What Effect Does Music Have on the Brain?

Post by Amanda McFarlan

Music and the brain

Listening to music can be very visceral - it can evoke strong emotions, trigger memories and modulate physiological responses in the body. For example, songs with an upbeat tempo and major chords can evoke feelings of cheerfulness, while songs with a slower tempo using minor chords can evoke feelings of sadness. Learning to play music, especially from a young age, has been shown to have positive benefits that extend beyond enhanced musical abilities. Here, we will discuss how musical training as well as listening to music changes the brain.

What happens to our brain when we play music?

Playing a musical instrument is a complex task requiring coordinated use of multiple brain areas. Consider playing the guitar: The motor cortex and basal ganglia control the synchronized movements in the right and left hands for strumming and fingering. Meanwhile, feedback from the somatosensory cortex about hand, finger, and body positioning is relayed to brain areas like the cerebellum and prefrontal cortex for continuous modulation of movements. The auditory cortex analyzes the sounds being produced so play can be adjusted if necessary. If the musician is following a musical score, the visual system reads and interprets the musical symbols on the page. 

With such complex integration of nearly all sensory systems and higher-order cognitive processing in the brain, it is reasonable to think that playing a musical instrument might lead to changes in brain plasticity. Indeed, it has been shown that compared to non-musicians, musicians have larger brain volumes in areas involved in auditory and visuo-spatial processing, motor control and feedback integration. Studies have also demonstrated differences in how musicians vs. non-musicians process sounds — both for simple tones or complex melodies. For example, one study found that musicians had stronger cortical activation when they were presented with piano tones compared to pure tones, and that this activation was related to the age at which the individual began practicing their instrument. A different study found that auditory cortical representations in highly trained musicians are enhanced for musical timbres that are associated with their principal instrument, but not for musical timbres associated with other instruments. Musicians are also known to have enhanced abilities for musical imagery. In one study, participants were presented with the beginning of familiar melodies and were asked to imagine the melody. They were then presented with a tone and had to decide whether or not it was the next tone in the melody. Musicians were better at identifying whether the presented tone was correct compared to non-musicians. Thus, musical training may lead to a superior ability for musical imagery.

Considering the overlap between cortical networks for music and language, researchers have hypothesized that the two may be related. Research shows that musical training can have beneficial effects on language processing and in particular, in the discrimination of pitch. Musicians have a more robust neural representation of pitch contours compared to non-musicians. This increased ability was associated with the number of years of training, suggesting that years of experience may lead to better pitch discrimination.

What happens to our brain when we listen to music?

Not everyone plays a musical instrument, but nearly everyone listens to music. Just like playing an instrument, listening to music requires the activation of many brain areas, like the auditory cortex to discern and analyze pitches, timbres, rhythms, etc. in the music. Listening to music also recruits high-order brain areas involved in emotions, memory and attention. Indeed, listening to music can influence mood and arousal and evoke strong emotional responses including joy, sadness or tranquility. 

Unlike other rewarding stimuli like food or drugs of abuse, music does not have an obvious benefit for survival, nor addictive properties. However, music has been reported to produce very strong feelings of euphoria for the listener in some cases, commonly described as ‘chills down the spine’. Brain imaging studies have shown that listening to ‘chills down the spine’ music compared to neutral music results in increased cerebral blood flow to reward-related brain areas (e.g. the ventral striatum). The nucleus accumbens (also implicated in reward) was also found to be activated while listening to unfamiliar joyful music compared to silence and singing compared to speech. In line with these findings, positron emission tomography (PET) imaging studies have shown that dopamine release in the nucleus accumbens occurs during passages of music that induce ‘chills down the spine’.

In addition to having a rewarding effect and regulating mood, listening to music can affect arousal. Studies have shown that listening to relaxing music (slow tempo, low pitch and no lyrics) can reduce stress and anxiety brought on by an invasive medical procedure. Furthermore, music therapy that uses relaxation techniques and classical music was shown to reduce stress-related hormones and the activity of the hypothalamic-pituitary-adrenal (HPA) axis, responsible for the body’s stress response. The brainstem is thought to play an important role in changes in arousal while listening to music. One hypothesis to explain how music regulates stress and arousal is via the initiation of reflexive responses in the brainstem, which mediates heart rate, pulse, blood pressure, and body temperature. Listening to fast, upbeat music can cause an increase in these vital signs, while slow, relaxing music can decrease them.  

How does music affect the developing brain?

