Emotions elicited by music influence can influence and even bias visual judgments, according to University of London’s Nidhya Logeswaran and Joydeep Bhattacharya.
They presented volunteers with short excerpts of “happy” music or “sad” music, then showed neutral, “happy,” and “sad” faces.
When people listened to a “happy” music, they were more likely to perceive faces as “happy” even when the face was neutral.
Similarly, the “priming” with “sad” music was associated with more ratings of faces as “sad,” even if they were neutral.
The team also observed the effects of musical “priming” in electrophysiological measures of brain potential components within 100 milliseconds after the faces were presented, suggesting rapid neuronal information processing.
Even if listeners’ perceptions and judgments can be biased by emotional music, listeners do not experience the precise emotions they hear in music.
Listeners can identify strong emotions conveyed by music, but do not experience the same degree or type of emotion, according to Tokyo University of the Arts’s Ai Kawakami and Kiyoshi Furukawa, who collaborated with University of Tokyo’s Kentaro Katahira and Kazuo Okanoya.
Kawakami and team distinguished “perceived emotion” from “felt emotion” in response to music, and presented two pieces of “sad” music (Mikhail Glinka’s “La Séparation” in F minor) and one piece of “happy” music to 44 volunteers, both musicians and non-musicians.
Participants rated their perceived emotions and felt emotions in response to each musical selection using 62 descriptions on a scale from 0 (not at all) to 4 (very much).
Although participants recognized the “sad” music’s negative emotions, most reported feeling “romantic,” and “blithe,” rather than negative or unpleasant.
“Muzak” (now Mood Media) audio in workplaces can evoke emotional responses that may lead to biased business decisions.
As long ago as the 1950s, concerned American citizens claimed that Muzak practiced “brainwashing” with its planned musical sequences in quarter-hour segments.
Muzak’s playlist is synchronized to time of day to “increase energy” at predicted low-energy times based on its patented “Stimulus Progression.”
These 15-minute sequences feature about six songs with varying “stimuli values,” based on tempo, rhythm, instrumentation and orchestra size.
The next 15-minute period features silence.
Over a 24-hour period, tunes with higher “stimulus value” are played when people are typically “lethargic” – 11 a.m. and 3 p.m., and slower songs are played “after lunch” and at the end of the work day.
Muzak claimed that this programming “increases morale and productivity at workplaces, increase sales at supermarkets, and even dissuade potential shoplifting at department stores.”
The emotional tone of music may bias other cross-sensory judgments.
Adrian C. North, working at University of Leicester and Herriott Watt University, tested the effect of music in a supermarket on wine selections and olfactory/gustatory judgments wine’s properties.
North ensured that French accordian music or German Bierkeller brass band music were played on alternating days for two weeks at the supermarket.
French wines and German wines had similar prices and their order on the shelf was changed each day.
After 82 shoppers selected wines, an interviewer asked customers to complete a questionnaire about the purchase, including:
- Preference for French or German wines
- Extent to which the music brought to mind France or Germany
- Degree to which the music influenced specific wine selection.
The results from 44 shoppers suggest that music influenced shoppers’ wine selections: More French wine was sold when French music played (40 bottles of French wine vs 8 bottles of German wine), and more German wine was sold when German music played (22 bottles of German wine vs 12 bottles of French wine).
North concluded that barely audible music can implicitly, unconsciously affect thoughts, perceptions, decisions, and even buying action.
Music can trigger thoughts similar to the music’s mood, context, or speed, according to the Preference-for-prototypes model proposed by Macquarie University’s Charles Areni and David Kim of Texas Tech.
-*When have your judgments and performance been altered by ambient music?
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