Information Retrieval is a multidisciplinary field where knowledge from engineering andinformation theory is combined with media technologies, linguistics, or musicology to deal with the variety of digitally available information. In the past two decades, even neuroscience was involved, showing how brain activity can be used to control future IR systems. The other way around, namely IR informing neuroscience, was only explored starting in 2012. We used computational extraction of features from continuous digital music to obtain time series variables that were related to the brain signal measured while participants were listening to the music in a magnetic resonance scanner. Since then, several other studies with other brain technologies were also conducted. This methodology has been helpful to move from artificial stimulation paradigms, typically used in neuroscience for maintaining control over manipulated variables, towards a naturalistic paradigm where variables are both well controlled and closely matched to real-life conditions. The potential of this naturalistic paradigm is becoming evident to the cognitive neuroscience community, also in relation to clinical applications, although use of IR to inform brain signals remains still mainly confined to music and sounds. Further avenues of applications can be pursued by fostering new interdisciplinary contaminations.