The Time Varying Networks of the Interoceptive Attention and Rest

Abstract

and the fellowship 721415 received from Consejo Nacional de Ciencia y Tecnología (CONACYT). FAB acknowledges the partial funding from the CB255462 project. The authors thankfully acknowledge the imaging resources and support provided by the "Laboratorio Nacional de Imagenología por Resonancia Magnética", CONACYT network of national laboratories Consejo Nacional de Ciencia y Tecnología (CONACYT). CONACYT had no role in study design, data collection, analyses nor writing the manuscript. We are grateful to M.Sc. Leopoldo González-Santos and Dr. Erick Pasaye for technical support and Dr. M.C. Jeziorski for his manuscript editing.

Inducing a meditative state by artificial perturbations: A mechanistic understanding of brain dynamics underlying meditation

“…Moreover, this DMN-salience-control network interplay has been described in models of focused attention meditation developed by Hasenkamp et al (2012) and Ganesan et al (2022) . Different static and seed-based approaches have analyzed blood oxygen level-dependent (BOLD) signal activity and network connectivity changes of meditation in health ( Garrison, Scheinost, Constable, & Brewer, 2014 ; Ives-Deliperi, Howells, Stein, Meintjes, & Horn, 2013 ; Kilpatrick et al, 2011 ; Kyeong, Kim, Kim, Kim, & Kim, 2017 ; Martínez et al, 2021 ; Pagnoni, 2012 ; Vishnubhotla et al, 2021 ) and brain disorders ( Datko et al, 2022 ; Goldin, Ramel, & Gross, 2009 ; Li et al, 2022 ; Lifshitz et al, 2019 ). Furthermore, theoretical methods have considered the underlying brain dynamics ( Bremer et al, 2022 ; Lim, Teng, Patanaik, Tandi, & Massar, 2018 ; Martínez et al, 2021 ; Marusak et al, 2018 ; Mooneyham et al, 2017 ), including whole-brain approaches such as turbulent dynamics ( Escrichs et al, 2022 ), dynamical complexity ( Escrichs et al, 2019 ) and structural and effective connectivity ( De Filippi et al, 2022 ).…”