Dementia and music: a promising connection.

By Caroline Harbison, Eleanor Matthewman, Eimear North, Miriam Olsen, Amy Rakei


We are living longer, that is a fact! In the last 20 years, the average life expectancy in the UK has increased from 78- to 81-years-old, mainly due to advancements in medicine, nutrition and lifestyle. But living longer comes at a cost. This improved life expectancy has caused additional strain on our physical and mental health, and consequently an increase in neurodegenerative conditions such as dementia. Dementia, a syndrome primarily associated with the aged population, is characterised by a decline in brain function. Dementia affects millions of sufferers and families worldwide with cases rising year on year. There are currently around 850,000 people living with dementia in the UK alone. 

Researching the brain is highly complex so let’s dig into the science briefly. As we get older, proteins, which are an essential part of every living organism, can become pathogenic (disease-causing). A healthy functioning brain relies on neurotransmitters, chemical messengers associated with the communication of brain cells, and proteins for brain stability and health. This intelligent organ uses neural proteins for predictive coding, a basic function to predict sensory input such as hearing, to accelerate a specific response and reduce reaction time. However, sometimes pathogenic neural proteins can lead to broken neural pathways causing common dementia symptoms. The big question of what pathogenic proteins are associated with different dementia types is still poorly understood, making early diagnosis difficult.  

There are numerous types of dementia, the most common being Alzheimer’s Disease (AD), which involves the loss of episodic memory: memory of events, situations and experiences. Frontotemporal Dementia (FTD) is a less common form of dementia, characterised by problems with behaviour and language. Subtypes of FTD include bvFTD, nfvPPA and svPPA, involving behavioural change, speech production difficulties and loss of semantic knowledge (aphasia), respectively (Alzheimer’s Society, n.d.). Unfortunately, there are no treatments that can cure these diseases, or stop the degeneration. However, there are medications available that can lessen symptoms and slow progression. Early diagnosis allows patients to receive the right treatment and support. Currently, there is no “go-to” method of diagnosing specific types of dementia, especially early in disease progression, but scientists are working tirelessly on developing innovative tools to make this possible. One such tool showing incredible promise for early diagnosis is music.

While some cognitive functions may be lost in patients with dementia, the widespread neural complexity of music processing means it is less susceptible to progressive damage. Music can be used both recreationally and in clinical settings to soothe dementia patients. Music therapy can be used to treat and ease symptoms while also being very enjoyable for the patients. People with dementia participate in music-making sessions, by either singing, listening to music or playing an instrument. Researchers Wall and Duffy (2010) analysed the benefits of music therapy and found it can reduce anxiety and aggression, restore cognitive and motor functions and generally improve quality of life. 

Music is useful in dementia research for several reasons (Benhamou and Warren, 2020). Firstly, music is highly codifiable and it involves the whole processing hierarchy of the brain (Peretz & Coltheart, 2003), allowing more neural connections to be utilised. Secondly, no musical training is necessary. Finally, music has the power to cut through cultural and language barriers and can evoke strong physiological responses which are easy for researchers to measure (Carpentier & Potter, 2007; Landreth & Landreth, 1974). For these reasons, Elia Benhamou, a clinical neuroscientist at the Dementia Research Centre at University College London, uses music as a tool to probe behavioural and physiological changes due to the deposition of pathogenic proteins in different forms of dementia and make early diagnosis easier.

When we listen to a piece of music, our brain generates expectations to which incoming information can be compared on multiple levels. Benhamou’s research (Benhamou et al., 2021) examines how these predictive cognitive processes may be impaired in AD and FTD patients. Although their behavioural responses to music have previously been measured (Johnson & Chow, 2015), Benhamou also measured pupil responses as an additional physiological parameter, thus providing additional information about the characteristics of each syndrome. In an experiment studying musical expectations based on prior knowledge, participants were exposed to a range of familiar melodies where a single note was replaced by white noise, an out-of-key note or a different in-key note. Whereas AD patients showed similar responses to the control group, FTD patients showed impaired musical surprise processing on both a syntactic and semantic level. nfvPPA patients were particularly interesting as, in contrast to other FTD patients, they displayed slightly enhanced pupil responses for all melodic deviants, indicating this syndrome exhibited different behavioural and physiological profiles of musical surprise processing. A second experiment focusing on the tracking of deviations in unfamiliar melodic sequences revealed nfvPPA patients were still able to successfully track and identify melodic deviations through processes of statistical learning, whereas other FTD patients showed different levels of impairment both in the behavioural and physiological responses. These findings can help us create pathological profiles relating to musical surprise processing for these different dementia syndromes, which could eventually become a useful tool for early diagnosis. 

Benhamou’s research has contributed to a deeper understanding of the behavioural and physiological differences in these types of dementia. Her research brings us one step closer to earlier diagnoses and a more accurate stratification of dementia. She has also shownusing music instead of language (which becomes impossible in patients with aphasia) provides an enjoyable, engaging and relaxing experience for dementia patients.  Benhamou and colleagues are breaking new ground and hoping to develop an intervention for patients with Alzheimer’s Disease, Parkinson’s Disease, and aphasia via a new app. This app will incorporate music tests and will be personalised to each specific syndrome and stage of the disease, allowing for the close tracking of behavioural changes. Music is a significant outlet for many people, especially when the world around them is becoming ever more confusing. When language is no longer accessible and friendly faces become unfamiliar, music can provide solace, which is precisely why research into dementia and music, such as Benhamou’s, remains as relevant and important as ever.

References
Alzheimer’s Society—United Against Dementia. (n.d.). Retrieved 10 April 2021, from https://www.alzheimers.org.uk

Benhamou E., Warren J. D. (2020). Disorders of music processing in dementia. In L. L. Cuddy, S. Belleville, A. Moussard (Eds.), Music and the Aging Brain (pp. 107-149). Academic Press.

Benhamou E., Zhao S., Sivasathiaseelan H., Johnson J. C. S., et al. (in press). Decoding expectation and surprise in dementia: the paradigm of music. Brain communications.

Benhamou, E. (2021). Predictive cognition in dementia: The case of music [PhD Dissertation]. University College London.

Carpentier, F. R. D., & Potter, R. F. (2007). Effects of music on physiological arousal: Explorations into tempo and genre. Media Psychology, 10(3), 339-363. https://doi.org/10.1080/15213260701533045

Johnson, J. K., & Chow, M. L. (2015). Hearing and music in dementia. Handbook of Clinical Neurology, 129, 667–687. https://doi.org/10.1016/B978-0-444-62630-1.00037-8

Landreth, J., & Landreth, H. (1974). Effects of music on physiological response. Journal of Research in Music Education, 22(1), 4-12.  https://doi.org/10.2307/3344613

Peretz, I., & Coltheart, M. (2003). Modularity of music processing. Nature Neuroscience, 6(7), 688-691. https://doi.org/10.1038/nn1083

Sacks, O. (2007). Musicophilia: Tales of Music and the Brain. Knopf.

Wall, M. and Duffy, A. (2010). The effects of music therapy for older people with dementia. British Journal of Nursing, 19(2), 108-113. https://doi.org/10.12968/bjon.2010.19.2.46295

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The unforgettable melodies – Can music help us understand how memories form?

By: Viviana Caro, Annina Huhtala, Henry Lee, Andrew McNeill, Kate Schwarz

“Your memory is a monster; you forget – it doesn’t. It simply files things away”, wrote John Irving in his enticing novel A Prayer for Owen Meany. But how do memories form in the first place? And could the storyteller be right, does our brain store more than we can actively evoke? 

According to current understanding in neuroscience, we are tracking our environment at a rate of milliseconds, whether it be what we see, touch, taste, smell, or hear. This process is fully automatic, mostly unconscious, and we can’t switch it off, as it has evolved to keep us safe. When we take a walk in a park, our brains keep calculating probabilities about what will happen next and compare the present moment to past experiences. When we hear footsteps from behind, we assume they belong to a runner, not to a hungry beast, and we keep calm. It seems that sensory data is not something we actively remember, but it’s stored in our long-term memory.   

Neuroscientist Roberta Bianco is shedding light to these mechanisms with the help of music. In her recent study, she tested participants with soundtracks that included rapid, only milliseconds-long, sound sequences, to see whether people form long-term memories by just being exposed to auditory stimuli. The results? People detected these very brief patterns in novel music excerpts even after seven weeks of first hearing them. Bianco’s research confirms the idea that humans have the ability to build models from sensory input.

For researchers to better understand music perception, they have investigated how we encode and store music in our memory. Most forms of music have sequences and patterns that contain groups of notes and rhythms. Whenever we hear music, our auditory system does a great job at recognising these patterns and spotting any unexpected notes or chords. This effortless processing is called statistical learning, and it affects how we listen to and memorise music. We implicitly learn ‘normal’ sequences and patterns in music and build predictive models to estimate what will happen next and to notice irregularities.

In a study by Koelsch and colleagues, a group of participants, who were right handed non-musicians, passively listened to two chord progressions while the electrical activity in their brains was recorded using electroencephalography, EEG. The chord progressions ended in either an expected chord or unexpected chord. In the example below, the last chord of the second progression is a D flat major chord within a C major chord progression, which is unexpected. The graph shows that when a chord violates Western music theory rules, the brain notices.Screen Shot 2020-04-10 at 12.15.45 PM

In the experiment, participants’ brains showed a strong, negative response to the incongruent endings. The incongruent chord being a violation to the progression they expected. 

