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We present an analytical framework aimed at predicting the local brain activity in uncontrolled experimental conditions based on multimodal recordings of participants' behavior, and its application to a corpus of participants having conversations with another human or a conversational humanoid robot. The framework consists in extracting high-level features from the raw behavioral recordings and applying a dynamic prediction of binarized fMRI-recorded local brain activity using these behavioral features. The objective is to identify behavioral features required for this prediction, and their relative weights, depending on the brain area under investigation and the experimental condition. In order to validate our framework, we use a corpus of uncontrolled conversations of participants with a human or a robotic agent, focusing on brain regions involved in speech processing, and more generally in social interactions. The framework not only predicts local brain activity significantly better than random, it also quantifies the weights of behavioral features required for this prediction, depending on the brain area under investigation and on the nature of the conversational partner. In the left Superior Temporal Sulcus, perceived speech is the most important behavioral feature for predicting brain activity, regardless of the agent, while several features, which differ between the human and robot interlocutors, contribute to the prediction in regions involved in social cognition, such as the TemporoParietal Junction. This framework therefore allows us to study how multiple behavioral signals from different modalities are integrated in individual brain regions during complex social interactions. [ABSTRACT FROM AUTHOR]

The anthropomorphic bias describes the finding that the perceived naturalness of a biological motion decreases as the human-likeness of a computer-animated agent increases. To investigate the anthropomorphic bias in autistic children, human or cartoon characters were presented with biological and artificial motions side by side on a touchscreen. Children were required to touch one that would grow while the other would disappear, implicitly rewarding their choice. Only typically developing controls depicted the expected preference for biological motion when rendered with human, but not cartoon, characters. Despite performing the task to report a preference, children with autism depicted neither normal nor reversed anthropomorphic bias, suggesting that they are not sensitive to the congruence of form and motion information when observing computer-animated agents' actions.

We investigated the consequences of premature birth on the functional neuroanatomy of the dorsal stream of visual processing. fMRI was recorded while sixteen healthy participants, 8 (two men) adults (19 years 6 months old, SD 10 months) born premature (mean gestational age 30 weeks), referred to as Premas, and 8 (two men) matched controls (20 years 1 month old, SD 13 months), performed a 1-back memory task of Object or Grip information using a hand grasping a drinking vessel as stimulus. While history of prematurity did not significantly affect task performance, Group by Task analysis of variance in regions of interest spanning the occipital, temporal and parietal lobes revealed main effects of Task and interactions between the two factors. Object processing activated the left inferior occipital cortex and bilateral ventral temporal regions, belonging to the ventral stream, with no effect of Group. Grip processing across groups activated the early visual cortex and the left supramarginal gyrus belonging to the dorsal stream. Group effect on the brain activity during Grip suggested that Controls represented the actions' goal while Premas relied more on low-level visual information. This shift from higher- to lower-order visual processing between Controls and Premas may reflect a more general trend, in which Premas inadequately recruit higher-order visual functions for dorsal stream task performance, and rely more on lower-level functions. (Contains 2 tables and 2 figures.)

The adaptive threat-detection advantage takes the form of a preferential orienting of attention to threatening scenes. In this study, we compared attention to social scenes in 15 high-functioning individuals with autism (ASD) and matched typically developing (TD) individuals. Eye-tracking was recorded while participants were presented with pairs of scenes, either emotional positive-neutral, emotional negative-neutral or neutral-neutral scenes. Early allocation of attention, the first image fixated in each pair, differed between groups: contrary to TD individuals who showed the typical threat-detection advantage towards negative images, the ASD group failed to show a bias toward threat-related scenes. Later processing of stimuli, indicated by the total fixation to the images during the 3-s presentation, was found unaffected in the ASD group. These results support the hypothesis of an early atypical allocation of attention towards natural social scenes in ASD, that is compensated in later stages of visual processing.

In recent years, neurophysiological evidence has accumulated in favor of a common coding between perception and execution of action. We review findings from recent neuroimaging experiments in the action domain with three complementary perspectives: perception of action, covert action triggered by perception, and reproduction of perceived action (imitation). All studies point to the parietal cortex as a key region for body movement representation, both observed and performed.

Robotic devices, thanks to the controlled variations in their appearance and behaviors, provide useful tools to test hypotheses pertaining to social interactions. These agents were used to investigate one theoretical framework, resonance, which is defined, at the behavioral and neural levels, as an overlap between first- and third- person representations of mental states such as motor intentions or emotions. Behaviorally, we found a reduced, but significant, resonance towards a humanoid robot displaying biological motion, compared to a human. Using neuroimaging, we've reported that while perceptual processes in the human occipital and temporal lobe are more strongly engaged when perceiving a humanoid robot than a human action, activity in areas involved in motor resonance depends on attentional modulation for artificial agent more strongly than for human agents. Altogether, these studies using artificial agents offer valuable insights into the interaction of bottom-up and top-down processes in the perception of artificial agents.