Biological psychiatry. Cognitive neuroscience and neuroimaging
April 1, 2025
Vaibhav Tripathi, Ishaan Batta, Andre Zamani et al.
23 citations
The default mode network (DMN) is linked to self-referential thinking, memory, and goal-directed cognition. Its functional connectivity with frontoparietal networks involved in attention and executive control may indicate cognitive health. This review examines DMN connectivity metrics as potential biomarkers across states like attention, mind wandering, and meditation, and in conditions such as Alzheimer's disease, Parkinson's disease, depression, and ADHD. It also addresses the reliability of network estimation and offers recommendations for using functional connectivity measures as biomarkers of cognitive health.
Biological psychiatry. Cognitive neuroscience and neuroimaging
April 1, 2025
Saampras Ganesan, Fernando A Barrios, Ishaan Batta et al.
6 citations
Meditation practices, which have shown therapeutic benefits for conditions like depression, pain, addiction, and anxiety, have been studied with neuroimaging over the past decade. However, existing neuroscientific models are based on small, heterogeneous datasets, limiting generalizability and replicability. The ENIGMA-Meditation consortium is the first worldwide collaborative effort to conduct systematic meta- and mega-analyses of globally distributed neuroimaging data using standardized methods. This framework aims to improve statistical power and address multidomain heterogeneity in meditation practice types, experience, and experimental design. The consortium will generate rigorous neuroscientific insights into the mechanisms underlying meditation's therapeutic effects on psychological and cognitive attributes.
April 8, 2024
Saampras Ganesan, Aki Tsuchiyagaito, Greg J. Siegle et al.
2 citations
preprint
Meditation practices, which have been adapted into manualized interventions for conditions like depression, pain, addiction, and anxiety, show therapeutic promise, but their neuroscientific basis remains unclear. Current neuroimaging studies rely on small, heterogeneous datasets that vary in practice types, participant experience, clinical targets, and imaging methods, limiting generalizability and replicability. To address this, the ENIGMA-Meditation consortium was formed as a global collaboration to conduct systematic meta- and mega-analyses of distributed neuroimaging data using standardized methods. This framework aims to improve statistical power and rigorously characterize the neural mechanisms underlying meditation's effects on psychological and cognitive attributes, advancing the field of contemplative neuroscience.