In a recent study, Bianco and colleagues had pianists play a chord sequence without hearing a sound. The results showed that the incongruent endings activated temporal-frontal networks, which are brain areas associated with memory, even in silence – demonstrating that the brain stores a meticulous representation of patterns in memory. To build strong predictive models, our brain needs long term exposure to melodic patterns. Our brain encodes and groups the information into tiny ‘storage units’ or n-grams. The more we get exposed to a specific melodic pattern, the stronger and more salient the n-grams become, incurring in fast retrieval of information. Most memories decay when time passes, but Bianco’s work indicates that when models are reinforced, they last longer despite memory decay.

How precise are these predictive models then? To understand how reliable our memory really is, Bianco and colleagues exposed participants briefly to melodic patterns and then tested how well they could recall them. Participants could recognise some patterns, but in most cases the results were relatively poor. Bianco then tested reaction times to recurring melodies. Results showed that repeating patterns were recognised much faster. For Bianco, this lack of correlation between familiarity and reaction time indicates a dissociation between what we remember implicitly and the degree of which we can explicitly recall. It seems that our cautious brain preserves as much information as possible, even if that information is not relevant to the task at hand, and stocks it away in long-term memory. It does this to protect the capacity of our short term memory. If short term memory gets saturated, we are not able to adapt and control our behaviour in the present moment; therefore, storing information in the long-term memory is a way to economise cognitive resources.

For how long does our long-term memory store information? Bianco and her group set up an experiment where listeners heard both novel music excerpts which had planted in them musical sequences that they had heard seven weeks before. Incredibly, the participants recognised the previously heard patterns, which lasted a matter of milliseconds, even after seven weeks! 

Bianco’s research in music helps us to gain more understanding of how memory works. It’s fascinating how hearing patterns, and pattern violations, can lead to the brain effortlessly constructing a model that is sensitive in detecting and identifying repeating structures. Of course, the implications of Bianco and her group’s research is far reaching. Understanding the way our brain preserves sequential information, and the way it deteriorates could be essential in the application of therapeutic medicine for those who have cognitive impairment. 

Our brain is very much like a computer; it can create and update complicated models. In addition, it can pick up data actively and store it in our passive memory bank just in case we need it again. Our brain is also a bit like a jukebox player, that collects and archives all the songs and sounds from its environment. There is no disputing the facts however that this computer and jukebox give us the tools to make sense of our environment and make decisions about the world around us. After all, there is also some truth to how our memory is a monster, but there’s still a lot we don’t understand about this particular monster. Perhaps we should, ultimately, it’s our beautiful monster that we’re taking care of. 

References:

Bianco, R., Harrison, P. M. C., Hu, M., Bolger, C., Picken, S., & Marcus, T. (2020). Long-term implicit memory for sequential auditory patterns in humans. BioRxiv, https://doi.org/10.1101/2020.02.14.949404.

Cowan, N. (2008). What are the differences between long-term, short-term, and working memory?. Progress in Brain Research, 169, 323-338.

Conway, C. M., & Pisoni, D. B. (2008). Neurocognitive basis of implicit learning of sequential structure and its relation to language processing. Annals of the New York Academy of Sciences, 1145, 113–131. https://doi.org/10.1196/annals.1416.009.

Daikoku, T. (2019). Statistical learning and the uncertainty of melody and bass line in music. PloS One, 14(12), E0226734. 

Koelsch, S., Gunter, T. C., Wittfoth, M., & Sammler, D. (2005). Interaction between syntax processing in language and in music: An ERP study. Journal of Cognitive Neuroscience, 17(10), 1565–1577. https://doi.org/10.1162/089892905774597290.

Tillmann, B., Bigand, E., & Bharucha, J. J. (2000). Implicit Learning of Tonality: A Self-Organizing Approach. Psychological Review, 107(4), 885–913. https://doi.org/10.1037//0033-295X.107.4.885.

 

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Music: The Comparable Power to Attract and Repel

By Ceren Ayyildiz, Alicia Kelleher-Clarke, Anthi Georgiadou, Alex Weber, Sean-Lee Duncan

Aesthetic Judgement: An Historical Context

Have you ever wondered how a piece of operatic music can bring one person to tears and yet make another want to obliterate the source from which the sound is emanating? Or how a pumping EDM track can make one feel as though they are on top of the world and yet make another feel as though they’re going insane? Undoubtedly, these are situations we have all experienced. But do we ever give much thought to the mechanisms underlying such stark contrasts in emotional response? You might say “we are all different and therefore have different tastes” and, whilst this is true, does it then follow that musical quality cannot be objectively measured? Or when one makes a self-assured proclamation that he or she has no musical taste, can it be proven? Or is itsimply a matter of subjectivity? Can our various aesthetic judgments and emotional responses to music be tested systematically?

These questions belong to the branch of philosophy known as aesthetics – the study of the nature of beauty and taste. The past few centuries have raged with debate to this end. 18th-century philosophers, Hogarth and Kant, did not believe music to be worthy of aesthetic consideration, arguing that instrumental music lacked moral purpose (Hogarth, 1753; Kant, 1781). The 19th-century ‘War of the Romantics’ saw the emergence of formalism, which asserts that a composition’s meaning is solely dependent on its form. 21st-century scholars, such as Holland and Sarath, proposed contemporary music, such as jazz improvisation, could serve as a model for understanding society (Holland, 2008; Sarath, 2013). And the topic continues to be researched and ruminated upon to this day.

Do aesthetic judgements and emotions interact? In a nutshell, perhaps not.

Increasingly, studies investigate brain structures and neural connectivities associated with perceived emotions whilst listening to music. However, far less is known about the effect of an explicit act of judgment on the neural processing of the pleasantness of an emotional music (Liu et. al., 2017). Emotion priming studies have shown conflicting results, reporting both negative and positive aesthetic experiences with exposure to different pleasurable and non-pleasurable music. For instance, one research showed strong subjective positive emotion and peak pleasurable responses to music, such as shivers, via measuring heart rate and skin conductance (Grewe et al., 2009). In Egermann and Reuben’s 2020 study, which will be discussed in further detail, the researchers were unable to establish a significant link between aesthetic judgement and emotional connection to contemporary music.

Here we can reflect upon the merits of repeated gradual exposure, one of the fundamental mechanisms of enculturation and acquisition of taste. Could the same fundamental principle be attributed to contemporary music, which is oftentimes idiosyncratic? It could be said that these heuristics are largely determined by what the individual grew up hearing. On the other hand, they might be dependent on the environmental and attentional factors in various contexts, such as one’s attention and liking of a piece of music may change while being in a restaurant with friends than themselves being alone in their rooms with narrower attention. Hence, the same music has both comparable power to attract and repulse (Maurer, 2020).

“Beauty is how you feel inside”: Concert as Artistic Frame by Hauke Egermann and Federico Reuben (2020).

 One thing that is mostly and clearly established is that music is an art form that elicits strong emotional responses (Koelsch, 2010). This phenomenon motivated Egermann and Reuben’s 2020 study into the relationship between aesthetic judgement and emotional responses in 20th-century contemporary music.

Egermann and Reuben (2020) chose 20th-century contemporary music as the stimulus for their study, due to its recognised polarising emotional responses in listeners. What better stimulus to investigate the link between aesthetic judgements and psychophysiological response measures of emotions? One of the key features of contemporary music (and an element of musicology, which Egermann has researched extensively) is its defiance of listener’s expectations. Expectations are formed based on our past experiences and on the assumption that relevant occurrences would take place in the future (Skarada, 1989). With regards to music, expectations help provoke emotions, either positive or negative (Steinbeis et al., 2006). In other words, emotions are triggered when musical expectations are fulfilled or suspended. If expectations are fulfilled, listeners relax; whereas unexpected twists and turns elicit feelings of tension.

Egermann and Reuben (2020) ran two experiments to evaluate various levels of aesthetic judgements in participants. Emotional responses were quantified using self-report questionnaires on emotional experience and measures of peripheral nervous system stimulation. To evoke various levels of aesthetic judgments, one group of participants listened to an informative pre-concert talk on aesthetic appreciation of 20th-century music, whereas the other (control) group listened to a non-musical topic. Subsequently, all participants attended performances of contemporary works, such as Karlheinz Stockhausen’s “Klavierstück IX” (Figure 1).

Figure 1. Stockhausen, Karlheinz: Klavierstück IX (Audio + Score) – YouTube. 

Egermann and Reuben (2020) were able to establish that aesthetic judgment could be categorised into sub-factors, as shown in Table 1.

Sub-FactorsAs Related to Aesthetic Judgement
1. AnalyticalCognitive encounter with the music, such as showing interest and skill 
2. SemanticFundamental meaning of the music, such as transferring a message 
3. Tradit AestheticConnects with traditional viewpoints of aesthetics e.g. beauty
4. TypicalitySuitability of the piece of music to earlier notions of music and its typicality
Table 1. Sub-factors of Aesthetic Judgement as identified by Egermann and Reuben (2020).

Ultimately, Egermann and Reuben (2020) found no significant effect of the ‘trigger’ pre-concert talk about aesthetic judgement on emotional responses to the contemporary music performances; participants in each group reported similar levels of emotional valence, which was ratified by physiological tests of arousal. This can only mean that there is plenty more research to be done on the effects of aesthetic judgement on musically-induced emotions!

