Rapid dynamics of electrophysiological connectome states are heritable

• Published in: Harvard data science review Vol. 8; no. 4; pp. 1065 - 1088
• Main Authors: Jun, Suhnyoung, Alderson, Thomas H., Malone, Stephen M., Harper, Jeremy, Hunt, Ruskin H., Thomas, Kathleen M., Iacono, William G., Wilson, Sylia, Sadaghiani, Sepideh
• Format: Journal Article
• Language: English
• Published: 255 Main Street, 9th Floor, Cambridge, Massachusetts 02142, USA MIT Press 10.12.2024; MIT Press Journals, The; The MIT Press
• Subjects: Brain; Cognition & reasoning; Cognitive ability; Dynamic functional connectivity; Dynamics; Electrophysiology; Heritability; Hidden Markov modeling; Markov chains; Multivariate analysis; Neural networks; Neurosciences; Theta rhythms; Time measurement; Transition probabilities; Twin study; Twins; Variance component modeling; Electrophysiology; Dynamic functional connectivity; Heritability; Hidden Markov modeling; Twin study; Variance component modeling

Time-varying changes in whole-brain connectivity patterns, or connectome state dynamics, are a prominent feature of brain activity with broad functional implications. While infraslow (<0.1 Hz) connectome dynamics have been extensively studied with fMRI, rapid dynamics highly relevant for cognitio...