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Is there evidence to suggest that music can trigger release of a particular kind of neurotransmitter?

Is there evidence to suggest that music can trigger release of a particular kind of neurotransmitter?

I've recently listened to a podcast, "The music in your brain", in which Dr. Daniel Levitin suggests that:

  • Soothing music can trigger release of oxytocin
  • Sad music triggers release of prolactin
  • An unknown kind of music triggers release of dopamine.

This may be related to my previous question about "psychoactive music"

Is there evidence to support the claim that music can trigger the release of specific neurotransmitters in the brain?


Music is known as a form of an abstract stimulus, which can arouse feelings of euphoria, similar to tangible rewards that involve the striatal (corpus striatum) dopamine system.

In a study, published in nature neuroscience, researchers used the neurochemical specificity of 11C Raclopride positron emission tomography scanning, combined with psychophysiological measures of autonomic nervous system activity, to find endogenous dopamine release in the striatum at peak emotional arousal during music listening. To examine the time course of dopamine release, they used functional magnetic resonance imaging with the same stimuli and listeners, and found a functional dissociation: the caudate was more involved during the anticipation and the nucleus accumbens was more involved during the experience of peak emotional responses to music. These results indicate that intense pleasure in response to music can lead to dopamine release in the striatal system. Notably, the anticipation of an abstract reward can result in dopamine release in an anatomical pathway distinct from that associated with the peak pleasure itself.

Music characterized by genres and musical elements evoke distinct patterns of messenger production.Music of Johann Strauss caused rises in atrial filling fraction and atrial natriuretic peptide and falls in cortisol and tissue-type plasminogen activator (t-PA). Prolactin, cortisol, noradrenaline, and t-PA concentrations decreased after listening to the music of H.W. Henze. Ravi Shankar's music resulted in lowered concentrations of cortisol, noradrenaline, and t-PA.Listening to techno music was found to alter levels of b-endorphin, adrenocorticotropic hormone (ACTH), norepinephrine , growth hormone, prolactin, and cortisol in healthy people.Critically ill patients who listened to Mozart's slow piano sonatas had increased growth hormone and decreased interleukin (IL)6 levels.

From the neurochemistry of music by Mona Lisa Chanda and Daniel J. Levitin, Department of Psychology, McGill University, Montreal, Quebec, QC H3A 1B1, Canada

Disclaimer: I will keep editing my answer, this is just a start!


References:

  • Krumhansl, C.L. An exploratory study of musical emotions and psychophysiology. Can. J. Exp. Psychol. 51, 336-353 (1997).
  • Egerton, A. et al. The dopaminergic basis of human behaviors: a review of molecular imaging studies. Neurosci. Biobehav. Rev. 33, 1109-1132 (2009).
  • Dube, L. & Lebel, J. The content and structure of laypeople's concept of pleasure. Cogn. Emot. 17, 263-295 (2003).
  • Sloboda, J. & Juslin, P.N. Psychological perspectives on music and emotion. in Music and Emotion: Theory and Research (ed. Sloboda, J.) 71-104 (Oxford University Press, Oxford, 2001).
  • Möckel M, Röcker L, Stoörk T. Immediate physiological responses of healthy volunteers to different types of music: cardiovascular,hormonal and mental changes. Eur J Appl Physiol. 1994;68(6):451-459.
  • Gerra G, Zaimovic A, Franchini D, et al. Neuroendocrine Responses of healthy volunteers to 'techno-music': relationships with personality traits and emotional state. Int J Psychophysiol.1998;28(1):99-111.

So much to learn

“I originally trained as a music therapist but when I went into practice 15 years ago, I found that so little formal research had been done on how or why it works,” says Prof Christian Gold of the Grieg Academy Department of Music at the University of Bergen in Norway. Gold studies how music therapy can help people with a wide variety of conditions, ranging from learning disabilities to schizophrenia and dementia. “I had planned to go back into clinical practice after spending a few years in research but 15 years later, I’m still researching. There’s just so much to learn.”

Perhaps the most familiar notion of the power of music is the claim that listening to Mozart is good for your brain. But that only tells half the story. Listening to classical music (or any kind of music, even earworms) does have quantifiable impacts on aspects of cognition, such as visual puzzle solving. However, everything you do – solving puzzles, playing sports, painting landscapes – has an impact on your brain.

But nothing seems to anatomically, chemically and beneficially alter your brain the way music can. The grey matter, which is the outer layer of the brain that contains the synapses – the ends of the neurones where signals are relayed – thickens with musical training. Furthermore, the cerebellum, which is the wrinkly bulb at the back of the brain that’s crucial for balance, movement and motor control, is bigger in pianists.

Neuroscientists have documented many other anatomical changes that come with musical experience but the most profound is thought to be the fact that the corpus callosum – a band of nerve fibres that connect the left and right hemispheres to each other – thickens. No-one is quite sure what helping the two sides of the brain to communicate with each other accomplishes, but 20 years after this discovery, nobody has found anything else that does this.

What’s more, MRI scans and EEG recordings show that playing – or even just listening to – music engages almost every region of the brain. From top to bottom, front to back, every part of the brain is involved in the process. The newest parts of the brain, such as the frontal cortex, which is associated with higher thinking, tune in. Older structures in the middle, such as the hippocampus (crucial for memory formation) and the amygdala (central to fear and emotion), are also stimulated by the sound. As are even older parts of the brain, such as the cerebellum. Even the brainstem, the most prehistoric part, responds to music – but not to spoken language.

As far as we know, nothing engages as many parts of the brain as music, which suggests that it might have played an important role in our evolution.


