) while watching movies in which the agent grasped an unfamiliar tool with two different grips (power or precision) and manipulated it to achieve two different goals (open the box or turn on the light). If motor resonance is specific for movement kinematics, CSE should be unaffected by exposure to biased probabilities
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