By Dragoș Pînzaru and Jisha Vallachalil Jayaprakash
The internet is filled with informative videos on various psychological concepts that claim to be evidence-based, promising to help citizens of the internet lead better lives. We decided to explore the science behind some statements made within one of videos of the famous youtuber and Stanford professor Andrew Huberman.
The internet is filled with informative videos on various psychological concepts that claim to be evidence-based. You’ll find “gurus” in hundreds helping citizens of the internet lead better lives. But perhaps it would be advisable for impressionable citizens to exercise critical thinking when perusing through these treasure-troves of knowledge. Yes, it might be relevant to really see if it is all based on scientific evidence or if it is just misinformation/deceptive practices. And so, we decided to explore the science behind some statements made within one of videos of the famous youtuber and Stanford professor Andrew Huberman.
In his podcast episode “Optimise Your Learning & Creativity With Science-Based Tools”, Stanford professor Andrew Huberman provides suggestions aiming to enhance learning, creativity and associated processes, with particular emphasis on music as a facilitating method. Throughout many of his podcasts, he claims the statements expressed are evidence-based/asserts the evidence-based nature of his statements, with the description box pointing to research papers. Naturally, when this specific podcast displayed no references, we were intrigued. He suggests that listening to music could improve focus for learning, provided specific individual characteristics related to arousal (alert or attentive state) are met. This is the statement we chose to investigate.
Huberman’s podcasts are often a mix of scientific discussion and practical suggestions. In this episode, he delves into how certain types of music might positively affect our learning processes. The claim centres around the brain’s frontal-basal ganglia networks, particularly the dopamine-mediated D1 and D2 pathways. These pathways, according to Huberman, govern our ‘go’ (active, engaged) and ‘no-go’ (inhibitory, less active) behaviours. The essence of his argument is that for individuals in a ‘no-go’ state, music can facilitate a shift to a more conducive state for learning. The functioning of this network leads to three forms of arousal (arising from the different balance of D1 and D2 mediated activity), which can generally characterise the individual (like a personality trait) or are more moment-specific (current state), Huberman notes. The first is dominated by D1 ‘go’ activity, with the person likely being overstimulated and unable to focus well on the learning task. The second form displays a balance in D1 and D2 mediated activity, with the individual aroused enough to pursue the learning activity, yet also able to suppress possible distractors. The third and final form of arousal is dominated by D2 activity, with the person bound to a ‘no-go’ state, in stark opposition to the alertness required to initiate and maintain learning. The essence of his argument is that for individuals in a ‘no-go’ state, music can facilitate a shift to a more conducive state for learning.
Maybe we need to break down the science a bit? The frontal-basal ganglia, where D1 and D2 receptors play their role, is crucial for behavioural regulation. Think of D1 as the accelerator in your car, driving ‘go’ behaviours, and D2 as the brake, handling ‘no-go’ responses. Huberman posits that when we’re dominated by D2 activity, resulting in low arousal or focus, music can help elevate us to a balanced state optimal for learning.
Indeed, research in this field provides some support to Huberman’s statements. Studies like those by Sandrini et al. 2020 and Cohen & Frank (2009) have shown basal ganglia’s involvement in no-go inhibitory responses and reinforcement learning through D1 and D2 pathways.
Another function that the basal ganglia are implicated in, is processing music. The basal ganglia, alongside other brain structures like the putamen, play a crucial part in both the production and perception of rhythmic sounds. This is exemplified in the work of Grahn & Rowe (2009), who explored how these brain areas activate the perception of rhythms, particularly those with preferred tempos, linking them closely with the premotor cortex.
In addition, the emotional experiences induced by music are also intricately tied to the basal ganglia’s interactions with other structures. Brodal et al. (2017) highlight how listening to music can evoke strong emotional reactions through its neuroanatomical interactions, particularly with the amygdala. This relationship is further deepened by the involvement of a network that governs reward experiences and expectations, a process often accompanied by elevated dopamine release, especially when there is an anticipated emotional response to music. While music has been found to affect arousal levels, there is literature suggesting that this has an impact on the learning process also. With reference to the Yerkes-Dodson’s U-curve, optimal levels of arousal have been found to promote learning (Yerkes & Dodson, 1908). Music thus, does not directly impact learning, but instead does so through other mediators such as arousal and mood, which is also the premise for the arousal-mood-hypothesis (Lehmann & Seufert, 2017).
However, the leap from these findings to a direct enhancement of learning through music is not straightforward. While arousal levels, undoubtedly influenced by music, can impact learning (as per Yerkes-Dodson’s law), the direct effect of background music on complex learning tasks remains underexplored and somewhat contentious. For instance, de la Mora Velasco & Hirumi (2020) highlighted the challenges in conclusively linking music to learning outcomes due to methodological variations and the complexity of the subject matter.
In essence, while there is a scientific foundation for a relationship between music, arousal, and brain activity the direct application of this to learning enhancement, as posited by Huberman, remains an area ripe for further research. It suggests that while music might play a role in creating an optimal learning environment, its direct influence on complex learning tasks is not yet definitively established. Consequently, it is our belief that the claim is at best an educated guess meant to make use of Huberman’s relational processing to provide a piece of advice, yet that makes it merely a half-truth. And as avid learners and enthusiasts of neuroscience, it’s crucial to approach such claims with both interest, AND a healthy dose of scepticism!
Podcast link: https://youtu.be/uuP-1ioh4LY?t=1512
References
Brodal, H. P., Osnes, B., & Specht, K. (2017). Listening to Rhythmic Music Reduces Connectivity within the Basal Ganglia and the Reward System. Frontiers in Neuroscience, 11. https://www.frontiersin.org/articles/10.3389/fnins.2017.00153
Cohen, M. X., & Frank, M. J. (2009). Neurocomputational models of basal ganglia function in learning, memory and choice. Behavioural Brain Research, 199(1), 141–156. https://doi.org/10.1016/j.bbr.2008.09.029
de la Mora Velasco, E., & Hirumi, A. (2020). The effects of background music on learning: A systematic review of literature to guide future research and practice. Educational Technology Research and Development, 68(6), 2817–2837. https://doi.org/10.1007/s11423-020-09783-4
Grahn, J. A., & Rowe, J. B. (2009). Feeling the beat: Premotor and striatal interactions in musicians and nonmusicians during beat perception. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 29(23), 7540–7548. https://doi.org/10.1523/JNEUROSCI.2018-08.2009
Lehmann, J. A. M., & Seufert, T. (2017). The Influence of Background Music on Learning in the Light of Different Theoretical Perspectives and the Role of Working Memory Capacity. Frontiers in Psychology, 8. https://www.frontiersin.org/articles/10.3389/fpsyg.2017.01902
Sandrini, M., Xu, B., Volochayev, R., Awosika, O., Wang, W.-T., Butman, J. A., & Cohen, L. G. (2020). Transcranial direct current stimulation facilitates response inhibition through dynamic modulation of the fronto-basal ganglia network. Brain Stimulation, 13(1), 96–104. https://doi.org/10.1016/j.brs.2019.08.004
Yerkes, R. M., & Dodson, J. D. (1908). The relation of strength of stimulus to rapidity of habit-formation. 459–482.
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