Barabási, Dániel L, Bianconi, Ginestra, Bullmore, Ed, Burgess, Mark, Chung, SueYeon, Eliassi-Rad, Tina, George, Dileep, Kovács, István A, Makse, Hernán, Nichols, Thomas E, Papadimitriou, Christos, Sporns, Olaf, Stachenfeld, Kim, Toroczkai, Zoltán, Towlson, Emma K, Zador, Anthony M, Zeng, Hongkui, Barabási, Albert-László, Bernard, Amy, Buzsáki, György (August 2023) Neuroscience Needs Network Science. The Journal of Neuroscience, 43 (34). pp. 5989-5995. ISSN 0270-6474
PDF
2023_Barabasi_Neuroscience_Needs_Network_Science.pdf - Published Version Restricted to CSHL Campus Only Available under License Creative Commons Attribution. Download (519kB) |
Abstract
The brain is a complex system comprising a myriad of interacting neurons, posing significant challenges in understanding its structure, function, and dynamics. Network science has emerged as a powerful tool for studying such interconnected systems, offering a framework for integrating multiscale data and complexity. To date, network methods have significantly advanced functional imaging studies of the human brain and have facilitated the development of control theory-based applications for directing brain activity. Here, we discuss emerging frontiers for network neuroscience in the brain atlas era, addressing the challenges and opportunities in integrating multiple data streams for understanding the neural transitions from development to healthy function to disease. We underscore the importance of fostering interdisciplinary opportunities through workshops, conferences, and funding initiatives, such as supporting students and postdoctoral fellows with interests in both disciplines. By bringing together the network science and neuroscience communities, we can develop novel network-based methods tailored to neural circuits, paving the way toward a deeper understanding of the brain and its functions, as well as offering new challenges for network science.
Actions (login required)
Administrator's edit/view item |