Summary

Sociologically, we refer to one’s pattern of aesthetic choice as taste. Taste, as an abstraction, allows us to grapple with aesthetic judgements within a larger cultural framework. Egermann and Reuben (2020) investigated the way in which we grapple with aesthetic judgement in a musical context. They pointed out that Analytical, Semantic and Typicality values have effect on how we perceive the aesthetic value of music in our own way, and correspondingly, how they affect our emotions. Contemporary music contains a number of challenging components that can be categorized and measured, but we might experience these challenges more holistically – ‘I just don’t get it,’ we may say.  While many who don’t love classical or contemporary music might feel that those who do reside in an ‘ivory tower’ or are stuffy, other art forms are accused of not being sophisticated enough. There is still much to consider about how these cognitive mechanisms work. It seems we will continue to argue the merits of our favourite art with friends and family for some time.

References

Antokoletz, E. (2016). A History of Twentieth-Century Music in a Theoretic-Analytical Context. London: Routlege.

Egermann, H. R. (2020). “Beauty is how you feel inside”: Aesthetic judgements are related to emotional responses to contemporary music. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.510029

Gerger, G. P. (2019). Does Priming Negative Emotions Really Contribute to More Positive Aesthetic Judgments? A Comparative Study of Emotion Priming Paradigms Using Emotional Faces Versus Emotional Scenes and Multiple Negative Emotions With fEMG. Emotion, 19(8), 1396-1413.

Grewe, O., Nagel, F., Kopiez, R., & Altenmuller, E. (2007b). Listening to music as a re-creative process-Physiological, psychological and psychoacutical correlates of chills and strong emotions. Music Perception, 24, 297-314.

Hogarth, W. (1781). The analysis of beauty: Written with a view of fixing the fluctuating ideas of taste. Georg Olms Verlag.

Holland, E. (2008). Jazz improvisation: music of the people-to-come. Deleuze, Guattari and the Production of the New.

Kant, I. (1781). Critique of Judgment. Hackett Publishing.

Koelsch, S. (2010). Towards a neural basis of music-evoked emotions. Trends in Cognitive Sciences, 14(3), 131-137.

Liu, C. B.-J. (2017). Effect of Explicit Evaluation on Neural Connectivity Related to Listening to Unfamiliar Music. Frontiers in Human Neuroscience, 11(611).

Maurer, C. a. (2020). Pretty Ugly: Why we like some songs, faces, foods, plays, pictures, poems, etc., and dislike others. Cambridge Scholars Publishing. .

Nyman, M. (1999). Experimental Music: Cage and Beyond. Cambridge: Cambridge University Press.

Sarath, E. W. (2013). Improvisation, creativity, and consciousness: Jazz as integral template for music, education, and society. SUNY Press.

Skarada, C. (2006). Alfred Schutz’s Phenomenology of Music Understanding The Musical Experience (ed. Smith). Gordon and Breach, 43-100.

Steinbeis, N. K. (2006). The Role of Harmonic Expectancy Violations in Musical Emotions: Evidence from Subjective, Physiological, and Neural Responses. Journal of Cognitive Neuroscience, 18(8), 1380-1393.

Stockhausen, Karlheinz [Contemporary Classical]. (2020, May 20). Stockhausen – Klavierstück IX (Audio + Score) [Video]. YouTube. https://www.youtube.com/watch?v=KGlp0XSCKu0&ab_channel=ContemporaryClassical​​​​​​​.

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Rhythms Around The World

By Alice Bowmer, Stella Betton, Alfie Lyon-Ray, Lisbeth Sorensen and Jordan Roche

Rhythm is a universal experience that most people associate with sounds and movement. For example our heart beats with a pulse, we walk and dance to a beat and our music is made up of lots of different rhythms which can be really complex! In order to understand the structure of these difficult musical rhythms we have to combine our ‘now’ experience with our previous knowledge which is then woven together internally by our brains. Amazingly, despite the wide variety of musics found across the world, there are a few patterns of rhythm that seem to appear in most of the world’s cultures:

1:1:1; 2:1:1; and 1:1:2 (the rhythm pattern when you sing “Jingle Bells”).

Researcher, Nori Jacoby and his colleagues have been mapping how musical rhythms are represented in different people across 36 different places of the world. So far, they’ve found some unusual and complex rhythm ratios in Mali (2:3:7) and Uruguay (3:4:9) and some other surprising findings – all of the students they worked with seem to be heavily influenced by pop music!

This map shows where Nori’s team have learnt about different peoples’ rhythm perception:

Globally, the team have shown that there are some rhythmic ratios or patterns that seem to be more easily understood and used by people more often than others e.g. 1:1:2, 2:1:1 and 1:2:1. In western classical music these ratios are written like this:

1:1:2
2:1:1
1:2:1

Generally, rhythm perception is quite difficult to explain using words, even when people speak the same language! So to avoid this problem and the extra hurdle involved with language translation, the team used a ‘Chinese whispers’ like tapping task to explore what rhythms people were perceiving. The idea was that participants begin by hearing an uncommon rhythm and they are then recorded trying to tap it back. Their reproductions are then played back to them (unwittingly) as the ‘new’ stimuli, and eventually, after lots of trials, their response becomes a more common rhythm, or what Nori calls a “perceptual prior”.

However, whilst this novel tapping task seems to cleverly identify the different natural rhythm patterns present across cultures, the task isn’t purely measuring what rhythms people hear – it asks them to tap the rhythm as well, which technically means they are measuring perception of production! To overcome this methodological problem the team explored a few control conditions which you can learn more about in papers published by Jacoby and McDermott (2017). It has also been suggested that some people might feel more comfortable using their own musical instrument which responds in a way they would be used to. It’s possible that this way of measuring might give the researchers more accurate rhythm responses than tapping, but new problems in terms of the different attack times of multiple instruments used across cultures disturbs rhythmic precision in other ways.

In another avenue of interest, colleagues of Jacoby and McDermott looked to see if they could track rhythm perception in younger age groups. They found that even children as young as 6, had already learnt the simple, universal rhythmic patterns available to them. Next, Jacoby hopes to work with 5-year olds in order to see when rhythm priors become recognisable.

Cross Cultural Variations

To explore cross-cultural rhythm variations, the team carried out the Chinese-whispers tapping experiment with people from the Tsiman  tribe in the Bolivian Amazon, who have had almost no exposure to western music. Interestingly, both cultures (Tsimane and US residents) show similarities in their performance of simple integer rhythm ratios, but there seem to be large differences in performance among the more complex rhythms.

For example, in people from China and Turkey, the researchers found some rhythm proficiencies (3:3:2 in Turkey and 2:2:1 in China) which were absent in other places. The triangular rhythm maps above show that some countries have unique and quite complex rhythm ratio ‘hotspots’ (areas in red). For example, in Uruguay, participants recognised the very unusual 3:4:9 rhythm, and in Mali’s capital Bamako some participants recognised the 2:3:7 rhythm.

In Mali, Nori noted that some people would laugh when they heard the 2:3:7 rhythm. When he asked them why they laughed, people said they had heard this rhythm being played by traditional musicians in a jembe piece called “Maraka”. He also noted that participants in Bulgaria would laugh in the same way when they recognised rhythms used in Balkan music, which shows that participants were sensitive to and responding strongly to well known/ well-used patterns when they heard them.

Another interesting finding from the team’s research was uncovered amongst all of the groups of students who took part. When it came to rhythmic preference, students across the world had very similar, almost universal preferences – they demonstrated the same strong rhythm patterns despite being from completely different countries and cultures! The research team anecdotally attributed this phenomenon to the global student population listening to a lot of western pop music which has led to a similarity in their musical experiences. However, this phenomenon has also affected the overall cross-cultural variability because students were found to under-represent the rhythmic variation of their culture.

To increase the reliability of the pioneering research discussed here, it would be great for the team to be able to gather data from even more world cultures, particularly those less influenced by western pop. It would also be very interesting to look at the impact of age – how does age impact rhythm perception? And, is there still a notable bias for these simple musical rhythms in older adults, suggesting a maintained and long-lasting understanding for them? We are keenly watching to see where this research will travel to next…

References:

Hannon, E. E., Nave-Blodgett, J. E., & Nave, K. M. (2018). The developmental origins of the perception and production of musical rhythm. Child Development Perspectives, 12(3), 194- 198.

Jacoby, N., & McDermott, J. H. (2017). Integer ratio priors on musical rhythm revealed cross-culturally by iterated reproduction. Current Biology, 27(3), 359-370.

London, J., Polak, R., & Jacoby, N. (2017). Rhythm histograms and musical meter: A corpus study of Malian percussion music. Psychonomic bulletin & review, 24(2), 474-480.

Murton, O., Zipse, L., Jacoby, N., & Shattuck-Hufnagel, S. (2017). Repetition and a Beat- Based Timing Framework: What Determines the Duration of Intervals Between Repetitions of a Tapping Pattern?. Timing & Time Perception, 5(3-4), 244-259.

Polak, R., Jacoby, N., Fischinger, T., Goldberg, D., Holzapfel, A., & London, J. (2018). Rhythmic prototypes across cultures: A comparative study of tapping synchronization. Music Perception: An Interdisciplinary Journal, 36(1), 1-23.

Polak, R., London, J., & Jacoby, N. (2016). Both isochronous and non-isochronous metrical subdivision afford precise and stable ensemble entrainment: A corpus study of Malian jembe drumming. Frontiers in Neuroscience, 10, 285.