Introduction

One of the most intriguing debates in music psychology research is whether the emotions people report when listening to music are ‘real.’ Various authorities have argued that music is one of the most powerful means of inducing emotions, from Tolstoy’s mantra that “music is the shorthand of emotion,” to the deeply researched and influential reference texts of Leonard Meyer (𠇎motion and meaning in music” Meyer, 1956) and Juslin and Sloboda (“The Handbook of music and emotion” Juslin and Sloboda, 2010). Emotions evolved as a response to events in the environment which are potentially significant for the organism’s survival. Key features of these ‘utilitarian’ emotions include goal relevance, action readiness and multicomponentiality (Frijda and Scherer, 2009). Emotions are therefore triggered by events that are appraised as relevant to one’s survival, and help prepare us to respond, for instance via fight or flight. In addition to the cognitive appraisal, emotions are also widely acknowledged to be multidimensional, yielding changes in subjective feeling, physiological arousal, and behavioral response (Scherer, 2009). The absence of clear goal implications of music listening, or any need to become �tion ready,’ however, challenges the claim that music-induced emotions are real (Kivy, 1990 Konecni, 2013).

A growing body of 𠆎motivist’ music psychology research has nonetheless demonstrated that music does elicit a response in multiple components, as observed with non-aesthetic (or ‘utilitarian’) emotions. The generation of an emotion in subcortical regions of the brain (such as the amygdala) lead to hypothalamic and autonomic nervous system activation and release of arousal hormones, such as noradrenaline and cortisol. Sympathetic nervous system changes associated with physiological arousal, such as increased heart rate and reduced skin conductance, are most commonly measured as peripheral indices of emotion. A large body of work now illustrates, under a range of conditions and with a variety of music genres, that emotionally exciting or powerful music impacts on these autonomic measures of emotion (see Bartlett, 1996 Panksepp and Bernatzky, 2002 Hodges, 2010 Rickard, 2012 for reviews). For example, Krumhansl (1997) recorded physiological (heart rate, blood pressure, transit time and amplitude, respiration, skin conductance, and skin temperature) and subjective measures of emotion in real time while participants listened to music. The observed changes in these measures differed according to the emotion category of the music, and was similar (although not identical) to that observed for non-musical stimuli. Rickard (2004) also observed coherent subjective and physiological (chills and skin conductance) responses to music selected by participants as emotionally powerful, which was interpreted as support for the emotivist perspective on music-induced emotions.

It appears then that the evidence supporting music evoked emotions being ‘real’ is substantive, despite no obvious goal implications, or need for action, of this primarily aesthetic stimulus. Scherer and Coutinho (2013) have argued that music may induce a particular ‘kind’ of emotion – aesthetic emotions – that are triggered by novelty and complexity, rather than direct relevance to one’s survival. Novelty and complexity are nonetheless features of goal relevant stimuli, even though in the case of music, there is no significance to the listener’s survival. In the same way that secondary reinforcers appropriate the physiological systems of primary reinforcers via association, it is possible then that music may also hijack the emotion system by sharing some key features of goal relevant stimuli.

Multiple mechanisms have been proposed to explain how music is capable of inducing emotions (e.g., Juslin et al., 2010 Scherer and Coutinho, 2013). Common to most theories is an almost primal response elicited by psychoacoustic features of music (but also shared by other auditory stimuli). Juslin et al. (2010) describe how the 𠆋rain stem reflex’ (from their 𠆋RECVEMA’ theory) is activated by changes in basic acoustic events – such as sudden loudness or fast rhythms – by tapping into an evolutionarily ancient survival system. This is because these acoustic events are associated with events that do in fact signal relevance for survival for real events (such as a nearby loud noise, or a rapidly approaching predator). Any unexpected change in acoustic feature, whether it be in pitch, timbre, loudness, or tempo, in music could therefore fundamentally be worthy of special attention, and therefore trigger an arousal response (Gabrielsson and Lindstrom, 2010 Juslin et al., 2010). Huron (2006) has elaborated on how music exploits this response by using extended anticipation and violation of expectations to intensify an emotional response. Higher level music events – such as motifs, or instrumental changes – may therefore also induce emotions via expectancy. In seminal work in this field, Sloboda (1991) asked participants to identify music passages which evoked strong, physical emotional responses in them, such as tears or chills. The most frequent musical events coded within these passages were new or unexpected harmonies, or appoggiaturas (which delay an expected principal note), supporting the proposal that unexpected musical events, or substantial changes in music features, were associated with physiological responses. Interestingly, a survey by Scherer et al. (2002) rated musical structure and acoustic features as more important in determining emotional reactions than the listener’s mood, affective involvement, personality or contextual factors. Importantly, because music events can elicit emotions via both expectation of an upcoming event and experience of that event, physiological markers of peak emotional responses may occur prior to, during or after a music event.

This proposal has received some empirical support via research demonstrating physiological peak responses to psychoacoustic 𠆎vents’ in music (see Table 1). On the whole, changes in physiological arousal – primarily, chills, heart rate or skin conductance changes – coincided with sudden changes in acoustic features (such as changes in volume or tempo), or novel musical events (such as entry of new voices, or harmonic changes).

TABLE 1. Music features identified in the literature to be associated with various physiological markers of emotion.

Supporting evidence for the similarity between music-evoked emotions and ‘real’ emotions has also emerged from research using central measures of emotional response. Importantly, brain regions associated with emotion and reward have been shown to also respond to emotionally powerful music. For instance, Blood and Zatorre (2001) found that pleasant music activated the dorsal amygdala (which connects to the ‘positive emotion’ network comprising the ventral striatum and orbitofrontal cortex), while reducing activity in central regions of the amygdala (which appear to be associated with unpleasant or aversive stimuli). Listening to pleasant music was also found to release dopamine in the striatum (Salimpoor et al., 2011, 2013). Further, the release was higher in the dorsal striatum during the anticipation of the peak emotional period of the music, but higher in the ventral striatum during the actual peak experience of the music. This is entirely consistent with the differentiated pattern of dopamine release during craving and consummation of other rewarding stimuli, e.g., amphetamines. Only one group to date has, however, attempted to identify musical features associated with central measures of emotional response. Koelsch et al. (2008a) performed a functional MRI study with musicians and non-musicians. While musicians tended to perceive syntactically irregular music events (single irregular chords) as slightly more pleasant than non-musicians, these generally perceived unpleasant events induced increased blood oxygen levels in the emotion-related brain region, the amygdala. Unexpected chords were also found to elicit specific event related potentials (ERAN and N5) as well as changes in skin conductance (Koelsch et al., 2008b). Specific music events associated with pleasurable emotions have not yet been examined using central measures of emotion.

