Draft of a submission
Research Paper Manuscript for MUSICAE SCIENTIAE
Inducing involuntary musical imagery: an experimental study
Lassi A. Liikkanen1, 2, 3
Running head:
1
Inducing involuntary musical imagery
Helsinki Institute for Information Technology HIIT,
Aalto University and University of Helsinki
2
University of Helsinki, Department of Behavioral Sciences
and
3
Stanford University, Department of Communications
Address correspondence to
Lassi A. Liikkanen, HIIT,
P.O.Box 19215, FI-00076 Aalto University, Finland
Email: [email protected]
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ABSTRACT
It is still a mystery why we sometimes experience the repetition of
memories in our minds. This phenomenon seems to be particularly
prominent in music. We believe that present lack of knowledge relates to
the lack of methods available for the study of this topic. To improve the
understanding of involuntary musical imagery (INMI), this paper proposes
a novel method to induce it in experimental settings. We report three
experiments that were conducted to evaluate two research questions
related to INMI: Can it be experimentally induced and if so, which factors
influence its emergence? Investigation particularly focused on how recent
activation of musical memory might predict INMI. The questions were
tested in single-trial experiments conducted over the Internet. The
experiments utilized a cued-recall method to induce INMI and delayed
self-reports. Among a large sample of people, the prevalence of the
phenomenon was considerable. When the familiarity with the stimuli was
controlled for, inducing INMI experimentally succeeded in over 50% of
participants. It was found that music rehearsal in the near past was a more
important predictor for INMI than very recent activation of musical
memories. This suggests that recent activation is a facilitating but not a
necessary condition for INMI. Overall, induction of INMI is possible, and
several ways to improve the method are proposed.
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INTRODUCTION
Musical imagery is a human skill that allows us to mentally play back music.
Sometimes we lose control over this power and music becomes “stuck in our thoughts”,
resulting in so-called “earworms”, or repeated involuntary musical memories. How does
this happen? Surprisingly, we do not have a good psychological explanation for this
phenomenon (Bailes, 2007; see also; Kvavilashvili & Mandler, 2004). This is
unfortunate from a psychological point of view. Instead of charming, but nonsense
concepts such as earworms, this phenomenon deserves a description in psychological
terms as it seems to be an integral part of music cognition. In this paper, the
phenomenon is called involuntary musical imagery (Sacks, 2007) and it is abbreviated
as INMI (Liikkanen, 2008). The working definition is that involuntary musical imagery
refers to all imagined musical experiences that originate without the subjects’ intention
and are not pathological.
Recent explorations in experimental and music psychology offer insight about
deliberate musical imagery (e.g. Brodsky, Kessler, Rubinstein, Ginsborg, & Henik,
2008; Godøy & Jørgensen, 2001; Halpern, 1984, 1988; Kraemer, Macrae, Green, &
Kelley, 2005; Zatorre & Halpern, 2005), but research on involuntary musical imagery is
only taking its first steps (Bailes, 2006, 2007; Baruss & Wammes, 2009; Bennett, 2003;
Kellaris, 2001; Liikkanen, 2008, in press). For instance, this topic is included but not
treated exhaustively in some recent monographs on music psychology (Levitin, 2006;
Sacks, 2007). The lack of research is peculiar given that this consciousness phenomenon
is more common than, for instance, synesthesia. Synesthesia is a rare condition and
involves a private, mental experience akin to involuntary musical imagery, but it has
still been studied extensively (see Kadosh & Henik, 2007).
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Involuntary musical imagery is here distinguished from clinical phenomena
such as musical obsessions (Terao & Ikemura, 2000), musical hallucinations
(hallucinosis), or pseudo-hallucinations (Hermesh et al., 2004). They have some
commonalities, but as involuntary musical imagery seems to be a much more prevalent
phenomenon than the clinical conditions, these cases are not considered here.
INMI can be connected to main stream psychology through involuntary
memory research, which has lately gained momentum (see Mace, 2007). Preliminary
studies of involuntary semantic memory highlight INMI as likely the most prevalent
form (Kvavilashvili & Mandler, 2004; Liikkanen, 2008). In contrast to involuntary
semantic memories, involuntary autobiographical memories have been studied
experimentally (Mace, 2005). Mace showed that explicit attempts to recall
autobiographical events from elementary school and high-school years increased the
number of similar involuntary memories in a subsequent diary study. Similar methods
seem promising for exploring involuntary musical imagery as well.
In this paper I propose a new empirical method to explore involuntary musical
imagery. Specifically, I study how prior activation of musical memory relates to later
INMI experiences using an induction paradigm. Employing familiarity-controlled
musical stimuli, I test the power of voluntary musical imagery to evoke involuntary
experiences later on. The test of this method involves the assessment of two research
questions about INMI. The introduction starts by reviewing the present state of INMI
research and pointing out the need for experimental research. The research questions
and hypotheses relating INMI to well-known properties of cognition are introduced
right after. Through three experiments I proceed to evaluate the merit of those
hypotheses in predicting the emergence of INMI.
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Previous INMI research
Perhaps the first psychological treatment of what is here called INMI was
provided by psychoanalyst Theodor Reik (1953). Through introspection he identified
two forms of INMI: mundane, exposure-based INMI and INMI as an indicator of
repressed memories. His monograph dealt with the latter form and he hypothesized that
this “haunting” music could guide psychoanalysis. For contemporary psychology, the
mundane type of INMI seems more attractive and tangible. This line of research
recently started as psychologists began asking questions such as how common INMI is,
what kind of personality or background characteristics make people prone to it, and how
pervasive it is in daily life.
