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Vaibhav Tripathi

Center for Brain Science and Department of Psychology, Harvard University, Cambridge, Massachusetts; Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts.

7 papers in the library · 98 citations · publishing 2021-2025

Papers

Neuroscience of the yogic theory of consciousness

Neuroscience of Consciousness January 1, 2021 Vaibhav Tripathi, P. Bharadwaj 28 citations

Yoga, a practice and philosophy with roots over 4500 years old, has gained renewed scientific interest. This review outlines the dualistic Sankhya philosophy of yoga as summarized by Patanjali, describing the five vrittis (modulations of mind), practices like pratyahara and dhyana, and states of samadhi. The authors propose a yogic theory of consciousness (YTC) that models both external modulations and internal mental states, suggesting attention, sleep, and mind wandering are unique modulatory states. YTC can model external states, meditation, samadhi, and disorders of consciousness. The article lists testable neuroscientific hypotheses and discusses benefits and limitations of this framework.

Default Mode Network Functional Connectivity As a Transdiagnostic Biomarker of Cognitive Function.

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.

Functional connectivity changes in meditators and novices during yoga nidra practice.

Scientific reports June 5, 2024 Suruchi Fialoke, Vaibhav Tripathi, Sonika Thakral et al. 21 citations

During yoga nidra, a practice that aims for deep relaxation with heightened awareness, experienced meditators show reduced connectivity within the default mode network (DMN) compared to novices, as measured by fMRI. This decoupling of DMN regions was not present during ordinary resting states before or after the practice. The degree of reduced DMN connectivity correlated with the participants' cumulative hours of meditation and yoga experience. The findings suggest that yoga nidra produces a distinct neural state in experienced practitioners, supporting their subjective experience of being restful yet aware, and offer insight into the neural mechanisms underlying the practice.

Mindfulness Meditation and Network Neuroscience: Review, Synthesis, and Future Directions.

Biological psychiatry. Cognitive neuroscience and neuroimaging April 1, 2025 Ruchika S Prakash, Anita Shankar, Vaibhav Tripathi et al. 13 citations

Network neuroscience examines brain organization by mapping connections between its elements. This review describes how mindfulness meditation may alter structural and functional brain networks. Although evidence is preliminary, studies suggest mindfulness shifts connector hubs—the anterior cingulate cortex, thalamus, and mid-insula—and reduces intraconnectivity within the default mode network. Global connectivity findings are mixed. The authors call for rigorous study designs, open science, and diverse samples to better understand mindfulness's impact on brain networks.

ENIGMA-Meditation: Worldwide Consortium for Neuroscientific Investigations of Meditation Practices.

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.

Electroencephalographic dynamics of rhythmic breath-based meditation

bioRxiv Preprint Server March 9, 2022 Vaibhav Tripathi, Lakshmi Bhasker, Chhaya Kharya et al. 5 citations preprint

During Sudarshan Kriya Yoga (SKY), a rhythmic-breathing meditation, brain oscillations slow from alpha to theta to delta as the practice progresses. In 43 subjects, alpha-wave amplitude in the parieto-occipital region decreased during rhythmic breathing and dropped sharply in meditation. Theta amplitude and peak frequency increased in the centro-frontal region during rhythmic breathing but remained sustained and low during meditation. Delta-wave amplitude was unaffected by breathing, but both delta power and peak frequency rose during meditation in the centro-frontal region. A decrease in the 1/f aperiodic signal across the brain during meditation suggests a shift in excitation-inhibition balance. Each phase of SKY has a unique electrophysiological signature.

ENIGMA-Meditation: Worldwide consortium for neuroscientific investigations of meditation practices

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.