Davidson and Irwin (1999), Davidson (2000, 2004), and Davidson et al. (2000), have demonstrated that a left bias in frontal cortical activity is associated with positive affect. Broadly, a left bias frontal asymmetry (FA) in the alpha band (8� Hz) has been associated with a positive affective style, higher levels of wellbeing and effective emotion regulation (Tomarken et al., 1992 Jackson et al., 2000). Interventions have been demonstrated to shift frontal electroencephalograph (EEG) activity to the left. An 8-week meditation training program significantly increased left sided FA when compared to wait list controls (Davidson et al., 2003). Blood et al. (1999) observed that left frontal brain areas were more likely to be activated by pleasant music than by unpleasant music. The amygdala appears to demonstrate valence-specific lateralization with pleasant music increasing responses in the left amygdala and unpleasant music increasing responses in the right amygdala (Brattico, 2015 Bogert et al., 2016). Positively valenced music has also been found to elicit greater frontal EEG activity in the left hemisphere, while negatively valenced music elicits greater frontal activity in the right hemisphere (Schmidt and Trainor, 2001 Altenmüller et al., 2002 Flores-Gutierrez et al., 2007). The pattern of data in these studies suggests that this frontal lateralization is mediated by the emotions induced by the music, rather than just the emotional valence they perceive in the music. Hausmann et al. (2013) provided support for this conclusion via mood induction through a musical procedure using happy or sad music, which reduced the right lateralization bias typically observed for emotional faces and visual tasks, and increased the left lateralization bias typically observed for language tasks. A right FA pattern associated with depression was found to be shifted by a music intervention (listening to 15 min of ‘uplifting’ popular music previously selected by another group of adolescents) in a group of adolescents (Jones and Field, 1999). This measure therefore provides a useful objective marker of emotional response to further identify whether specific music events are associated with physiological measures of emotion.

The aim in this study was to examine whether: (1) music perceived as 𠆎motionally powerful’ and pleasant by listeners also elicited a response in a central marker of emotional response (frontal alpha asymmetry), as found in previous research and (2) peaks in frontal alpha asymmetry were associated with changes in key musical or psychoacoustic events associated with emotion. To optimize the likelihood that emotions were induced (that is, felt rather than just perceived), participants listened to their own selections of highly pleasurable music. Two validation hypotheses were proposed to confirm the methodology was consistent with previous research. It was hypothesized that: (1) emotionally powerful and pleasant music selected by participants would be rated as more positive than silence, neutral music or a dissonant (unpleasant) version of their music and (2) emotionally powerful pleasant music would elicit greater shifts in frontal alpha asymmetry than control auditory stimuli or silence. The primary novel hypothesis was that peak alpha periods would coincide with changes in basic psychoacoustic features, reflecting unexpected or anticipatory musical events. Since music-induced emotions can occur both before and after key music events, FA peaks were considered associated with music events if the music event occurred within 5 s before to 5 s after the FA event. Music background and affective style were also taken into account as potential confounds.


Why Does House Music Feel ‘So Damn Good’?

“House music is a feeling” is a phrase coined by multiple producers, DJs and other prominent figures in the electronic music scene. It is also an unoriginal title shared by around a hundred house tracks. Is this just a figure of speech or is there sound scientific reasoning behind it?

You may have heard of dopamine, a neurotransmitter found in the brain most commonly known for its association with feelings of happiness. When dopamine is released from a region in the brain known as the ventral tegmental area, it stimulates dopamine-sensitive neurons in other parts of the brain, namely the nucleus accumbens, amygdala and hippocampus. This is known as the mesolimbic pathway, commonly referred to as the reward pathway. Dopamine is released when we partake in rewarding and pleasurable activities which activate the aforementioned pathway. This includes activities essential to one’s survival such as eating and having sex, which our bodies reward us for. Furthermore, drugs such as nicotine, cocaine and heroin boost dopamine levels. So, why does listening to music also trigger this response?

Although listening to music can produce a rewarding feeling, it is not intrinsic to human survival. As such, the effect of music on the reward pathway has baffled people from the common party-goer to the puzzled scientist. Hence, a multitude of studies have investigated the subject, with the majority utilising brain scans to explore the neural correlates of this reward system. A study at McGill University carried out by Salimpoor and Zatorre shed some light on this topic 1 . The study showed that listening to music generates a strong transmission to the nucleus accumbens. Zatorre claims “music has such deep roots in the brain that it engages this biologically ancient system”, and the results of his study support this. The findings demonstrated that when participants listened to one of their favourite songs for 15 minutes, dopamine levels in the brain significantly increased by 9% compared to the dopamine levels of participants who did not listen to music. However, it is important to note that only eight volunteers participated in the study and it did not investigate different genres of music. Although this study demonstrates the influence of music on the brain’s reward or dopaminergic system, it is unclear whether different genres have different effects on the dopaminergic reward pathway. Nonetheless, several studies that examine the specific traits of house music suggest that listening to house music is an extra pleasurable experience.