The survey studies of INMI conducted this far show that characteristics such as
young age, gender (being female), ongoing musical activities (Bennett, 2003; Kellaris,
2001; Liikkanen, 2008, in press), and increased levels of trait neuroticism (Kellaris,
2003) or transliminality (Baruss & Wammes, 2009) are all positively related to a high
retrospectively reported frequency of INMI. Transliminality is an infrequently used
measure of susceptibility to internally generated psychological phenomena developed
by Thalbourne and Delin (1994). The method of introspection was lately utilized by
Brown (2006) who described his personal INMI experiences in great detail. A slightly
different self-reporting method to study INMI was used by Bailes (2006, 2007), who
used experience sampling. In her study of eleven musicology undergraduates, INMI
episodes were reported frequently and were often preceded by musical activities. Most
recently Beaman and Williams (2010) reported two experiments, one using a
questionnaire and another involving diaries. Their results revealed considerable
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individual variation in experiences and a reporting bias as the survey respondents
estimated the duration of the INMI episodes longer than the diary keepers.
The current study
This study addresses two research questions. The first question is: Can INMI be
experimentally induced? This concerns whether there are experimental procedures and
manipulations that can produce consistent and statistically verifiable results. If we can
induce INMI in this way, the second question is: What influences the emergence of
INMI? The latter question is here examined using two hypotheses about prior activation
of musical memory. An important assumption of the present study is that involuntary
imagery is similar to voluntary musical imagery except that it is initiated unintentionally
(cf. Bailes, 2006) and tends to recur without effort. The phenomenology of INMI, for
instance saliency, vividness, and musical elements of imagery, is excluded from this
study (but see, Liikkanen, in press).
How to induce INMI?
A new method to induce INMI experiences and gather self-reports is described
here. The method combines two concepts: cued memory recall and mechanisms of
anticipation. Cued recall (e.g. as in Nobel & Shiffrin, 2001) is a general technique for
retrieving memories in which hints are used to assist memory access. For music, cues
such as lyrics or artist photographs are effective for facilitating recall of memories
(Cady, Harris, & Knappenberger, 2008). Anticipation is an important feature of music
cognition and refers to predicting music expected to be heard soon based on external
stimuli (Huron, 2006; Levitin, 2006). It can even be considered as a form of musical
imagery, namely anticipatory imagery. This capacity has been previously used to
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investigate implicit musical memory access in a music perception task, which revealed
increased activation of left auditory cortex during gaps inserted into familiar tunes
(Kraemer et al., 2005). Recently, anticipatory imagery for familiar tunes was associated
with brain activity in the rostral prefrontal cortex (Leaver, Van Lare, Zielinski, Halpern,
& Rauschecker, 2009).
Here, the ideas of cued recall and anticipation were combined in a task that
required participants to complete the lyrics for several popular songs after presentation
of a cue (try completing Obladi oblada… for instance). This is considered as a variant
of the musical image scanning task (Halpern, 1988), in which completing a lyrics recall
task evokes musical imagery for the melody of the song (see also Cady et al., 2008).
Here it was assumed that this memory activation might lead to INMI afterwards.
Because this activation is based on imagery, it is devoid of many acoustic and musical
features of stimuli, for instance intensity and dynamics, that are not salient in auditory
imagery (Hubbard, 2010; Reisberg, 1992), but which would be present in real music and
might be relevant for INMI. This procedure also allows assessing and controlling for the
familiarity with the songs because open-ended completion questions require elaborate
responses.
A third component of the method is delayed reporting of recent conscious
experiences after a distraction. This delay is crucial because it is assumed that if the
participant succeeds in the intentional recall and imagery, then music representations
might be maintained active in working memory. A distractor task with a variable
attentional demand between the phases of the experiment is hence needed to clear out
the working memory. Variable attentional demand is important because we do not know
whether attentional load affects INMI and we do not want to fully suppress involuntary
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imagery of music either. Thus, in the absence of any evidence, we assume that any task
requiring attention, not just musical, could achieve the distraction effect by capturing
the participant’s attention for a while. To report INMI experiences reliably, participants
must be informed about what counts as INMI. In the adapted procedure, the cued-recall
task served as an illustration of musical imagery, and the definition of involuntary
experience was additionally communicated to the participants when the report was
requested.
INMI is a currently poorly understood and unpredictable research subject. To
minimize experimental artefacts due to learning and expectations, a single-trial design
(Baddeley & Scott, 1971) was used. In this case it meant targeting only naive and
independent participants and taking care to disguise the experiment’s real intent. A large
sample of subjects was considered necessary to achieve adequate statistical power. For
these reasons the experiment was implemented in an electronic medium over the
Internet to gather a large, cross-sectional sample (regarding the reliability of web-based
experiments, see Gosling, Vazire, Srivastava, & John, 2004; Honing & Ladinig, 2008;
Skitka & Sargis, 2006).
Hypotheses for the study
Without any hypotheses specific to INMI to be found in literature, the working
hypotheses were derived from related research. Two hypotheses were considered: most
recent activation and prolonged activation. These hypotheses make different predictions
about the effect of processing music on INMI. They are based on two assumptions.
First, processing music by listening to it or imagining it predisposes individuals to INMI
afterwards (cf. Kvavilashvili & Mandler, 2004). Second, we assume that INMI can be
described as a competition of musical representations for auditory attention. This
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auditory attention model is derived from the competition model of visual attention
(Desimone & Duncan, 1995) which claims that only the most strongly activated
memory can capture attention and lead to a conscious experience. Different music
memory representations have their own activation levels that determine their potency.