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Better than drugs? How Music Makes Us Feel, Create and Fulfil

By Austin Coates, Christopher Charlwood, Ellen Murphy, Keerthana Vishwanath, Margot Dehove

Have you ever wondered what motivates you throughout your day? Where do our desires and pleasures come from? These highly inter-connected experiences are orchestrated by a set of brain regions known as the reward system. These areas coordinate their action by using a common messenger, or neurotransmitter, called dopamine. After extensive research, the role of dopamine has been more precisely defined. While it plays a part in individuals’ response to pleasure, it has been shown to also have a huge role in the reward expectation mechanism. Indeed, our brains can be modelled as huge machines constantly analysing our external and internal environments and making predictions about them. When what you predicted turns out to be true, you are rewarded, and dopamine is released. 

The reward system is also involved in all sorts of phenomena, ranging from experiencing drugs to enjoying music. This sparks great interest because unlike food or sex, music does not provide an individual directly with survival advantages, yet it stimulates similar brain networks to those activated by primary rewards (Blood & Zatorre, 2001). Recently, Belfi and Loui (2020) further refined this rewarding aspect of music by studying people suffering from musical anhedonia, a condition resulting in an inability to derive pleasure from music. They found that the reason why some of us like music while others don’t is because some of the auditory brain structures involved in the predictive process are connected to the dopaminergic reward system.

Musically Induced ‘Chills’

As Psyche Loui so aptly put it in her recent talk with MMB and PANC students, “there is no one-size fits all in how music activates the brain”. Music can induce an entire array of emotions. Aesthetic responses to art and especially to music have been reported as physiological sensations that range from awe and being touched to chills and heart palpitations (Harrison & Loui, 2014). Many of us have experienced the intensely pleasurable feeling of ‘chills’ when listening to certain music. This feeling of ‘chills’ has been shown to arise because of the activation of the reward circuitry in the brain. It has been shown that the body plays a part in this feeling, with an increase in skin conductance (sweatiness) in both those who feel chills and those who don’t, as well as an increase in heart rate in chills perceivers (Sachs et al., 2016). 

This difference in physiological response has been suggested to have a neural basis, with a difference in brain connectivity of those who experience chills when listening to music compared to those who don’t. There is a larger amount of white matter connectivity (nerve fibre bundles connecting different areas of the brain) between the superior temporal gyrus (important for auditory perception), the anterior insula (involved in the perception of sensations within your own body) and the medial prefrontal cortex (important for evaluating value) in chills perceivers’ brains. So, people that feel ‘chills’ may have functional differences in their brains that results in this intense response.

Real-time Creativity: The Reward System in Action

The role of the reward system extends beyond listening to music. It also plays a fundamental role in how musicians improvise, influencing creative choices in real time as they play. Loui (2018) found that the real-time creative process takes place in multiple stages (see fig.1). The process begins with the goal that the improviser wishes to achieve, invoking the feeling of warmth for example. This is then filtered through the knowledge base of the improviser to hone the most effective way to achieve that goal. This can include selecting particular musical devices and/or drawing from existing pieces of music. These are then applied in real time to generate auditory-motor patterns that activate the dopaminergic reward system. 

Figure 1. Model of real-time creative process proposed by Loui (2018).

Training in musical improvisation can alter the reward expectation mechanism when listening to music. Przysinda et al (2017) showed that jazz musicians trained in improvisation found unexpected musical changes more rewarding than classical musicians and non-musicians. Jazz musicians’ brains reacted to unexpected musical change faster than classical musicians, but the effect of the change lasted longer in classical musicians, demonstrating that unexpected changes are more novel to a musician with less experience in improvisation.

Alzheimer’s, Music Therapy, and Happiness

The reward system is very important to everyone’s happiness and enjoyment of music, but it is not always intact and can degrade overtime, especially in people with neurological diseases like Alzheimer’s. Alzheimer’s disease is the leading cause of dementia which is marked by a rapid decay of brain tissue in later stages of life. As seen in the figure 2 below, areas associated with auditory processing, pleasure, and reward centres, as well as their overlap, diminish as a result of Alzheimer’s and early onset of Alzheimer’s (MCI below), causing a patient’s quality of life to also diminish. Music once held dear to the patient becomes less fulfilling, rewarding, or stimulating. 

Figure 2. Brain scanner’s results depicting reward and auditory systems regions which interact while we listen to music. Control (healthy brains); MCI (Mild Cognitive Impairment); AD (Alzheimer’s Disease). 

Thankfully, music therapy can help slow the decay of the brain’s functions. Music therapy is already known to directly increase a patient’s mood by directly triggering these linked auditory-reward systems, but it can also make the patient’s brain naturally strengthen these overlapping areas. A very recent study carried out at Loui’s MIND lab (Wang et al., 2020) underpinned the importance of these overlapping areas, especially in early stage and moderately impaired individuals, and emphasized that earlier treatment and care may be vital to prolonging or even repairing the reward systems that allow these patients to still enjoy music.

Overall, the reward system is an important feature that allows us to experience feelings such as pleasure and physical responses to activities that stimulate it. Listening to and performing music has been shown to activate this system in similar ways to that of primary rewards, while music therapy can help with prolonging and repairing it. With these benefits, it can be shown that music is intrinsically rewarding and provides a more holistic and natural way to activate the reward system, possibly making it even more powerful than a drug.

References

Belfi, A., & Loui, P. (2020). Musical anhedonia and rewards of music listening: current advances and a proposed model. Annals Of The New York Academy Of Sciences, 1464(1), 99-114. doi: 10.1111/nyas.14241

Blood, A. J., & Zatorre, R. J.. (2001). Intensely pleasurable responses to music correlate with activity in brain regions implicated in reward and emotion. Proceedings of the National Academy of Sciences, 98(20), 11818–11823. https://doi.org/10.1073/pnas.191355898

Harrison, L., & Loui, P.. (2014). Thrills, chills, frissons, and skin orgasms: toward an integrative model of transcendent psychophysiological experiences in music. Frontiers in Psychology, 5. https://doi.org/10.3389/fpsyg.2014.00790

Loui, P. (2018). Rapid and flexible creativity in musical improvisation: review and a model. Annals of the New York Academy of Sciences, 1423(1), 138–145. https://doi.org/10.1111/nyas.13628

Przysinda, E., Zeng, T., Maves, K., Arkin, C., & Loui, P. (2017). Jazz musicians reveal role of expectancy in human creativity. Brain and Cognition, 119, 45–53. https://doi.org/10.1016/j.bandc.2017.09.008

Sachs, M. E., Ellis, R. J., Schlaug, G., & Loui, P.. (2016). Brain connectivity reflects human aesthetic responses to music. Social Cognitive and Affective Neuroscience, 11(6), 884–891. https://doi.org/10.1093/scan/nsw009

Wang, D., Belden, A., Hanser, S. B., Geddes, M. R., & Loui, P. (2020). Resting-State Connectivity of Auditory and Reward Systems in Alzheimer’s Disease and Mild Cognitive Impairment. Frontiers in human neuroscience, 14, 280. https://doi.org/10.3389/fnhum.2020.00280

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Tails of Wriggling Earworms And Losing Control over Musical Imagery What are Earworms?

An Introduction to Musical-Mental Imageries


To understand where earworms, academically known as involuntary musical imagery (INMI), come from, Pearson (2013) believes that one must first consider the various types of mental imagery that support the everyday functioning of our mind. He defines mental imagery as the simulation or recreation of perceptual experience in the absence of a corresponding direct external stimulus from the physical environment. This mental simulation, like perception, can be experienced across different senses; for example, the visual, auditory, gustatory, olfactory, kinaesthetic and tactile domains.

Research in mental imagery has highlighted parallels between the experiences of perceiving and imagining visual, spatial, and auditory stimuli (Finke, 1986; Hubbard, 2010). However, unlike perception of external stimuli, imagery relies on memory whereby recreation is based on one’s memory recall of the previously perceived stimulus features. In this context, understanding how mental imagery is formed can reveal the processes of our perceptual and memory systems. Mental imagery in which an individual imagines musical sound in the absence of direct external stimuli is called musical imagery (see Figure 1). Musical imagery exists in many different forms which fall on a spectrum. While it is atypical, some individuals are unable to experience musical imagery whatsoever. Alternatively, some individuals have pathological experiences of musical imagery which manifest as musical obsessions or musical hallucinations. Figure 1. A breakdown of typical and atypical musical imagery
However, most of us typically do experience musical imagery. Occurrences may be voluntary, as musicians practice mental rehearsal or how you might sing a song in your head while washing your hands; it may be automatic, in response to a certain stimulus; or it may be involuntary. Involuntary musical imagery (INMI) is the experience of a song popping into your head out of the blue, or all of a sudden, having a catchy tune you heard on the radio stuck in your head. The latter example is called an earworm, which is something that researchers suggest happens at least once a week in 90% of the population (Liikkanen, 2012).


Why, When, Where, and How Earworms Crawl into our Minds? Current Trends in Research on Involuntary Musical Imagery


The compelling case for the experience of earworms, infamous as ‘the stuck song syndrome’ or ‘cognitive itch’ (Sacks, 2007) in nearly everyone’s everyday lives has spurred the interests of musicologists and neuroscientists alike. Researchers have delved deep and wide into this domain – from intra-musical features (Floridou, under review) to the socio-cultural factors like popularity that affect the occurrence of earworms (Jakubowski et al, 2017) to interpersonal differences and environmental factors. This post will further triangulate Floridou’s approach to studying earworms in particular.


