Dr. Mac Shine is a Joint-NHMRC Emerging Leadership Fellow/Bellberry Fellow at the Brain and Mind Centre, The University of Sydney, Australia. Dr. Shine is fascinated by how different parts of the brain work together to give rise to cognitive function. He primarily uses functional brain imaging to track communication patterns between brain regions, which allows him to characterize the brain network architecture in various states. One of his key interests is in understanding how different arms of the ascending arousal system affects the dynamic reconfiguration of the brain networks. Recently, Dr. Shine has become interested in using computational modeling to understand how the complex dynamics of brain function emerge, bridging the gap between microscopic neurobiological principles and macroscopic whole-brain phenomena.

Dr. Shine’s passion for science was ignited early on by his academic family, guiding him through biochemistry in college to medical school, where he was captivated by systems biology. His fascination deepened with the complexities of brain function, leading him to pursue a PhD in Cognitive Neuroscience at The University of Sydney and then a postdoctoral fellowship at Stanford University with Russell Poldrack. He now runs a systems neuroscience group at The University of Sydney that aims to combine functional neuroimaging with concepts from dynamical systems and theoretical neurobiology.

In this interview, Dr. Shine shared his stories, including how a pivotal rejection led to profound insights and collaborations, ultimately transforming his research approach and leading to the publication of his paper in Neuron. He also shared his vision for the future of human brain mapping, especially his excitement about the breakdown of disciplinary boundaries and the potential for increased conversations among experts in neuroanatomy, statistics, and modeling.

In his Keynote Lecture at OHBM 2024 in Seoul, Korea, Dr. Shine will present some of the recent work from his group on dynamical systems, neuroimaging, computational modeling, and neurobiology.