These levels change over time due to decay and reinforcement, and they largely
determine how easy these memories are to retrieve voluntarily or involuntarily. Note
that this assumption remains neutral about the detailed structure of musical memory
(e.g. Peretz & Coltheart, 2003).
The most recent activation hypothesis is motivated by observations that people
often report that INMI has been preceded by recent music listening or imagining
(Bailes, 2007; also Reik, 1953). This suggests that INMI might be akin to the recency
effect, a robust phenomenon established for short- and long-term memory tasks, e.g.
free recall of lists (see Baddeley & Hitch, 1993; Glenberg, Bradley, Kraus, & Renzaglia,
1983; Howard & Kahana, 1999). In short-term memory tasks it describes the high
accessibility of the most recently processed information, but this effect persists for
learned list representations in long-term memory (Glenberg et al., 1983). The prediction
here is that if several songs are processed in a short period of time, the last song is the
most likely to be later experienced as INMI. This means that a rapid, transient increase
in the activation level of a memory would be a more significant predictor of future
INMI than baseline activity (prestimulus activation level for the memory representation;
see Desimone & Duncan, 1995), assuming decay happens quite quickly afterwards.
The prolonged activation hypothesis claims that consecutive memory
activations for a piece of music build a high activation level that decays relatively
slowly. Thus the recent activations in the past are an important precondition for INMI.
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This hypothesis is derived from research on involuntary memory (Kvavilashvili &
Mandler, 2004), which asserts that the activation of involuntary semantic memories
might be best understood through the concept of spreading and decaying activation in
memory networks over an extended period of time (see also Anderson, 1983). This
hypothesis predicts that among a set of songs recently activated, the song that has built
up most activation over a longer time will most likely trigger an INMI experience. If
this assumption holds, we should be most prone to experience familiar, recently
activated music.
Testing the hypotheses involved designing two experiments. The most recent
activation hypothesis was evaluated by changing the presentation order of musical cues,
which were supposed to trigger voluntary musical memories. A recency effect would be
revealed by inspecting the serial position curve of later reports about involuntary
experiences. The prolonged activation hypothesis was tested by comparing two sets of
cued music, contemporary (Experiment 1) and classic hit songs (Experiment 2). The
prolonged activation hypothesis predicts that contemporary music, which has more
likely been more recently processed (reinforced), should evoke INMI experiences more
often, regardless of the most recent processing order. If the prolonged activation was
unimportant, then there might be a considerable recency effect. To differentiate between
the two, we needed to control for the familiarity of the songs which would likely
correlate with the amount of baseline activation.
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EXPERIMENTS 1 & 2
Method
This section describes the procedure, analysis and general characteristics of
participants for two consecutive and very similar experiments. Experiments differ only
by stimuli. Both experiments 1 and 2 were organized over the Internet. They were
preceded by an online pilot study (N=1553), which tested potential items and scales and
urged people to describe their most recent INMI experiences to generate a database of
“catchy” songs. This input was used to develop the instrument and materials for the two
actual experiments that followed immediately after the pilot.
Participants
I recruited 9967 Finnish Internet users as subjects for Experiments 1 & 2. The
recruitment process started among students in several Finnish universities. They were
contacted by email and urged to participate in the “Music in Mind 2007” study
accessible at the University of Helsinki web server. After the participants had completed
the experiment, they were given the opportunity to invite their personal contacts via
email. This option was used several thousand times and expanded the sample beyond
university boundaries, only 29% of all subjects were university staff or students. For the
reference, 75% of the population in Finland were using the Internet at least weekly in
2007 (Harala, 2007). The participants were assigned to experiments and experimental
groups pseudo-randomly based on the entry date.
The qualified respondents (see analysis subsection) were predominantly female
and right-handed. The mean age was 28 years, ranging from 8 to 75 years. The majority
had some musical training, the median being 1-3 years (see Table 1 for details). A
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minority of subjects (8%) were suffering from hearing loss, neurological disorder, or
were currently under medication affecting the central nervous system. Because these
characteristics did not influence the main dependent variables, these participants were
also included in the study.
INSERT TABLE 1
Stimuli
Anecdotal evidence implies that there are differences between musical pieces in
the capacity to induce INMI. However, there is currently no scientific method to assess
the INMI potential or “catchiness” of a song analytically, hence a statistical approach
was adopted for the selection of stimuli. Songs repeatedly reported to evoke INMI in the
pilot study were chosen as the stimuli for Experiment 1 in an attempt to guarantee
catchiness. In addition, a well-known classic tango that was not repeatedly nominated in
the pilot was selected as a control item (see Appendix A for details). The recency effect
was investigated with a variable presentation order between experimental groups.
Experiment 1 involved two groups and the order of the songs was simply reversed
between them. Data were collected until at least 1000 responses per group had been
acquired.
Procedure
To induce INMI, we used a musical-image scanning task facilitated with cuedrecall. In the task the participants were instructed to complete the next three words of
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lyrics for five Finnish songs, presented in a serial order. Each song was cued using four
or five distinctive words either from the beginning of the song or from the chorus. The
cues were presented next to a text book for inputting the answer. It was emphasized that
the lyrics should be filled in as (or if) remembered and verbatim recollection was
nonessential. This was done to discourage the participants from consulting external data
sources.
The experiments had a six-phase sequence illustrated in Figure 1 and no time
quota. At the start, the participants were briefed regarding the general purpose of the
study (not mentioning musical imagery), the ethics of data usage, and were asked to
provide consent for participation. In the second phase the subjects provided information
about their past and present musical activities. This was followed by the cued-recall task
(third phase).