Multiple factors can trigger INMI and mind-wandering, such as low-level attention activities, time of the day and mood. Studying such a subjective and frequent experience can be difficult as it relies on the participants to be introspective and aware of inner processes that we are often not aware of. Previous studies in this field of research have measured INMI by using data from retrospective studies or in behavioural studies, using diary entries (Byron & Fowles, 2013; Floridou, Williamson, & Müllensiefen, 2012; Hyman et al., 2013). In Floridou et al (2015) study, researchers used the experience sampling method (ESM) which is used to explore everyday occurrences and provide rich data on experience-based phenomena. This method involved using everyday technology, like personal phones, to collect data on INMI and mind wandering. Participants were prompted several times throughout the day to record information about the activity they were doing, their current mood and potential triggers if they experienced INMI. This prompting for information encourages the participant to look introspectively and become aware of their actions throughout the day; this sheds light on the little control we have on our conscious intentions regarding these occurrences.


Another issue that arises when studying INMI is that participants may be aware of the study’s aim, especially when clear questions about INMI are involved, resulting in potential biases when measuring various aspects of the phenomenon as its voluntariness. Floridou developed in her study a covert and ecologically valid strategy to overcome this problem: once exposed to the musical and visual stimuli, subjects were asked to judge their experience with a set of questionnaires (Floridou et. al., 2017). Among this, the ad-hoc created ‘Mind Activity’ Questionnaire was included: it was used to assess participants’ general level of mind wandering as well as its specificity in the musical, visual and speech-based domains, the last two serving as a mask for the real nature of the study. Clearly, earworms seem to permeate deeper layers of scientific inquiry than a mere soft-fascination of a whistling wandering mind. Can we harness its potential?


What if Earworms didn’t Wriggle as much? Applications, Limitations, and Future Directions


Freddie Mercury in a leotard dancing with the Mic stand? Hear anything yet? Started tapping the table yet?


Ra Ra-ra-ah-ah-ah, Roma-roma-ma, Gaga, ooh la-la, what’s your …..? Can you hear it playing? Did you start grooving to it yet?

Remember the time you won that un-winnable game? Do you hear the song that accompanied your victory-dance?


Earworms are beyond the annoying melodic mental tics you can’t shake off on an idle (or equally busy) day. Research implicates the activation of the brain’s motor system during simple movements in relation to imagined or cued musical imagery (Halpern and Zatorre, 1999; Leaver et al., 2009; Herholz et al., 2012). Some studies conducted using Functional Magnetic Resonance Imaging and Positron Emission Tomography also show similarities between the neural activations of music imagination and music perception (Halpern and Zatorre, 1999; Kraemer et al., 2005; Herholz et al., 2012). Moreover, the use of music as a cue for movement-based recreational activities like dancing or coordinated actions such as marching is rather well known. What’s even more fascinating is the research behind the efficacy of musical cueing for increasing athletic endurance (Karageorghis et al., 2010) and decreasing perceived exertion (Bood et al., 2013).


But only a few studies have examined the use of imagined music as a cue for movement in rehabilitation settings. Schauer and Mauritz (2003) have presented anecdotal evidence of music-based interventions that have promoted people to imagine the music while they walked or even the use of imagined singing to regularise gait in a small group of Postural Deformity patients as showed by Satoh and Kuzuhara (2008). Clearly musical cue has the potential to be elicited internally though musical imagery. These findings do highlight the trail leading up to Floridou’s current explorations about the feasibility of musical imagery for motor facilitation. Her findings question the role of imagined, heard, and absent musical cues on brain waves – especially when the cues prompt (or in the control conditions, don’t prompt) movement. Differences were observed during the active state compared to the non-aroused state of the participants’ brains. Floridou is optimistic about the findings and their applications in motor therapy.


Possible Limitations and Future Directions in Earworms Research How far can with this research lead into the practical applications in the world? Firstly, the viability of earworms in movement facilitation appears to be promising; a meaningful therapeutic application must only follow stronger, reliable, and empirically supported evidence from a lot more studies. The discrepancy between earworm frequency and musical training, as well as between aging and earworm vividness are some of the topics that been challenging the current understanding. Larger samples that reflect the diversity in
demographics are necessary for developing a reliable understanding of how earworms vary across the population and accordingly, how the role they might play in motor therapy will vary across patients.


Eventually, an exploration of the future possibilities and ambitious applications will evolve this domain. Just as exciting the proposed link between earworms and mind-wandering sounds, future studies could employ a more multidimensional approach to understand the relationships between earworms, spontaneous thought, mindfulness, and creativity. Although mindfulness is often regarded as antithetical to mind-wandering (e.g., Jo et al, 2014), recent research has suggested that mindfulness may in fact positively interact with mind-wandering (Agnoli et al., 2018), and investigating how these experiences interact with earworms may provide insight into how earworms can be harnessed in the creative process. After all, the cross-pollination of the arts and sciences thrives on curious explorations of what makes us truly human – from questions of why earworms wriggle in our minds to their tails and tales that lend us creative and therapeutic affordances.


References

Agnoli, S., Vanucci, M., Pelagatti, C., & Corazza, G. E. (2018). Exploring the link between mind wandering, mindfulness, and creativity: A multidimensional approach. Creativity Research Journal, 30(1), 41-53.


Bood, R. J., Nijssen, M., Van Der Kamp, J., & Roerdink, M. (2013). The power of auditory-motor synchronization in sports: enhancing running performance by coupling cadence with the right beats. PloS one, 8(8).

Byron, T. P., & Fowles, L. C. (2013). Repetition and recency increases involuntary musical imagery of previously unfamiliar songs. Psychology of Music, 1–15. Czsikszentmihalyi, M., & Larson, R. (1987). Validity and reliability of the experience sample method. J Nerv Ment Dis, 175(9), 526-536. Finke, R. A. (1986). Some consequences of visualization in pattern identification and detection. The American journal of psychology, 257-274.

Floridou, G. A., & Müllensiefen, D. (2015). Environmental and mental conditions predicting the experience of involuntary musical imagery: An experience sampling method study. Consciousness and Cognition, 33, 472–486. https://doi.org/10.1016/j.concog.2015.02.012

Floridou, G. A., Williamson, V. J., & Stewart, L. (2017). A Novel Indirect Method for Capturing Involuntary Musical Imagery under Varying Cognitive Load: Quarterly Journal of Experimental Psychology. https://journals.sagepub.com/doi/10.1080/17470218.2016.1227860

Halpern, A. R., & Zatorre, R. J. (1999). When that tune runs through your head: a PET investigation of auditory imagery for familiar melodies. Cerebral cortex, 9(7), 697-704. Herholz, S. C., & Zatorre, R. J. (2012). Musical training as a framework for brain

plasticity: behavior, function, and structure. Neuron, 76(3), 486-502. Hubbard, T. L. (2010). Auditory imagery: empirical findings. Psychological bulletin, 136(2), 302.

Hyman, I. E., Jr., Burland, N. K., Duskin, H. M., Cook, M. C., Roy, C. M., McGrath, J. C., et al (2013). Going Gaga: Investigating, creating, and manipulating the song stuck in my head. Applied Cognitive Psychology, 27, 204–215.


Jakubowski, K., Finkel, S., Stewart, L., & Müllensiefen, D. (2017). Dissecting an earworm: Melodic features and song popularity predict involuntary musical imagery. Psychology of Aesthetics, Creativity, and the Arts, 11(2), 122.

Jo, H. G., Wittmann, M., Hinterberger, T., & Schmidt, S. (2014). The readiness potential reflects intentional binding. Frontiers in human neuroscience, 8, 421.

Karageorghis, C. I., Priest, D., Williams, L. S., Hirani, R. M., Lannon, K. M., & Bates, B. J. (2010). Ergogenic and psychological effects of synchronous music during circuit-type exercise. Psychology of Sport and Exercise, 11(6), 551-559.

Keller, P. E. (2012). Mental imagery in music performance: underlying mechanisms and potential benefits. Annals of the New York Academy of Sciences, 1252(1), 206-213.
Kraemer, D. J., Macrae, C. N., Green, A. E., & Kelley, W. M. (2005). Sound of silence activates auditory cortex. Nature, 434(7030), 158-158. Leaver, A. M., Van Lare, J., Zielinski, B., Halpern, A. R., & Rauschecker, J. P. (2009). Brain activation during anticipation of sound sequences. Journal of Neuroscience, 29(8), 2477-2485. Liikkanen, L. A. (2012). “Inducing involuntary musical imagery: An experimental study” (PDF). Musicae Scientiae. 16 (2): 217–234. doi:10.1177/1029864912440770. Liikkanen, L. A. (2012). Musical activities predispose to involuntary musical imagery. Psychology of Music, 40(2), 236–256. https://doi.org/10.1177/0305735611406578

Liikkanen, Lassi A. (2008). “Music in Everymind: Commonality of Involuntary Musical Imagery” (PDF). Proceedings of the 10th International Conference on Music Perception and Cognition (ICMPC 10). Sapporo, Japan: 408–412. ISBN 978-4-9904208-0-2. Archived from the original (PDF) on 2014-02-03.