House music has particular qualities that make it ‘so damn good’. Beats per minute (BPM) plays a fundamental role in how humans process music. House music has an average speed of 120 to 130 BPM. Interestingly, studies show that music that lies between 90 to 150 BPM produces greater feelings of happiness and joy as well as diminishing emotions associated with sadness 2 . Tempo directly affects a person physiologically, namely their respiratory and cardiovascular system, by stimulating the sympathetic nervous system. Evidence has shown that the respiratory system exhibits a degree of synchronisation with the tempo of the music with faster tempos increasing heart rate, blood pressure and breathing rate, whereas a slower tempo produces the opposite effect. These effects on the cardiovascular and respiratory system explain how house music can generate feelings of excitement and happiness.

Another theory is that the ‘build up and drop’ incorporated into house music influences the dopamine reward system. The drop is when there is a drastic change in beat and rhythm momentum is built up and then the bass and rhythm ‘hit hard’ or ‘drop’. It has been suggested that the length and intensity of anticipation during the build up to a drop in a house track plays an important part in how much of a reward your brain gives to you 3 . Studies conducted by David Huron, Professor in the School of Music and in the Center for Cognitive and Brain Sciences at the Ohio State University, aim to fully understand and explain why this is 4 . Huron uses a five response factor system involving imagination, tension, prediction, reaction and appraisal to understand the effects of musical anticipation. Combined, these five factors cause a person to react to music. For example, say you are listening to a song and a build up begins, you are already imagining that there is going to be a satisfying drop. The tension response is preparing your body for the drop (and also preparing a dopamine hit to the brain) as does the prediction response. The reaction and appraisal response occur when the body assessing its environment and situation and determines that the dopamine should be released.

Other factors that influence the relationship between house music and the dopamine system include socialising and dancing. Humans are social creatures – we love to interact with others and crave a sense of belonging. Furthermore, as you have probably experienced, emotions are contagious and spread through social networks, a fact supported by psychological studies. In one study, participants were shown photographs of another person who displayed either a happy or sad expression 5 . The emotions experienced by those viewing the photographers were assessed using MRI scans and, in the majority of cases, they were found to experience the same emotion as the person in the photograph. Therefore, when in a room full of others enjoying themselves and dancing a collective positive mood can be generated due to our brains subconsciously mimicking the perceived emotions of those around you.

Dancing is also part of the dopamine release process – be it in a club or if you are just home alone having a boogie. Like many other physical activities, dancing releases endorphins into the bloodstream. Endorphins are another form of neurotransmitter and their main function is to decrease levels of pain felt in the body. When they are released they can also stimulate feelings of euphoria when you dance, you can feel great. Therefore, when dancing to house music, you can experience the dual action of dopamine and endorphins, a hugely pleasurable combination.

It is important to consider that personal taste affects how a person feels when listening to music. House fans have a predisposition to repetitive, pulsating rhythms and the characteristics of house, including the previously discussed BPM and build up and drop. It is thought that various personality traits can affect a person’s music taste such as extraversion, agreeableness and neuroticism. Extraverts tend to enjoy upbeat and energetic music (such as house), which people who demonstrate a high level of agreeableness also prefer. Neurotic people tend to experience higher levels of emotional response from music, both positive and negative. Influences like age, gender and how an individual wants to be viewed also affect what kind of music you listen to and how it makes you feel. Cultural assumptions can result in certain prejudices towards music with regards to gender – it is often assumed that boys prefer rock music and girls prefer pop. Similarly, we think of older people preferring quieter classical music as opposed to bass-heavy EDM.

The unique features of house music can explain why passionate fans say it just feels ‘so damn good’. Through its physiological influence on our dopaminergic reward system, music affects us both mentally and physically. One could say that house music listeners take full advantage of this phenomenon. Our brains cannot help it that we love house music’s big beats and we cannot help two-stepping away to it, with our dopaminergic system loving it just as much 6 .

Here is one of my favourite playlists so have a listen and get your dopamine fix:

This article was specialist edited by Sonya Frazier and copy-edited by Kirsten Woollcott.


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Music 'releases mood-enhancing chemical in the brain'

The study, reported in Nature Neuroscience, found that the chemical was released at moments of peak enjoyment.

Researchers from McGill University in Montreal said it was the first time that the chemical - called dopamine - had been tested in response to music.

Dopamine increases in response to other stimuli such as food and money.

It is known to produce a feel-good state in response to certain tangible stimulants - from eating sweets to taking cocaine.

Dopamine is also associated with less tangible stimuli - such as being in love.

In this study, levels of dopamine were found to be up to 9% higher when volunteers were listening to music they enjoyed.

The report authors say it's significant in proving that humans obtain pleasure from music - an abstract reward - that is comparable with the pleasure obtained from more basic biological stimuli.

Music psychologist, Dr Vicky Williamson from Goldsmiths College, University of London welcomed the paper. She said the research didn't answer why music was so important to humans - but proved that it was.

"This paper shows that music is inextricably linked with our deepest reward systems."


Antisocial Personality Disorder Causes

The specific cause or causes of antisocial personality disorder (ASP) are unknown. Like many mental health issues, evidence points to inherited traits. But dysfunctional family life also increases the likelihood of ASP. So although ASP may have a hereditary basis, environmental factors contribute to its development.

Theories About ASP

Researchers have their own ideas about ASP&rsquos cause. One theory suggests that abnormalities in development of the nervous system may cause ASP. Abnormalities that suggest abnormal nervous system development include learning disorders, persistent bedwetting and hyperactivity.

A recent study showed that if mothers smoked during pregnancy, their offspring were at risk of developing antisocial behavior. This suggests that smoking brought about lowered oxygen levels with may have resulted in subtle brain injury to the fetus.

Yet another theory suggests that people with ASP require greater sensory input for normal brain function. Evidence that antisocials have low resting pulse rates and low skin conductance, and show decreased amplitude on certain brain measures supports this theory. Individuals with chronically low arousal may seek out potentially dangerous or risky situations to raise their arousal to more optimal levels to satisfy their craving for excitement.

