Amir Mano
Computational Neuroscience from the Sagol School of Neuroscience
Neuroplasticity Induced by Music Learning and Practice
Project description
Skill learning refers to the dedicated process of learning and practicing to enhance the accuracy, speed, or overall performance of a specific perceptual, cognitive, or motor task. This form of learning heavily depends on neuroplasticity; as one practices and repeats specific actions, the individual’s brain forms new connections and amplifies existing ones to optimize performance. Diffusion MRI methods can reveal these learning-induced neuroplastic changes, from the microscopic level – by exploring the microstructural characteristics of brain tissue; to the whole-brain network level – by focusing on the connections between brain regions, as known as ‘connectomics’.
Playing a musical instrument is a complex cognitive task involving higher cognitive functions, multisensory integration, and motor control. Therefore, it serves as a multimodal model for studying skill learning, which is suitable for both between-subjects comparisons and longitudinal studies. Combining both approaches can help define the characteristics of a musician's brain, and provide insights on how skill learning might affect the brain in general.
In my MSc study, we found gray matter changes induced by a two-month trumpet learning course in a real-life learning environment, as revealed by the diffusion MRI metric 'mean diffusivity'. While these results show microscopic changes, broader approaches like 'connectomics' are necessary for a comprehensive understanding of music learning effects.
In this study, we intend to explore how music learning affects the brain and define which characteristics are more dominant in the musician’s brain. To do so, we plan to combine within- and between-subjects approaches. We will analyze the data from my MSc study using connectomics and explore the general population using the expanding ‘Brain Bank’. This database includes subjects with diverse levels of musical involvement: non-musicians, professionals, and everything in between.
About me
Amir holds a BSc in Linguistics and Biology with an emphasis on neuroscience, and an MSc in Computational Neuroscience from the Sagol School of Neuroscience at Tel Aviv University. His master’s thesis, under the supervision of Prof. Yaniv Assaf, focused on grey matter plasticity induced by learning a musical instrument.
In his PhD, Amir delves deeper into the interplay between neuroplasticity and music, exploring the effect of music learning on the general population. With his background as a trombone player, Amir sees music's complexity as a valuable model for understanding skill acquisition more broadly. Furthermore, as a teaching assistant across various disciplines, he seeks to identify the factors influencing success or failure during complex, real-life learning processes.