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Risto Miikkulainen

3 papers in the library · 217 citations · publishing 2010-2015

Papers

Intensive training induces longitudinal changes in meditation state-related EEG oscillatory activity.

Frontiers in human neuroscience January 1, 2012 Manish Saggar, Brandon G King, Anthony P Zanesco et al. 136 citations

Intensive meditation training produces replicable changes in brainwave activity. In a controlled study, participants who practiced focused attention meditation for three months showed reduced beta-band power over anterior and posterior scalp regions during meditation, compared to a wait-list group that later received identical training. Individual alpha frequency also decreased across both retreats, and the decrease was directly related to the amount of meditation practice. These longitudinal changes in brain oscillatory activity help explain how meditation may support long-term improvements in attention and cognition.

A computational approach to understanding the longitudinal changes in cortical activity associated with intensive meditation training

BMC Neurosci January 1, 2010 Manish Saggar, Stephen R Aichele, Tonya L Jacobs et al. 50 citations

Advanced computational methods reveal that intensive meditation training produces lasting alterations in brain activity patterns, beneficially modifying how the brain functions. The approach identifies positive longitudinal changes in cortical activity, suggesting that dedicated meditation practice can reshape the brain and enhance neural well-being.

Mean-field thalamocortical modeling of longitudinal EEG acquired during intensive meditation training.

NeuroImage July 1, 2015 Manish Saggar, Anthony P Zanesco, Brandon G King et al. 31 citations

Intensive meditation training alters brain dynamics by increasing the delay between cortical and thalamic cells and reducing inhibitory connections within the thalamus. These changes, identified through computational modeling of EEG data from two 3-month meditation retreats, provide a neural mechanism for the previously observed slowing of individual alpha frequency. The reduced thalamic inhibition enhances dynamical stability in the model. This is the first computational approach incorporating anatomical and physiological constraints to formally model brain processes underlying intensive meditation, offering testable hypotheses for attention training and potential clinical applications.