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Editorial: Advancing our understanding of the impact of dynamics at different spatiotemporal scales and structure on brain synchronous activity, volume II
Editorial on the Research Topic Advancing our understanding of the impact of dynamics at different spatiotemporal scales and structure on brain synchronous activity, volume II The study of complex networks in neuroscience, coupled with dynamical models, has emerged as a powerful approach to unraveli...
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Published in: | Frontiers in computational neuroscience 2024-03, Vol.18, p.1386652-1386652 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | Editorial on the Research Topic Advancing our understanding of the impact of dynamics at different spatiotemporal scales and structure on brain synchronous activity, volume II The study of complex networks in neuroscience, coupled with dynamical models, has emerged as a powerful approach to unraveling the intricate workings of the brain across species. Leveraging complex network analysis and dynamical modeling, researchers can investigate how alterations in brain network organization are related to neurological disorders (see e.g., Stam, 2014). [...]understanding the mechanisms by which synaptic adaptation influences network dynamics can provide insights into disease pathology and potential therapeutic targets (see e.g., Berner et al., 2023; Sawicki et al., 2023). Translational studies involving both human subjects and animal models, such as mice, facilitate the validation of findings across species and provide valuable insights into the generalizability of therapeutic interventions. [...]the integration of complex networks, dynamical models, synaptic adaptation, and stimulation techniques represents an approach with significant potential for advancing our understanding of brain function and informing novel therapeutic strategies for neurological and psychiatric disorders. The power density distribution followed a power law with an average scaling exponent of ~1.4 across IMF frequencies (2–2,000 Hz). |
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ISSN: | 1662-5188 1662-5188 |
DOI: | 10.3389/fncom.2024.1386652 |