Active Visual Semantics Dataset (AVS)

Bridging MEG, eye tracking, and natural scene understanding

The Active Visual Semantics (AVS) dataset provides a comprehensive neuroimaging resource combining magnetoencephalography (MEG), eye tracking, and semantic scene captioning to study active visual processing during natural scene exploration. Built upon scenes from the Natural Scenes Dataset (Allen et al., 2022), AVS captures the neural dynamics of fixation-locked visual processing across 4,080 natural images with high temporal resolution.

The AVS dataset addresses a critical gap in visual neuroscience by providing high-quality neural recordings during active, naturalistic vision. Unlike traditional paradigms requiring central fixation, AVS captures the neural dynamics of self-directed visual exploration.

AVS Dataset Overview — Dataset design combining MEG recordings and eye tracking with natural scene understanding. Adapted from Sulewski et al., 2025.

AVS at a glance

4,080 natural scenes from NSD (Allen et al., 2022)
Free viewing and German sentence-level captioning
Eye movement-locked event-related fields (ERFs) in MEG
Individual head stabilisation and MRI-guided source modelling
5 participants with more than 10 hours of recordings each
235,000+ gaze events
4s scene presentation with eye tracking and MEG
306-channel MEG system
5,100 German scene descriptions, transcribed
Raw and preprocessed data with MNE-Python pipelines

Early access available

Request beta access and collaboration opportunities via our online form.

AVS Dataset Analysis Pipeline — Balanced semantic scene sampling approach. Adapted from Sulewski et al., 2025.

Experimental design and technical specifications

Free Viewing Task

4,080 scenes from NSD
4s exposure per scene
~9 fixations recorded per scene

Captioning Task

25% of scenes followed by captioning
German verbal descriptions
sBERT semantic embeddings

Semantic Scene Sampling

60 semantic clusters from MS-COCO captions
Balanced sampling over clusters
Includes NSD shared1000

Neural Data

Fixation-locked MEG event-related fields
Source-projected neural activity (dSPM)
HCP and NSD region parcellations

Behavioural Data

Eye movement parameters and sequences
Object labels for fixated locations
Rich trial metadata