Robin W. Wilkins, Ph.D.
Network Neuroimaging Lab
When an Idea
becomes a Movement
Visualization of Network-based Statistics & the Effects of Music Listening Preferences:
Degree and Global Efficiency.
Here is an image depicting how the brain network responds to preferred versus non-preferred or "diskliked". Degree is indicated by the peaks in the brain. Global Efficiency is depicted by color. Notice the red peaks when the music is preferred within the precuneus, a pivitol region within the default mode network.
Network-based approaches to the study of complex systems have become ubiquitous in a variety of research areas. Steeped in the mathematical foundation of graph theory, network science has led to a greater understanding of the interactions between components in systems as disparate as social networks, biological systems, communication arrays, and transportation networks. More recently, the fields of neuroscience more broadly and neuroimaging more specifically have greatly benefited from network science methods. Here, the brain is subdivided into regions (represented as network nodes) and inter-regional interactions (represented as network edges) estimated from structural or functional imaging modalities, including diffusion tensor imaging (DTI), functional magnetic resonance imaging (fMRI), electroencephalography (EEG), or magnetoencephalography (MEG).
Studying the brain as a complex system presents an opportunity to utilize network science methods to uncover patterns in inter-regional interactions that are not apparent with more traditional neuroimaging methods. A focal impetus behind these studies arises from the hypothesis that network science provides an accurate representation of the brain as an interconnected system, an organizational property that is often neglected in traditional neuroimaging methods. Perhaps even more importantly, network methods allow for a statistically principled investigation of different brain states and psychiatric or neurological disorders under a common representational framework.
The Effects of Music on the Brain.
Most people think music is entertainment.
Yet, neuroscientifically, the human brain somehow 'understands' and is affected by this complex acoustic phenomenon without needing any instruction. Perhaps understanding how the brain is affected by music can help us understand how the brain functions as a complex system.
Leading beyond incrementalism, the lab seeks to employ new network neuroscience strategies and innovative methods to generate evidence-based research and optimize outcomes measurements for the ultimate translation and application of network neuroimaging results, based on "The effects of music on the brain".
Our work aims to: 1) advanced a Network Neuroscience understanding of the complex system of the brain 2) understand strategies for enhancing and controlling optimal mental performance to strengthen brain function, and 3) develop network-based frontiers between Nanoscience and Nanotechnology to provide new evidence for how to understand, change, and restore human brain performance.
We seek to pull back the veil...
to understand the full power that can result from an understanding of complex systems
The Effects of Music on the Brain.
Within the brain, music affects an intricate set of complex neural processing systems. These include structural components as well as functional elements implicated in cognition, sensory and motor planning and execution, memory, and mood or emotional fluctuation. Because music affects such diverse systems, it is an ideal tool for exploring the complex system of the brain through network science methods. These studies here explore how music listening and intensive musical training influence structural and functional brain network connectivity. While still in its infancy, the field of network neuroscience promises to continue to inspire new discoveries in one of nature’s most complex systems – the human brain. For more information, please click on research projects.
This figure depicts how listening to different types of preferred music can alter functional brain networks. This figure is representative of the consistency of community structure in the brains of 21 young adults listening to their favorite music. Some had favorite songs with lyrics but others did not.
We measured this data using community structure methods Qcut and Scaled Inclusivity. Notice that if you 'like' the music, the frontal regions of the brain are engaged with brain regions that are suggested to support our ability to self-reflect and ruminate or when we think about our 'hopes and dreams' called the Default Mode Network. However, when the music is disliked, the frontal regions appear to be disengaged in the community. Interestingly, the bright red area is a very tight community and essentially not included in the community of brain region suggested as important for introspective thoughts, such as our mind wandering and daydreaming experiences.
When listening to a favorite song--regardless of the presence or absence of lyrics or the type of music-- the regions of the brain are similar to preferred music, but this result clearly show that the brain regions used for self-reflection are tightly coupled in the brain's responses to the music. Click here to read more....