Presentation of stimuli and recording of participants’ responses were carried out using

Cogent (http://www.vislab.ucl.ac.uk/cogent_graphics.php) running in Matlab 6.5 (MathWorks™). In each of the six experimental sessions, a T2*-weighted, gradient-echo, echo-planar imaging sequence was used to acquire 164 40-slice (2 mm thickness and 1 mm gap; TE = 65 ms; α = 90 °) volumes covering the whole brain and cerebellum with an in-plane resolution of 3 × 3 mm (64 × 64 matrix, fov 192 × 192 × 144 mm3; TR = 2600 ms). A high-resolution (1 × 1 × 1 mm3) structural image (MPRAGE sequence) was also collected. fMRI TSA HDAC chemical structure data were analysed using SPM8 (http://www.fil.ion.ucl.ac.uk/spm) procedures, running in Matlab 7.6 (MathWorks™), after discarding the first four dummy volumes in each session to allow for T1 equilibrium effect. Slice timing correction was applied to correct for offsets of slice acquisition. EPI volumes were realigned to the first volume for each subject to correct for interscan movement, and unwarped for movement-induced inhomogeneities of the magnetic field using realignment CX-5461 mouse parameters (Andersson

et al., 2001). EPI volumes were stereotactically normalized into the standard space defined by the Montreal Neurological Institute (MNI) using a two-step procedure: the mean EPI image created during realignment was coregistered with the structural image, which was spatially normalized to the SPM T1 template using a 12-parameter affine and non-linear cosine basis function transformation, both transformations being subsequently applied to all EPI volumes. new Normalized images were smoothed using an 8-mm isometric Gaussian kernel to account for residual inter-subject differences in functional anatomy (Friston et al., 2007). Analysis of the functional imaging data entailed the creation

of statistical parametric maps representing a statistical assessment of hypothesized condition-specific effects (Friston et al., 1994). A random effect procedure was adopted for data analysis. Within individual subjects, the 20-s stimulations were modelled for the three types of stimuli (Control, Oldowan, Acheulean), the 5-s tasks were modelled for the three types of stimuli and two tasks (Imagine, Evaluate), and the motor responses were modelled as events (duration 0) irrespective of the experimental condition. Rest was modelled as a 12-s condition. Each condition was defined with a boxcar function convolved with SPM8 canonical haemodynamic response function to estimate condition-specific effects with the General Linear Model. Low-frequency drifts were removed by a high-pass filtering with a cut-off of 128 s.