FIGURE 1.

The experimental and computational frameworks. (A) Healthy participants performed a weather-prediction task through the association of card types to a binary weather output (sunny/rainy). (B) Two stages of trials were presented sequentially to subjects where each trial was composed by four sections: a first phase characterized by the visual presentation of the card, a second stage wherein the user makes the choice (sun/rain), a third phase with the visual feedback (correct/wrong) and a short final rest phase with a blank screen. Depending on the task type, the feedbacks could be assigned deterministically or probabilistically. (C) The AFNI preprocessing pipeline used for the structural MRI and the BOLD signals. (D) Axial view samples of the two atlases used to parcellate the fMRI volumes: the FSL and the Brainnetome (BN). (E–G) Examples of, respectively, adjacency matrices (E), their related topological (F) and MNI space embeddings (G). (H) Exemplary collections of complex network statistics plotted in Box–Whisker (1st, 25th, 50th, and 99th percentiles) with scattering points as measure of dispersion. (I) The classification accuracy reported by the original works (Poldrack et al., 2001; Aron et al., 2006) shows that probabilistic feedbacks did not evoke any consistent association learning.