Meditation Alters Cognitive Load: EEG Fractal-Based Classification and HRV Geometric Assessment
Swati Singh, Laxmidhar Behera, Suvendu Samanta
International Conference on Computational Intelligence and Communication Networks December 20, 2025 DOI: 10.1109/cicn67655.2025.11368257 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Observational cohort Peer reviewed |
|---|---|
| Duration | 8-week intervention |
| Topics | Meditation |
| Key findings | Eight weeks of Hare Krishna Mantra meditation reduced cognitive load and stabilized brain-heart dynamics during cognitive tasks, as shown by decreased separability between rest and task states in EEG and HRV measures. |
Abstract
Objective measures of cognitive load are essential for understanding how the brain and body respond to demanding tasks and how meditation modulates these responses. This study examines nonlinear complexity features from electroencephalography (EEG) and heart rate variability (HRV) for distinguishing rest from task states and assessing meditation effects during cognitive tasks. Cognitive load was quantified using the Hurst exponent (HE) and Higuchi fractal dimension (HFD) from EEG, capturing temporal correlations and signal irregularity, and the SD2/SD1 ratio from HRV as an index of sympathovagal balance. Classification between rest and task periods was performed using Support Vector Machine (SVM) and Random Forest (RF). Task performance showed decreased HE, increased HFD, and higher SD2/SD1, indicating elevated load and sympathetic dominance. After eight weeks of Hare Krishna Mantra (HKM) meditation, smaller variations in HE, HFD, and SD 2/SD 1 were observed, and SVM accuracy decreased from 80.1% to 61.0% while R F accuracy dropped from 81.4% to 62.0%, confirming reduced separability between rest and task states. These findings demonstrate that HKM meditation lowers cognitive load and stabilizes brain-heart dynamics, supporting EEG and HRV features as effective multimodal indicators of mental effort.
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
Cites 3
- Decoding Cognitive Load Changes Induced by Mantra Meditation From Physiological Signals Using Deep Neural Networks IEEE Sensors Journal November 14, 2025
- Meditative State Classification Using Neuronal Multi-IMF Band Power and Complexity Features National Conference on Communications February 23, 2023
- Meditation and Cognitive Enhancement: A Machine Learning Based Classification Using EEG IEEE International Conference on Systems, Man and Cybernetics October 9, 2022