Abstract
A powerful methodology is required to resolve what is still one of the greatest methodological challenges in the cognitive neuroscience of vision: When dealing with complex visual stimuli, how can a brain response be attributed to a specific object category (e.g. a face), a specific feature (e.g. the eye) or a specific function (detecting an eye detector or responding to diagnostic face information)?
Here, we introduce a new principled approach (based on “Bubbles”) which uses face stimuli as their own control to determine the features driving a brain response (here, the N170 and P300). At a given latency (ms) the measured amplitude (mV) at particular electrode sites can be correlated with the stimulus giving rise to this amplitude. Our analyses on two observers resolving two different face categorization tasks (gender and expressive or not) reveal that the N170 responds to the eyes within a face irrespective of task demands and that the P300 responds to task specific information.
With this new technique it is possible to track the emergence of ERP components at each electrode site directly without performing an explicit search. Once identified an amplitude modulation is further explored to render how specific stimulus information modulates the amplitude. A dynamic rendering of the use of information over multiple electrode sites is then constructed, resulting in a model of the ERP response to stimulus information.
Such attribution of function suggests a new methodology to directly attribute function to different components of the neural system for perceiving complex stimuli.