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New EEG dataset and benchmark for meditation research released

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced the L-FAME dataset, which includes EEG recordings and psychological assessments from 74 college students undergoing a six-week meditation program. The dataset is designed to study the neural effects of different meditation techniques, specifically two mantra-based practices and a breath-focus method. A benchmark suite is also proposed, featuring tasks for decoding cognitive states, classifying meditation techniques, and evaluating model generalization across the longitudinal data. AI

IMPACT Provides a new dataset and benchmark for developing and comparing analytical methods in computational meditation research and EEG-based machine learning.

RANK_REASON The cluster contains an academic paper introducing a new dataset and benchmark for a specific research area. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New EEG dataset and benchmark for meditation research released

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The cluster contains an academic paper introducing a new dataset and benchmark for a specific research area. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Angqi Li, Ab Basit Rafi Syed, Hamzeh Alzweri, Taosheng Liu, Barry H. Cohen, Saiprasad Ravishankar ·

    L-FAME: Longitudinal Focused Attention Meditation EEG Dataset and Benchmark

    arXiv:2605.22893v1 Announce Type: cross Abstract: We introduce a novel Longitudinal Focused Attention Meditation Electroencephalography (L-FAME) dataset and an accompanying benchmark, designed to foster research into the neural effects of various meditation practices and the evol…

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