'RAP - Rhythmic Attentional Precision, Muenster, Mai 2019'
(AsPredicted #24120)
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1) Have any data been collected for this study already?
No, no data have been collected for this study yet.

2) What's the main question being asked or hypothesis being tested in this study?
In a Posner-like cued attention paradigm, subjects have to perform a continuous reproduction task. More specifically, subjects are asked to report the exact position of a gap in a briefly presented target (Landolt C) which can occur in two possible locations and at different stimulus onset asynchronies(SOAs) after being exogenously cued to the correct or incorrect location (valid/invalid cue).
We predict that precision but not guess rate of the report for the continuous reproduction task (modelled with two-parameter Standard Mixture Models) will oscillate across SOAs at theta frequency (4-8Hz).
Further, we predict that these oscillations occur in anti-phase between valid and invalid cued position.


3) Describe the key dependent variable(s) specifying how they will be measured.
The observed error distribution of the gap report will be modelled using Standard Mixture Models with a precision and a guess rate parameter. The frequency spectrum for the parameter’s time course across SOAs will serve as dependent variable.

4) How many and which conditions will participants be assigned to?
SOA: We use dense sampling by varying the SOA between cue and target in 41.67ms steps (192ms to 984ms), leading to 20 SOAs.
Cue validity: valid (target occurs at cued location) vs. invalid (target occurs at uncued location).
Across eight test sessions, each SOA x cue validity combination is presented 96 times in total.


5) Specify exactly which analyses you will conduct to examine the main question/hypothesis.
1) Extract error distribution (ranging from -180 to 180, centered at zero, which reflects the target position) for each condition combination.
2) We model each of these error distributions with a two-parameter Standard Mixture Model with a precision and guessing parameter using MEM Toolbox (Suchow, Brady, Fougnie, & Alvarez, 2013; memtoolbox.org).
3) A Fast-Fourier transformation on both parameter’s time courses across SOAs will lead to a frequency spectrum.
4) Permutation tests: Peaks in the observed frequency spectrum will be tested against permutations (leading to a distribution of permuted frequency spectra).


6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations.
1. Trial level
Trials fulfilling one of the following criteria will be aborted and repeated at the end of the respective session:
1.1. Fixation was not kept in the required boundaries of 2° visual angle around screen center.
1.2. Subjects do not deliver their report within 5 seconds.

2. Session level
For analysis, we will only consider sessions …
2.1 …that were completed at least up to 50%.
2.2 …in which the subject showed at least moderate task performance as indicated by an error within +/-90° around the target location in 60-80% of the trials.

3. Subject level
For analysis, we will only consider subjects who delivered at least 80 trials per SOA/cue validity combination after applying the outlier rules listed for the session level.


7) How many observations will be collected or what will determine sample size?
No need to justify decision, but be precise about exactly how the number will be determined.
Fourteen subjects who fulfill the criteria listed in “Outliers & Exclusions”.

8) Anything else you would like to pre-register?
(e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?)
Data have only been collected for a prestudy to determine the most suitable timepoint for the first SOA (see 4.Conditions) .