A large body of research demonstrates the benefits of exposing children to music at a young age. As discussed in the previous sections, playing music involves the recruitment of many different areas of the brain. One study showed that school-age children who received 15 months of musical training had increased grey matter density compared to age-matched children who did not receive musical training. Similarly, an MRI study revealed differences in macro and microscopic brain structure, including the maturation of cortical thickness in the temporal lobe, in students in a music program, but not those in a sports program. Research has shown that musical training in young children benefits speech. For example, rhythmic training can have a positive effect on both phonological processing and reading. One study in 9-month old babies revealed that babies who participated in a 12-session music program were better able to identify violations in music and speech versus a control group. Another study in young children found that those who received music (versus painting) instruction demonstrated stronger reading and pitch discrimination. Finally, musical training can also impact math skills. Students with low mathematics achievement improve in number production (reading, writing and counting numbers) after participating in non-instrumental musical training classes. All together, these findings suggest that musical training in young children can have beneficial effects that extend beyond enhanced musical abilities.

How can music help heal us?

The effects of music on mood and arousal make it a useful tool to improve well-being. Music therapy is a type of treatment whereby trained professionals administer music-based interventions, modulating attention, emotion, cognition, behaviour and communication. For example, listening to or playing music can be a useful distraction from negative sensations such as pain, anxiety, or sadness. Music-based interventions have been shown to decrease anxiety, perceived pain and depression symptoms in cancer patients. Therapeutic approaches using music can be helpful for the treatment of disorders such as depression, anxiety, and post-traumatic stress disorder, which are known to be associated with limbic system abnormalities. Further, music therapy can also have therapeutic effects in neurological disorders like stroke and Alzheimer’s disease. Music is a natural way to improve mood and well-being and is a promising tool for a wide variety of diseases or conditions. A greater understanding of the neurochemical effects of music is developing, however, more research is needed to understand the full potential of music therapy.

References

Chanda, M. L., & Levitin, D. J. (2013). The neurochemistry of music. Trends in cognitive sciences, 17(4), 179–193. https://doi.org/10.1016/j.tics.2013.02.007

Fernandez S. (2018). Music and Brain Development. Pediatric annals, 47(8), e306–e308. https://doi.org/10.3928/19382359-20180710-01

González-Martín-Moreno, M., Garrido-Ardila, E. M., Jiménez-Palomares, M., Gonzalez-Medina, G., Oliva-Ruiz, P., & Rodríguez-Mansilla, J. (2021). Music-Based Interventions in Paediatric and Adolescents Oncology Patients: A Systematic Review. Children (Basel, Switzerland), 8(2), 73. https://doi.org/10.3390/children8020073

Koelsch S. (2009). A neuroscientific perspective on music therapy. Annals of the New York Academy of Sciences, 1169, 374–384. https://doi.org/10.1111/j.1749-6632.2009.04592.x

Pantev, C., & Herholz, S. C. (2011). Plasticity of the human auditory cortex related to musical training. Neuroscience and biobehavioral reviews, 35(10), 2140–2154. https://doi.org/10.1016/j.neubiorev.2011.06.010

Särkämö, T., & Soto, D. (2012). Music listening after stroke: beneficial effects and potential neural mechanisms. Annals of the New York Academy of Sciences, 1252, 266–281. https://doi.org/10.1111/j.1749-6632.2011.06405.x

Wang, S., & Agius, M. (2018). The neuroscience of music; a review and summary. Psychiatria Danubina, 30(Suppl 7), 588–594.

Integration of New Memories in the Hippocampal Network

Post by Anna Cranston

What's the science?

The incorporation of new memories without disrupting acquired ones is critical for adaptation and survival. Prior memories have been shown to influence and promote further learning as well as the ability to re-active memories held in the hippocampus network. However, the exact network-level operations underlying cross-memory interaction are not yet known. This week in Nature Neuroscience, Gava and colleagues investigate the organizational mechanisms that allow for the continuous integration and interaction of hippocampal memories.

How did they do it?

The authors took recordings from the dorsal CA1 region of the hippocampus in mice, using microdrives containing electrodes that were surgically implanted at the site of the CA1 hippocampal pyramidal layer. In these recordings, mice were exploring a familiar environment before and after associating a separate, novel environment with a reward (sucrose), using a behavioral test known as the conditioned place preference (CPP) task. They analyzed the compartment preference for the mice that were conditioned by sucrose solution in the CPP task, while simultaneously recording neuronal spiking in these mice. Next, using recordings of spike trains, which are representations of neuronal activity at defined time-points, the authors recorded the mice during active exploration to determine the firing pattern relationships between sets of co-active, or nearby neurons during each task. The authors also constructed mathematical graphs that represent the spike relationships among CA1 principal cells recorded in a given CPP task session. Finally, they analyzed spatial coherence and topology of neuronal cluster firing, to determine grouped firing patterns of neurons (how the neurons co-fire together) that depended on the location of the mice during the task.

What did they find?

