Nostalgia is a mixed emotion that is often evoked by music. Nostalgic music may induce temporary improvements in autobiographical memory in individuals with cognitive decline. However, the neural mechanism underlying music-evoked nostalgia and its associated memory improvements is unclear. With the ultimate goal of understanding how nostalgia-evoking music may help retrieve autobiographical memories in individuals with cognitive impairment, we first sought to understand the neural underpinnings of these processes in healthy younger and older adults. Methodological constraints, including the lack of personally tailored and experimentally controlled stimuli, have impeded our understanding of this mechanism. Here, we utilized an innovative machine-learning-based method to construct three categories of songs, all matched for musical features: (1) personalized nostalgic, (2) familiar non-nostalgic, and (3) unfamiliar non-nostalgic. In 57 participants (29 aged 18-35
28 aged 60 and older), we investigated the functional neural correlates of music-evoked nostalgia using fMRI. Four main findings emerged: (1) Listening to nostalgic music, more than familiar non-nostalgic or unfamiliar music, was associated with bilateral activity in the default mode network, salience network, reward network, medial temporal lobe, and supplementary motor regions, (2) Psychophysiological interaction (PPI) models indicated that listening to nostalgic music involved increased functional connectivity of self-referential (posteromedial cortex) and affect-related regions (insula), (3) Older adults had stronger BOLD signals than younger adults in nostalgia-related regions during nostalgic listening, (4) While the BOLD response to nostalgic music in younger adults was associated with trait-level factors of nostalgia proneness and cognitive ability, the response in older adults was related to affective responses to the music. Overall, our findings serve as a foundation for understanding the neural basis of music-evoked nostalgia and its potential use in future clinical interventions.