🤖 AI Summary
This study addresses the scarcity of lightweight, browser-based tools for synchronized multimodal visualization in cognitive neuroscience. The authors present an open-source web application that enables time-aligned, interactive visualization and real-time processing of EEG, eye-tracking, and speech data, supporting both local and GitHub-hosted datasets. Designed with a channel-agnostic architecture, the system accommodates EEG systems of varying electrode densities and integrates ICA-based denoising, cross-modal correlation analysis, and spatial gaze heatmaps. Built on Plotly for efficient interactivity, the tool has been successfully deployed with the EMMT corpus, demonstrating its capacity to flexibly and effectively support multimodal data exploration in cognitive neuroscience and translation studies.
📝 Abstract
MEEDAV is an open-source web-based application for the synchronised visualisation of electroencephalography (EEG), eye-tracking, and audio data collected in psycholinguistic research. While originally developed for the Eyetracked Multi-Modal Translation (EMMT) corpus, which uses four-channel EEG data from the Muse 2 headband, MEEDAV also supports higher-density EEG setups thanks to its channel-agnostic processing pipeline. The system performs time alignment across all modalities and provides optional ICA-based EEG denoising. It features interactive Plotly visualisations, including unified EEG-audio-gaze timelines, gaze-intensity plots, event markers, and spatial heatmaps of fixation/saccade patterns. Researchers can filter by participant and stimulus, inspect raw versus cleaned signals, and compute cross-modal correlations. All processing is handled in real time, with a modular backend that supports local file access or GitHub-based streaming. Although initially tailored to the structure of the EMMT dataset, MEEDAV demonstrates a generalisable approach to multimodal data exploration and offers a lightweight, browser-accessible solution for cognitive neuroscience and translation studies.