Back

Meditation as a Bioactive Intervention: Molecular and Neurophysiological Mechanisms Revealed by Connectivity Mapping

Joshi, A.; Patel, D.; Muralidharan, V.; Mukerji, M.

2025-12-29 systems biology
10.64898/2025.12.27.696659 bioRxiv
Show abstract

Meditation practices are often used as non-pharmacological adjunct therapy for managing stress and well-being benefits. We propose that beneath their non-pharmacological facade, meditation practices might operate via drug target modulation having profound neurophysiological effects. Firstly, we leverage the Connectivity Map (CMap) to investigate (a) the overlap between meditation-induced molecular signatures and established drug responses, and (b) the pathways and mechanisms contributing to meditation potential therapeutic effects. This was studied in a comprehensive temporal RNAseq dataset comprising premeditation, meditation, and follow-up stages from a clinical trial involving 106 participants practising inner engineering meditation. Meditation signatures overlapped with over 438 drugs, but predominantly with drugs targeting the neuroactive ligand receptor pathways, capable of modulating the brains excitation-inhibition (E/I) balance. Next, to bridge the meditation-induced molecular changes to measurable neurophysiological effects, we performed a comprehensive meta-analysis of drugs affecting E/I balance through the lens of non-invasive brain stimulation, i.e., transcranial magnetic stimulation (TMS-EMG and TMS-EEG). Using multiple correspondence analysis, we then clustered the CMap informed neuroactive drugs and their E/I effects on the same latent space. We found that meditations effects mimic drugs targeting the GABAergic, Glutametergic and other neuromodulatory system pathways. Our findings lead to a working model to objectively test neurophysiological changes resulting from meditation that can lead to evidence-based clinical applications. Overall, these findings support the view that meditation acts as a biologically active intervention capable of modulating molecular pathways and cortical excitability, rather than functioning solely as a psychological or contemplative practice.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.