Brain imaging studies have also suggested that abnormal brain function is a cause of antisocial behavior. Likewise, the neurotransmitter serotonin has been linked with impulsive and aggressive behavior. Both the temporal lobes and the prefrontal cortex help regulate mood and behavior. It could be that impulsive or poorly controlled behavior stems from a functional abnormality in serotonin levels or in these brain regions.

The Environment

Social and home environments also contribute to the development of antisocial behavior. Parents of troubled children frequently show a high level of antisocial behavior themselves. In one large study, the parents of delinquent boys were more often alcoholic or criminal, and their homes were frequently disrupted by divorce, separation, or the absence of a parent.

In the case of foster care and adoption, depriving a young child of a significant emotional bond could damage his ability to form intimate and trusting relationships, which may explain why some adopted children are prone to develop ASP. As young children, they may be more likely to move from one caregiver to another before a final adoption, thereby failing to develop appropriate or sustaining emotional attachments to adult figures.

Erratic or inappropriate discipline and inadequate supervision have been linked to antisocial behavior in children. Involved parents tend to monitor their child&rsquos behavior, setting rules and seeing that they are obeyed, checking on the child&rsquos whereabouts, and steering them away from troubled playmates. Good supervision is less likely in broken homes because parents may not be available, and antisocial parents often lack the motivation to keep an eye on their children. The importance of parental supervision is also underscored when antisocials grow up in large families where each child gets proportionately less attention.

A child who grows up in a disturbed home may enter the adult world emotionally injured. Without having developed strong bonds, he is self-absorbed and indifferent to others. The lack of consistent discipline results in little regard for rules and delayed gratification. He lacks appropriate role models and learns to use aggression to solve disputes. He fails to develop empathy and concern for those around him.

Antisocial children tend to choose similar children as playmates. This association pattern usually develops during the elementary school years, when peer group acceptance and the need to belong start to become important. Aggressive children are the most likely to be rejected by their peers, and this rejection drives social outcasts to form bonds with one another. These relationships can encourage and reward aggression and other antisocial behavior. These associations may later lead to gang membership.

Child abuse also has been linked with antisocial behavior. People with ASP are more likely than others to have been abused as children. This is not surprising since many of them grow up with neglectful and sometimes violent antisocial parents. In many cases, abuse becomes a learned behavior that formerly abused adults perpetuate with their own children.

It has been argued that early abuse (such as vigorously shaking a child) is particularly harmful, because it can result in brain injury. Traumatic events can disrupt normal development of the central nervous system, a process that continues through the adolescent years. By triggering a release of hormones and other brain chemicals, stressful events could alter the pattern of normal development.


Study shows dopamine plays a role in musical pleasure

Ball-and-stick model of the dopamine molecule, a neurotransmitter that affects the brain's reward and pleasure centers. Credit: Jynto/Wikipedia

An international team of researchers has found evidence of dopamine in the brain playing a role in the pleasure people feel when they listen to music. In their paper published in Proceedings of the National Academy of Sciences, the group describes experiments they carried out with volunteers who were given a dopamine precursor or antagonist and what they found.

People are known to experience a range of emotions when listening to music, from annoyance to euphoria. And while researchers have long believed that at least some of the pleasure people derive from listening to music is tied to an increase in brain dopamine levels, the idea had never been tested until now. In this new effort, the researchers gave volunteers drugs that increased or decreased their dopamine levels and then administered various tests to gauge whether doing so caused a change in the experience of musical pleasure.

In the study, 27 volunteers were given either levodopa, a dopamine precursor that raises levels of the neurotransmitter in the brain, or risperidone which has the opposite effect. Some were also given a placebo. Over the course of three separate sessions (on different days), the volunteers were asked to listen to music for a period of 20 minutes. Some of the songs were chosen by the experimenters and others were chosen by the volunteers themselves. Pleasure responses were measured via a skin sensor that measured electrodermal activity (goosebumps) and through questionnaires. They also asked each of the volunteers if they would be willing to buy the songs they were listening to, and if so, how much they would be willing to pay for them.

The researchers found that those volunteers who received levodopa reported experiencing more pleasure while listening to music than did the placebo group. They were also more willing to buy the music and to pay more for it. Conversely, those given risperidone reported experiencing less pleasure and were less willing to pay for the music.

The researchers suggest their findings indicate that dopamine plays a major role in the pleasure sensations that people experience from listening to music. They further suggest that their experiments indicate that enjoyment of music can be regulated by the use of drugs that impact dopamine levels.


Smartphone apps can reduce depression

New Australian-led research has confirmed that smartphone apps are an effective treatment option for depression, paving the way for safe and accessible interventions for the millions of people around the world diagnosed with this condition.

Depression is the most prevalent mental disorder and a leading cause of global disability, with mental health services worldwide struggling to meet the demand for treatment.

In an effort to tackle this rising challenge, researchers from Australia's National Institute of Complementary Medicine (NICM), Harvard Medical School, The University of Manchester, and the Black Dog Institute in Australia examined the efficacy of smartphone-based treatments for depression.

The researchers systematically reviewed 18 randomised controlled trials which examined a total of 22 different smartphone-delivered mental health interventions.

The studies involved more than 3400 male and female participants between the ages of 18-59 with a range of mental health symptoms and conditions including major depression, mild to moderate depression, bipolar disorder, anxiety and insomnia.

The first of its kind research, published today in World Psychiatry found that overall smartphone apps significantly reduced people's depressive symptoms, suggesting these new digital therapies can be useful for managing the condition.

Lead author of the paper, NICM postdoctoral research fellow Joseph Firth says this was an important finding which presented a new opportunity for providing accessible and affordable care for patients who might not otherwise have access to treatment.

"The majority of people in developed countries own smartphones, including younger people who are increasingly affected by depression," said Mr Firth.

"Combined with the rapid technological advances in this area, these devices may ultimately be capable of providing instantly accessible and highly effective treatments for depression, reducing the societal and economic burden of this condition worldwide."

