Finally, resting-state ORFs reliably decoded most ocular behaviours across eye features and regularity conditions, even from task-related neural activity during passive listening, highlighting their robustness and versatility. (7/8)

We then applied resting-state ORFs to a passive listening task. 🎶🧠 This "proof-of-principle" revealed overlaps in midbrain, temporal, and parietal regions, suggesting shared mechanisms between auditory and saccade-related activity, with saccades potentially influencing auditory responses. (6/8)

...and vice versa! We could also reliably decode eye features from neural data, either using whole-brain information or PCA-based methods 🧠👁️ (5/8)

Our approach allows for the temporally and spatially precise prediction of neural activity based on ocular action... 🌀👁️ (4/8)

We propose a solution: "Ocular Response Functions". We used simultaneous magnetoencephalographic (MEG) and eye-tracking recordings during the resting-state combined with temporal response functions to precisely map the relationship between oculomotion and neural activity. (3/8)

Finally, resting-state ORFs reliably decoded most ocular behaviours across eye features and regularity conditions, even from task-related neural activity during passive listening, highlighting their robustness and versatility. (7/8)

We then applied resting-state ORFs to a passive listening task. 🎶🧠 This "proof-of-principle" revealed overlaps in midbrain, temporal, and parietal regions, suggesting shared mechanisms between auditory and saccade-related activity, with saccades potentially influencing auditory responses. (6/8)

...and vice versa! We could also reliably decode eye features from neural data, either using whole-brain information or PCA-based methods 🧠👁️ (5/8)

Our approach allows for the temporally and spatially precise prediction of neural activity based on ocular action... 🌀👁️ (4/8)

We propose a solution: "Ocular Response Functions". We used simultaneous magnetoencephalographic (MEG) and eye-tracking recordings during the resting-state combined with temporal response functions to precisely map the relationship between oculomotion and neural activity. (3/8)