Pearson, D., Deeprose, C., Wallace-Hadrill, S., Heyes, S., & Holmes, E. (2013). Assessing mental imagery in clinical psychology: A review of imagery measures and a guiding framework. Clinical Psychology Review, 33(1), 1-23. Reason, J. T., & Mycielska, K. (1982). Absent-minded?: The psychology of mental lapses and everyday errors. Prentice Hall. Sacks, Oliver (2007). Musicophilia: Tales of Music and the Brain. First Vintage Books. pp. 41–48. ISBN 978-1-4000-3353-9. Satoh, M., & Kuzuhara, S. (2008). Training in mental singing while walking improves gait disturbance in Parkinson’s disease patients. European Neurology, 60(5), 237-243.

Schauer, M., & Mauritz, K. H. (2003). Musical motor feedback (MMF) in walking hemiparetic stroke patients: randomized trials of gait improvement. Clinical rehabilitation, 17(7), 713-722.

Williamson, V. J., Jilka, S. R., Fry, J., Finkel, S., Müllensiefen, D., & Stewart, L. (2012). How do “earworms” start? Classifying the everyday circumstances of Involuntary Musical Imagery. Psychology of Music, 40(3), 259–284. https://doi.org/10.1177/0305735611418553

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Hearing Health and Musicians

By: Jasmin Galvan, India Haire, Roos Mehrtens, Caroline Rafizadeh

Introduction

Over 11 million people in the UK experience hearing loss (Report UK, 2015). By 2035, it is thought to affect more than 15 million people in the UK, one in five of us. The two most common causes of hearing loss are age-related hearing loss (presbycusis) and noise-induced hearing loss (NIHL). Being exposed to noises above 70 dB over an extended period can be harmful to your ears while noises above 120 dB may cause direct impairments to hearing ability. To put this into perspective, the average noise level in Manchester pubs and bars is 100 dB and rock concerts can exceed values of 120 dB.

As music often surpasses safe noise levels, musicians are exposed to a greater risk of NIHL. Hearing aid technologies can improve impairments significantly, though may cause auditory and social challenges. Taking precautions such as wearing hearing protection during exposure can reduce the risk of NIHL. However, they are not widely used.

Hearing impairment not only affects physical hearing ability, it also negatively impacts social and personal life. It causes difficulty in communicating, which can lead to social exclusion and fewer job opportunities. It can also diminish engagement with music and musical activities, therefore reducing quality of life.

Hearing loss and perceptual consequences

Hearing loss can be conductive, caused by the outer or middle ear, but it is most often sensorineural, caused by nerve damage in the inner ear. The inner ear contains a shell-shaped structure called the cochlea, which contain hair cells. Outer hair cells amplify low-level sounds that enter the cochlea, while inner hair cells turn sound frequency information into signals that the brain then interprets. Over time these cells become damaged, which is the cause of presbycusis. However, constant exposure to very loud noises can also damage these cells. Music induced hearing loss is common for professional musicians and even music enthusiasts who listen to music with headphones too loudly. The louder a noise is, the less time it takes to cause irreversible damage.

Damage to the outer hair cells leads to a reduction in the amount of basilar membrane vibration. This means that sounds need to be louder in order to be heard and high frequency sounds may not be heard at all. Damage to inner hair cells leads to less precise coding of sound information, which leads to diminished pitch perception and sound localization. Hearing loss poses a special problem for musicians since a large part of their lives depends on being able to hear music properly. They can face issues with losing high frequency information, difficulties in discerning musical instruments, and perceiving different pitches in each ear. Additionally, ringing in the ears (tinnitus) can be disruptive during quiet passages of music and music over a certain loudness level might cause pain.

Hearing Aids


For those who have experienced hearing loss, one of the most popular forms of hearing technology are hearing aids. Hearing aids work by enhancing sounds to make them louder and clearer as they are delivered to the ear canal. They are designed to identify and amplify speech, rather than background noise, which would be problematic for the wearer. Hearing aid devices compensate for threshold elevation and loudness recruitment through the use of two types of automatic gain control systems. One type adjusts gain automatically for different listening situations. The second type is intended to make impaired perception of loudness more like that of a non-impaired listener. Most hearing aids do not provide gain for frequencies below 200 Hz or above 5000 Hz, these limitations in range can lead to enjoyment problems for hearing aid users.

There are approximately 2 million hearing aid users in the UK, however, those in need of hearing aids are closer to around 6 million (McCormack & Fortnum, 2013), due to the stigma surrounding the use of hearing aids. There are even those within the musical population who suffer from hearing loss, with 34 percent reporting hearing problems (Gembris, Heye & Seifert, 2018). In a Schink et al. (2014) study, musicians were found to have a 3.51 higher incidence of NIHL and 1.45 higher incidence of tinnitus than the general public. However, a large portion of those musicians did not wear hearing aids (Patel, 2008) due to the fact that they can cause distortion and feedback when playing and listening to music. Despite these limitations, hearing aids are extremely beneficial for those with hearing loss. Hearing aids have been shown to reduce the psychological, social, and emotional effects that hearing loss has on a person (Chisholm et al., 2007).

Hearing Protection for Musicians

The organisation Help Musicians UK (HMUK) is committed to researching musicians’ use of hearing protection as well as providing musicians with the appropriate protection at a reduced cost. HMUK collects survey data regarding help-seeking behaviors and the usage of protective equipment within the professional community, while also offering specialist diagnostics and advice. Factors such as attitudes towards the usage of hearing protection as well as personal connections to members of the community with hearing loss are investigated. However, perhaps surprisingly, when asked if administered a hearing test within the last three years, nearly a third of a population of 561 musicians had not, citing not knowing which channels to seek in support (Greasley et al., 2018).

Personalized to meet each individual’s needs, HMUK offers a reduced cost hearing exam for £40 (typically upwards of £250) as well as bespoke hearing protection. In collaboration with the Musicians’ Union as well as Musicians’ Hearing Services (Harley Street Clinic), a follow-up exam is also provided two years after an initial visit. In attempting to increase the predominance of hearing protection–previously reported at a dismal 15% of survey takers (Greasley et al., 2018), HMUK takes a strong stance on the front-lines of hearing disorder prevention. With the prevalence of hearing loss on the rise, it is the primary mission of HMUK to prevent hearing disorders rather than allow professionals to suffer the adverse social and psychological effects of hearing loss.

Conclusion

The rising prevalence of hearing impairments in the UK is alarming and cannot solely be explained by age-related hearing loss. NIHL is a crucial factor and will be an ever-rising phenomenon if precautionary action is not taken. Although hearing aids offer significant hearing support, people, especially musicians, still experience unnatural auditory distortions and face the pressure of the social stigma that is associated with it.

Awareness in hearing health and precautions, such as hearing protection,shouldbecome a priority in everyday life. “Noise-induced hearing loss is 100% preventable but once acquired, hearing loss is permanent and irreversible.” (Ritzel, 2013).

References


Chisholm, T.H. Johnson, C.E. Danhauer, J.L. Portz, L.J. Abrams, H.B. Lesner, S. McCarthy, P.A. Newman, C.W. (2007) A systematic review of health-related quality of life and hearing aids. ​Journal of American Academy of Audiology 18:​ 151-183

Gembris, H., Heye, & Seifert. (2018). Health problems of orchestral musicians from a life-span perspective: Results of a large-scale study. ​Music & Science, 1, Vol.1.

Greasley, A. E., Fulford, R. J., Pickard, M., & Hamilton, N. (2018). Help Musicians UK hearing survey: Musicians’ hearing and hearing protection. ​Psychology of Music.

Mccormack, A., & Fortnum, H. (2013). Why do people fitted with hearing aids not wear them? International Journal of Audiology, 52 (5), 360-368.

Patel, J. (2008). Musicians’ hearing protection: A review. ​Prepared by the Health and Safety Laboratory for the Health and Safety Executive.

Report UK. (2015). ​Hearing Matters, Why urgent action is needed of deafness, tinnitus and hearing loss across the UK. Action On Hearing Loss.

Ritzel, D. O. (2013). Hearing Loss Prevention and Noise Control. ​Umwelt Und Gesundheit Online 2018.

Schink, T., Kreutz, G., Busch, V., Pigeot, I., & Ahrens, W. (2014). Incidence and relative risk of hearing disorders in professional musicians. ​Occupational and Environmental Medicine.

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The Interacting Brains of Clients and Therapists: Investigating Music Therapy with a Dual-EEG Approach

Written by J’Ana Reed, Phoebe Tsou, Joon Oh, Matt Eitel, and Kate Chard

Have you ever wondered what is happening in the brain of the client during therapy? How about the brain of the therapist? What changes in the brain are happening as a session moves forward? Recently, MMB and PANC students were lucky enough to listen to a talk from visiting speaker Dr. Clemens Maidhof – a postdoctoral researcher with the Cambridge Institute for Music Therapy Research. His research focuses on the cognitive neuroscience of music and, in his talk, Dr. Maidhof presented his research on music therapy utilising a procedure named hyperscanning and guided imagery in music (GIM). This procedure records activity in two participants’ brains simultaneously, allowing researchers to investigate the interaction between a music therapist’s and a client’s brain activity.

A recent study by Dr. Maidhof explored spontaneous imagery and how it is emotionally processed in a two-person therapeutic relationship. The study involved two female participants, a Guide (music therapist) and a Traveller (client), with the latter seeking therapy to help her cope with the anxiety caused by the potential loss of her grandchild. Both client and therapist wore EEG caps to capture electrical signals in the brain, and the session was also recorded using video cameras. A resting-state EEG was recorded, which was subsequently compared against the EEG recorded during the therapy.