Through the spike train recordings obtained during the CPP performance task, the authors found that the new CPP memory reorganized pre-existing hippocampal firing topology. In addition, through a principal component analysis of co-firing maps generated from recordings throughout the CPP tasks, they found that the co-firing maps could be described by three principal components (in other words, the data varied primarily along three axes in three ways): 1) Similar co-firing patterns could be seen across different sessions in the same environment, indicating the location of the memory and considered to represent the core or main part of the memory, 2) Different co-firing patterns described different aspects of the behavioural task/CPP sessions, and 3) Different co-firing patterns differentiated between exposure and re-exposure to an environment. Overall, new memories obtained during the CPP task influenced existing firing patterns of hippocampal neurons representing prior memory. Finally, the authors found that high- and low-activity cells contribute differently to these hippocampal network co-firing axes, working together to segregate memories by space, novelty, and events.

What's the impact?

This study investigated the topology of neuronal co-activity and found that memory information spans multiple functional axes of the neuronal network in the mouse hippocampus. Their findings reveal underlying principles of organization for how memories are integrated, and provide novel insights into the division of labor between distinct types of hippocampal neurons.  

Gava et al. Integration of New Memories in the Hippocampal Network. Nature Neuroscience (2021). Access the original scientific publication here.

Expectations of Reward and Efficacy Guide Cognitive Control Allocation

Post by Andrew Vo

What's the science?

Each day, we are faced with tasks and challenges for which we must decide whether the mental effort (in the form of cognitive control) to invest is worthwhile. The Expected Value of Control theory posits that people adjust the amount of mental effort they invest in a task by integrating information about the expected reward (the expected outcome) and the efficacy of task performance (the likelihood that investing effort will yield the desired outcome) to determine the expected value of control. The role of reward expectancy in shaping cognitive control is well-established, however, the effects and neural mechanisms of efficacy are far less studied. This week in Nature Communications, Frömer and colleagues investigated the contributions of reward, efficacy, and their interaction on behavioral and neural measures of control allocation.

How did they do it?

Across three studies, the authors tested their hypothesis that the allocation of cognitive control is based on the expected value of control. The worth of executing different types and amounts of control is determined by weighing its costs (i.e., mental effort) against its benefits. These benefits are shaped by a combination of the two incentive components: reward and efficacy.

Participants completed a modified version of the color-word Stroop task that dissociated reward and efficacy effects on control allocation. On each trial, participants were initially presented with an incentive cue that disclosed whether they would receive a high or low monetary reward if successful ($0.10 vs. $1.00) and whether their efforts would be high or low in efficacy (success determined by their performance versus by the flip of a coin). They were then shown a Stroop stimulus — a color-word printed in either the same (congruent) or different (incongruent) color — to which they needed to respond with the color the word was written in rather than the word itself. Feedback was then given to indicate the value of the reward received. Correct reaction times (i.e., how fast the participant made a correct response) were used as a measure of task performance.

In Study 2, participants performed the task as their brain activity was recorded using EEG. The authors were interested in how reward and efficacy modulated the magnitude of two specific event-related potentials (ERP): the P3b (250-550 ms after cue onset that reflects incentive evaluation) and the CNV (500 ms before Stroop target onset that reflects control allocation).

What did they find?

The authors found that both reward and efficacy, as well as their interaction, modulated task performance. Participants were faster to make a correct response for higher levels of reward and efficacy. This pattern of findings was consistent whether each incentive component was varied in a binary manner (Study 1 and 2) or parametrically across four levels (Study 3). Control analyses ruled out that these effects were not simply due to speed-accuracy trade-offs, task difficulty, or practice effects.

EEG recordings (Study 2) revealed that reward and efficacy manipulations modulated the amplitude of both ERPs of interest. The P3b and CNV amplitudes were significantly larger in response to cues signaling larger rewards and efficacy. Notably, only the CNV was sensitive to the interaction of both incentive components. Examining trial-by-trial variability, the authors found that larger amplitudes in both ERPs were associated with an increased likelihood of correct responses and faster correct reaction times, with a more pronounced effect in CNV than P3b.

What's the impact?

This study provides behavioral and neural evidence supporting the critical roles of both reward expectancy and efficacy in determining the value of exerting cognitive control. The results are in line with predictions made by the EVC theory, which suggests that the integration of both incentive components (reward and efficacy) shapes how mental effort is allocated. As the authors succinctly state, “Cognitive control is critical but also costly”. This study illustrates how we may go about computing the worth of investing mental effort (in the form of cognitive control) towards achieving goals throughout our daily lives.

Frömer et al. Expectations of reward and efficacy guide cognitive control allocation. Nature Communications (2021). Access the original scientific publication here.