Co-author, NICM deputy director, Professor Jerome Sarris highlighted the importance of the findings for opening up non-stigmatising and self-managing avenues of care.

"The data shows us that smartphones can help people monitor, understand and manage their own mental health. Using apps as part of an 'integrative medicine' approach for depression has been demonstrated to be particularly useful for improving mood and tackling symptoms in these patients," said Professor Sarris.

When it comes to the question of "Which app is best?" and "For who?," the results suggested these interventions so far may be most applicable to those with mild to moderate depression, as the benefits in major depression have not been widely studied as of yet.

The researchers found no difference in apps which apply principles of mindfulness compared to cognitive behavioural therapy or mood monitoring programs.

However, interventions that used entirely 'self-contained' apps -- meaning the app did not reply on other aspects such as clinician and computer feedback -- were found to be significantly more effective than 'non-self-contained' apps.

The authors suggested this might be due to the comprehensiveness of these particular stand-alone apps rather than the combination of therapies.

Despite the promising early results, there is currently no evidence to suggest that using apps alone can outperform standard psychological therapies, or reduce the need for antidepressant medications.

According to co-author and co-director of the digital psychiatry program at Beth Israel Deaconess Medical Center and a clinical fellow in the department of psychiatry at Harvard Medical School, Dr John Torous, the research is a timely and promising step forward in the use of smartphones in mental health.

"Patients and doctors are faced with a vast array of mental health apps these days, and knowing which ones are actually helpful is imperative," said Dr Torous.

"This research provides much needed information on the effectiveness of apps for depression, and offers important clues into the types of apps which can help patients manage their condition."

Jennifer Nicholas, a PhD Candidate at Black Dog Institute and co-author of the paper says with the knowledge that apps can be effective for managing depression, future research must now investigate which features produce these beneficial effects.

"Given the multitude of apps available -- many of them unregulated -- it's critical that we now unlock which specific app attributes reap the greatest benefits, to help ensure that all apps available to people with depression are effective."


Results

VAS Ratings.

Three patients with aspects of visual neglect participated in the study. Fig. 1 depicts the lesion reconstructions in the patients from MRI scan. Further patient details are provided in the SI Methods. VAS scores were analyzed by means of nonparametric Kruskal–Wallis tests with music as a factor (see Statistical Analyses in the SI Methods for a justification of the choice of statistical tests). In the case of MP, ratings of musical enjoyment and mood were more positive with preferred music compared with unpreferred music [χ 2 (1) = 6.94, P = 0.008, and χ 2 (1) = 6.9, P = 0.009], whereas arousal ratings were highest in the unpreferred music condition [χ 2 (1) = 6.86, P = 0.009]. Patient RH rated a higher musical enjoyment and mood with preferred music compared with unpreferred music [χ 2 (1) = 5.33, P = 0.02, and χ 2 (1) = 5.4, P = 0.02], whereas his arousal ratings were highest with preferred music [χ 2 (1) = 5.33, P = 0.021]. In the case of AS, musical enjoyment and mood ratings were more positive with preferred music compared with unpreferred music [χ 2 (1) = 6.81, P = 0.009 and χ 2 (1) = 6.86, P = 0.009], whereas there were no significant differences on arousal ratings across conditions [χ 2 (1) = 1.33, P = 0.249]. This pattern shows consistent effects of preferred music on positive affect but inconsistent effects on arousal responses across patients. A single VAS rating for mood and arousal was also taken from each of the patients in a neutral condition, without music (Table 1).

Lesion reconstructions in the patients from MRI scan (see the Lesion Reconstruction section in the SI Methods for further details). Left of the slice represents the left hemisphere.

VAS ratings of music enjoyment, mood, and arousal (from 0 to 10)

We also assessed whether the preferred pleasant music influenced enjoyment, mood, and arousal differently across the patients. The results indicated that preferred music triggered a higher positive affect response in MP relative to the other patients (Supporting Analyses in the SI Methods). With regard to the arousal ratings, these were higher for patients RH and AS relative to MP.

Study 1: Behavioral Experiments.

Perceptual report task.

Patients were required to report different colored geometric shapes (i.e., “blue square,” “green triangle,” etc.) presented in the left or right visual field either one at a time or in pairs on a computer screen (see SI Methods for details). Performance was assessed when each patient listened either to his preferred music, to unpreferred music, or in silence. The means for each patient's performance for each of the 4 blocks of trials collected within each music session were treated as independent observations (29). A 3 (patient) × 3 (music: preferred vs. unpreferred vs. silent) × 2 (number of targets: 1 vs. 2) × 2 (visual field: contralesional vs. ipsilesional) ANOVA was conducted. The pattern of results appears in Fig. 2A. There was an overall effect of music (F2,18 = 15.54, P = 0.0001), with higher target identification when there was preferred compared with unpreferred music (P = 0.0001) and with preferred music compared with silence (P = 0.011). Performance was better on single- rather than on 2- object trials (F1,9 = 148.6, P = 0.0001) and also for ipsilesional relative to contralesional targets (F1,9 = 134.34, P = 0.0001). The effect of the number of targets present interacted with the positions of the targets in the visual field (F1,9 = 81.66, P = 0.0001). This demonstrates an extinction effect, with identification of contralesional targets being greater on single- compared with 2-object trials. Interestingly, music modulated the effect of visual field (F2,18 = 11.45, P = 0.002), and the 3-way interaction between music, visual field, and number of objects was also significant (F2,18 = 4.24, P = 0.036). Posthoc t tests showed that the identification of single contralesional targets increased with preferred music relative to both unpreferred music [t(11) = 2.17, P = 0.052] and silence [t(11) = 3.2, P = 0.008]. Contralesional performance in the 2-object condition was also better with preferred music than with both unpreferred music [t(11) = 5.3, P = 0.0001] and with silence [t(11) = 2.15, P = 0.055]. In addition, performance on 2-object trials was worse with unpreferred music than with no music [t(11) = −3.31, P = 0.007]. There were no significant effects of music on the identification of ipsilesional targets. We also note that the 3-way interaction was also modulated by patient (F2,18 = 3.43, P = 0.036). The benefits of preferred music on patient MP were larger than for the other patients (AS and RH). Importantly, however, the analyses led to a very similar pattern with MP omitted (see Supporting Analyses in SI Methods).