One of the aims of a music therapist, in this particular case, is to work towards ‘moments of interest’ (MOI), when they make a meaningful connection with their client, as well as take note of ‘moments of non-interest’ (MONI). During the session, classical music was played and the client experienced different guided images of family members and messages from them. At one point during the session, the client’s brain activity moved from indicating negative feelings to a positive peak. As the therapist realised the session was really working, her scan indicated similar results; these feelings were confirmed in subsequent. In order to identify the MOIs and a MONI for the analyses, the Guide, Traveller, and two independent experienced GIM therapists were given a video recording of the therapy session. The MOIs identified by each of the raters were combined and two parts of the session were repeatedly rated as MOIs across all raters. The first MOI regarded the client experiencing a message from her deceased grandmother, informing her “not to worry”. The second MOI depicted the traveller describing feelings of spirituality and connectedness as her family gathered around a tree, suggesting that the singing currently being heard (the classical music being played) in the session was directed toward her unborn grandchild. To measure visual imagery, recordings of mean occipital alpha power were recorded. Frontal alpha asymmetry (FAA) between left and right frontal cortical areas was used a way to measure emotional valence during the therapy session, as increased activity in the left and right areas reflect positive and negative emotional processing, respectively.

Measurements collected during MOIs suggested that visual imagery was stronger during moments of peak emotion, as observed from greater mean occipital alpha power during MOIs. FAA data from the traveller revealed MONIs and rest periods being more positive than MOIs, on average. This suggests that the undergoing therapeutic process was emotionally challenging, as MOIs were processed negatively relative to other periods. Interestingly, this indication of shared emotional processing during MOIs was reflected in significant cross-correlations between FAA measurements for the traveller and the guide. An important point note is that EEG results showed that during therapy the emotions were not positive or pleasurable – this confirms that in the study they were working with negative emotions and anxiety. However, the setting used offered a secure place to work with such feelings to allow the traveller to gain the perspective that change is possible. This change was recorded when an imagined specific person to the traveller delivered a positive message, because the emotional processing changed from negative to positive – this was shared between traveller and guide.

One of the key advantages of this study was its natural, real-life setting, as the findings can be said to have high ecological validity (i.e we can use these to predict how people will behave in real life). Advances in technology also allowed the researchers to explore in hindsight, the shared emotional experiences in the therapy session using dual-EEG; this highlights some incredibly exciting new avenues for psychological experiments! However, if you fancy some more food for thought, arguably an interesting development on this would be to carry out these same procedures in an experimental setting – this would enable us to see what is potentially unique about the therapeutic setting. There are also some important limitations to note about this study. Firstly, this was a single case study, and when exploring the experiences of just one person we have to be incredibly careful about generalising this too far. What’s to say these experiences are in fact completely unique? Additionally, could there be an influence of ‘expert bias’? Expertise seems an odd thing to potentially undermine the findings of a study, but it is possible that having a collective 30+ years of music therapy experience between the Guide, Traveler, and two independent raters may have influenced how MOIs were selected and described. However, this isn’t guaranteed, and it is also possible that expertise allowed for greater access to this emotional information; it simply needs to be explored further (i.e repeat the study with non-experts).

The brain synchronizations of the current study could lead to investigations and evaluations in not only qualitative but also quantitative data. The combination of EEG and video-based qualitative data could be a promising approach in the future to show underlying mechanisms of music therapy and how and when these interventions could be effective. We thoroughly enjoyed this talk and would like to thank Dr. Clemens Maidhof for his time and insight into such an interesting and developing field!

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Dr. Maidhof’s study:

Fachner, J. C., Maidhof, C., Grocke, D., Nygaard Pedersen, I., Trondalen, G., Tucek, G., & Bonde, L. O. (2019). ‘… telling me not to worry…’Hyperscanning and neural dynamics of emotion processing during Guided Imagery in Music. Frontiers in psychology10, 1561. https://doi.org/10.3389/fpsyg.2019.01561

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Boogie with the Brain

By Caitlin Colapietro, Gabriella Tan, Shin Chien Chua, Sophie Brodtkorb, Valeria Perboni, Zoe Sole

 
The Neuroaesthetics of Dance

Why is dance infectious? Dance is a form of art with the ability to arouse aesthetic experience — a “gratification of senses” by any sensory stimulus (Goldman, 2001).
Literature suggests that there is an underlying reason as to why we feel like dancing when we observe dance. However, there is limited research investigating the neural correlates of the aesthetic experience in dance. As one of the first people to conduct research on the neuroaesthetics of dance, Beatriz Calvo-Merino discussed in her talk how the brain processes aesthetic judgement, evaluation and interpretation of artistic movement. She suggested that in order to study movement itself, the stimuli has to be dynamic and standardised. Thus, the kinematics of dance movement should be studied rather than static movements, while keeping other visual features such as background and costumes constant, as they could be confounding factors. Hence, dancers of similar body type, no music, and same neutral background should be considered for the study of dance.

The aim of the first study conducted on the neural correlates of dance aesthetics, set out to identify relationships between movement and related brain areas (Calvo-Merino et al., 2008). Using a mixed methods approach of questionnaires and fMRI, the study recorded non-dance experts’ brain activity while they watched video clips of classical ballet and capoeira. Results showed that only the like-dislike dimension had significant neural correlates on aesthetic experience, compared to the other four dimensions (simple-complex, dull-interesting, tense-relax, weak-powerful). This was found especially in the right premotor cortex, and bilateral early visual cortexes. Results also revealed that these brain regions prefer whole body movements that are displaced in space; such as jumping. Whereas body movements that were confined to a single limb, with no displacement in space, were least activated in the brain regions. Based on these brain activations, this research indicates people prefer full body movement over single limb movements. Activation in both parts of the brain suggests that the premotor cortex ‘mirrors’ actions. Mirror neurons refer to the principle that the same areas of the brain are activated when an action is observed and performed — as if the observer is performing the action in their mind.

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Figure 1. Examples of dance movement that achieved the highest and lowest scores on the aesthetic questionnaire

 

The role of familiarity and expertise

From the above mentioned study, we now know what happens in the brain when we view dances we enjoy. Calvo-Merino is also interested in how this may relate to viewers’ dance expertise. Using the same methodology as Calvo-Merino et al. (2008) amongst non-dancers, ballet dancers, and Capoeira experts, Calvo-Merino et al. (2004) found those who liked the dance sequence had higher strength in motor resonance in the dorsolateral premotor cortex. In summary, experts in the same motor activity i.e. dancers watching dancing, will have a different neurological response compared to novice counterparts. This suggests participants are able to use their mirror neuron system to internally participate in the motor movement they are familiar with whilst spectating. For example, for participants familiar with Capoeira, the same brain regions will be active whilst watching the movement sequence, as those executing them. However, this study was unable to distinguish which comes first, liking or strength of motor resonance.

Calvo-Merino’s use of fMRI is extremely useful as it allows for implicit data to be collected, in addition to traditional explicit data. Implicit preferences are  unconscious, opposed to explicit data often obtained via surveys and questionnaires. Explicit data can come with complications for researchers such as bias and social desirability. Because implicit data is unconscious, it bypasses these issues and can be used in conjunction with explicit data to further the understanding of a variety of human behavior.

 

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Figure 2. Classical Ballet and Capoeira movements performed by experts

 

How can we examine the perception of dance?

Christensen et al. (2019) has created a library of normalized dance videos aimed to reduce confounding factors. By separating the ‘dancer’ from the ‘dance’, the library allows researchers to examine the individual motions — the kinematics. Dance sequences are converted into movements of dots replacing the dancer’s joints and head. This eliminates the confounding body stimulus, contributing to forming an aesthetic perception of the dance movement (Calvo-Merino et al., 2010). This separation decouples the movement from its emotional salience, since not the movement sequence itself, but rather the quality of the movement is responsible for transferring emotions (Christensen et al., 2016). Hence, this allows the study of movement without the interference of emotional value.

However, any such experimental study of dance can arguably lack ecological validity in a number of ways, for example, trying to separate the body from the movement, or watching videos in and out of scanning devices. More importantly, experiments fail to account for the emotional responses of the complementary aspects of dance such as music, staging, theatre, costumes, context, atmosphere, storyline and number of dancers.

Nevertheless, neuroaesthetic dance research has a number of practical applications including, but not limited to, changing dance teaching practices, implementing choreographic devices and the possibility of creating ‘choreography for the brain’. By knowing what aesthetic judgments and which movements evoke stronger aesthetic responses in an individual, one might expect that neuroaesthetics of dance can be used to create the ‘perfect’ dance performance. However, many choreographers refuse this model of application, as it is in contrast with ideologies of creativity. It is important to consider that the idea of a ‘perfect dance’ is in itself flawed. In fact, different levels of expertise influence the subjective emotional response and objectively measurable physiological arousal of dance. Although universal response tendencies for dance movements can be found, the ultimate evaluation differs individually (Christensen et al., 2016).

In conclusion, objective quantitative measures of emotional response to the aesthetic stimulus are still only one component in the overall experience of dance. From research, we can say the brain ‘likes’ dance movement that we explicitly like, and we prefer movement we are more familiar with. Although breaking dance down into its individual components allows us to gain a more in depth understanding of its neural correlates, from a Gestalt approach, ‘the whole is greater than the sum of its parts’. Arguably, if you reduce dance movement to its bare components it is no longer an authentic aesthetic experience. Overall, subjectivity related to previous experience is what makes our emotional response to the aesthetic experience of dance so varied.

