Mean-field thalamocortical modeling of longitudinal EEG acquired during intensive meditation training.
Manish Saggar, Anthony P Zanesco, Brandon G King, David A Bridwell, Katherine A Maclean, Stephen R Aichele, Tonya L Jacobs, B Alan Wallace, Clifford D Saron, Risto Miikkulainen
Neuroimage July 1, 2015 DOI: 10.1016/j.neuroimage.2015.03.073 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Observational cohort Longitudinal Peer reviewed |
|---|---|
| Population | Meditating participants during two separate 3-month-long shamatha meditation retreats |
| Intervention | shamatha meditation |
| Duration | 3-month-long retreats |
| Topics | Meditation |
| Keywords | Beta-band power Computational modeling Mean-field modeling Intensive meditation training Brain adaptations Positive adaptations EEG Data Modeling Brain network modeling Brain dynamics Brain activity Brain networks Dynamical stability Cortical-thalamic delay Thalamic inhibition Neurophysiology Alpha frequency shifts |
| Citations | 31 |
| Key findings | Intensive meditation training increased cortical-thalamic delay and decreased thalamic reticular nucleus inhibition, with the delay linked to reduced alpha frequency and the inhibition reduction associated with greater dynamical stability. |
Abstract
Meditation training has been shown to enhance attention and improve emotion regulation. However, the brain processes associated with such training are poorly understood and a computational modeling framework is lacking. Modeling approaches that can realistically simulate neurophysiological data while conforming to basic anatomical and physiological constraints can provide a unique opportunity to generate concrete and testable hypotheses about the mechanisms supporting complex cognitive tasks such as meditation. Here we applied the mean-field computational modeling approach using the scalp-recorded electroencephalogram (EEG) collected at three assessment points from meditating participants during two separate 3-month-long shamatha meditation retreats. We modeled cortical, corticothalamic, and intrathalamic interactions to generate a simulation of EEG signals recorded across the scalp. We also present two novel extensions to the mean-field approach that allow for: (a) non-parametric analysis of changes in model parameter values across all channels and assessments; and (b) examination of variation in modeled thalamic reticular nucleus (TRN) connectivity over the retreat period. After successfully fitting whole-brain EEG data across three assessment points within each retreat, two model parameters were found to replicably change across both meditation retreats. First, after training, we observed an increased temporal delay between modeled cortical and thalamic cells. This increase provides a putative neural mechanism for a previously observed reduction in individual alpha frequency in these same participants. Second, we found decreased inhibitory connection strength between the TRN and secondary relay nuclei (SRN) of the modeled thalamus after training. This reduction in inhibitory strength was found to be associated with increased dynamical stability of the model. Altogether, this paper presents the first computational approach, taking core aspects of physiology and anatomy into account, to formally model brain processes associated with intensive meditation training. The observed changes in model parameters inform theoretical accounts of attention training through meditation, and may motivate future study on the use of meditation in a variety of clinical populations.
Comparable studies
Other observational and cohort studies on meditation, most cited first.
| Study | Year | Design | Participants |
|---|---|---|---|
| Using Self-Report Assessment Methods to Explore Facets of Mindfulness Undergraduate students | 2006 | Observational cohort | |
| Effectiveness of a meditation-based stress reduction program in the treatment of anxiety disorders Patients with generalized anxiety disorder or panic disorder with or without agoraphobia | 1992 | Observational cohort | n = 22 |
| Meditation experience is associated with increased cortical thickness Participants with extensive Insight meditation experience and matched controls | 2005 | Observational cohort | n = 20 |
| Meditation experience is associated with differences in default mode network activity and connectivity Experienced meditators and matched meditation-naive controls | 2011 | Observational cohort | |
| Long-term meditators self-induce high-amplitude gamma synchrony during mental practice Long-term Buddhist practitioners and controls | 2004 | Observational cohort |
Citations in the library
Cited by 13
- Meditation training influences mind wandering and mindless reading. Psychology of Consciousness Theory Research and Practice March 1, 2016
- Mapping meditative states and stages with electrophysiology: concepts, classifications, and methods. Current Opinion in Psychology August 1, 2019
- Differences in Functional Connectivity of the Insula Between Brain Wave Vibration in Meditators and Non-meditators Mindfulness March 19, 2018
- Effect of a one-week spiritual retreat on dopamine and serotonin transporter binding: a preliminary study Religion, Brain & Behavior March 22, 2017
- Nondual awareness: Consciousness-as-such as non-representational reflexivity. Progress in Brain Research 2019
and 8 more in the library
Cites 22
- Neural correlates of attentional expertise in long-term meditation practitioners Proceedings of the National Academy of Sciences June 28, 2007
- Mental Training Affects Distribution of Limited Brain Resources PLoS Biology May 4, 2007
- The meeting of meditative disciplines and western psychology: A mutually enriching dialogue. American Psychologist 2006
- Physiological Effects of Transcendental Meditation Science March 27, 1970
- Intensive meditation training improves perceptual discrimination and sustained attention. Psychological Science June 1, 2010
and 17 more in the library