Behavioral data from Study 1. (A) Proportion of correct identification responses in the different music conditions as a function of the number of targets and their position in the visual field. (B) Proportion of correct detections as a function of the visual field and the music conditions. C, contra lesional I, ipsilesional.

Detection task.

Here, we required patients merely to detect the onset of a red target by means of a key button press (and to withhold responses to green targets). Patients MP and RH performed 2 sessions, each containing 2 different blocks on each of the music conditions. Patient AS performed 3 sessions. Responses on catch trials were withheld as instructed. A 2 (music) × 2 (target visual field) ANOVA was conducted on the means for each patient (with performance on each session treated as independent observation). The main effect of music was marginal (F1,6 = 5.67, P = 0.076). There was impaired detection of contralesional targets compared with ipsilesional targets (F1,6 = 17.45, P < 0.014). The effect of visual field was modulated by music (F1,6 = 10.11, P < 0.034) neglect of contralesional targets reduced in the preferred music condition relative to the unpreferred music condition (Fig. 2B).

We also assessed music effects on the reaction times taken to detect the target, to examine whether preferred music listening enhanced overall readiness to react. Because of the low number of correct responses to contralesional targets, reaction time data from both contralesional and ipsilesional fields were combined. A paired t test showed no significant differences in reaction times (RT) between preferred music (mean = 707 ms) and unpreferred music (mean = 711 ms) [t(6) < 1, P = 0.7]. The same pattern emerged when only reaction times for ipsilesional targets were considered. Preferred music listening did not appear to facilitate decision stages of the reaction to the target. The effect of preferred music seems more linked to an enhancement of the patients' awareness.

A further control experiment was carried out with one of the patients (MP) to assess whether the music needed to be played during the task to generate effects or whether music-induced mood before the task would also facilitate awareness. To induce positive emotions before the task, the patient was exposed to a musical video of his favorite artist, and he was asked to retrieve good feelings and memories. The music was not played during the task. The experimental protocol was similar to the above detection task, except that here we included pictures from the International Affective Picture Scale (IAPS) (30) before each trial to “sustain” the positive mood induced before the task. After 1 block on the positive mood condition, the patient was given a break. Subsequently, the experimenter raised a conversation on the current financial crisis to reduce the level of positive emotion. Then, the patient received 2 blocks of trials in the more “negative” mood condition, where each trial was preceded by a “negative” affect picture from the IAPS. Positive and negative pictures differed in their normative ratings of valence [7.3 vs. 3.37 for the more and less pleasant cases, respectively t(7) = 11.14, P < 0.001], and they were matched on the dimension of arousal (4.67 vs. 4.51 for the positive and negative pictures, respectively t < 1). The patient was instructed that pictures were irrelevant to the task and that he or she should concentrate on detecting the red target. The session finished in the more positive mood condition, with positive mood again induced by playing a musical video before the task and by asking the patient to retrieve pleasant memories. The results confirm our prior observations. MP did not show any sign of visual neglect in the positive mood condition. Target detection was perfect both for contralesional and ipsilesional targets (32 of 32 trials). In contrast, in the more “negative” mood condition, the patient only detected 9% of contralesional targets (3 of 32), whereas the patient detected 88% of the ipsilesional targets (28 of 32). This finding provides compelling evidence that positive mood induction played a critical role at improving the patient's awareness.

Star cancellation.

MP and AS were asked to search for small stars presented along with big stars and letter distractors on a paper sheet and to mark them with a pencil. RH did not show neglect on this task. MP and AS performed the task with (i) unlimited time conditions and (ii) with a limited time window of 3 min. Note that 3 min is easily long enough for control participants to perform the task. The data averaged across the patients are depicted in Table 2. The data indicate that a contralesional cancellation deficit was apparent under both task durations. Log-linear analyses assessed the number of correct to error trials as a function of the patient, task duration, music type, and visual field. There was a significant interaction between all factors [χ 2 (1) = 7.023, P = 0.008]. Next, we reanalyzed the data taking only performance under time-limited conditions. There were fewer cancellations in the contralesional than the ipsilesional field [χ 2 (1) = 28.027, P = 0.0001]. In addition, the number of cancellations increased with preferred compared with unpreferred music [χ 2 (1) = 5.44, P = 0.02]. Again, preferred music led to enhanced awareness. The results from the log-linear analyses failed to show differential effects of music as a function of visual field, but Table 2 indicates that the effects of preferred music were more evident on the contralesional side. We also note that music effects in MP were stronger with unlimited exposure conditions, whereas patient AS showed stronger music effects under the 3-min limited time window. These results may reflect that MP moved toward a floor effect with time-limited conditions, whereas AS was close to ceiling with unlimited exposures.

Percentage of star cancellation responses with unlimited time for the task and with a limited time window

Line bisection.

This task required the patient to draw a cross at the center of varying numbers of lines presented in random locations on an A4 sheet of paper. Only MP was tested here, because the other patients (RH and AS) did not show neglect on this task, as indicated by our prior neuropsychological assessment. MP bisected 10 of 18 stimuli in the contralesional field when the preferred music was played, and 9 of 18 with unpreferred music. All lines on the ipsilesional side of the page were bisected. His individual bisection judgments, when attempted, were also assessed in the preferred and unpreferred music conditions. With preferred music, MP bisected the lines on average 0.03 cm to the right from the midline—a distance that was not significantly different from zero [t(27) = 1.43, P = 0.16]. With unpreferred music, a right-side bias of 0.15 cm was found, which differed significantly from both the deviation found with preferred music [t(26) = 3.38, P = 0.002] and from zero t(26) = 5.3, P = 0.0001].