FIGURE 1
In the fourth phase of the experiment, subjects spent approximately four
minutes completing a filler (distractor) task. This was an important part of the procedure
as it was meant to guarantee that the participants’ attention was taken away from the
recalled music and occupied by something else. The questions probed several unrelated
factors including personality and non-musical involuntary memories. The distractor was
followed by an experience sampling phase. This started with an explanation of what
INMI was, and the respondents were asked if they had experienced INMI (distinct from
cued recall) during the filler phase of the experiment (for similar procedures, see e.g.
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Baddeley & Andrade, 2000; Teasdale et al., 1995). If this had occurred, they were asked
to identify the song among the cued songs or to name some other tune. In the final
phase, background information including retrospective INMI commonality was
gathered and the subjects were debriefed.
Analysis
The data consisting of 9967 records for both experiments were inspected and
refined by applying several rejection criteria. These included an unrealistically short or
long duration of the experiment (less than 2 minutes or more than 30 minutes), repeated
entries from the same individual (duplicate email or IP address), semantic signs of
mischief (foul language) and the lack of intra-individual variation between items. This
excluded 523 subjects, and 135 cases were additionally excluded for missing data. The
next part of the analysis screened the remaining 9267 participants for familiarity with
the stimuli. Only those who had correctly completed lyrics for at least four of the five
songs presented were included, discarding 1794 subjects (1009 for Experiment 1 and
785 for Experiment 2). The steps leading to the final sample (N=7515) are presented in
Table 2.
INSERT TABLE 2
The dependent variables included a familiarity index and a hit percentage for
each song, both calculated over all subjects. The familiarity index represented the
percentage of correctly completed songs (scaled range 0-100%) based on assessment of
each response. As verbatim recall was not requested, the responses were evaluated
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against the gist of the song. The author thoroughly familiarized himself with the correct
lyrics. First, literally correct answers were accepted and then borderline cases were
judged based depending on whether it seemed likely that the person had recalled and
imagined the right song.
The count of reported INMI experiences during the previous phases of the
experiment was transformed into a relative hit percentage probability describing how
often a particular song among all stimuli induced an INMI experience (scaled 0-1). Each
participant could nominate only one song. Statistics were computed in SPSS 15 and in
Microsoft Excel. Only results relevant to the two research questions are reported here.
Other aspects of the data are reported separately (e.g., findings for distractor tasks,
extended background profiles, retrospective INMI reports; Liikkanen, 2008 and in
press) due to space limitations.
Results: Experiment 1
Almost all participants (99.5%) had a history of INMI experiences on at least a
monthly basis. The average familiarity with the stimuli was 65.0%. The threshold of
four correctly recognized songs reduced the number of eligible subjects to 991. Among
them, the INMI induction generally succeeded as over two thirds (68.2%) reported
experiencing one of the cued songs during the experiment (see Fig. 2).
INSERT FIGURE 2
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There were considerable differences in the hit percentages between the songs
(Table 3). However, there was no significant effect of reversed presentation order
(χ2 = 2.90, df = 4, p > .05 for Table 4), although songs A and E both had higher hit
percentages in the final serial position. Thus the induction procedure did not seem to
evoke a recency effect. Based on the assumption that the new stimuli might have strong
prolonged activation levels and thus interfere with the serial position effects, the
stimulus set was changed for the next experiment to include older songs.
INSERT TABLE 3
INSERT TABLE 4
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Experiment 2
Participants
The participants for the second experiment were drawn from the same subject
pool as in the first experiment but at a different time. There were small, but significant
differences in the background variables (see Table 1). On average, subjects in
Experiment 2 were older (by four years), more often male, did not listen to music so
much, were less likely to be associated with a university, and had a lower
retrospectively reported INMI frequency. The significance of the differences will be
assessed later on.
Stimuli and procedure
The procedure and analyses for Experiment 2 were identical to previous
experiment, but as stimuli four out of five contemporary songs were replaced by more
classic ones, including older pop songs, tangos, and the Finnish national anthem (see
Appendix B). An 8-year-old pop song from Experiment 1 remained as a reference item.
The classic songs were expected to be more familiar, but to have lower baseline
activation levels than the contemporary ones. The stimulus sets were created by a listwise permutation of these songs, so that every song appeared once in each serial
position, relative positions fixed (first set: ABCDE, second: BCDEA, etc.). This
produced five distinct experimental groups, and it was assumed that there would be no
interaction effects in the order. Per group, 1400 responses at minimum were acquired.
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Results: Experiment 2
The stimuli of the second experiment were better recognized than those in the
first experiment (average familiarity 88.9%). Among the 6524 qualified participants, an
INMI experience was evoked less often than in the first experiment (binomial test
p < .001) and 49.7% of subjects reported a primed song (see Fig. 2). There were again
substantial differences between the songs in hit percentages (see Table 5A), but now
there was also a difference related to different stimulus positions (χ2 = 91.59, df = 16,
p < .001; for Table 5B).
INSERT TABLE 5
To visualize the difference between different serial positions, the hit
percentages were plotted according to the serial positions. This revealed the curve
displayed in Figure 3, in which the final song position has non-overlapping 95%
confidence intervals with other positions (final position 95% CI 25.6-31.6, CI range for
other positions 15.5-24.0%).
