One contribution of 17 to a theme issue 'From social brains to social robots: applying neurocognitive insights to human -robot interaction'.We present a novel functional magnetic resonance imaging paradigm for second-person neuroscience. The paradigm compares a human social interaction (human-human interaction, HHI) to an interaction with a conversational robot (human-robot interaction, HRI). The social interaction consists of 1 min blocks of live bidirectional discussion between the scanned participant and the human or robot agent. A final sample of 21 participants is included in the corpus comprising physiological (blood oxygen leveldependent, respiration and peripheral blood flow) and behavioural (recorded speech from all interlocutors, eye tracking from the scanned participant, face recording of the human and robot agents) data. Here, we present the first analysis of this corpus, contrasting neural activity between HHI and HRI. We hypothesized that independently of differences in behaviour between interactions with the human and robot agent, neural markers of mentalizing (temporoparietal junction (TPJ) and medial prefrontal cortex) and social motivation (hypothalamus and amygdala) would only be active in HHI. Results confirmed significantly increased response associated with HHI in the TPJ, hypothalamus and amygdala, but not in the medial prefrontal cortex. Future analysis of this corpus will include fine-grained characterization of verbal and non-verbal behaviours recorded during the interaction to investigate their neural correlates.This article is part of the theme issue 'From social brains to social robots: applying neurocognitive insights to human -robot interaction'.

The TARDIS project aims to build a scenario-based serious-game simulation platform for NEETs and job-inclusion associations that supports social training and coaching in the context of job interviews. This paper presents the general architecture of the TARDIS job interview simulator, and the serious game paradigm that we are developing. 1 NEET is a government acronym for young people not in employment, education or training. 2 ec.europa.eu/eurostat 3

Recent research has shown that virtual agents expressing empathic emotions toward users have the potential to enhance human-machine interaction. To provide empathic capabilities to a rational dialog agent, we propose a formal model of emotions based on an empirical and theoretical analysis of the users' conditions of emotion elicitation. The emotions are represented by particular mental states of the agent, composed of beliefs, uncertainties and intentions. This semantically grounded formal representation enables a rational dialog agent to identify from a dialogical situation the empathic emotion that it should express. An implementation and an evaluation of an empathic rational dialog agent have enabled us to validate the proposed model of empathy.