Across-brain neurodynamic organizations arise when teams perform coordinated tasks. We describe a symbolic electroencephalographic (EEG) approach that identifies when team neurodynamic organizations occur and demonstrate its utility with scientific problem solving and submarine navigation tasks. Each second, neurodynamic symbols (NS) were created showing the 1-40 Hz EEG power spectral densities for each team member. These data streams contained a performance history of the team's across-brain neurodynamic organizations. The degree of neurodynamic organization was calculated each second from a moving window average of the Shannon entropy over the task. Decreased NS entropy (i.e., greater neurodynamic organization) was prominent in the ~16 Hz EEG bins during problem solving, while during submarine navigation, the maximum NS entropy decreases were ~10 Hz and were associated with establishing the ship's location. Decreased NS entropy also occurred in the 20-40 Hz bins of both teams and was associated with uncertainty or stress. The highest mutual information levels, calculated from the EEG values of team dyads, were associated with decreased NS entropy, suggesting a link between these two measures. These studies show entropy and mutual information mapping of symbolic EEG data streams from teams can be useful for identifying organized across-brain team activation patterns.
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http://dx.doi.org/10.1080/17470919.2015.1056883 | DOI Listing |
Cogn Neurodyn
December 2025
Shanghai University, Shanghai, China.
Neurodynamic observations indicate that the cerebral cortex evolved by self-organizing into functional networks, These networks, or distributed clusters of regions, display various degrees of attention maps based on input. Traditionally, the study of network self-organization relies predominantly on static data, overlooking temporal information in dynamic neuromorphic data. This paper proposes Temporal Self-Organizing (TSO) method for neuromorphic data processing using a spiking neural network.
View Article and Find Full Text PDFNeural Netw
December 2024
School of Mathematics and Statistics, Yili Normal University, Yining 835000, China.
In this paper, a recurrent neural network is proposed for distributed nonconvex optimization subject to globally coupled (in)equality constraints and local bound constraints. Two distributed optimization models, including a resource allocation problem and a consensus-constrained optimization problem, are established, where the objective functions are not necessarily convex, or the constraints do not guarantee a convex feasible set. To handle the nonconvexity, an augmented Lagrangian function is designed, based on which a recurrent neural network is developed for solving the optimization models in a distributed manner, and the convergence to a local optimal solution is proven.
View Article and Find Full Text PDFCureus
November 2024
Internal Medicine, Mahatma Gandhi Institute of Medical Sciences, Wardha, IND.
Introduction: Yoga practices emphasize spinal energy's role in physical, mental, and spiritual well-being, suggesting specific techniques that can enhance energy flow along the spine. Modern research aims to validate these claims and understand the mechanisms behind these effects, potentially integrating them into contemporary healthcare models. This study explores the relationship between yoga breathing techniques, spinal energy dynamics, and health based on yoga philosophy and bioenergetics.
View Article and Find Full Text PDFMedicina (Kaunas)
November 2024
Departamento de Fisioterapia, Facultad de Medicina, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, 28660 Boadilla del Monte, Spain.
Neural Netw
October 2023
University of Rijeka, Rijeka, Croatia.
Accentuation has been proposed as a general principle of perceptual organization. Here, we have developed a neurodynamic architecture to explain how accentuation affects boundary segmentation and shape perception. The model consists of bottom-up and top-down pathways.
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