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Overview Main Input Contrasts and Probabilities Review Console RESET Settings
Design parameters
These parameters refer to your design and need your careful attention.




Trial structure

What does one trial look like? Probably there is some time before the stimulus of interest (the target), where a fixation cross is shown. Maybe there is some time after the stimulus is presented.




Duration of experiment

  • If you give duration: number of trials = duration/(trialduration + mean ITI)
  • If you give number of trials: duration = (trialduration + mean ITI)* number of trials






Inter Trial Interval (ITI)

The ITI's can be fixed or variable. Variable ITI's can be sampled from a uniform model or a truncated exponential model.





Contrasts

How many contrasts do you want to optimise? You can choose to include all pairwise comparisons. You can also add custom contrasts (to be specified on the next page). You can do both.



Rest blocks

Do you want to include rest blocks? If not: leave these boxes empty.






Design optimisation parameters

There are 4 criteria that quantify the optimality of the design:

  1. Estimation efficiency (estimating the HRF)
  2. Detection power (activation detection)
  3. Final frequencies of each trial type
  4. Avoiding psychological confounds

Please provide the weights that you want to give to each of the design criteria.

Ideally, the weights sum to 1. If not, they will be rescaled as such.




Design specifications to avoid psychological confounding
Trial contingencies

To prevent predictability of the design, you can control the contingencies in the design. Eg.

  • Order 1: P(AA) = P(BA).
  • Order 2: P(AxA) = P(BxA)
  • Order 3: P(AxxA) = P(BxxA)
  • ...

To which order do you wish to control the contingencies (maximum 10)? In other words: how far back do you want to control the predictability?





Trial blockedness

To prevent predictability of the design, you can control the number of times a stimulus type is repeated.