Music and traffic noise can shape how people imagine scenes in their minds, according to a study published in Humanities and Social Sciences Communications and announced on Apr. 2. The research found that both types of sounds influence the vividness, emotional tone, and even the speed or distance imagined during mental tasks.
The findings are relevant for understanding how background sounds may affect cognitive processes such as memory, planning, or decision-making. The results could also have implications for therapeutic settings that use guided imagery techniques.
In the study, researchers examined how undergraduate students from an Australian university responded to different auditory backgrounds—music, traffic noise, a combination of both, or silence—while performing a directed mental imagery task. Participants watched a short video clip showing a figure ascending a hill toward a distant landmark before closing their eyes to imagine the figure's journey while listening to one of the sound conditions.
Participants reported more vivid imagery when exposed to any sound compared with silence. Music alone led to greater positive emotional sentiment in imagined content than either silence or traffic noise. "Music enhanced vividness, imagined time, imagined distance, and positive sentiment compared to silence," the authors said.
Traffic noise increased the vividness of mental images but did not improve positive emotion or extend imagined travel time as much as music did. When music was combined with traffic noise (with music louder than noise), it reduced some of music’s positive effects on sentiment but did not significantly change other aspects like vividness or distance traveled in imagination.
The researchers noted that auditory environments do not uniformly enhance all aspects of mental imagery; instead, different types of background sound can have distinct effects on what people imagine and how they feel about those images. They also cautioned that factors such as participants' own listening devices and sample characteristics might limit generalizability.
