TY - JOUR
T1 - Neuroscience Needs Network Science
AU - Barabási, Dániel L.
AU - Bianconi, Ginestra
AU - Bullmore, Ed
AU - Burgess, Mark
AU - Chung, Sue Yeon
AU - Eliassi-Rad, Tina
AU - George, Dileep
AU - Kovács, István A.
AU - Makse, Hernán
AU - Nichols, Thomas E.
AU - Papadimitriou, Christos
AU - Sporns, Olaf
AU - Stachenfeld, Kim
AU - Toroczkai, Zoltán
AU - Towlson, Emma K.
AU - Zador, Anthony M.
AU - Zeng, Hongkui
AU - Barabási, Albert László
AU - Bernard, Amy
AU - Buzsáki, György
N1 - Publisher Copyright:
Copyright © 2023 the authors.
PY - 2023/8/23
Y1 - 2023/8/23
N2 - 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.
AB - 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.
KW - Connectomics
KW - Network Neuroscience
KW - Network Science
KW - NeuroAI
KW - Neurodevelopment
KW - Systems Neuroscience
UR - http://www.scopus.com/inward/record.url?scp=85168596012&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85168596012&partnerID=8YFLogxK
U2 - 10.1523/JNEUROSCI.1014-23.2023
DO - 10.1523/JNEUROSCI.1014-23.2023
M3 - Article
C2 - 37612141
AN - SCOPUS:85168596012
SN - 0270-6474
VL - 43
SP - 5989
EP - 5995
JO - Journal of Neuroscience
JF - Journal of Neuroscience
IS - 34
ER -