Reading test.

The task required the patient to read pronounceable nonwords presented in mixed case (“cHuNe,” “fotCh”). These items were chosen because they were likely to induce neglect errors, given that parietal patients are sensitive to both lexical status and case mixing (31). Again, only MP was tested. The stimuli were randomly scattered across an A4 sheet. When his preferred music was played, he correctly read nonwords presented on both the contralesional and ipsilesional sides of the page (28 of 28 and 28 of 28 respectively). With unpreferred music, MP almost read all of the nonwords on the ipsilesional side (27 of 29: the 2 errors were due to MP neglecting the initial letter of the string). In addition, he missed 16 of 28 of the nonwords on the contralesional side of the page.

Study 2: Assessing Effects on Arousal.

Galvanic response data (GSR).

We assessed the effects of preferred and unpreferred music on arousal by measuring the GSR (22). During the recordings, the patients were asked just to concentrate on the music. Fig. 3A depicts the average of the GSRs across slots of 30 s in the different music conditions for each patient [see Supporting Analyses (GSR Data) in SI Methods].

Psychophysiological data. (A) Time course of the GSRs and (B) time course of the heart rate [average beats per minute (BPM)] in the 3 patients tested. Solid rectangle, silence conditions solid square, preferred music solid triangle, unpreferred music.

Heart rate (HR) data.

Fig. 3B depicts the average of the beats per minute across the different 30-s slots and music conditions for each patient [see Supporting Analyses (HR Data) in SI Methods].

There was no consistent pattern of differences in GSR and HR across the patients and across the measurement periods. Note that, if anything, the highest level of arousal appeared with unpreferred music relative to the other conditions, though this pattern did not hold across all of the patients, across the different measurement periods (i.e., RH), or across the different dependent measures (GSR and HR) (see Supporting Analyses in SI Methods for more details).

Study 3: Neuroimaging of the Music Effect.

The neural correlates of the music effect were delineated by fMRI in one of our patients (MP). The behavioral task used was identical to the detection task used in study 1.

The responses on catch trials were withheld (as instructed) on 100% of the trials. We performed a 2 (target field) × 2 (music) ANOVA on the proportion of correct detections, with the mean of each session taken as an independent observation. There was an effect of target field (F1,7 = 579.4, P < 0.0001). Crucially, the effect of target field interacted with the music condition (F1,7 = 131.3, P < 0.0001) the amount of contralesional neglect was greatly reduced under preferred music conditions (Fig. 4A).

Functional neuroimaging data. (A) Proportion of correct responses as a function of the target visual field and the music conditions. (B) The music effect in the fMRI data. (C) The interaction between music and awareness of contralesional targets in the fMRI data, reflecting selective increases in activity to contralesional targets when there was preferred music playing. (D) PPI results indicating the functional coupling between the OFC and undamaged areas of the right posterior parietal cortex and early visual cortex on hit trials of the preferred compared with the unpreferred music condition.

We turn now to the fMRI data. The effect of the target location was clearly seen in the pattern of activations in early visual cortex. Right targets were associated with clusters of activation around left occipital cortex (BA18), whereas left targets activated the right occipital cortex (BA18). This suggests that MP did maintain eye fixation at the center of the display.

We first delineated the brain regions sensitive to the “music enjoyment” by contrasting activity in the preferred vs. unpreferred conditions. We found enhanced activity in the left inferior frontal gyrus (including Broca's area), the left dorsolateral prefrontal cortex, and the cingulate gyrus (Fig. 4B and Table S1). The enhancement of awareness of contralesional targets under pleasant music listening conditions was associated with increased activity in the left orbitofrontal cortex (OFC) and a network of early visual areas around the lingual gyrus in the right hemisphere that extended to the fusiform gyrus and the middle temporal cortex, and also in the caudate. This pattern of activity was indicated by a contrast that assessed the interaction between music and awareness factors carried out only for targets on the contralesional side (Fig. 4C and Table S1). It is also interesting to note that the music effect and its interaction with awareness of contralesional targets also correlated with activation in the amygdala (−20, −8, −16, and −28, −10, −22, respectively) at a more relaxed threshold (P = 0.01).

Lastly, a functional connectivity analysis [based on a psychophysiological interaction (PPI)] (32) was performed. The aim of the PPI analysis was to provide evidence that regions involved in positive affect induced by music (i.e., left OFC) were functionally connected with attention and visual brain areas. The results confirmed this prediction. There was increased coupling between OFC (MNI seed: −12, 58, −12) and clusters within undamaged areas of the right posterior parietal cortex (40, −54, 38 Z = 5.65, P = 0.001) and early visual cortex (left: −10, −76, 8 Z = 4.64, P = 0.001, and −16, −42, −4 Z = 4.16, P = 0.001 right: 20, −42, 2 Z = 6.25, P = 0.001) on hit trials in the preferred compared with the unpreferred music condition (Fig. 4D and Table S2). This result indicates a coupling driven by MP listening to pleasant music between emotional brain areas in the left OFC (20) and regions concerned with attentional modulation of visual processes (posterior parietal and early visual cortex). This is consistent with positive affect increasing the attentional resources available for visual perception.


Music to Inspire

At the end of the day, the music you listen to in order to get into a productive mindset depends on what you feel like listening to that day and what type of music puts you in the best mood. Look for playlists on streaming services like Spotify or YouTube that you can put on and let play while you refresh or do some light admin work.

This article is just a start – there is a plethora of research available that discusses what types of music are the best for creativity.

Whether it is writer’s block or you’re feeling deprived of inspirational oxygen, sometimes the best cure is a good playlist.


Watch the video: BlimE! - Dynamitt - Nicolay Ramm - BlimE-dansen 2021 - NRK Super (January 2022).