INSERT FIGURE 3
Results: Comparing Experiments 1 and 2
The INMI induction worked clearly better in the first experiment. Is this
evidence in favour of the prolonged activation hypothesis? Do the different background
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profiles explain the difference between the experiments in the success of INMI
induction? To examine this possibility with logistic regression, the background
variables mentioned earlier were first analyzed with a log-linear model to test for
possible interaction effects in predicting INMI reports. No second order or higher
interactions were found for the variables. Next, the dependent variable that expressed
whether the participant had reported a cued song was subjected to a binary logistic
regression analysis without interaction terms. This analysis showed that gender,
retrospectively reported frequency of INMI (see Table 1), age, and the experimental
stimulus set were all independently associated with cueing effectiveness (Table 6).
Hence the difference between the stimulus sets in the capability of inducing INMI was
not only an artefact of a difference in background variables.
INSERT TABLE 6
A final notable result comes from those subjects who indicated that they had
experienced INMI during the experiment, but the song was none of the cued ones (see
Fig. 2). This indicates that these participants comprehended the INMI reporting
question. They were also asked to report how much time had passed since this song had
been listened to, sung, played, or imagined. It was found that approximately one third of
these songs had been activated on the same day, another third on the same week, and the
rest a longer time ago (see Table 7). The fact that in two thirds of the cases songs had
not been heard the same day supports the notion that baseline activation rather than
immediate activation is an important precondition for INMI.
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INSERT TABLE 7
Discussion: Experiments 1 and 2
The results of the two experiments show that in a large and heterogeneous
sample of people, involuntary musical imagery is a recognized and even a quite
common feature of consciousness. Based on the collected self-reports, the adopted
induction procedure worked in most cases, but was dependent upon the stimuli. The
question of how prior activation influences INMI was assessed through a test of most
recent and prolonged activation hypotheses. The newer songs in the first experiment
evoked INMI more often than the older ones of the second experiment. This supports
the prolonged activation hypothesis, indicating that presumably higher baseline
activation facilitates the emergence of INMI for the newer songs.
Experiment 2 provided some support for the recent activation hypothesis by
revealing the existence of a recency effect for INMI. The magnitude of the effect was
subtle, in comparison to differences between the songs. However, the odds for reporting
a cued song over any other song were more than 2.7 fold. This suggests that cueing
remarkably increased the odds for an INMI experience later on, although music outside
the stimulus song set was also reported. The high number of outside songs in
Experiment 2 is puzzling. Many of these songs seemed to be idiosyncratic but some
current hit songs were nominated repeatedly. However, because no control condition
without cueing was included, it is unknown whether or how the cueing task influenced
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INMI for non-cued songs through various musical and non-musical associations (Cady
et al., 2008).
The present data are open to alternative explanations and hypotheses. For
instance, one could argue that the different songs have inherent properties, such as
‘catchiness’ (a musical structure) which operates regardless of the baseline activation
and interacts with transient enforcement. This kind of musical characteristics hypothesis
cannot be ruled out. However, if the musical characteristics were a very strong factor
and not individually idiosyncratic, one could predict that a single song should be
dominant over the other songs (assuming comparable familiarity and baseline
activations). The results of Experiment 1 do not support this prediction, but the second
experiment had a dominating song (D). However, it happened that this particular song
was included in both experiments with statistically constant familiarity level, but had a
high hit percentage only in the second. Even though this song was aged at the time of
the experiment, less time had passed since its radio power play times than for the rest of
the songs. The high hit percentage is more likely explained by a comparatively high
prolonged activation level due to the relative freshness of the song rather than by its
musical characteristics.
Finally, the experiment could be criticized for lack of experimental control.
Maybe the results regarding INMI and the recency effect are an experimental artefact.
What if the participants did not report their involuntary imagery in the reporting phase
but just recalled or recognized the stimuli from the cued-recall phase? There are some
arguments to support our interpretations. First, the instructions did their best to illustrate
the definition of INMI to participants, and the single-trial structure utilized in the
experiment ensured that the data entries are independent. This suggests that the results
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are valid within the constraints of self-reporting. Second, in the sampling phase, the
participants repeatedly reported experiencing songs that were outside the stimulus set,
i.e. had not been cued. This result would have been impossible if the subjects had just
willingly recalled earlier songs. Third, if the subjects had randomly recognized one of
the songs and falsely reported this as an INMI experience, one would expect the results
to show stronger serial position trends (if it were just recall of list items) and less
variation between the songs overall because they were all equally well recalled
(familiarity was controlled). None of these effects was observed in the experiments.
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EXPERIMENT 3
In Experiments 1 and 2, the song cues were presented in a serial order, but no
precautions were taken to ensure that the participants did not return later on to revise
missing or faulty answers. This could have been detrimental for testing the recent
activation hypothesis. Experiment 1 found no recency effect and this was believed to be
linked to the contemporary, less thoroughly known stimuli. A possibility is that
problems in recalling the cued songs may have changed the strategy in completing the
task. For instance, the participants may have initially skipped items and afterwards
returned to revise them. Therefore, in a control experiment (Experiment 3), we
investigated what kinds of strategies are commonly used to complete these tasks.
Method
Participants
Thirty-four undergraduate students engaged in an introductory lesson in
cognitive science were asked to volunteer in a musical memory study. None of them
had participated in the previous experiments.
Material and Procedure
This investigation was carried out using printed materials, identical to the
electronic ones used in earlier experiments including instructions. The experiment was
arranged in a lecture hall and the participants were asked to proceed at their own pace
and focus on their own task. The linear completion of the task was implied, but the
participants were free to complete it in any order. They completed two cued-recall lyrics
tasks involving the songs from Experiments 1 and 2. Immediately after completing each
task, they were asked several questions regarding how they completed the task. These
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probed for tip-of-tongue experiences, adequacy of time, confidence of correct recall, use
of imagery, and perceived proactive interference. Subjects were also asked to rank the
lyrics according to the order of completion. The rank order data were used to infer a
completion strategy. The strategies were classified as linear or non-linear. For instance,
given songs {A,B,C} the rank order {A, B,C} would be a linear strategy, but {B, A, C}
and other permutations would count as non-linear strategies.
