Separating Components of Attention and Surprise
This work addresses the challenge of measuring cognitive processes like attention and surprise in real-world settings, offering a practical tool for mobile computing applications, though it is incremental as it extends earlier experiments.
The study tackled the problem of separating neural components of attention and surprise in decision-making by using low-cost eye tracking in mobile contexts, demonstrating that robust signatures of attention and surprise can be retrieved based on pupil dilation.
Cognitive processes involved in both allocation of attention during decision making as well as surprise when making mistakes trigger release of the neurotransmitter norepinephrine, which has been shown to be correlated with an increase in pupil dilation, in turn reflecting raised levels of arousal. Extending earlier experiments based on the Attention Network Test (ANT), separating the neural components of alertness and spatial re-orientation from the attention involved in more demanding conflict resolution tasks, we demonstrate that these signatures of attention are so robust that they may be retrieved even when applying low cost eye tracking in an everyday mobile computing context. Furthermore we find that the reaction of surprise elicited when committing mistakes in a decision task, which in the neuroimaging EEG literature have been referred to as a negativity feedback error correction signal, may likewise be retrieved solely based on an increase in pupil dilation.