Abstract

Most people have a soundtrack of life, a set of special musical pieces closely linked to certain biographical experiences. Autobiographical memories (AM) and music listening (ML) involve complex mental processes ruled by differentiate brain networks. The aim of the paper was to determine the way both networks interact in linked occurrences. We performed an fMRI experiment on 31 healthy participants (age: 32.4 ± 7.6, 11 men, 4 left-handers). Participants had to recall AMs prompted by music they reported to be associated with personal biographical events (LMM: linked AM-ML events). In the main control task, participants were prompted to recall emotional AMs while listening known tracks from a pool of popular music (UMM: unlinked AM-ML events). We wanted to investigate to what extent LMM network exceeded the overlap of AM and ML networks by contrasting the activation obtained in LMM versus UMM. The contrast LMM>UMM showed the areas (at P < 0.05 FWE corrected at voxel level and cluster size>20): right frontal inferior operculum, frontal middle gyrus, pars triangularis of inferior frontal gyrus, occipital superior gyrus and bilateral basal ganglia (caudate, putamen and pallidum), occipital (middle and inferior), parietal (inferior and superior), precentral and cerebellum (6, 7 L, 8 and vermis 6 and 7). Complementary results were obtained from additional control tasks. Provided part of tLMM>UMM areas might not be related to ML-AM linkage, we assessed LMM brain network by an independent component analysis (ICA) on contrast images. Results from ICA suggest the existence of a cortico-ponto-cerebellar network including left precuneus, bilateral anterior cingulum, parahippocampal gyri, frontal inferior operculum, ventral anterior part of the insula, frontal medial orbital gyri, caudate nuclei, cerebellum 6 and vermis, which might rule the ML-induced retrieval of AM in closely linked AM-ML events. This topography may suggest that the pathway by which ML is linked to AM is attentional and directly related to perceptual processing, involving salience network, instead of the natural way of remembering typically associated with default mode network.

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