Speaker
Description
Achieving precise synchronization between neural, visual, and motor signals is crucial for investigating event-related potentials (ERPs) in sensorimotor paradigms. We developed a high-precision acquisition system integrating 256-channel high-density electroencephalography (hd-EEG), OptiTrack motion capture, and a custom photodiode-based triggering setup to study ERPs during a visually guided reaching task.
A large circle was continuously displayed on screen to represent the touch-sensitive surface. When the participant’s finger was not in contact, the circle appeared red; upon contact, it turned black. Visual targets appeared within this black circle and served as cues for the reaching movement. The task included four key event triggers: (1) trial onset, marked by the visual transition of the circle from red to black upon finger contact, (2) arrival at a predefined home position, which triggered target appearance (still unreachable), (3) a color change of the target indicating the go-cue, and (4) trial end, signaled by finger lift (end of contact), with the circle reverting to red.
Two photodiodes detected luminance changes corresponding to these events, with signals sent simultaneously to both the EEG amplifier and the motion capture DAQ, ensuring millisecond-level synchronization. The mean absolute latency difference between EEG and OptiTrack triggers was 4.8 ms.
ERP analysis focused on the home position and trial end. A sustained negativity (CNV) peaked ~280 ms over central electrodes following target appearance. At trial end, visual feedback elicited a biphasic P1–N2 complex over occipital sites. These time-locked responses validate the system’s precision for resolving closely spaced neural events in visuomotor tasks.
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