 

 


References

 Calvo-Merino, B., Ehrenberg, S., Leung, D., & Haggard, P. (2010). Experts see it all: Configural effects in action observation. Psychological Research PRPF, 74(4), 400–406. Calvo-Merino, B., Glaser, D. E., Grèzes, J., Passingham, R. E., & Haggard, P. (2004). Action observation and acquired motor skills: an FMRI study with expert dancers. Cerebral cortex, 15(8), 1243-1249.
Calvo-Merino, B., Jola, C., Glaser, D. E., & Haggard, P. (2008). Towards a sensorimotor
aesthetics of performing art. Consciousness and cognition, 17(3), 911-922.
Christensen, J. F., Gomila, A., Gaigg, S. B., Sivarajah, N., & Calvo-Merino, B. (2016).
Dance expertise modulates behavioral and psychophysiological responses to affective body movement. Journal of Experimental Psychology: Human Perception and Performance, 42(8), 1139–1147.
Christensen, J. F., Lambrechts, A., & Tsakiris, M. (2019). The Warburg Dance Movement Library—The WADAMO Library: A Validation Study. Perception, 48(1), 26–57.
Goldman, A. (2001). The Routledge companion to aesthetics. In B. Gaut & D. McIver Lopes (Eds.), The aesthetic (pp. 181–192).

 

 

 

 

 

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Mind-Wandering During Music Listening: when music takes your mind on a metaphorical stroll

By Aleksandra Igdalova, Annie Dehaney-Stevens, Charlotte Grainger, Reina Khoury, Robyn Landau, and Stephanie Wilain.

Have you ever found yourself driving or walking somewhere, listening to music, and suddenly found you’ve arrived at your destination but have no recollection of how exactly you got there? While moments such as this seem spontaneous and subjective, studies are showing that such experiences are not as untameable as we think. Liila Taruffi, PhD, an interdisciplinary music researcher at the University of Durham, works at the intersection of psychology, neuroscience, and aesthetics, investigating music’s capability to evoke emotions and to influence specific types of thought patterns such as mind-wandering.  She explains how the music you’re listening to can change the way your mind wanders.

Mind-wandering is a growing field in cognitive neuroscience, and while research in the field has developed over the past 20 years, it is still a poorly defined concept. Mind-wandering is an umbrella term encompassing different mental states such as daydreaming (visual mind-wandering), earworms or inner speech (auditory mind-wandering), as well as higher cognitive functions such as episodic memories or social cognition. It is a universal phenomenon of the mind that we encounter approximately 50% of our waking time (Killingsworth & Gilbert, 2010), however – because it is a fundamentally internal and subjective experience, the objective measurement can be challenging. Despite this, mind-wandering remains an important and necessary topic of study, with impact across our everyday lives affecting emotions, decision-making, wellbeing, and even creativity (Baird et al., 2012).

Often described as ‘auto-pilot’ mode, mind-wandering is an internally-driven experience where attention is task-independent. It is said to create an immersive collection of experiences where one almost loses touch with the external world. Put simply, the focus is shifted away from environmental stimuli and towards self-generated and internally orientated thoughts and images, which are free-flowing and uncontained.

Switching modes

During the day, our brain goes through many different states of consciousness. Mind-wandering happens notably during easy tasks, especially when a task has been practised repeatedly enough to cause habituation. Conversely, the more challenging the task, the less the mind is free to wander, as attentional resource is allocated to the task. Mind-wandering is also more present during periods of fatigue when the mind is more vulnerable to intrusions from inner thoughts. While mind-wandering is linked to both past and present thoughts, individuals more often focus on the future which can be linked to both positive and negative outcomes, depending on personality, state of mind and environmental stimuli. Each one of us can relate to the experience of daydreaming, where these self-referential thoughts occur, often centred around future unresolved goals.

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The Default Mode Network (in purple) has so far been linked with mind-wandering. (image source)

The brain area that has so far been linked with mind-wandering is the Default Mode Network (DMN), a large set of brain regions on the medial surface of the brain, so named because it activates by ‘default’ when a person is not engaged in a task which requires focused attention (Fox et al., 2010). These regions are activated during wakeful rest and are anti-correlated with the Executive Control Network (ECN), which activates when we engage in challenging tasks, demanding high focus. Brain imaging studies looking at DMN and ECN reveal that we are constantly shifting between these two different attentional modes, either directed internally or externally.

Mind-wandering and thought content: putting music in the driver’s seat

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Individuals diagnosed with post-traumatic stress disorder (PTSD), experience a highly negative and disquieting involuntary mind-wandering. (image source)

Our emotions and thoughts help shape our mind-wandering experiences. For example, past-oriented mind-wandering and rumination of repetitive thoughts, especially in the case of individuals suffering from depression, often result in a negative mind-wandering experience (Ruby et al., 2013); and future-oriented mind-wandering may evoke a more positive mood (Ruby et al., 2013). The latter is commonly observed in narcissistic individuals who demonstrate a future-oriented mindset, executing thoughts that have a more optimistic, self-absorbed approach. In contrast, individuals diagnosed with post-traumatic stress disorder (PTSD), experience a highly negative and disquieting involuntary mind-wandering.

Researchers, such as Dr Liila Taruffi, are exploring ways to drive thought content into a positive direction, and music has been preliminarily shown to help facilitate this. Using the knowledge that individuals use sad music to introspect or daydream, Taruffi, Perhs, Skouras, and Keolsh (2017), explored the modulation of mind-wandering through happy and sad music. Participants were probed about their mental states and self-awareness while listening to classical instrumental music and movie soundtracks. Specifically, they were asked when a mind-wandering episode would occur and whether the form of their thoughts was in images or words. The experiment revealed that sad music was associated with increased mind-wandering and decreased meta-awareness. Sad music prompted more self-referential thoughts, while happy music provoked more positive ones. For all participants, thoughts occurred more in the form of images than words, regardless of the music being sad or happy. This experiment illustrates the power of music to induce emotional states and provides evidence that music affects mental activity and the way our mind wanders. We have all experienced this subjectively, however, we can now draw a scientific link between aesthetically-induced emotions and the contents of thoughts. Even more, music can be used to induce positive mind-wandering episodes, which has crucial implications for clinical populations with dysfunctional DMN activity and negative mind-wandering.

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Differences in mind-wandering properties depending on the music (sad or happy) (retrieved from Taruffi, L., Pehrs, C., Skouras, S. et al. Effects of Sad and Happy Music on Mind-Wandering and the Default Mode Network. Sci Rep 7, 14396 (2017).
https://doi.org.gold.idm.oclc.org/10.1038/s41598-017-14849-0).

Capture d’écran 2020-04-30 à 16.35.00

Word cloud of thought content during sad and happy music (retrieved from Taruffi, L., Pehrs, C., Skouras, S. et al. Effects of Sad and Happy Music on Mind-Wandering and the Default Mode Network. Sci Rep 7, 14396 (2017).
https://doi.org.gold.idm.oclc.org/10.1038/s41598-017-14849-0).

From research to art: composing music to shape the way we think

Dr Taruffi’s research on music as a tool to stimulate mind-wandering in order to create adaptive experiences led her to set up a collaborative project with Disquiet, an online music community. She invited musicians to compose music that would either decrease our mind’s tendency to wander or trigger mind-wandering episodes.

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Understanding how music can modulate mind-wandering can give rise to our own unique, immersive ‘therapy’ which we can incorporate into our everyday life. (image source)

Collaborations between the arts and sciences such as this not only contribute to our understanding of our brains on music but also shed light on the particularities of our music listening behaviour. For example, have you ever wondered how or why ambient concerts where artists play soft electronic music for hours have become so successful in recent years? The answer may lie in mind-wandering and the resulting emotional states that trigger such episodes when we are engaged in these musical experiences. Studying the effects of mind wandering across different musical settings can be used to enhance development in this area of research concerning the beneficial nature of music. Understanding how music can modulate the phenomenon of mind-wandering to evoke pleasurable emotions suited to the individual can give rise to our own unique, immersive ‘therapy’ which we can incorporate into our everyday life.

 

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References

Baird, B., Smallwood, J., Mrazek, M. D., Kam, J. W. Y., Franklin, M. S., & Schooler, J. W.   (2012). Inspired by Distraction: Mind Wandering Facilitates Creative Incubation. Psychological Science, 23(10), 1117–1122. https://doi.org/10.1177/0956797612446024

Fox K.C., Spreng R.N., Ellamil M., Andrews-Hanna J.R., Christoff K. (2015). The wandering brain: meta-analysis of functional neuroimaging studies of mind-wandering and related spontaneous thought processes. Neuroimage, 111, 611–21. https://doi.org/10.1016/j.neuroimage.2015.02.039

Killingsworth, M. A., & Gilbert, D. T. (2010). A wandering mind is an unhappy mind. Science 330, 932. DOI: 10.1126/science.1192439

Ruby, F. J. M., Smallwood, J., Engen, H., & Singer, T. (2013). How Self-Generated Thought Shapes Mood—The Relation between Mind-Wandering and Mood Depends on the Socio- Temporal Content of Thoughts. PLoS ONE, 8(10), e77554. DOI:10.1371/journal.pone.0077554

Taruffi, L., Pehrs, C., Skouras, S. et al. Effects of Sad and Happy Music on Mind-Wandering and the Default Mode Network. Sci Rep 7, 14396 (2017).
https://doi.org.gold.idm.oclc.org/10.1038/s41598-017-14849-0

 

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