Minimal DD values of emergent <i>n</i>-macros in the 5-node network with local dynamics defined by a SJ3D NMM.

<p>Each matrix presents a parameter sweep across global coupling (y-axis) and dynamical noise (x-axis). The top row shows DD values for 2-macros and 3-macros in the coupled brain network. The bottom row presents the corresponding DD values for the uncoupled brain network. Darker colours indica...

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Bibliographic Details
Main Author:	Borjan Milinkovic (21349908) (author)
Other Authors:	Lionel Barnett (21349911) (author), Olivia Carter (194606) (author), Anil K. Seth (8755419) (author), Thomas Andrillon (6039964) (author)
Published:	2025
Subjects:	Biophysics Biochemistry Medicine Cell Biology Cancer Infectious Diseases Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified work also provides using information theory two key aspects significant scientific challenge global coupling parameter counteracts global coupling complex neural systems complete computational implementation biophysical neural model independent dynamical process adding dynamical noise macroscopic variable </ dynamical independence </ leveraging transfer entropy div >< p emergent neural dynamics emergent dynamical structure functional integration within dynamical independence transfer entropy dynamical dependence macroscopic dynamics structure remains level dynamics functional integration macroscopic variables macroscopic processes thereby elucidating sustaining coherent results indicate relatively minimised minimal 5 microlevel variables method identifies lower levels less localised g ., functional segregation finding suggests brain organisation balanced points balanced point
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Minimal DD values of emergent <i>n</i>-macros in the 5-node network with local dynamics defined by a SJ3D NMM.

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