The commonly-used paradigm to investigate Dennett’s “intentional stance” compares neural activation when participants compete with a human versus a computer. This paradigm confounds whether the opponent is natural or artificial; and whether it is intentional or an automaton. This fMRI study is the first to investigate the intentional stance by orthogonally varying perceptions of the opponents’ intentionality (responding actively or passively according to a script) and embodiment (human or a computer). The mere perception of the opponent (whether human or computer) as intentional activated the mentalizing network: the temporo-parietal junction (TPJ) bilaterally, right temporal pole, anterior paracingulate cortex and the precuneus. Interacting with humans versus computers induced activations in a more circumscribed right lateralized sub-network within the mentalizing network, consisting of the TPJ and the anterior paracingulate cortex, possibly reflective of the tendency to spontaneously attribute intentionality to humans. The interaction between intentionality (Active versus Passive) and opponent (Human versus Computer) recruited the left frontal pole, possibly in response to violations of the stances most commonly adopted towards humans and computers. Employing an orthogonal design is important to adequately capture Dennett’s point that mentalizing applies equally well to any system (human or artificial) provided that system behaves intentionally.

The data consist of two task: The ToM localizer task and the RPS task. Data were acquired in a single scanning session using a 3T Philips Achieva scanner. 176 T2*-weighted standard echo planar imaging (EPI) volumes were obtained in each of the RPS task runs, using a 32 channel head coil. Parameters used to achieve whole brain coverage are as follows: TR=2.5s, TE=35ms, acquisition matrix = 80 x 80, flip angle =83°, isotropic voxels 3x3x3 mm³, 42 slices axial acquisition obtained consecutively in a bottom-up sequence. Using the same parameters, 71 EPI volumes were acquired for each run of the localizer task. A T1-weighted scan was then acquired as a single volume at higher spatial resolution as a 3D TFE image (matrix size 288x288, 175 slices, sagittally acquired and reconstructed to 1x1x1 mm³ isotropic voxels. TE =3.8ms. TR = 8.4 ms).

Preprocessing and statistical analyses of the data were performed using the FMRIB software library (FSL version v.5.0.6; FMRIB, Oxford, www.fmrib.ox.ac.uk/fsl). For both experiments, initial preprocessing of the functional data consisted of slice timing correction, and motion correction (MCFLIRT). The blood oxygen level dependent (BOLD) signals were high-pass filtered using a Gaussian weighted filter to remove low-frequency drifts in the bold signal. Spatial smoothing of the BOLD signal was performed using a 5mm full-width-half-maximum kernel. The functional data were registered to their respective structural images and transformed to a standard template based on the Montreal Neurological Institute (MNI) reference brain, using a 6-DoF linear transformation (FLIRT).

The data consist of two clearly labeled folders one containing the data for the ToM localizer task, and one for the RPS tasks. Specific questions about the data can be directed to corresponding authors.