Results
Responses showed that nearly all subjects were consciously aware of the
involvement of musical imagery in completing the task (91.9% in agreement), as
expected (Cady et al., 2008; Halpern, 1988). The material in Experiment 2 was wellknown and applying the original qualification criterion (4 of 5 songs correct), 91.9% of
participants qualified. Nearly all of them (86.5%) followed a linear, item-by-item
completion strategy. The songs in Experiment 1 were less well-known. Only a third of
participants qualified, and their usage of a linear strategy dropped to 69.4%. This
within-subjects effect indicated that the completion strategy was influenced by the
familiarity with the songs. This finding called for an investigation regarding whether the
non-linear patterns implied the systematic use of an alternative completion strategy.
The analysis of non-linear patterns showed that the subjects were still
astoundingly orderly in their work. The majority of non-linear patterns (10 of 11)
contained a type of intrusion in which one of the previously skipped songs appeared
later on in a “wrong” position. For example, the song B in a pattern {A,C,D,E,B}.
Among the stimuli of Experiment 2, this intrusion was apparently random, but in
Experiment 1 it was most often the generally best known song C, indicative of a tip-oftongue recall effect. A reversed linear strategy was never used.
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Discussion
Experiment 3 investigated how a cued musical memory task such as used in
Experiments 1 and 2, is commonly performed. The results demonstrate that the
participants relied on musical imagery and predominantly on a linear, item-by-item
completion strategy. However, if the material was more unfamiliar, participants
sometimes chose a non-linear strategy. The significance of this finding for the recency
hypothesis is that the differences in completion strategies create an additional source of
variance for data. This variance might partially explain the lack of a recency effect in
Experiment 1, which utilized stimuli that the subjects were less acquainted with, and
consequently the use of non-linear completion strategies was more probable. However,
the effect was likely attenuated because the familiarity was controlled for and subjects
most unfamiliar with the stimuli were left out. For Experiment 2, the non-linearity was
unlikely to be a problem, because for these stimuli the use of linear response strategies
dominated, and the few non-linear cases were randomly distributed among the songs.
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GENERAL DISCUSSION
Involuntary musical imagery has remained unexplored for a surprisingly long
time. Inspired by the recent advances in studies of involuntary memory, the goal of the
present study was to introduce an experimental research method for assessing INMI.
Results from the three experiments show that the participants could be induced to
experience INMI by first activating their musical memory. We believe that the
induction method will be a useful starting point for future experiments, with some room
for improvements. For instance, controlling the presentation time, sequence, stimulus
familiarity, and selecting cues strategically could enhance the quality of data by
reducing variation. Generally, the study of the topic would be greatly served if one
could get around the necessity of self-reporting, which afflicts all present research
efforts. This is a prospect for future studies using physiological measures of the brain
and body.
Having collected empirical data about INMI, I tried to relate these data to
psychological theories. After introducing a competition model of auditory attention (cf.
Desimone & Duncan, 1995), our question was: If there are several distinct musical
memories activated in a short time window, what determines which musical
representation might gain a competitive edge and be later experienced as INMI? We
presented evidence in favour of two memory-related hypotheses. A recency effect
supporting the most recent activation hypothesis was discovered, but it was too small to
predict the emergence of INMI in the majority of cases. Instead, the evidence is more
compatible with the prolonged activation hypothesis and the notion of long-term
accumulating, or spreading, activation in memory. In other words, INMI is grounded in
the activation levels of permanent memory which are transformed over a longer period
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of time by repeated exposure to music. This indicates that INMI might be a memory
feature distinct from the momentary effect of semantic priming (Lucas, 2000), or
recency (Baddeley & Hitch, 1993; Glenberg et al., 1983), and not predictable from mere
familiarity with music. This means that familiarity with the processed music is not
adequate but (can be) a necessary condition for INMI.
Additionally it was found that processing the same song as a part of two
different stimulus sets changed the resulting hit percentage remarkably, which could be
generally interpreted as compatible with the competence model of auditory attention.
However, as this experiment relied on well-memorized musical material, it must be
noted that musical properties may influence which music can be memorized and how
easily. This would have indirect impact on INMI as well and cannot be ruled out here.
Having argued about the role of permanent memory in INMI, what can we say
more generally about its relation to mind and brain? There are some hints that INMI is a
by-product of human learning mechanisms (Liikkanen, in press), and the biological
foundations of INMI could be linked to consolidation and long-term potentiation
(Malenka & Nicoll, 1999). The tentative evidence for this claim is that just like the
characteristics of general learning capacity and memory performance (Addis, Wong, &
Schacter, 2008; Burke & MacKay, 1997), the disposition to INMI has been shown to
decrease with aging (Bennett, 2003; Liikkanen, 2008; see also Schlagman,
Kvavilashvili, & Schulz, 2007). However, addressing this question thoroughly will
require longitudinal studies. Even if this mnemonic proposition turns out to be true, it is
uncertain whether INMI is functional or epiphenomenal with regard to musical memory
(cf. Pylyshyn, 2002), i.e. is the experience of INMI necessary for normal memory
function or not.
