Using music to model the brain s realisation of time
Name of applicant
Leonardo Bonetti
Amount
DKK 877,960
Year
2020
Type of grant
Visiting Fellowships at University of Oxford
What?
Time is a central constituent of the physical world and thus characterises and regulates human life. Indeed, to pursue a successful existence and achieve a flourishing state, humans are required to find ways to come to terms with the concept of time. Even though many great contributions have been produced, much is left to learn about how the brain encodes the perception of time and how time interacts with the brain to make the world meaningful to humans. Thus, in my project I wish to understand and mathematically model how the brain successfully processes temporal sequences and information evolving over time.
Why?
Throughout history, the interaction between humans and time has received a wide attention from several fields, spanning from mathematics, physics and natural sciences to the arts and humanities. Moreover, the last decades of neuroscience showed that the brain is a dynamic system characterized by (de)synchronization of neuronal populations and transitions between different functional states. Yet, what are the specific brain mechanisms that allow a sequence of information extended over time (such as music) to become meaningful for people? Indeed, what are the brain mechanisms required to remember and attribute meaning to the past, process the present and predict the future? Answering such questions may lead us to the very core of the flourishing human brain.
How?
In this project, I propose to expand the field by developing and using advanced analysis methods for brain data recorded with state-of-the-art machines such as magnetoencephalography (MEG) and magnetic resonance imaging (MRI). Indeed, I wish to combine clustering algorithms with mathematical models to describe and simulate the brain understanding of temporal sequences. Moreover, since music is the human art that mainly acquires meaning through the logical combination of sounds extended over time, I wish to use mathematically controlled musical patterns as ideal and unique proxies to investigate the dynamical brain mechanisms responsible to build the meaning of past and present events and information and make predictions about future ones.