The present study compared the cue-to-target P3 ratios in neutral and visuospatial cueing, in order to estimate the contribution of valid visuospatial information from the cue to target stages of the task performance, in terms of cognitive load.
The parameters of the models are learned jointly with the target of the specific task.
The long-term filter banks proposed here can be implemented by neural networks and trained jointly with the target of the specific task.
The pictures are identical, but for one change that is the target of the detection task.
This change in the peak position of the tuning function could be accounted for by a general shifting in frontoparietal resources away from resolving the ambiguous target-distractor decision at morph 1 and towards recognition of the target as the task becomes more familiar.
Like for the simulated data, we estimated the similarity between the different tasks by calculating the correlation between the actual target values of the tasks.
While we did not include regularized bias terms in our experiments because of the aforementioned reason, it can be profitable for GRMT if the average target values of the tasks differ substantially.
To ensure that subjects attended to the target classification aspect of the task just as they had done in the experiment proper, we elicited prime-identification responses only on trials in which the target was correctly classified.
The inputs of the tool are goals and targets related to the task of the course schedule for a session.
Specifically, we propose that when subjects detect the targets of the letter task this reinforcement signal results in plasticity of neurons that are active at that time.
This finding has provided a challenge to attentional theories of perceptual learning [10] [12] because the motion-direction stimulus was learned even though it provided no information regarding the identity, or temporal position in the sequence, of the targets of the RSVP task.