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One could criticize the aims of this experiment and ask whether it is not against
the very nature of INMI that it should be controlled, i.e. experimentally induced? Is
INMI induction not a conceptual paradox? The way I see it, it is appropriate to try to
induce INMI because it is defined as an involuntary phenomenon. There is a difference
between an involuntary memory recall and automatic (internal regulation), controlled
(voluntary regulation), or spontaneous (no regulation) memory recall. This could be
compared to administration of a skin paste that contains a possibly irritating agent and is
expected to cause rash later on. The appearance of rash is neither automatic, nor
controlled, nor spontaneous, but if rash can be observed and reported reliably then we
have a method for inducing it, even if we do not understand the causal mechanisms in
detail. Following the same logic, INMI induction is a valid approach if we can rely on
the measurement of outcome.
In conclusion, the present study confirmed that experimental research can
investigate INMI and test related hypotheses. The present findings are still preliminary
and follow-up studies with musical stimuli and controlled long-term exposure are
needed. The validity of induction methods should be established and the
phenomenology of “induced” vs. “spontaneous” INMI experiences should be studied.
Future theories should elaborate the relation of INMI to the conceptions of attention,
memory, and consciousness (Brown, 2006). The present results suggest that high
baseline activation combined with transient enforcement is an important precondition
for INMI and neither of the components alone is enough. In other words, it is not simply
the latest song that we have on our minds, the songs of Yesterday count as well.
AcknowledgementsI thank all people who helped me in developing this paper,
including Markus Mattsson, Sinikka Hiltunen, Irma-Leena Notkola, Antti Oulasvirta,
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Sirke Nieminen, Jari Lipsanen, Heikki Summala, and Tuukka Sandström. Otto Lappi
helped to organize Experiment 3. The contribution of volunteer participants was
immeasurable and the final form of the paper owes much to the comments of
anonymous reviewers and Bruno Repp. The publication process was supported by
Academy of Finland research project Musiquitous. The results discussed in this paper
were initially presented at the 7th Triennial Conference of European Society for the
Cognitive Sciences of Music (ESCOM 2009).
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TABLE CAPTIONS
TABLE 1
Background characteristics of the qualified participants in Experiment 1 and 2.
TABLE 2
Analysis of discarded data, showing the steps leading to the final sample size
TABLE 3
The songs of Experiments 1 and 2 and their average familiarity indexes
calculated over all subjects and overall hit percentages among qualified subjects
reporting a cued song.
Note. The song D1 was the same in both experiments.
TABLE 4
Hit percetanges for the different stimuli songs utilized in Experiment 1 for two
experimental groups, which had a reversed presentation order. Data are arranged
by stimulus position, cue identities in parentheses.
TABLE 5
Hit percentages for the stimuli utilized in Experiment 2. The table is organized
by different serial positions, cue identities in parentheses.
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TABLE 6
Results of a binary logistic regression analysis. Factors that explain the
difference in reporting a cued song as INMI as a function of gender, previous
INMI experiences, age, and different set of stimuli (Experiment 1 or 2).
Statistics include square and standard error for the beta coefficient (B^2 and S.E.
respectively).
TABLE 7
The frequencies of reports to how long ago did the participant say they had
heard, imagined, or performed music that they reported as the most recent INMI
experienced in cases where this song was none of the cued ones.
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TABLE 1
Exp. 1
(N=991)
Exp. 2
(N=6542)
Overall
(N=7515)
Exp. 1
Singing, playing or composing
77.5 %
70.5 %
71.4 %
Not at all
36.8 %
22.5 %
29.5 %
28.6 %
Monthly or seldom
12.9 %
Weekly
26.1 %
23.7
28.2
27.7
Daily, < 2h
17.5 %
Mean age
Daily, > 2h
6.7 %
Handedness
Music listening activity
Right
89.4 %
89.6 %
89.6 %
Daily, > 2h
68.9 %
Left
7.5 %
6.9 %
7.0 %
Daily, < 2h
22.8 %
Ambidext.
3.1 %
3.5 %
3.4 %
Weekly
8.2 %
Monthly or never
0.2 %
Retrospective evaluation of INMI frequency in daily life Music studies in the past
Several times a day
33.7 %
26.3 %
27.3 %
None
35.7 %
Every day
37.3 %
33.7 %
34.2 %
< 1 years
16.8 %
Weekly
24.7 %
32.6 %
31.6 %
1-3 y.
22.9 %
Monthly
3.8 %
5.5 %
5.2 %
4-10 y.
8.8 %
More seldom or
0.5 %
1.9 %
1.7 %
10-15 y.
2.6 %
never
>15 y.
13.3 %
Sex
Women
Men
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Exp. 2
Overall
35.4 %
13.8 %
27.6 %
16.9 %
6.3 %
35.6 %
13.7 %
27.4 %
17.0 %
6.4 %
53.7 %
29.8 %
14.6 %
1.9 %
55.7 %
28.9 %
13.8 %
1.6 %
29.6 %
18.4 %
25.2 %
10.7 %
4.9 %
11.1 %
30.4 %
18.2 %
24.9 %
10.5 %
4.6 %
11.4 %
All rights reserved
TABLE 2
All entries
-Rejected:duration, duplicates, mischief
Eligible candidates
-Rejected: less than 4 songs recognized
-Rejected: missing response to INMI song identity
Valid participants familiar with stimuli
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Percent of
All Entries
All
9967
523
9444
94.8 %
1794
135
7515
75.4 %
Exp. 1
2172
161
2011
1009
11
991
Exp. 2
7795
362
7433
785
124
6524
All rights reserved
TABLE 3
Song
A1
B1
C1
D1
E1
Author version
Experiment 1
Contemporary
Familiarity Hit rate
(N=2172)
(N=675)
0.573
11.3 %
0.497
21.0 %
0.871
20.4 %
0.781
8.7 %
0.526
38.5 %
Song
A2
B2
C2
D1
E2
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Experiment 2
Classics
Familiarity Hit rate
(N=7795) (N=3231)
0.972
2.8 %
0.942
13.6 %
0.787
27.8 %
0.768
50.5 %
0.975
5.4 %
All rights reserved
TABLE 4
Position
1
2
3
4
5
Author version
Group 1
(A1) 9.6 %
(B1) 22.2 %
(C1) 21.0 %
(D1) 7.8 %
(E1) 39.3 %
Group 2
(E1) 37.7 %
(D1) 9.6 %
(C1) 19.9 %
(B1) 19.9 %
(A1) 12.9 %
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Mean
23.2 %
15.5 %
20.0 %
13.6 %
25.4 %
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TABLE 5
Order
First
Second
Third
Fourth
Last
Group 1
(A2) 2.8 %
(B2) 13.1 %
(C2) 27.6 %
(D1) 48.4 %
(E2) 8.0 %
Author version
Group 2
(E2) 5.7 %
(A2) 1.4 %
(B2) 10.3 %
(C2) 22.1 %
(D1) 60.6 %
Group 3
(D1) 46.6 %
(E2) 5.7 %
(A2) 2.2 %
(B2) 11.0 %
(C2) 34.6 %
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Group 4
(C2) 30.2 %
(D1) 44.4 %
(E2) 3.9 %
(A2) 3.0 %
(B2) 18.5 %
Average
Group 5
(B2) 15.1 %
20.9 %
(C2) 25.4 %
18.4 %
(D1) 51.2 %
19.5 %
(E2) 3.7 %
19.4 %
(A2) 4.5 %
28.6 %
All rights reserved
TABLE 6
95% CI for B^2
Independent
variable
Sex
Retrospective
INMI frequency
Stimulus set
Age
Author version
B
0.5392
B^2
1.7146
S.E. B
0.0522
p
< .001
Wald
106.55
Lower
1.5478
0.2903
-0.7533
0.0127
1.3368
0.4708
1.0127
0.0251
0.0741
0.0030
< .001
< .001
< .001
133.80
103.47
17.61
1.2727
0.4072
1.0068
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Upper
df
1.8995
1
1.4042
0.5443
1.0187
1
1
1
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TABLE 7
Less than twenty minutes
A few of hours
Today
This week
Longer time ago
Cannot tell
N
Author version
Exp. 1
8.1 %
10.2 %
20.4 %
34.3 %
18.7 %
8.1 %
626
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Exp. 2
6.2 %
6.3 %
14.9 %
30.0 %
29.9 %
12.6 %
2997
Total
6.5 %
7.0 %
15.9 %
30.7 %
28.0 %
11.9 %
3623
All rights reserved
FIGURE CAPTIONS
Figure 1. Flowchart of the six phase procedure used in Experiments 1 and 2.
Minutes indicate estimated average completion times for each phase among
qualified participants.
Figure 2. Success of induction procedure in the two experiments. Vertical bars
display percentages of people reporting a cued song, some other song or no song
in the experience sampling phase. The error bars denote 95% confidence
intervals for the hit percentages.
Figure 3. Results of the INMI induction Experiment 2. The figure illustrates the
average hit percentages over all songs relative to the serial positions (N=3242).
Error bars denote 95% confidence intervals for the hit percentage.
f
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1. Briefing &
Consent
~1 min.
2. Musical background
~2 min.
3. Induction procedure
(cued-recall)
a) Somewhere over the…
b) Obla-di, obla-da, life…
c) Rudolf the Rednosed…
etc.
(examples not real)
~1 min.
4. Filler task
~4 min.
5. Experience sampling
for INMI
~1 min.
6. General background
& Debriefing
~1 min.
Figure 1.
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Percentages of participants reporting INMI
80%
Cued
song
68.2%
70%
60%
Other
song
49.7%
50%
None
40%
32.0%
30%
18.6%
20%
18.3%
13.2%
10%
0%
Exp. 1 Contemporary (N=991)
Exp. 2 Classics (N=6524)
Figure 2.
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35%
Average hit rate
30%
Hit percentage
25%
20%
15%
10%
5%
1
2
3
Serial position
4
5
Figure 3.
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All rights reserved
Appendix
Table A. Songs and presentation orders in Experiment 1.
Composer
Title
A Linna K.
Kultainen Nuoruus
B Sjöroos J.
Joku Raja
C Vuorinen M. &
Leave Me Alone
Huttunen M.
D Kolehmainen M. Lopeta
E Virtanen T.
Pokka
Presentation order
Group 1
A, B, C, D, E
Group 2
E, D, C, B, A
Genre
Tango
Contemporary rock
Contemporary pop
First
release
1949
2007
2007
Contemporary pop
Contemporary rock
1999
2007
Table B. Songs and presentation orders in Experiment 2.
Composer
A Pacius, F.
B Nieminen P.
C Markkula R.
D Kolehmainen M.
E Mononen U.
Stimulus sets
Set 1
Set 2
Set 3
Set 4
Set 5
Author version
Title
Maamme (National
Anthem of Finland)
Autiotalo
Sä Kuulut Päivään
Jokaiseen
Lopeta
Satumaa
Genre
Classic
First
release
1848
80’s rock
Tango
1984
1972
Contemporary pop
Tango
1999
1955
A, B, C, D, E
E, A, B, C, D
D, E, A, B, C
C, D, E, A, B
B, C, D, E, A
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